To answer that question for you, we recently took the exam. Below is a breakdown of everything you need to know in order to be successful when taking the DOP-C02.

What’s the difference between DOP-C01 vs DOP-C02?

There have been significant changes in the exam domains and weighting of the AWS Certified Developer Associate exam. All but one of the domains has changed weighting, with the biggest change being the Policies and Standards Automation domain has changed to Security and Compliance.

This is more than just a renaming, but a major shift in focus to security, with an increased weighting from 10% to 17%, as shown in the diagram below.

Despite the changes, if you’re studying A Cloud Guru’s AWS Certified DevOps Engineer – Professional prep course, you’ve already got a strong foundation for the DOP-C02 exam – you just need to learn a bit more to cover your knowledge gaps. Thankfully, we’ve worked hard to update this prep course to help you crush the new exam version, and it is now in line with the new requirements.

New Domain: Security and Compliance

As you’d expect, this new domain is dedicated to security with a focus on applying automation for security controls and data protection. You can expect to encounter questions related to AWS Identity Center (formerly known as AWS Single Sign-on), AWS Security Token Service (STS), and other services such as AWS Network Firewall, AWS WAF, AWS Shield, Amazon Detective, Guard Duty, and Security Hub. 

Some of these (Network Firewall, WAF, Shield) are important because the domain mentions applying “automation for security controls and data protection.” If you’re weak in any of these areas, I’d dedicate some time in getting to know these service offerings.

There’s a greater focus on multi-account and multi-region concepts

In your exam preparation, devote a lot of energy to services that help in multi-account and multi-region scenarios. The exam guide mentions these fifteen times across almost all of the exam domains.

Most Valuable Service for Multi-Account and Multi-Region Environments: AWS Organizations

There are a ton of AWS services to know about, so it helps where to spend the most learning bang for your buck. In sports, we have the MVP (Most Valuable Player), but in AWS, what’s the most MVS (Most Valuable Service) when it comes to the multi-account and multi-region scenarios mentioned above?

Certainly, CloudFormation StackSets are a valuable tool when deploying at scale. But as you get more experience with these diverse environments, you’ll find there is one service that’s always getting its hands dirty and helping us manage all of our accounts across multiple regions. And so, our nomination for MVS in these scenarios is AWS Organizations.

Understanding how AWS Organizations works and its features, as well as how it fits into the big picture and can be used to solve complicated scenarios, will be critical to your success in the exam. It’s a service that helps manage all accounts across multiple regions and is closely coupled with AWS Control Tower, a newer service which should also receive proper attention in your preparation.

Sticking with the AWS Organizations theme, what’s our main tool for security in AWS Organizations? Service Control Policies (SCPs). And what about compliance across multiple accounts? Well, when we see the word compliance in AWS, the first service that should come to mind is AWS Config. 

But how do we implement AWS Config in a multi-account, multi-region environment? We can use the AWS Config Aggregator. An aggregator is an AWS Config resource type that collects AWS Config configuration and compliance data from multiple accounts and regions. And the aggregator can also collect data from an organization in AWS Organizations and all the accounts in that organization which have AWS Config enabled. All of this really points to AWS Config being an important player on the DevOps Pro exam. 

Deployment pipelines is still a large part of the exam

Deployment Pipelines remains a big focus in the DOP-C02 exam, with an emphasis on pipeline security and performing deployments across multiple accounts. You’ll need to use the principle of least privilege for accessing various accounts, such as dev, test, and prod. Knowing how to implement least privilege as your accounts become more restrictive (with prod being the most restrictive) is crucial.

Preparing for the AWS Certified DevOps Professional Exam

So that sums up the new AWS DevOps Pro DOP-C02 exam. You still need to understand deployment pipelines, but you need to build on that and extend your knowledge to multiple accounts and regions (Hint: AWS Organizations!) and know how to apply security to our deployment pipelines across multiple accounts.

If you’re studying for the DOP-C02, we highly recommend you check out A Cloud Guru’s cert prep course for the AWS Certified DevOps Engineer – Professional. It will teach you everything you need to go in and ace the exam. Also, don’t forget to read the official exam guide to check out more about the new weightings and requirements.

We also have three practice exams you can use to make sure you’re prepared and confident to sit the real thing, which you can check out below. Note that you will need an A Cloud Guru account to take these:

• Practice exam #1
• Practice exam #2
• Practice exam #3

We know you’ll crush the exam on the day. As always, keep being awesome, gurus!

These are all situations where the AWS Well-Architected Framework comes in handy. In this article, we’ll explain how this framework can help you apply proper design principles and best practices for the cloud.

What is the AWS Well-Architected Framework?

The AWS Well-Architected Framework is a collection of best practices and guidelines for designing and operating reliable, secure, efficient, and cost-effective systems in the cloud. It is designed to help organizations understand the trade-offs and decisions they need to make when designing and operating cloud-based systems and applications.

The framework is primarily focused on six pillars that are essential to a well-architected system: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. 

However, the benefit of the framework doesn’t end there — it includes AWS Lenses, and AWS Guidance papers. These papers shine a light on general industries like the game industry, and specific scenarios like disaster recovery.

Why is the AWS Well-Architected Framework useful?

The Framework can be used to fine-tune your resources and design patterns to curb costs and environmental impact, while improving performance, reliability, security, and operations. It can help to put a four-dimensional view on your designing, building, evolution, and flow of your environment across every milestone.

The Framework can also help to shine some light into the business end of the pillars, which we will expand on below.

The six pillars of AWS Well-Architected Framework, explained

As mentioned above, the framework focuses on AWS’s six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. From start to finish, the Framework includes the six pillars.

Each pillar is composed of design principles, and best practices that describe how to apply those design principles. The design principles have some overlap, but each application of them is precise in how it should be carried out to apply to the relevant pillar.

1. Operational Excellence

The operational excellence pillar focuses on the ability to support development and run workloads effectively. This will mean diving into operations metrics and continuously evolving processes and procedures over time. 

The pillar dives into four best practices: organization, prepare, operate, and evolve.

Because this pillar focuses on operations, it has a strong business end to ensure that organizations are able to carry operational excellence across them as a whole – not just across a workload or workflow.

2. Security

The security pillar focuses on protection – protection of data, systems, and any assets, really that you have in the cloud or interacting with your cloud environment. This means strong control, awareness, and management. 

The pillar dives into six best practices: security, identity and access management, detection, infrastructure protection, data protection, and incident response.

Security is a beast in and of itself, and the pillar is robust reflecting that. Depending on your workload requirements, security might seem daunting. The Framework helps to ensure that you understand all of the check-boxes necessary to maintain a strong security stance. Thankfully, AWS has provided several services that make security management easier.

3. Reliability

The reliability pillar aims to ensure a workload performs correctly and consistently. This means setting a strong foundation, architecture choice, and preparing the unexpected. 

The pillar has four best practices: foundations, workload architecture, change management, and failure management.

One of the main factors that can impact reliability is resiliency or the dynamic elasticity of the workload and how your workload recovers from and mitigates incidents. The pillar thoroughly covers how to implement resilience in your architecture.

4. Performance Efficiency

The performance efficiency pillar focuses on using computing resources efficiently to balance meeting system requirements and efficiency through the evolution of your workload and technologies available to use. This means compute optimization, vigilant monitoring, and consistency. 

The pillar has four best practices: selection, review. monitoring, and tradeoffs.

Tradeoffs offer a valuable perspective shift when considering what is important to implement for a workload. Some workloads have rigid cost boundaries or specific requirements that dictate what resources have to be implemented. Sometimes workloads have more flexibility and allow for trade offs like reliability for cost optimization, and that is when you can make a shift in your design to implement different architectures to meet different goals.

5. Cost Optimization

The ever popular cost optimization pillar zeroes in on how to continuously run your workload while meeting the lowest price point. This means understanding costs, resource selection, and continuous optimization over time. 

The pillar has six best practices: practice cloud financial management, expenditure and usage awareness, cost-effect resources, manage demand and supply resources, and optimize over time.

Usage awareness plays a major part in cost optimization because there are resources that incur costs for sitting such as elastic IP addresses and snapshots. These types of resources may not be in use or even necessary to have sitting available, but are incurring costs, so cleaning up resources should be practiced with regularity. 

To learn more about this pillar and cost optimization in AWS, check out this blog post.

6. Sustainability

The sustainability pillar shines the spotlight on the environmental impact of your workload. This includes energy consumption and efficiency, as well as resource usage. 

The pillar dives into six best practices: region selection, user behavior patterns, software and architecture patterns, data patterns, hardware patterns, and development and deployment patterns.

AWS has committed to being 100% renewable by 2030 and are well ahead of that goal and expecting to be renewable by 2025! Their commitment and implementation of this sixth pillar takes how we utilize the cloud and adds another dimension to our considerations. 

Meeting workload requirements can now include sustainability goals, leading to better growth – sustainable growth and a brighter future for everyone and everything depending on our planet for survival.

What is the difference between the AWS and Azure Well-Architected Frameworks?

There are some key differences between AWS and Azure’s take on the Well-Architected Framework. You’ll notice a difference in pillars and a difference in depth.

AWS includes best practices for each pillar both for your environment AND your organization. There are design principles that lend a deeper focus to how an organization can support the environment in each pillar. So, having the business aspect is helpful for any businesses just entering into the cloud and are kind of clueless. AWS offers that aspect of support and depth.

Azure has a hard focus on best practices for your environment and does NOT go into the business side of each pillar. Some businesses don’t need that level of support and may prefer a Framework that cuts to the chase. Azure is also missing the Sustainability Pillar and that is a big piece of the Cloud puzzle – for me and some businesses who are actively pursuing leaving a smaller carbon footprint in their cloud endeavors. 

Committing to learning more about the AWS Well-Architected Framework is a big step, but an important one to really understand and set a strong foundation for utilizing the cloud in the best way possible. Each pillar acts as a cornerstone to your design and having a full understanding of each one can strengthen the way you implement solutions, evolve your architecture, and maintain that architecture over time.

If you are ready to dive into the AWS Well-Architected Framework, check out the AWS Well-Architected Framework Deep Dive course where you can explore each pillar in depth. The course covers 12 AWS Lenses, 3 Guidance papers, 2 case studies, and includes how to apply and review the Framework using the Well-Architected Tool.

Thank you so much for joining me today, gurus! I hope this helps to clear up any questions you had about the Framework. Don’t forget to join our Discord server. Deep breaths, baby steps, and as always, keep being awesome!

In this blog post, we’ll explore the differences between Kubernetes and VMs, and how each platform is suited for different use cases.

What is Kubernetes? A quick overview

Kubernetes, also known as K8s, is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. With Kubernetes, developers can focus on writing code, while the platform handles the details of deploying and managing the application. 

Kubernetes is designed to be cloud-native, meaning that it can run on any public or private cloud platform, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). 

To learn more about Kubernetes in general, check out this article: What is Kubernetes, and why should I learn it?

What is a Virtual Machine?

A virtual machine (VM) is a software emulation of a physical computer that can run its own operating system and applications. In a VM environment, a hypervisor is used to create and manage virtual machines. Each virtual machine runs its own operating system and applications, completely isolated from other virtual machines running on the same physical server. 

Kubernetes vs VMs: What’s the difference?

While Kubernetes and VMs share some similarities, there are some fundamental differences between the two platforms.

1. Kubernetes is designed for deploying and managing containerized applications, not the whole OS

With Kubernetes, developers can define the desired state of their application, and the platform will automatically handle the deployment and scaling of the application. Kubernetes also provides built-in load balancing capabilities, making it easy to distribute traffic across multiple instances of an application.

In contrast, VMs are designed to run entire operating systems and applications, rather than just containers. This means that deploying and managing applications in a VM environment can be more complex, as each VM must be manually provisioned and configured. VMs do provide greater flexibility in terms of operating system and application compatibility, but they require more manual management and maintenance.

2. Kubernetes uses fewer resources than a VM

In a VM environment, each virtual machine runs its own operating system. This provides complete isolation between virtual machines, but it can also lead to resource inefficiencies. Since each operating system requires its own set of resources, running multiple virtual machines can be resource intensive.

Kubernetes, on the other hand, is designed to run containerized applications. Containers share the host operating system, which means that multiple containers can run on the same host, using fewer resources than would be required by VMs.

3. Kubernetes can automatically scale apps based on demand, no manual provisioning

One of the primary benefits of Kubernetes is its ability to automatically scale applications based on demand. With Kubernetes, developers can define the desired state of their application, and the platform will automatically handle scaling the application up or down as needed with a simple command.

In a VM environment, scaling can be more complex. Each virtual machine must be manually provisioned, and scaling requires additional resources to be allocated to each virtual machine. 

4. Kubernetes is Cloud Native, VMs are not

Kubernetes is designed to be cloud-native, meaning that it can run on any public cloud platform. This makes it easy to deploy and manage applications across different cloud providers, without having to worry about compatibility issues.

In contrast, VMs are not specifically designed for cloud-native environments. While they can be used in the cloud, they may require additional configuration and management to ensure compatibility across different cloud providers.

Also, because Kubernetes is designed specifically for running containerized applications, it is better suited for modern, cloud-native applications than a VM. 

In conclusion

Kubernetes and virtual machines are two different platforms that are suited for different use cases. 

• Kubernetes is designed specifically for deploying and managing containerized applications, while virtual machines are designed for running entire operating systems and applications. 
• Kubernetes is cloud-native and provides automatic scaling, load balancing, and efficient resource usage, making it well-suited for modern, cloud-native applications. Virtual machines provide greater flexibility in terms of operating system and application compatibility, but require more manual management and maintenance. 

Ultimately, the choice between Kubernetes and virtual machines will depend on the specific needs and requirements of the application being deployed.

How can I learn more about Kubernetes? 

If you want to learn more about Kubernetes, there are several courses available that can take you from being a complete beginner to getting Kubernetes certified. Here are some we highly recommend:

• Introduction to Kubernetes
• Deploying a Basic Kubernetes Cluster
• Learn Kubernetes by Doing
• Kubernetes Essentials
• Certified Kubernetes Administrator (CKA)

Action. Reaction. 

That’s it! Action and reaction. That’s Google Cloud Functions in a nutshell. But of course, since this doesn’t capture all the ways this service is cool, let’s go into a bit more detail. 

In this article, I’ll give you a more detailed overview of Google Cloud Functions, compare the 1st gen and 2nd gen environments, and discuss some good uses for the service. I’ll also explain how to deploy a simple Cloud Function.

Google Cloud Functions is a serverless compute platform that allows you to run code in response to events without having to provision or manage servers. Because Cloud Function is a fully managed service, it is a great way to efficiently automate tasks, build microservices, and connect your applications to other cloud products and services, both on and off Google Cloud. I like to think of Cloud Functions as the “glue” between services that allow you to extend the built-in capabilities to achieve your programmatic goals.

Cloud Functions falls into the Functions as a Service (FaaS) category of computing. FaaS is all about the code–and just the code. With Google Cloud Functions, you have your choice of working with a range of runtimes: Go, Java, .NET Core, Node.js, PHP, Python or Ruby. Here’s an example of a simple Cloud Function in Python:

This Cloud Function is triggered directly by an HTTP request, and represents one of two major types, the other being an Event. This is a 2nd gen Cloud Function (more about that in a bit) which makes it easy to include all the necessary libraries with a single import of the functions_framework. Then, the entry point or main function is registered with the chosen runtime framework. Because it is an HTTP triggered function, supported HTTP method types or verbs (such as GET, POST, and PUT) are referenced. Finally, all Cloud Functions must return a response.

The initial release of Cloud Functions–now known as 1st gen–could be triggered directly by an HTTP request, as noted above, or an event from one of a limited number of Google Cloud Platform services, including Cloud Storage, Cloud Pub/Sub, and Cloud Firestore. Google Cloud completely re-architected Cloud Functions for their 2nd gen release. Built on a foundation of Cloud Run (Google Cloud’s serverless container computing product) and Eventarc, a platform-wide triggering service, Cloud Functions 2nd gen capabilities were greatly expanded.

Now, Cloud Functions can be triggered directly by 18 different Google Cloud services as well as through changes to Audit Logs covering over 90 products, and even a handful of 3^rd-party services–as well as HTTP requests, by default. The 2nd gen revamping brought a doubling of computing power and memory available in addition to an increase of concurrent requests by a thousand-fold. 

Cloud Functions can be put to use in a myriad of ways:

• Asynchronous microservices integration: Connect with 3^rd-party APIs, pull data from mobile app backends, or enhance workflow automation.
• Operational streaming analytics: Gather info from IoT devices, perform video or image analysis, or send your massaged data to BigQuery for near real-time analysis. 

Cloud Functions is particularly useful when working with AI APIs as with this workflow that takes an uploaded image, optically recognizes the text, translates it into five different languages and then stores the translations into separate documents:

The Google Cloud Functions console allows you to create and deploy a Cloud Function quickly and efficiently. In fact, the creation process is identical to deployment.

Cloud Functions can also be deployed via the command line. Here’s the command for deploying a 1st gen HTTP function:

gcloud functions deploy FUNCTION_NAME --source=LOCAL_PATH
--entry-point=CODE_ENTRYPOINT --trigger-http

Deploying a 2nd gen function, triggered by a audit log event such a Cloud SQL instance failover, is just as straight-forward:

gcloud functions deploy FUNCTION_NAME --gen2 \
  --event-filters="type=google.cloud.audit.log.v1.written" \
  --event-filters="serviceName= serviceName=cloudsql.googleapis.com" \
  --event-filters="methodName= cloudsql.instances.failover" \
  --service-account=PROJECT_NUMBER-compute@developer.gserviceaccount.com

Google Cloud Functions are an essential element of today’s microservice, cloud-based event architecture. Because they’re serverless, they scale effortlessly as needed to connect almost any declared action to your desired reaction.

Want to learn more? Check out the following resources:

Terraform state is one of the great things about Terraform. It maps the resources in your configuration to their real-world counterparts. This allows you to easily detect drift between your desired state and the actual state of your resources. 

But it doesn’t stop there – Terraform state also improves performance when deploying large configurations, because it allows you to skip the required back-and-forth between the provider’s API and the Terraform executable. Normally Terraform will refresh the state when you run Terraform Plan, by comparing real-world resources with what is currently in state. But you can easily skip this process and save some time, by setting the refresh option to false: terraform plan -refresh=false

State is an essential part of Terraform and you can’t use Terraform without state, but you don’t have to rely on Terraform to manage the state for you. 

• You can inspect resources in your state with the terraform show and terraform state list commands.
• You can import resources into state using the terraform import command.
• You can make terraform forget about real-world resources with the terraform state rm command.
• You can move resources in state with terraform state mv, which is useful when you change the local name in your configuration.

When you run the first terraform plan, Terraform will automatically create a local state file for you, the file is named terraform.tfstate and is placed in the same working directory as your configuration files. The state file isn’t anything special, it’s just a JSON (JavaScript Object Notation) file.

What’s great about the state (you see what I did there?), is that it stores everything, even sensitive data you might forget, like passwords. That’s cool, right?

Yeah, I agree, that’s totally NOT COOL. We all know passwords should never be stored in plain text, especially in the working directory! Also you should never, ever store your state file in a source control repository.

Terraform state should be treated just like any sensitive data. You should encrypt your state file at rest and in transit. Access to the state file should also be tightly controlled, and you should also back up your state. Terraform will automatically back-up the state file for you when you perform certain state-related operations, but it’s important to keep a recent copy as a backup.

One way to help you securely store your and access your state file is to use a backend. Backends allow you to store your state in a remote location, and share the state with your team. There are a range of backends available, including Azure Storage, Amazon S3 and more, but there is another option that handles all of the security for you, and that is Terraform Cloud. 

With Terraform Cloud, you can ensure your state is encrypted at rest and in transit and share the state with your team. Where Terraform Cloud falls short is on backups, you’ll need to make sure you keep a backup of your state in another secure location. The restoration process with a backup is much faster than the process you need to follow to recreate your state (oh yeah, nailed it, again, you’re welcome) from scratch.

You also should consider the size of your state file. You should apply the principle of least privilege, and a state file that is used to manage resources across multiple workload teams can be a security risk, so you should keep your configurations modular, which will lead to smaller and easier to secure state files. Terraform Cloud workspaces can be used to make this easier.

So, what are the most important considerations when managing your Terraform State?

• Always make sure you secure your state file and treat it just like you would any other secret;
• Secure your state at rest and in transit;
• Use the principle of least privilege by separating workloads out and using separate state files for different workload teams and environments; and 
• Always back-up your state files

If you’re keen to get hands-on with Terraform on Azure including how you can manage your state with Terraform Cloud, check out my latest course, Hands-on with Terraform on Azure, or if you’re ready to dive a little deeper, you can check out our complete Terraform library with heaps of lessons and labs to sink your teeth into.

What is Kubernetes? A quick refresher for the uninitiated

Kubernetes is an open-source container orchestration platform that allows you to deploy, manage, and scale containerized applications with ease. It automates the deployment, scaling, and management of containerized applications and services, providing a consistent and predictable environment for running them. 

Kubernetes can run on any infrastructure, whether it’s on-premises or in the cloud, and can manage any type of containerized application, regardless of the container runtime or programming language used. 

At the heart of Kubernetes is a cluster, which is a group of nodes that run containerized applications. The cluster is managed by a Kubernetes control plane, which consists of several components that work together to provide the desired state of the cluster. 

One such component is the Kubernetes API Server, which serves as the primary interface for users and other components to interact with the Kubernetes cluster.  The API server provides authorization and authentication, object schema validation, and also implements admission controllers. 

For anyone interested in learning more about Kubernetes, a great place to start is this video course: Introduction to Kubernetes

What are Kubernetes Admission Controllers?

Kubernetes admission controllers are a set of plugins that can be configured to run before or after a Kubernetes resource is created, modified, or deleted. They are responsible for intercepting requests to the Kubernetes API server and enforcing custom validation rules, policies, or default behaviors on the incoming resources. 

Admission controllers come in two types – mutating and validating. 

• Mutating Admission controllers are able to modify resources before they are persisted to the etcd database.
• Validating admission controllers are used to accept or reject a request based on a set of rules. 

Generally, admission controllers will either be mutating or validating, but, sometimes they can be both, which is the case for the LimitRanger admission controller. 

What is the LimitRanger Admission Controller?

The LimitRanger admission controller is a built-in admission controller that enforces resource constraints on Kubernetes namespaces. It allows administrators to specify resource requests and limits for a namespace and limits the amount of compute resources that can be used by pods in that namespace. 

The LimitRanger admission controller can enforce constraints on CPU, memory, and ephemeral storage resources, as well as the number of pods and services that can be created in a namespace.  When a pod is created in a namespace, the LimitRanger admission controller verifies that the pod’s resource requests and limits do not exceed the constraints defined in the namespace’s LimitRange.  

Just in case there is any confusion, the Kubernetes object is called “LimitRange” and the admission controller is called “LimitRanger”. 

How is LimitRanger different from ResourceQuota?

If you have any familiarity with Kubernetes admission controllers you may be wondering how LimitRanger is different from ResourceQuota. Both of the admission controllers are used to enforce resource constraints and quotas, but they differ in their scope and level of control. 

LimitRanger is used to limit the resources that can be used by pods in a specific namespace; whereas, ResourceQuota is used to limit the total amount of resources that can be consumed by all the pods in a namespace.

How to configure LimitRanger and deploy it in your Kubernetes System

LimitRanger is a built-in admission controller, which means that it ships with Kubernetes and is enabled by default. As long as it is not being explicitly disabled, you will have access to use it. Run the following command to view enabled or disabled admission controllers (built-in controllers will not be listed):

Enabled and disabled admission controllers will appear in a comma delimited list beside the following options:

Once you’ve validated that the admission controller is enabled, the next step is to create a manifest file for the LimitRange object. Below is an example of what the file should look like:

In this example, we’re creating a LimitRange object called “mem-cpu-limit-range”. This object sets constraints on the CPU and memory resources that can be used by pods in the “my-namespace” namespace.

The limits field is an array that can contain multiple limit definitions. In this case, we have only one limit definition, which applies to all containers in the namespace (type: Container).

The max field specifies the maximum amount of CPU and memory resources that can be used by a container. In this example, we’re setting a maximum limit of 0.5 CPU and 500Mi memory.

The min field specifies the minimum amount of CPU and memory resources that a container must request. In this example, we’re setting a minimum request of 0.1 CPU and 50Mi memory.

Next you need to deploy the object by running the following command:

By creating and applying this LimitRange object to a namespace, we can ensure that pods running in that namespace do not consume more than the specified CPU and memory resources. If a pod attempts to exceed these limits, Kubernetes will reject the creation of the pod and display an error message.

Conclusion

I hope that I’ve been able to show you how useful the LimitRanger admission controller can be in helping manage resources in your Kubernetes cluster. This is just one of the many admission controllers that are working in the background to keep your Kubernetes system running smoothly and efficiently. 

If you would like to learn more about LimitRanger and admission controllers in general, please check out my course Hands-On with Kubernetes Admission Controllers at A Cloud Guru.

To answer that question for you, we recently took the exam. Below is a breakdown of everything you need to know in order to be successful when taking the DVA-C02.

How different is DVA-C02 from DVA-C01? 

The new exam is not massively different from the previous one: the DVA-C01 and DVA-C02 have more similarities than differences. This is great news because if you have already started preparing using a course for DVA-C01 then most of the content is still going to be relevant.

This means if you’re studying A Cloud Guru’s AWS Certified Developer – Associate (DVA-C01) prep course, you’ve already got a strong foundation for taking — and passing! — the DVA-C02 exam. You can also rest assured we are already working on updates to bring this course in line with the new exam. 

Another bit of good news is the difficulty level and format of the exam remains the same:

• The exam will consist of 65 multiple choice and multiple answer (response) questions
• The exam is 130 minutes long and scored on a scale of 100 – 1000, with a passing score being 720 or above
• 15 unscored questions are included. These are questions that are being evaluated by AWS, before inclusion in the exam as scored questions. Unscored questions do not count towards your exam score.
• In terms of cost, the exam still costs $150 USD and can be taken either at a facility or remotely
• After completing the exam, you can expect to receive your result within 24 hours by signing in to your AWS Certification Account

There are no prerequisites for taking the exam. That said, AWS recommends that you have one or more years of hands-on experience in developing applications using AWS services. If you don’t, I highly recommend you have a basic understanding of the concepts covered on the Certified Solutions Architect Associate – Associate Exam. 

What courses can help me prepare for the DVA-C02?

• If you do not have one or more years of hands-on experience, we advise you to complete this course before moving on to the Certified Developer Associate course: AWS Certified Solutions Architect – Associate (SAA-C03) 
• If you already have at least one or more years of hands-on experience with AWS, use this course: AWS Certified Developer – Associate (DVA-C01)

Again, the AWS Certified Developer – Associate DVA-C01 course is currently being updated to reflect the changes and additions to the exam. If you take these courses as they are at the writing of this article (or if you have already taken them), you will already be 90% of the way there! 

Below are some insights and resources to help you to prepare for that additional 10%, so that you can ace the exam.

What exactly has changed for DVA-C02?  

Let’s take a look at how the domains have changed in the new exam: 

• The “Refactoring” domain has been removed 
• The weights of the domains have altered slightly:
  • “Development with AWS Services” has increased from 30% to 32% in weight
  • “Security” has remained the same at 26% in weight
  • “Deployment” has increased from 22% to 24% in weight
  • “Monitoring and Troubleshooting” has been renamed to “Troubleshooting and Optimization”, and increased from 12% to 18% in weight

In terms of new services covered, at the time of writing (March 2023) there have not been many major additions yet. However, this is likely to change as this version of the exam evolves over time and new questions are added to the pool. 

The list of services that could appear in the exam can be reviewed in the latest official DVA-C02 exam guide. However, based on our experience taking the exam, not all of the services that are listed as “might be covered” actually made an appearance in the exam. We expect that over time, AWS will develop additional questions to test on all the services that are listed in the guide. 

For now, let’s consider the following major categories of changes that you can expect to see in the exam in its current state. 

Monitoring tools for troubleshooting and optimization

The largest shift in weighting is the “Troubleshooting and Optimization” domain, which went from 12% of the total exam weight to 18%. This domain was also renamed to remove the emphasis on monitoring. However, do not let that fool you — monitoring is still a significant part of the exam!

Services like CloudWatch, CloudWatch Logs, CloudWatch Logs Insights, and X-Ray are all definitely worth knowing about, but rather than approaching them from a support and monitoring perspective, think about how these tools can be used by a developer to help troubleshoot an application that is not behaving as expected. For instance, how to use API Gateway CloudWatch metrics to troubleshoot an issue with your application, or how to access CloudWatch logs for AWS Lambda. 

It’s also important to understand generally what changes can be made to optimize applications running in AWS. 

Serverless deployment best practices

In this new revision of the exam, there was a slightly greater emphasis on serverless best practices in general. It’s worth making sure you understand the AWS recommended ways of configuring their services, in particular: 

• Lambda Best Practices
• Choosing Between Lambda Data Storage Options
• Best Practices for Advanced Serverless Developers
• Lambda Dead Letter Queues 
• API Gateway Mock Integrations
• Working With API Gateway Stages

Common serverless architecture patterns

It is worth becoming familiar with as many event-driven, serverless architectures as possible, and really gaining an in-depth understanding of how different AWS services can be integrated together to build a complete system. While researching updates for the course, the following resources are particularly helpful: 

• Best Practices For Organizing Larger Serverless Applications
• Building Well Architected Serverless Applications
• Well Architected Framework – Serverless Scenarios
• Integrating Amazon EventBridge into your serverless applications
• Sending and receiving Amazon EventBridge events between AWS accounts

Deployment in general

A few additional topics have appeared in relation to general deployment in AWS. For instance, you’ll need to be familiar with the use of EC2 Image Builder to create custom AMIs. You’ll also need to understand AMI Encryption, as well as how to copy an AMI to a different region. 

Other technologies that made a brief appearance in the exam include RDS and RDS Proxy, so it’s worth having a general understanding of the capabilities of each of these services. 

Development with AWS Services

When it comes to developing in AWS and building a CI/CD pipeline, it is important to understand which CloudWatch events can be used to Monitor CodeCommit events in order to use EventBridge to trigger your pipeline when code is updated. It’s also worth understanding how to Add a CodeBuild test action to a pipeline using CodePipeline.  

Security 

When it comes to security, consider the ways in which AWS services can help you deal with PII (Personally Identifiable Information). For instance, the use of services like Macie that helps you identify PII so that you can protect it accordingly. The exam guide specifically mentions the requirement to understand how to manage sensitive data. We recommend checking out this blog post on using Lambda to redact PII so that sensitive data is not returned in an S3 GET request: Protect PII using Amazon S3 Object Lambda.

The exam guide also mentions the need to understand Secrets management. We have a great blog post that covers exactly that topic, you can read all about it here: An Inside Look at AWS Secrets Manager vs AWS Parameter Store. 

We look forward to adding new lessons covering all these topics during Q2 2023, as well as general updates related to recent console changes. 

Free exam retakes available!

For a limited time, Pearson Vue is running a promotion allowing you to retake any AWS certification exam for free if you fail, which is a pretty good safety net.

To qualify, you will need to schedule and take the exam between March 15, 2023 and May 31, 2023, then apply a promo code before paying for the exam. Hopefully you won’t need to retake, but if you do, schedule the retake before August 1, 2023 and get it for free!

For more details and to get your promo code, click here. 

Conclusion

We hope you found this article helpful, and wish you good luck on the next steps in your learning and certification journey! Until next time, keep being awesome!

What is Emacs? (A quick summary)

Emacs is a powerful text editor designed for POSIX operating systems, and is available on Linux, BSD, macOS, Windows, and more. However, once you begin to learn about Emacs you will find that this software is very complex and that you can use it for far more than just editing text! It is an IDE for developers, you can use it to compile code, use it for email, or simply play some games with it.

How to Install Emacs

“Emacs sounds great! Now how do I install it?” Below, we share four different ways you can do that, depending on your operating system and your needs.

1. How to install Emacs on Ubuntu Linux using apt.

Installing Emacs on Ubuntu using the apt package manager is pretty straightforward, and should only take a few minutes to complete. 

First you need to update your package repository. This is simply done by running the following apt command:

sudo apt update

Once the update has finished, you can now move onto the next step of installing the Emacs package. This is also done using the apt command.

sudo apt install -y emacs
note: the -y is optional, without it you will need to manually reply to an install prompt.

Emacs has now been installed on your Ubuntu system!

Alternatively, you can use the snaps from the Snap Store to install the Emacs software. This is done using the snap command.

sudo snap install emacs --classic

2. How to install Emacs on CentOS 8 Linux using dnf.

Much like the first method, installing Emacs on CentOS 8 is also fairly simple. CentOS is an RPM based Linux OS, so instead of apt, we will be using dnf to install the Emacs software.

sudo dnf install -y emacs
note: the -y is optional, without it you will need to manually reply to an install prompt

The following dnf command will install the software onto your system.

If you happen to be running an older version of CentOS you will probably need to use yum instead of dnf, but the syntax looks the same.

sudo yum install -y emacs
note: the -y is optional, without it you will need to manually reply to an install prompt

And that is all there is to installing Emacs on your CentOS 8 system! 

3. How to build and install Emacs from the source code.

You may find that you want to install the newest version of Emacs, but it hasn’t been packaged for your particular Linux distribution yet. There’s no need to wait for the packaging to happen, you can build Emacs from the source code.

The first requirement to build Emacs from the source code is to make sure that you have an environment that has all the build tools properly installed. The extra packages you need to have installed may vary depending on what OS you have running, and what packages you may already have installed. The following extra packages are what I have typically had to install to get the source code to properly build.

Apt based system

libncurses-dev libgnutls28-dev gnutls-bin pkg-config

RPM based system

gcc make gnutls gnutls-devel ncurses ncurses-devel

Once you have a working environment to build Emacs, you need to download the source code. You can find the various archives on the Emacs ftp site. Next download the source code for the version you would like to use.

wget https://ftp.gnu.org/gnu/emacs/emacs-28.1.tar.xz
note: this would download the source code for version 28.1

Now you will need to extract the source code from the tar archive.

tar xvf emacs-28.1.tar.xz

After extracting the archive, it is time to build Emacs! The following commands can be used to accomplish this.

cd emacs-28.1
./configure
make
make install

The build may take several minutes to complete. Upon completion you will have the version of Emacs you downloaded installed on your system ready to use. 

4. How to install Emacs on other operating systems (OS X, Windows) 

Emacs is also available for OS X and Windows. To install it on OSX, the quickest way is to download it from the Emacs for OSX website. Once you have the .dmg file downloaded, just open it up and follow the instructions provided.

Similar to OSX, Emacs is also packaged up with an installer for windows. You can download the installer  from the Emacs FTP site. The easiest way to do this is to download the emacs-<version>-installer.exe and then run it on your system.

You have installed Emacs, now what?

Now that you have installed Emacs you are ready to get started using it. In a terminal window just enter ‘emacs’ and press enter, or launch the application via launchpad on OSX or the shortcut in Windows. You will now be in Emacs and are ready to start editing files, creating code, sending email, and even playing some built-in games like Tetris. Nice! 

If you would like to learn more about editing text with Emacs, then I invite you to join me in my course Text Editing with Emacs. I hope to see you there. Until next time, keep being awesome Gurus!

You rush to investigate, and learn that the outage is not caused on your end (whew!). It’s due to the cloud provider’s authentication mechanism failing and you’re not sure how long this outage will last. You need to get the site online as soon as possible, but what exactly can you do?

In this article, we cover what you can do when the cloud goes down (other than, you know, panic). 

What are the main causes of cloud services going down? 

Cloud failures can and will happen, which is why providers offer 99% to 99.99% uptime, never 100%. The top cause of outages are software or configuration errors, according to the Uptime Institute. Other common reasons are networking or connectivity issues, and mechanical or electrical failures at the data center. 

When software or configuration errors bring down the cloud, the issue can range from a bad deployment package, misconfiguration of the application, and more. An example of this kind of outage bringing down cloud services happened in February 2022 to Slack, when a configuration change to a database led to a widespread outage for about three hours.

Networking and connectivity is how the cloud is held together, so disruptions can cause all sorts of issues. In this category, the most common type of failures are related to configuration (are you noticing a trend?), change management, and third-party network provider errors. 

If we look at an outage from January 2022 on Google Cloud, we can see that a configuration error caused a few hours of increased latency where “the checkpoint data was incorrectly missing a particular piece of configuration information; this was propagated to ~15% of the network switches serving us-west1-b.”

On the mechanical or electrical failure side, most of the outages are caused by an uninterruptible power supply failure or from a utility or generator failure. Looking at an AWS outage from July 2022, a power outage to an availability zone caused a widespread outage of about two hours.

What happens when the cloud goes down?

As we saw in the introduction scenario, when the cloud goes down it’s rarely pretty or fun for us as the end users! It usually causes stress, anxiety, and a mad scramble to fix the issue, or find a backup solution or alternative. 

In a best-case scenario, our website is only down for a couple of minutes and only affects a small number of users. However, if we look at the worst-case scenario, our website could be down for days and would affect all of our customers from using our site. This potentially could cost us not only data loss from our site crashing but also reputation damage, loss of business, and more. 

A study was conducted back in 2015 by the Ponemon Institute where it was determined that on average, the cost of an outage per minute is nearly $9,000. A more recent study performed by the Uptime Institute found that more than half of the organizations they surveyed said that a recent outage cost more than $100,000!

Case Study: 2021’s Large-scale AWS Outage

We’ve seen a handful of smaller-scale outages earlier in this blog, but now let’s take a look at one of the most recent large-scale outages. 

On a cold December morning back in 2021, a large-scale AWS outage affecting multiple services took place. From 10:30 AM ET until approximately 9:40 PM ET (for full service recovery), several services including API Gateway, Fargate, EventBridge, and EC2 instances were affected. This caused widespread outages for several businesses and many Amazon services. People couldn’t order pizza and even AWS’s own service health dashboard was down. 

So what happened to cause all of this mayhem?

In short, an automated system in Amazon’s “us-east-1” region (North Virginia) tried to scale up an internal service running on AWS’s internal network. Unfortunately, there was an issue with this automated process and it flooded the network with traffic basically causing an unintentional Distributed Denial of Service (or DDoS attack). 

In order to fix the issue, Amazon engineers first tried to move DNS traffic away from the congested paths. While this seemed to have helped the issue, it was not the solution. Next, they disabled event delivery for EventBridge to help reduce the load on the affected network devices. At this point the congestion started improving and before long, AWS operators reported “all network devices fully recovered by 2:22 PM Pacific Standard Time.” However, some services still took a while to fully stabilize, namely API Gateway, Fargate, and EventBridge.

With any outage or IT issue, it should result in some lessons learned and takeaways for the future. For the AWS team, they resolved to fix the automated process bug and improve communication with customers during an outage like this. If you would like to learn more about the AWS outage, checkout the blog post here at ACG by Mattias Andersson. 

5 steps to take when the cloud goes down

Now that we’ve seen the effects and aftermath of cloud outages, how should you prepare for the next outage? Let’s walk through five steps you can take when the cloud goes down.

1. Before the cloud outage: Consider a multi-cloud strategy

First up, before an outage even happens, something to consider is a multi-cloud strategy for your environment. Now there are a few pros and cons to this approach as depending on your environment, architecture, and teams, a multi-cloud strategy might be more of a burden than a boon. 

Another alternative you might consider is making use of multiple regions with your preferred cloud provider. This gives you increased redundancy and provides protection from regional outages without having all of the baggage from having multiple cloud providers.

2. Before the cloud outage: Backup essential data

Second, before an outage occurs, you should be making sure to backup your essential data. 

• If you use Azure, Azure Backup is a solution that will backup data on your VMs, SQL servers, Azure Blobs, and more. 
• On the AWS side, you can use AWS Backup which supports the RDS service, EC2 instances, and much more. 
• With GCP, Google Cloud Backup and DR is going to keep you protected by backing up your data in GKE, VMs, and a whole lot more. 

If you have all of your essential data backed up before an outage, you’ll be able to restore it if there is data loss due to the outage or if the outage lasts for multiple hours or days.

3. Check for user errors first

For our third step, we can look at what to do after an outage has occurred. At this point, the best thing to do is determine if the issue is just on your end or not.

• The fastest way to rule out an issue with your internet or connection is to head over to the Down Detector and put in the URL to the website. Down Detector will let you know if any other users are reporting errors and if there is a widespread outage. They also include helpful links to the website’s support page, twitter, or facebook, if available. 

• Another helpful tool that will quickly check if a website is down and to help you rule out local connectivity issues is IsItDownRightNow.com. Is It Down Right Now will help you determine if the site you are checking is available and what the response time for the site looks like. 

If those detectors are not revealing any issues, you can check on the status page of your cloud provider. For example, to check on Google Cloud’s status, you can head to their status page that will reveal if they are having any service issues or service degradations. These status pages will sometimes contain updates about the issue, how long until resolution, and what steps are being taken to resolve the issue.

If the internet is completely down on your end or the power goes out, you can head to a local coffee shop and use their wifi and check to see if the provider is truly having an outage. Once you have ruled out any problems locally, we can move on to the next step in our list.

4. Contact your cloud provider

After we have ruled out any local connectivity issues, we can go ahead and contact the cloud provider to get more information on the outage. Be prepared to provide specific information about the issue you are experiencing, including what services are affected, any error messages, and what time the issue started. 

Each provider has a different method for contacting support and multiple ways to contact them:

• For Azure, you can use the Azure Portal or tweet Azure Support on Twitter. The latter is particularly helpful to get a quick response. 
• With AWS you can use the AWS support page or tweet AWS Support on Twitter. 
• Google Cloud gives you the option to use their support page. 
• If you are not using one of the big three cloud providers, then the easiest way to find out support information is on the providers website or by using Down Detector and the providers site, which will usually have a link to the support site for that provider. 

Once you have contacted the provider, please remember to be patient. During an outage the providers support team is scrambling to help customers and answer questions so it may take a bit for a response.

5. Check your cloud service agreement

Finally, you’ll want to check your provider’s cloud service agreement. Your agreement is important to review to understand the providers obligations and your rights as a customer. 

First, you’ll want to check your service level agreements (SLAs). An SLA is a commitment from the provider to maintain a certain level of availability. For example, if you are using AWS and your API gateway service is impacted, AWS has three levels of SLAs for the API gateway service. Depending on how much downtime that service has experienced in a specific month will entitle you to a partial or full refund. 

Let’s say the API gateway service was down for three hours earlier in the month, that equates to about 99.58% uptime. According to the SLA provided by AWS, you would be entitled to a 10% service credit. So, make sure you are reviewing your cloud service agreements!

Develop a multi-cloud strategy to protect your data

Cloud outages can be frustrating for anyone that relies on cloud services to perform their daily activities or run their business. By following the steps and resources in this article, you’ll be better prepared for an outage. However, as we have seen, cloud outages can and will happen at any time. 

In order to protect your business from an outage, you should determine if you can engineer your application or services to run from multiple regions either in an active-active style or active-passive where you can failover to another region when there is an issue.

If you are still concerned about downtime with a single cloud provider, the next step is to develop a multi-cloud strategy to protect your data. You’ll want to make sure that you have the right people and processes in place to make this strategy a success, and we recommend reviewing the pros and cons of going multi-cloud.

Google’s answer: Google Cloud Armor.

What is Google Cloud Armor?

Given these web app security risks, Google empowers its cloud customers to protect their apps with the Google Cloud Armor service. This security service integrates with Cloud Load Balancing to protect your back-end services and apps from distributed denial-of-service (DDoS) traffic that could compromise the availability of these assets. GCP Armor leverages Google’s global threat intelligence feeds and machine learning to recognize DDoS traffic targeting your Google Cloud Platform (GCP) resources and block that malicious traffic flow.

What does Google Cloud Armor do?

Google Cloud Armor incorporates a web application firewall (WAF) to protect web apps against many of the security risks listed on the OWASP top 10 list. GCP customers can leverage GCP Armor’s WAF function to block web app attacks using pre-configured WAF rules. Customers also have the ability to customize WAF rules and define conditions for filtering traffic based on IP origin, HTTP request headers, and other attributes.

What are the most common web application security risks?

The nonprofit organization Open Web Application Security Project (OWASP) created a list of some of the most notorious web application security risks on the internet. This list includes cross-site scripting (XSS) attacks and SQL injection (SQLi) attacks that can read confidential data stored in a SQL database. 

In XSS attacks, adversaries may inject malicious code into a web application or compromise a client’s browser. And let’s not forget DDoS attacks that seek to bring down web apps by overwhelming the application with massive traffic flow.

Starting out with GCP and not sure what certification is right for you?

Check out this post that identifies all the latest GCP cloud certifications, what they cover, and how you can use them to further your career.

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Is Google Cloud Armor free?

Google Cloud Armor has two pricing tiers: Standard and Managed Protection Plus. 

For Standard users, GCP Armor is a pay-as-you-go service with per-month or per-request costs. WAF requests are $0.75 per million requests, WAF security policies are $5 per policy per month, and WAF rules are $1 per rule per month. While this tier has no time commitment and no data processing fee, it doesn’t offer any protected resources.

For Managed Protection Plus users, GCP Armor is an annual subscription service that starts at $3,000 per month. Protected resources above the 100 included with the subscription cost an additional $30 per resource per month. While all WAF requests, security policies, and rules are included with this subscription, it has an added data processing fee.

New to GCP and want to learn how to secure resources and apps in Google Cloud?

Login to your ACG account to watch our Introduction to Google Cloud Security course. This course takes a look at Google Cloud Armor, Cloud Firewall, Cloud Identity, and other essential principles for securing your GCP resources.

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Where should I start the network troubleshooting process?

Just like a stream, your network can become accidentally or purposely blocked up. You need to be aware of dams or debris when you’re tending to your stream. Within your network, security groups, NACLs and routeables act like dams and debris causing water to flow in specific directions. Dams, or intentional rules, point water in directions that can help with power or irrigation, while debris, or accidental or malicious rules, can block off water by accident. When you have connection issues, these are the first places to look for issues.

What are security groups?

Security groups control what direction traffic can flow in relation to your resources. For example, if you have an EC2 instance that you need to connect to, you would put in a rule for port 22 or 3309 from your IP address to allow you, and only you, to connect to that resource.

What are NACLs?

NACLs are the firewalls that help keep your environment safe. They control inbound and outbound rules for your environment that allow traffic to flow either in or out of your environment.

What are route tables?

Route tables control the flow of your environment by allowing you to connect to other VPCs, which connect to other resources giving you endpoints via gateways. There are two types of gateways: transit and internet. Transit gateways connect your VPCs together so you can connect on-premises or other devices to your cloud devices. Internet gateways allow you to connect out to the internet. 

When you combine these services, you can keep your environment safe and secure while making sure you can connect to everything you need.

Is network troubleshooting difficult?

Networking is complex and changes all the time. Diagnosing a networking problem requires many kinds of knowledge, precise attention to detail, and excellent problem solving skills. Once you know where to look and what to look for, it’s easy to complete a differential diagnosis of the issue. You just have to make sure to start small and follow a clear path.

Learn more tips to troubleshoot AWS network connectivity

Whether you’re a Solutions Architect, SysOps Engineer, or a Developer, chances are you’ll encounter network connectivity issues at some point in your cloud journey. Learning how to quickly identify and solve networking issues in AWS is a great skill that will serve you well throughout your career.

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What are the three most common causes of networking issues?

Ports are closed

Assuming the connection isn’t having any issues from outside sources, your NACLs and security groups control what traffic flows through your environment. Check for rules within your security groups or NACLs that allow you to connect first and foremost. On Windows devices, look for rules with RDP from port 3389. On Linux devices, look for SSH rules on port 22 with your IP address.

Rules aren’t applied to all groups

It’s easy to connect to your devices so long as you have the protocols or rules in place. Rules are often missed because they’re configured on the EC2 section of the console and need to be added to each individual group. One of the most common issues is adding rules to one group but not the other.

Traffic is blocked by rules

The other connection issue you should always look into is your NACLs and route tables, which make sure that only the traffic that you want or need to come into or out of your network is allowed. You need this for things like servers that get out to the internet or if you’re hosting one or several websites. You should also make sure you don’t have redundant rules that can make your environment more complicated.

Where can I get more help with network troubleshooting?

The AWS whitepapers on networking provide valuable, in-depth information from AWS experts. But they can take a while to comb through. For answers to specific questions, Network Engineering Stack Exchange is a forum for network engineers to collaborate on networking issues.

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In order to monitor and manage the performance and resource usage of these VMs, it is important to collect logs and usage metrics. However, this can be a challenging task, especially when dealing with a large number of VMs.

Fear not, though, the wonderful folks at Google Cloud have a solution for you – the Cloud Ops Agent! 

The Cloud Ops Agent is a tool that provides a centralized and unified solution for collecting, processing, and analyzing logs and metrics from your GCE instances.

Some of the benefits of using the Cloud Ops Agent include:

• Centralized log collection: Collected logs from your GCE instances are sent to a centralized location for easy access and analysis. This eliminates both the need for manual log collection and the risk of missing important logs.
• Real-time monitoring: Logs and usage metrics are collected in real-time, allowing you to monitor your GCE instances and respond to any issues in a timely manner.
• Customizable metrics collection: Custom metrics can be collected, allowing you to track specific performance and resource usage metrics that are important to your applications.
• Scalable and highly available: The Cloud Ops Agent is designed to be scalable and highly available, making it easy to manage even the largest GCE deployments.

You may be saying to yourself, “This sounds great but how do we actually install the Cloud Ops agent to reap some of these benefits?” For that, we have a couple of different options such as the Google Cloud Console or directly through the command line of your virtual machine instance. Let’s run through both of these below! 

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How to install the Cloud Ops Agent using the Google Cloud Console:

For this, there are two approaches. 

First:

• Go to the VM instances page within the Compute Engine Service

• Click the instance to install the agent on

• Click the observability tab

• Select “Install OPS Agent” and follow the prompts 

Alternatively:

• Go to Dashboards page within the Monitoring service

• Select the VM instances dashboard

• Select the checkbox next to the instance(s) to install the agent on, then select Install/Update Agents and follow the prompts

How to install the Cloud Ops Agent on the Command Line:

1. Use the Cloud Shell or another SSH client to connect to the machine
2. Change to a directory that you have write access to (i.e., your home directory)
3. Run the following commands:

curl -sSO https://dl.google.com/cloudagents/add-google-cloud-ops-agent-repo.sh
sudo bash add-google-cloud-ops-agent-repo.sh --also-install

Once the Cloud Ops Agent is installed it will start collecting additional system usage metrics by default. It can, however, collect additional logs and metrics by creating a configuration file that specifies the data to gather. 

Now that the agent is installed and collecting logs and metrics, the data can be sent to a centralized location such as Google Cloud Logging, Stackdriver Monitoring, or a third-party logging and monitoring tool. This gives a lot of flexibility to users whether you subscribe to the entire Google Cloud ecosystem or you already have a logging and monitoring solution. 

The Cloud Ops Agent is a valuable tool for monitoring and managing GCE instances. By collecting logs and usage metrics in a centralized and unified manner, it makes it easier to monitor and respond to issues, and to make informed decisions about your cloud infrastructure.

Whether you are managing a small or large GCE deployment, the Cloud Ops Agent can help you to get the most out of your cloud investment. If you would like to learn more about the Cloud Ops Agent, Compute Engine, and other supporting services offered by Google Cloud, please check out my course, Running Linux Servers on Google Cloud, at A Cloud Guru.

To understand Lambda, let me tell you a story that made me understand and appreciate Lambda the hard and expensive way. At the beginning of my AWS cloud journey, I was building a simple website to collect and process specific data. The ultimate plan was to build a serverless application that acts as a recommendation engine using the collected data. The website itself didn’t have any dynamic features as I relied on external tools such as old plain google forms and CSV files to collect the data. The existing platform was working fine, but I wanted to try my hand at migrating the website and data to AWS.

“It will speed up the process of building the serverless application down the road.” – my brain reasoned. But if I’m being honest, I mainly wanted an excuse to tinker with AWS services.

I was excited to get started, and jumped into drawing a crude diagram of the architecture, without studying the available offerings. Once the diagram was done, I went ahead and migrated the website to EC2. Talk about under planning and overkilling a project.

Then life happened, and I decided to put the project on hold, so I diligently went ahead and took down all the assets and resources from AWS S3 while leaving nothing behind but a static “Coming Soon” page.

My role as a software engineer wired me to think of projects in terms of code, functionality, and product releases, hence why I took the features down. However, my methodology at the time didn’t account for the behind-the-scenes infrastructure. Or the fact that the needs of the website had drastically changed. So I left the EC2 instance type and configuration as-is.

EC2 is for the strong

The fact that I can’t recall how I configured that particular instance, I can’t remember whether it was a t2.micro or a t2.small instance indicates that I shouldn’t have been tinkering with EC2.

However,  I remember too well my confusion and surprise when I saw a rather hefty recurring AWS expense listed on my bank statements.

My confusion stemmed from the fact that the website didn’t have any active visitors. Moreover, my S3 bucket was practically empty. I’d hosted more complicated websites for much cheaper costs so what was causing the recurring charges? 

If you’re a cloud guru, you probably already know that with EC2 comes a lot of flexibility, and with flexibility comes more responsibility. Developers that use EC2 instances to host applications need to have a solid understanding of various technical components such as:

• How to pick the right instance type and instance purchasing option for the project
• How to scale EC2 and how to balance the workload on instances 
• How to work with Target Groups and Application Load Balancers
• When to shut down instances to avoid incurring unnecessary charges

Needless to say that I didn’t have the last one in my AWS Cloud toolkit at the time. Once I connected the dots, I realized I was using the wrong service altogether.

Luckily, all it took was a quick search to realize that using Lambda is a much better offering for my particular needs. Firstly, I was after the ‘doodle using pencil’ version of serverless applications vs. the ‘watercolor a canvas’ version. Secondly, I was more than happy to lose the fine grained control and hand over the reins of infrastructure to AWS. I also found out that I can easily integrate Lambda with S3, AWS Amplify, Amazon API Gateway and DynamoDB to build the entire application.

What is AWS Lambda?

• Lambda is a cloud computing service that runs an event-driven architecture, meaning that external triggers invoke the code to get it to run.

• It offers a pay-as-you-go model. For the scope of my experimental project, being charged per request and duration made more sense than having to pay for every second my EC2 instance was running.
• Lambda also offers comprehensive yet abstract control of the underlying resources whereby AWS manages everything pertaining to the underlying  infrastructure (e.g., scaling, running security patches, OS configurations, etc.). 
• Lambda is a Function as a Service (FaaS)—a category of cloud computing that enables you to focus solely on building, running, and testing responsive functions (units of code) to build serverless applications. In addition to abstracting the provisioning of the underlying resources, AWS takes care of auto-scaling the application to match the demand.

 This abstraction might hinder you from certain customizations. But in my case, I didn’t need a customized ecosystem, nor did I want to deal with getting down to the granular details of the cluster.

Configuring the memory and the execution timeout in Lambda was more than enough for my project.

For the application’s backend, I wrote and hosted robust code to process the data using AWS Lambda, setup S3 to store the data and uploaded the necessary files, and monitored the logs through CloudWatch that Lambda automatically sent to CloudWatch.

So three services were all I needed to build, host, test, and monitor the backend of a serverless project.

For a comprehensive tutorial, check out this hands on tutorial for building a serverless web application that uses AWS Lambda and DynamoDB for the backend, AWS Amplify to host the static website, and Amazon API Gateway to handle users’ requests.

Not to be overly dramatic, but I was having a Spanish dancer emoji moment reading the Lambda documentation, especially having been through the pain of wrapping my head around everything to do with hosting a simple application on AWS.

But the skeptic in me couldn’t quite enjoy the moment, so I started pondering about the catch. I wondered whether Lambda would only support an exclusive set of languages or if it has a steep learning curve. Or perhaps it is drastically slower than EC2.

Is AWS Lambda easy to learn?

Getting started with Lambda is easy and straightforward. However, there is a bit of a learning curve when it comes to writing code that is well suited for Lambda’s execution environment. For getting started, you can try this 10-minute “Hello, World!” 10-minute tutorial tutorial and judge for yourself. 

Lambda’s simplicity is thanks to its key features that enable you to write, test and execute code on the fly. Some of these features include:

The Interface

You can easily and quickly get acquainted with Lambda becausethe Lambda console provides an IDE-like environment similar to other popular IDE applications. The GUI has a  distinct section for authoring and testing the code, a tab for configuring the application, and a console to print out the results.

TheLambda console offers the following three ways by which you can create new functions:

• Author from scratch – as the name suggests, with this option, you get to create functions from scratch
• Blueprints – AWS offers Blueprints as ready-to-use templates pre-built with the necessary configurations. You can also use blueprints to see how to integrate Lambda with other AWS services and 3rd party libraries. 
• AWS Serverless Application Repository – this option allows you to browse as well as share pre-built applications. You can either publicly share applications or privately share them with specific AWS accounts.

Supported Frameworks

Lambda natively supports a variety of popular languages including Java, Python, Node.js, C#, .NET and PowerShell. Lambda also provides a Runtime API to power any additional programming languages and to support custom runtimes.

Layers

Lambda layers enable you to import external libraries (in the form of a .zip file) and other dependencies into your function. Layers can be third-party libraries, additional code, configuration files or even custom runtimes. And AWS offers its own set of libraries that you can use immediately. For instance, they have the AWS SDK for Pandas Layer that you can use to import pandas into your functions.

Integrated Monitoring

By default, all Lambda functions export logs to AWS CloudWatch. Therefore, you can use AWS CloudWatch Lambda Insight metrics to monitor or troubleshoot your applications.

Is Lambda slower than EC2?

Lambda is slower than EC2, in the sense that it will not instantaneously respond to events. This behavior is inherent since the serverless model only runs upon demand. However, it is unlikely that this kind of delay will cause issues unless you’re dealing with a highly critical application. 

Lambda functions are always available, but they’re not always running. Lambda only runs when an external event triggers it to do so. Think of it this way, you might be available all day, but you probably won’t check your slack DMs unless an external event (think notifications) reminds you to do so. 

Once invoked, a Lambda function might take up to 100 milliseconds to execute the code for up to 15 minutes. This is a hard limit so if your function absolutely needs more than 15 mins to run, then consider EC2 or an alternative service. 

A Lambda function might also withstand extra latency (over 1 second) when a new function instance needs to be created and initialized. “Cold start” refers to the time it takes to kick-start a new function instance. Depending on the type and urgency of the task, this may or may not be a problem. For more on this, check out our blog on How to Keep Your AWS Lambda Functions Warm. Also, check our summary on the Lambda SnapStart introduced in re: Invent 2022. Lambda SnapStart drastically cuts down cold start time for Java applications.  

And now that we’re somewhat acquainted with AWS Lambda, let’s get back to our story, where I attempt to build a simple serverless application. Besides the fact that AWS Lambda met all my functional requirements as a developer, Lambda was well suited for my ultimate objective of collecting and processing data.

AWS Lambda and Data Processing

Data processing is simply the process of turning raw data into meaningful information. And if data is the new oil, data processing is the new refinery. And we can’t talk about data processing without diving into data lakes first. Organizations use data lakes and pipelines to store and refine the data.

A data lake is a centralized storage repository containing all the raw data in its native format. It extracts data from a wide array of data sources.

The data can be structured, semi-structured, or unstructured. The data serves different groups at different stages. Data scientists and engineers use non-curated data at its early stages for analytical purposes using tools such as Amazon Athena. 

Afterward, the data goes through validating, cleaning, and other transformations to serve the business users and publish business reports.

Data processing is the umbrella term used to refer to the process of curating data. But this can be anything from converting and compressing files to validating, transforming, enriching, or filtering the data. And this is where AWS Lambda comes in. Lambda is well suited for preprocessing and processing data in data pipelines. In addition to processing data, Lambda can extract and ingest the data. For more on this, check out this project that uses Lambda to build an ETL (extract, transform, and load) pipeline. And for a more in-depth and complex example, watch Nextdoor’s 2017 AWS re: Invent talk to see how Nextdoor used AWS Lambda to streamline their ETL pipelines.

There are a few scenarios where you can use Lambda to process data: 

• Transforming data through simple transformations, for example, substituting selected values with specific constants 
• Converting and compressing files, for example converting a CSV file to a JSON file or vice versa 
• Streamline the process of compressing images to enhance performance and optimize costs on the cloud.

Conclusion

So to sum it all up, do you want to focus more on your code which takes less than 15 minutes to run? Does the idea of maintaining servers keep you up at night? Do you’ve difficulty justifying paying money for idle time? If you answered yes to any of the previous questions, you should consider Lambda. And remember, you do not always need a project to tinker with AWS cloud computing offerings.

If you’re interested in learning more about Lambda’s building blocks, check out my course on Processing Serverless Data Using AWS Lambda. The course will teach you how to utilize AWS Lambda to serve your business needs as a data professional. You’ll unpack Lambda by learning how to use it to transform data and integrate it with other AWS services to build simple pipelines.

What courses are free at A Cloud Guru for the month of February? Time to get your learning hat (is that a thing?) on with a whopping 34 premium pieces of free cloud training from our huge library of hands-on goodness. 

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Here are the new additions to this month’s batch of free cloud training:

• Applying DevSecOps to AWS Web Apps
• AWS Cost Optimization Deep Dive
• Build Your Own Linux Kernel from Scratch
• Creating Startup Scripts for VMs with Cloud-init
• Developing Kubernetes Operators from the Ground Up
• GCP Cost Optimization Deep Dive
• Introduction to Google Cloud
• Introduction to Microsoft Azure Compute
• Running Linux Servers on AWS
• Introduction to Python Scripting

You can also check out courses around a few of our most-searched-for topics — including a batch of Kubernetes content, a bevy of DevOps courses, and a bundle of free Amazon Web Services (AWS), Microsoft Azure, and Google Cloud (GCP) courses.

Whether you’re a newcomer looking to jump start your cloud career or a pro looking to level up those in-demand DevOps skills, our rotating roster of free cloud courses will have you laughing all the way to the bank as you pick up the skills needed to land some of the top-paying jobs in tech. ACG has you covered with the essentials you need to master AWS, Azure, Google Cloud, Linux, and beyond.

Continue on for the full rundown of this month’s free cloud training!

Ready to get started with ACG’s free cloud courses? Sign up for a free ACG account here (no credit card needed!), or get the full A Cloud Guru experience with a free 7-day trial.

Up to 47% off for studentsMaster the skills that’ll drive your career – and save a boatload. Students are eligible to save up to 47% on annual full access to our unlimited hands-on learning library. All you need is a .edu, .ac.uk, or .edu.au email address*.

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Free Amazon Web Services (AWS) Training

AWS skills are among the top-paying salary careers in cloud. Whether you’re already on an AWS certification path or you’re looking to master some of the most in-demand AWS skills, these free courses can get you where you want to go.

• AWS Certified Cloud Practitioner (CLF-C01)Whether you’re just wanting to learn the fundamentals of AWS, or become certified, this cert prep course is perfect for getting that vital foundational knowledge.

• Amazon DynamoDB Deep DiveBuild scalable, high-performance applications using DynamoDB in this course for all skill levels.

• AWS EssentialsThis no-AWS-experience-required course gives an in-depth introduction to all things AWS through real-world scenarios and hands-on activities. Please note we’ve recently updated this course!

• Introduction to AWSThis quickie course for AWS newcomers will quickly cover the basics of AWS.

• EKS BasicsUnlock the power of Amazon Elastic Kubernetes Service.

• Applying DevSecOps to AWS Web AppsLearn how to integrate DevSecOps into the software development lifecycle for AWS web applications.

• AWS Cost Optimization Deep DiveThis course is designed to present a deeper understanding of the Cost Optimization Pillar of the AWS Well-Architected Framework.

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Free Microsoft Azure Training

Azure skills are in high demand, and the top-paying Microsoft Azure certifications can even give AWS certs a run for their money. Whether you’re working on your Azure certification path or just looking to pick up some basics, our free Azure courses have you covered.

• AZ-900 Microsoft Azure FundamentalsWhether you’re just wanting to learn the fundamentals of Azure, or become certified, this cert prep course is perfect for getting that vital foundational knowledge.

• Azure ConceptsGet up to speed on the basics of Azure and cloud services in this Azure concepts crash course.

• Creating Startup Scripts for VMs with Cloud-initLearn to configure cloud-init boot up scripts for Azure Linux VMs.

• Introduction to Microsoft Azure ComputeLearn about Azure’s IaaS, PaaS, and FaaS compute offerings and how to choose the product or service that best fits your needs.

Free Google Cloud (GCP) Training

Plotting your Google Cloud career path can be tricky. These free GCP courses offer something for beginners and practitioners alike.

• Google Cloud Certified Cloud Digital LeaderWhether you’re just wanting to learn the fundamentals of GCP, or become certified, this cert prep course is perfect for getting that vital foundational knowledge.

• GKE BasicsLearn about Kubernetes and Google Kubernetes Engine (GKE).

• GCP Cost Optimization Deep DiveCost optimize your environment within the Google Cloud Platform (GCP).

• Introduction to Google CloudLearn the foundations of Google Cloud such as Identity and Access Management, Compute Engine instances, storage, and networking.

Free Linux Training

• How to Get a Linux JobListen closely as we reveal the secrets to landing your first Linux job.

• Running Linux servers on AWSThis course introduces you to running Linux systems on the AWS platform.

• Build Your Own Linux Kernel from ScratchThis course gives you the skills and knowledge needed to build your own Linux distribution.

WATCH: Post-COVID DevOps: Accelerating the FutureHow has COVID affected — or even accelerated — DevOps best practices for engineering teams? Watch this free, on-demand panel discussion with DevOps leaders as we explore DevOps in a post-COVID world.

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Free Data and Data Science Training

• Big Data FundamentalsLearn about Big Data, cluster computing, distributed storage, and cluster management.

Free DevOps and Serverless Training

Whether you’re looking to learn more about the basics of DevOps and agile or the different serverless options between AWS, Azure, and GCP, A Cloud Guru can help you level up your DevOps game.

• DevOps ConceptsSee how DevOps transforms software development.

• Serverless ConceptsGet a high-level overview of serverless, including the basic vocab and concepts.

• Developing Kubernetes Operators from the Ground UpLearn how to develop a Kubernetes operator and deploy it to your Kubernetes cluster.

Programming Language and Editor Training

• Introduction to Python ScriptingPython basics for the absolute beginner.

WATCH: Solving The “No Experience” Cloud Hiring ProblemYou can’t get experience without a job. But who’ll hire you without experience? Conundrum! Watch this free, on-demand webinar featuring a panel discussion on cloud career development and getting your first cloud job. 

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Free Cloud Training for Beginners

ACG’s intro and conceptual courses are perfect for newcomers to cloud and tech or non-technical roles who want to have a better understanding of the tech that powers modern organizations.

• Cloud Computing FoundationsOur explain-it-like-I’m-five (but I’m a super-smart five-year-old interested in tech) intro to the basics of cloud computing breaks down the basics and decodes the jargon that can make cloud feel impenetrable. This new course replaces our Intro to Cloud Computing course on the free course roster. You’ll learn the difference between PaaS and SaaS faster than you can figure out how to pronounce “IaaS.”

Subscribe to A Cloud Guru on YouTube for weekly cloud news, like us on Facebook, follow us on Twitter, and join the conversation on Discord.

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New Windows Core OS platform blog

While Windows Vista might have had a mixed reception, its server-based sibling Windows Server 2008, included one of the most important Windows Server features ever. 

Which feature is that?

Hyper-V, of course! Hyper-V is Microsoft’s virtualization platform, more commonly referred to as a Hypervisor. For anyone that isn’t familiar, a Hypervisor allows you to run multiple virtual machines on a single physical server. 

Microsoft recently confirmed that all Infrastructure as a Service (IaaS) and Platform as a Service (Platform as a Service) services including Virtual Machines, Web Apps, Azure Functions, and more all run on Hyper-V in a blog post on their new Windows Platform OS Blog. 

In the post, they detail the Azure Host Operating System, named Cloud Host, which is based on Windows and Hyper-V, but purpose built to be really good at running Virtual Machines. Which is kinda important for a public cloud!

It’s an interesting read, there is even a screenshot of Cloud Host running on an Azure host with 16 physical processors. Imagine how much serverless code you could run on that server!

If your company, like many others, still have workloads running on older versions of Windows Server, it’s probably important for you to know that Microsoft will let you run older versions of Windows Server on Azure or Azure Stack and receive extended security updates for free.

For anyone thinking, surely no one is STILL running Windows Server 2008…think again! Windows 7 market share is still estimated to be about 11%. There are servers hidden away everywhere running older versions of Windows.

For Windows Server 2008, 2008 R2, and Windows 7 on Azure, extended security updates ended on January 10. If you don’t want your company making news headlines for all the wrong reasons, it’s now past time to migrate those workloads to something more modern.

There are plenty of options, you can migrate to a newer version of Windows Server, or maybe there is a Software as a Service (SaaS) solution that can replace your aging app. Or maybe the functionality can be replicated in a Platform As a Service offering like Azure App Service.

We know how hard it can be to migrate or upgrade these workloads, see what you can do, and good luck getting those workloads migrated or decommissioned. Everything you do to help maintain the security of your customer’s data is worth the effort.

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Azure Automation Visual Studio Code extension

Microsoft announced the release of the Azure Automation Visual Studio Code extension in preview.

For anyone that isn’t aware, Azure Automation is an underrated Azure service that lets you (among other things) automate your hybrid computing woes away through Runbooks. Wayne Hoggett went into some detail about why he loves Azure Automation in a recent ACG blog post.

The Visual Studio Code extension for Azure Automation allows you to not only create, test, debug, and manage Azure Automation Runbooks, but it also lets you manage all the associated assets that make Runbooks so useful, like schedules, variables, and credentials right from Visual Studio code.

If you’re an ACG subscriber and you’re interested in learning more about Azure Automation, we have a couple of brand new Hands-on Labs where you can learn how to Automate Hybrid Processes or Configure Update Management Using Azure Automation.

General availability of Azure OpenAI Service

General availability of the OpenAI service was announced this week. While the announcement had the usual sprinkling of marketing buzzwords, it did also state that AI integration is coming to everything across Azure, including security, reliability, compliance, data privacy, and built-in Responsible AI capabilities. Yes, AI is being embraced big time on the Azure platform, and Microsoft is not holding back. AI is going to be the accelerator for cloud services and solutions in the very near future. Is it perfect? No, of course not, but it will improve rapidly.

If you want to see how the AI cookie is made, then Azure Machine Learning is the place. And this month a bunch of new features entered both preview and GA. A few highlights: 

• The ability to build an end-to-end model training pipeline without needing to write any code. This is in line with a move to more and more services that require less and less code.  
• Compare different pipelines to debug failure: You can now save debugging time with new insight into why a specific pipeline may have failed. There is also a feature to identify problematic nodes for debugging.  
• You can now secure the ingress and egress of managed online endpoints to ensure compliance with enterprise security standards. 
• And finally, you can now add, view, update, and/or delete customized tags on your workspaces and computes to gain deeper insights into cost patterns, spend patterns, and governance scenarios.  

There’s even more new features than just the above, so to check them all out go visit the general availability updates, or the preview announcements.

Want to keep on top of Azure News each week?

Azure This Week is your weekly news roundup for all things Azure. Join our expert hosts as they cover everything you need to know about the past week’s developments, keeping it short, fun and informative. 

Whether you’re just beginning your cloud journey, or you know your stuff, there’s something for everyone!

S3 encrypts by default

S3 now automatically encrypts all new files by default. It uses S3-managed, server-side encryption also known as SSE-S3 to all new objects that you upload, at no additional cost and with no impact on performance.

Now this type of encryption uses AES-256 bit encryption, which is an industry standard for server side encryption. And this is will be applied to all new, and existing, buckets. New objects that are uploaded will be encrypted, but existing objects will not change.

You will still be able to specify other types of encryption, for instance SSE-C, which uses customer-provided encryption keys, or SSE-KMS, which uses KMS-managed encryption keys, but you will not be able to disable automatic encryption for new objects.

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Train Sagemaker Canvas models 3x faster

Sagemaker Canvas can now train machine learning models up to 3 times faster than before.

And if you aren’t familiar with Sagemaker Canvas, it is a service that allows business analysts to generate Machine Learning predictions, using a visual interface, without needing any machine learning expertise. It provides a drag and drop interface which means you can easily generate predictions without having to wrote any code.

And with this announcement, they have made some significant performance optimizations, enabling you to build machine learning models that are able to train up to 3 times faster than before. This is going to be great for companies who need to experiment rapidly with different models, quickly create prototypes, and achieve their business outcomes much faster.

Two new Kendra connectors – S3 and Google Drive

Amazon Kendra now has 2 new connectors that allow you to easily index and search documents that are hosted in S3 and in Google Drives well.

And of you haven’t used Kendra before, it is an intelligent search service, powered by machine learning, that allows you to search structured and unstructured data using natural language processing. So this means you can ask it questions using normal language instead of having to write complex code or queries.

For instance you could ask Kendra to search an FAQ document that you have provided, and ask it questions like “How do I configure a VPN?” and it will find that information for you in the document provided.

Now there are 2 new connectors, the first one is for S3, and this allows you to securely index and search documents stored in S3, including the metadata that is stored for each object. This new connector enables Kendra to use a VPC to connect to your S3 data source, which means you do not need to access the data using the public internet.

The second new connector is for Google drives and this allows you to index and search documents that are stored in your own Google Drive, and in drives that are shared with you. This includes documents like HTML files, Powerpoint presentations, PDFs, Word documents, and structured documents like CSV files.

AWS Clean Rooms available in preview

One of the many data security announcements from last year’s re:Invent was a first look at a new service called AWS Clean Rooms. This month, AWS announced that you can get hands-on with clean rooms, as it’s now available for preview in 11 different regions.

Clean rooms are designed to keep your business data secret and safe, while still allowing analysts to draw insights from your collective data. Invite collaborators and finely control what data and queries can be used by each clean room participant. This is a great new secure way to collaborate on data insights while making sure your sensitive data remains secure and encrypted during analysis.

This will be great for marketing and advertising campaign analysis, or any case where you want to collaborate on data analysis without exposing all of the underlying data.

AWS Network Firewall now has IPv6 support

In other security news, AWS announced this month that AWS Network Firewall now has full IPv6 support.

Network Firewall is a managed firewall service that allows you to filter traffic to and from your VPCs or on-premesis network. You can now enable Network Firewall endpoints to filter both ipv4 and ipv6 traffic in any of your dual stack subnets. On top of that, this feature comes at no extra cost to those who want to use this new functionality.

Get the Cloud Dictionary of PainSpeaking cloud doesn’t have to be hard. We analyzed millions of responses to ID the top concepts that trip people up. Grab this cloud guide for succinct definitions of some of the most painful cloud terms.

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New maximum concurrency feature for Lambda & SQS

Also this month, AWS announced a quality of life update that’s sneaky-exciting for serverless developers.

Scaling out Lambda invocations to ingest events from an SQS queue has always been an extremely powerful serverless pattern. However, some customers run into an issue with maximum Lambda concurrency when they scale out to too many concurrent invocations, hitting their account limit. This causes events from an SQS queue to be sent back to the queue or dropped to a dead letter queue. You can set a maximum concurrency limit for your Lambda, but this doesn’t fix the issue of dropped messages.

AWS has now announced per-source maximum concurrency limits for your Lambda functions when ingesting messages from SQS. This means that you can define a limit of concurrent lambda invocations for a given SQS queue, and excess messages will be held in the queue until there is capacity for more concurrent lambda invocations.

This means no more fiddling with returned messages or dead letter queues, and a greater degree of control over your account’s Lambda concurrency limit.

Serverless Application Model integrates with CloudFormation Linter

One of our predictions at the top of the year was that AWS would continue to invest in the Serverless Developer Experience in 2023. AWS has already started to deliver, announcing an update to the serverless application model command line interface that is sure to make developer’s lives easier.

The Serverless Application model, or SAM for short, is an Infrastructure-as-Code platform that allows you to define and reuse AWS architecture in simple JSON/YAML format. This month AWS announced a new lint tool that will speed up development processes by checking your SAM template against a set of CloudFormation-based rules.

Now, whenever you run the sam validate command, you can optionally lint your template against this set of rules. This will make it much easier for SAM users to validate their SAM templates before deploying it, saving users lots of time and money.

Amazon OpenSearch Serverless is now generally available. And if you haven’t used OpenSearch before, it is a service that allows you to perform interactive log analytics and real time application monitoring, and you can also use it to visualize your application data and create dashboards to really understand what is going on inside your applications. And it is based on Elasticsearch.

Now before this announcement, using Amazon OpenSearch involved creating an OpenSearch cluster consisting of multiple EC2 instances running worker nodes and master nodes. And when designing a cluster like this, you need to understand your capacity requirements.

But with this announcement, there is now a serverless option, which is a much simpler way to get started. It means you don’t need to think about infrastructure requirements. And this is also great for variable and unpredictable workloads, because being serverless, it will scale automatically and it will even allow you to run petabyte-scale workloads.

But the best thing about it is that being serverless, you will only pay for what you are using, instead of paying for multiple large EC2 instances.

Another cool announcement for OpenSearch is that it now allows you to perform an enhanced dry run of any configuration changes to your OpenSearch cluster before you go ahead and apply the changes. This applies to OpenSearch clusters that of course consist of multiple EC2 instances.

So you can now validate configuration changes before applying them, and the OpenSearch service will check for validation errors, and it will also let you know if the change would require a blue / green deployment. So it’s going to tell you if you would need to deploy new instances in order to apply the new configuration, or if the configuration can be applied to the exiting instances in your cluster.

This feature is going to be great for those of us who are a little risk averse when it comes to making changes to the configuration of an OpenSearch cluster, and it’s gonna help us avoid applying changes that are going to break our cluster.

Porting Advisor for Graviton

Porting Advisor for Graviton is generally available, and Graviton is of course the name of the latest AWS processors, that are custom-built by AWS, optimised to deliver the best price and performance for AWS based workloads.

Graviton processors are available in a variety of different EC2 instance types, however as these processors utilise the Arm64 instruction set – which is the language used to tell the processor what to do – there can occasionally be additional steps required for applications that have been developed to run on x86 processors, because x86 uses a different instruction set.

It’s great that AWS have acknowledged that for some people there are additional considerations that need to be addressed. And they have provided a step-by-step transition guide to help support customers who are planning to port existing applications to Graviton-based instances.

Start building your cloud skills with these 10 fun hands-on projects to learn AWS.

Contiguous IPv6 CIDR Blocks

And lastly, AWS announced the general availability of Amazon-provided contiguous IPv6 CIDR blocks.

But what does that actually mean? Well you can now use the IP Address Manager (or IPAM) in your AWS account, to create contiguous IPv6 CIDR blocks that can be associated with your VPC. This allows you to create sequential CIDR ranges for your VPCs, so that you can implement CIDR ranges that make logical sense for your environment.

And if you no longer need your VPC and you delete it, you will still own the CIDR block and you’ll be able to re-allocate it to another VPC.

Now previously, the only way to get contiguous IPv6 CIDR ranges like this was to bring your own, so this new announcement is going to make it a lot easier for customers who are looking to utilise IPv6.

That’s all the biggest January headlines for AWS! 

Want to keep on top of weekly AWS news?

Check out AWS This Week for your weekly news roundup for all things AWS. Join our expert hosts as they cover everything you need to know about the past week’s developments, keeping it short, fun and informative. 

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Small bricks build big ships…

I remember a distinct Christmas morning when I was a child. I had wanted this spaceship Lego set and I may or may not have gotten a hold of the wrapped box to try and ascertain if that was indeed what was inside. I went to bed excited for the morning with the hope that I was right. 

I was! 

There was the massive frozen planet spaceship in all its glory. I excitedly opened the box and then paused… that was a LOT of pieces. So I pulled out the instruction book. That… was a LOT of pages. 

One of my parents took a look at the instructions and noticed that it broke down the spaceship into five components. They told me to just take it one component at a time, so I did. After all five components of the spaceship were complete, it was easy to see how they all fit together into a single unit.

… And it’s the same with the cloud

When moving an application to the cloud, especially with cloud transformation in mind, it can be difficult to see where to start. Instead of looking at the application as a whole, break it down into its component parts and apply the concept of cloud transformation to each component. Just like the giant Lego spaceship, we know that all of the pieces go together. 

This is not to say that we don’t have to take the whole architecture into account (we do) but we can explore our options at the component level while we explore the whole. Complex applications can make this more challenging but the principles used for a simple application migration can be applied even to complex ones. 

Using our Lego analogy, each of these components can be tackled one at a time for cloud transformation alternatives. Each needs to be evaluated independently to some extent based on your business needs. In some cases your component migration will involve less transformation for business reasons, and for other components you may end up re-thinking its operation entirely. 

An example of component based thinking with Azure

Let’s take a quick look at a database. Below are several, but not all, of the different types of database services offered in Azure. Each of these services tackle database technologies in different ways.

We may decide to do a direct migration from one technology, on-premises, to the same technology in the cloud (for simplicity’s sake). We might also have additional reasons, for example our database engineers may not need retraining immediately. Ok, great! If these business reasons make this decision a priority then it informs how we look at our next component. 

We need to make sure that whatever we choose for our API and frontend can work with our database decision. This is how we keep the whole in mind while dealing with the component. I could have built my spaceship components in different ways, but then there’s the risk that it might not have come together in all its spacefaring glory had I done so.

If you’re thinking about migrating an application to the cloud, don’t worry, our new course Moving An Application to the Cloud with Azure is for you!

We hope you’ll take a look and that it helps get you started.

(If you’re interested in checking out what our most popular courses were last year overall, check out our article: Top 10 ACG Cloud Courses of 2022).

1. AZ-900 Microsoft Azure Fundamentals

Certification courses are always popular, so naturally an Azure certification course topped our list. In early 2019, Microsoft developed the AZ-900 Microsoft Azure Fundamentals certification as an entry point for all students keen to begin navigating their way around the Azure cloud platform. A Cloud Guru partnered with Microsoft to create this course for our learners, and it has been immensely popular.

This course is taught by Azure superstar Lars Klint, and if you’ve had the pleasure of taking one of his courses, you’ll know that it’s anything but dry! Expect him to use everything from space rockets to coffee machines to explain basic concepts, making everything about Azure accessible for any audience. By the end, you’ll have a firm grasp of the different kinds of Azure tools and solutions available, as well as a smile on your face.

Check out this course: AZ-900 Microsoft Azure Fundamentals

2. AZ-104 Microsoft Azure Administrator Certification Prep

Our second most popular course covers a more advanced certification aimed at anyone aspiring to become (or currently working as) an Azure Administrator. A typical Azure admin implements, manages, and monitors identity, governance, storage, compute, and virtual networks in a cloud environment. This course gives you all the knowledge you need to do that, and trains you in the subject areas you need to memorize to pass the exam.

This eight-hour course is handled by the tag team of Chase Dovey and Robert Burnett, and boasts 23 hands-on labs you can use to get practical experience on top of the video lessons.

Check out this course: AZ-104 Microsoft Azure Administrator Certification Prep

3. Introduction to Azure

Want a crash course in Azure that you can fit into two hours? This course by Matthew Ulasein offers a sift starting point for learning the fundamentals of not just Microsoft Azure, but cloud computing in general. If you’re an absolute beginner, this is a perfect “start here” location for kicking off your career in cloud and Azure.

By the end of this course, you should know the fundamental concepts of cloud computing, have an overview of Azure’s organizational hierarchy and global infrastructure, the core services Azure offers and the business solutions these solve.

Check out this course: Introduction to Azure

4. Azure Concepts

The second in our introductory crash courses to Azure, this one was also very popular, and is a bit shorter than Introduction to Azure. It’s also completely free, and there’s nothing better than that, right? This course focuses more on the concepts around Microsoft Azure than Introduction to Azure, going over the core components of the Azure flavor of cloud, and how companies are using Azure today. And again, because it’s worth repeating, it’s completely free!

Check out this course: Azure Concepts

5. AZ-500 Microsoft Azure Security Technologies

Cybersecurity is one of the top five tech careers of 2023. In January 2023, there were 750,000 cybersecurity-rated job postings open across the U.S., with only enough professionals to fill 68% of those roles. It’s also one of the largest skill gaps tech professionals report having, according to Pluralsight’s State of Upskilling 2022 report. So it’s no surprise that this Azure cybersecurity certification is among the most popular courses on A Cloud Guru!

This course is ideal for people who are performing security tasks in their day-to-day job, or want to become Azure security specialists. It is designed to prepare you to sit for and pass your exam and to prove your skills in implementing secure solutions, services, identity, and operations within the Azure platform.

There are 17 hands-on labs, 16 course quizzes, and a practice exam for you to take, all on top of the robust 42 hours of lessons provided by veteran Azure technical trainer and solutions architect James Lee.

Check out this course: AZ-500 Microsoft Azure Security Technologies

6. Introduction to Azure DevOps

DevOps ain’t dead: it made the list of Pluralsight’s top skills for 2023, and it’s been one the most searched-for terms on Pluralsight and A Cloud Guru for the last three years. Gartner listed it as a “critical needs” skill in 2022, with a high number of open U.S. jobs calling for professionals with DevOps experience. The wages are also pretty great for anyone with DevOps or cloud certifications.

With all that in mind, learning more about Azure DevOps is a no brainer. In this course you will become familiar with Azure DevOps (formerly known as VSTS and before that, VSO) and explore the five services that make up Azure DevOps. Whether you are a developer or not, working alone or in a team, Azure DevOps can help you organize the way you plan, create and deliver software.

Check out this course: Introduction to Azure DevOps

7. AZ-204: Developing Solutions for Microsoft Azure

Did you know the average cloud solutions architect makes $153,105 USD per year? Both solutions architecture and cloud are hot fields, and anyone with both these skill sets are in incredibly high demand. This practitioner-level course is designed to help you obtain the knowledge and skills required to sit the AZ-204 Developing Solutions for Microsoft Azure exam. By the end, you’ll have hands-on experience designing, building, testing, and maintaining cloud applications on Microsoft Azure.

This course generally assumes you’ve got one to two years experience working with Azure services such as containers, databases, and functions, so if you don’t have this, it may be a bit of a challenge for the uninitiated.

Check out this course: AZ-204: Developing Solutions for Microsoft Azure

8. Microsoft Certified: Azure Data Engineer Associate (DP-203)

We live in a data-rich world where the size, complexity, and uses of data are growing exponentially every day. The modern data engineer must build solutions to move, transform, and consolidate both structured and unstructured data from a variety of sources. Azure provides all the necessary services to accomplish these tasks and build a robust data analytics solution. By getting the title of Microsoft Certified: Azure Data Engineer Associate, you can communicate to the world that you’re able to build these solutions.

This popular course teaches you exactly what you need to know to pass the exam, have a strong foundation in data engineering is and how Azure meets the needs of this role, as well as performing practical tasks such as data storage, data ingestion and transformation, building batch and stream processing, and more.

Check out this course: Microsoft Certified: Azure Data Engineer Associate (DP-203)

9. AZ-305: Designing Microsoft Azure Infrastructure Solutions

This course by James Lee covers everything you need to know to sit (and pass!) the AZ-305: Designing Microsoft Azure Infrastructure Solutions exam. This robust 35-hour course offers 13 hands-on labs, 14 course quizzes, and 3 practice exams so you are as prepared as you possibly can be to get your certification. It also covers how you can apply the knowledge you gain when architecting Azure solutions in the real world.

Check out this course: AZ-305: Designing Microsoft Azure Infrastructure Solutions

10. AZ-400: Designing and Implementing Microsoft DevOps Solutions

If you’re ready to become a true cloud guru, this popular course may be for you. Going through this course, you will gain hands-on experience designing and implementing DevOps processes and practices, but the lion’s share of the content is prepping you to meet the AZ-400 exam objectives. Matthew Ulasein, Alex Potasnick, and Mark Mikula form an unstoppable force to teach you everything you need to know, with plenty of hands-on labs, course quizzes, and practice exams to make sure the certificate is as good as yours the moment you sit the exam.

Check out this course: AZ-400: Designing and Implementing Microsoft DevOps Solutions

1. Hybrid cloud computing  

Many organizations are expected to continue to adopt a hybrid cloud model, which allows them to use a mix of on-premises, private, and public cloud services to meet their specific needs. This can provide greater flexibility and scalability, as well as the ability to choose the most appropriate platform for different workloads and data. Hybrid is becoming more and more important as companies moved gradually to the cloud, either with an aim to do it 100% or just have certain services on it.  

Azure will continue to invest in hybrid cloud services and products to make it as seamless as possible to move your “Llama Party Planner” app to the cloud!

2. Edge computing

With the proliferation of connected devices and the increasing amount of data being generated, there is a growing need for edge computing, which involves bringing computing power and storage closer to the data source. Think fruit quality data for each tree in an orchard, weather station observation data, live video streaming processing and much more.

Azure will create more hardware for running Azure services on the edge, and there will be more focus on moving data processing to the device that is collecting the data, such as an autonomous vehicle. It needs to know immediately what to do in any given scenario, as it is driving along and evaluating and reacting to the real world.  

If you want to know more about autonomous vehicles and edge computing, check out the first episode of my new podcast TECHnically Possible.

3. Artificial intelligence and machine learning

Cloud computing has made it easier for organizations to access and utilize advanced AI and ML technologies, and this trend is going to continue. These technologies can be used for a wide range of applications, including image and speech recognition, predictive maintenance, and personalized recommendations. Or what about AI chat services, like ChatGPT, which wrote this joke. 

A cloud, a news show host, and a llama walk into a bar. The cloud starts to pour rain, and the bartender says, “Hey, we don’t want any of that bad weather in here!” The news show host says, “Don’t worry, I’ll just turn on the lights and we’ll have a special report on it.” The llama looks at them and says, “I’m just here for the alpaca-ccino.” 

Okay, that might need some work…

4. Containerization

Containers are a lightweight, portable way to package and deploy applications, and they have become increasingly popular in the cloud. They allow developers to easily move applications between different environments and can help to improve the efficiency and scalability of cloud-based applications. 

We are going to see more focus on making containerising your apps even easier and integrate the services with other Azure products. Perhaps AI in containers? ?

And finally…

5. Security

Ensuring the security of cloud-based systems and data is a top priority for many organizations, and Azure will continue to invest in and improve their security measures. We will see much more investment in protecting against data breaches, such as securing the use of storage and VMs.  

Compliance with even more stringent regulations will make sure us cloud consumers feel even safer using the services, and I would personally love to see something that monitors access and permissions to Azure resources even more. Maybe AI again can help out here? 

Want to keep on top of Azure News each week?

Azure This Week is your weekly news roundup for all things Azure. Join our expert hosts as they cover everything you need to know about the past week’s developments, keeping it short, fun and informative. 

Whether you’re just beginning your cloud journey, or you know your stuff, there’s something for everyone!

#5 Azure Managed Grafana

I was going to do a top 52, but management said I had to keep it to 5. Sorry. Anyway, number 5 is one of the great words in tech: Grafana. Back in September Brian Roehm shared the story of Azure Managed Grafana.

Grafana is already widely used, but with this integration into Azure, all your Azure project dashboards could access the benefits of Grafana much easier. In particular, developers can integrate services on Azure as well as off Azure with the Managed Grafana instance, giving just that bit more flexibility.  

#4 Azure Monitor and one-minute alerts

Number 4 is getting even more use from Azure logs, in particular Azure Monitor.

Almost a year ago in January Wayne Hoggett told us about the usefulness of having alerts from your logs every minute. And while this might not sound terribly exciting, it is one of those small improvements that make a huge impact on your production stability and reliability.

Knowing as fast as possible when there is an issue is often critical to both fix the issue, but also minimise the impact. Apparently you thought so too with your views!

#3 Microsoft’s largest DDoS attack

This was one of those stories that you couldn’t look away from. Azure described their biggest DDoS attacks in 2021, as well as mentioning casually that Azure on average gets attacked from cyber criminal elements almost 2,000 times a day!

Oh, the biggest you ask? Yeah, it was 3.47Tb of data per second, or about 300GB of data being sent to a service every second. Which is a lot! As far as I know that is still the biggest attack on Azure.  

As I said back in February, DDoS won’t go away any time soon either. As long as bandwidth is cheap, plentiful, and accessible, we will see larger and larger attacks. They are easy to do. On the upside, Microsoft seems to be on top of the defense and there hasn’t been any successful attacks for some years (that we know of at least).  

#2 Azure exam sandbox

At number 2 is the Azure exam sandbox. As James Lee explained in January of 2022, you can now get familiar with the Azure certification exam format before you take it.

The exam sandbox shows question types and formats, as well as lets you do test questions, all without the time pressure or fear of failing it. It is a neat way of getting familiar with the process before you sit an actual exam yourself.

If you want even more sandbox experiences, we have world class Azure hands-on labs on the A Cloud Guru platform too, which can help you learn a ton of cloud stuff by actually doing it. 

And speaking of exams, by far the most popular topic on the show has been certifications. New certifications, updated certifications, certification mid-year updates, predictions, you just love it all.  

We got AZ-800 and AZ-801 for Windows Server Hybrid Administrator Associate, as well as AZ-720 Azure Support Engineer as all new shiny fresh smelling certifications. And on top of that there were updates to AZ-900, DP-900, AI-900, AZ-104, DP-300, AZ-600, AZ-305, and AZ-400.  

I get why certifications are top of the list to be honest. They transform careers, team capabilities and lives of many people. Which is also why we put so much time and effort into the courses for each of them!

Oh, and if your head is swimming with all these numbers, and you’re wondering where to start with your Azure studies, the best place to begin is our Azure Certification Guide.

So that’s all the biggest 2022 headlines for Azure wrapped up! 

Want to keep on top of Azure News each week?

Azure This Week is your weekly news roundup for all things Azure. Join our expert hosts as they cover everything you need to know about the past week’s developments, keeping it short, fun and informative. 

Whether you’re just beginning your cloud journey, or you know your stuff, there’s something for everyone!

Before you decide to use Amazon QuickSight as your BI solution, there are a few things to consider in order to make sure it will meet your cost and performance needs. QuickSight pricing and administration can be hard to parse, but I’ve broken down the main components in this article in order to give you a head start on your QuickSight journey.

So, before you dive right in to QuickSight, ask yourself these three questions:

1. How many users do you need?

The biggest driver of cost for Amazon QuickSight will usually be the number of users provisioned for the application. Users are basically broken into two roles: Authors and Readers.

Authors are the users that will be creating datasets from your data sources, and authoring data visualizations. Each Author user has a flat, monthly price ranging from $12/month to $34/month (USD), depending on the feature package you choose. You can also reduce this range to $9/month to $28/month if you choose to prepay annually rather than pay month-to-month.

Readers pay per-session, rather than per-user. A reader can be given permission to view and interact with authored dashboards, but cannot edit or author them. A reader session costs $0.30/session, and each reader user has a monthly maximum cost, which is usually $5. So, even if a reader logs thousands of sessions in a month, the most you will ever be charged for that reader is $5. But if a reader doesn’t use QuickSight at all, you pay nothing! That’s one of the great things about pay-as-you-go pricing models.

2. Where are your users and your data?

This is something we don’t often think about when it comes to hosting applications in the cloud; but before you provision QuickSight, it’s important to consider where your users and data live, in a physical sense.

If you are mostly concerned about cost, think carefully about where your data is, and make sure to provision the QuickSight application in the AWS region that is closest to your data. After all, if your data is hosted on AWS, you will be paying for the data transferred to QuickSight for analysis. So the closer your QuickSight application lies to your data, the more performative and cost-effective those data transfers will be. For example, if you use the us-west-2 region to host the RDS databases that you wish to analyze in QuickSight, you should provision QuickSight in us-west-2.

If you are concerned mostly with end-user performance, it is also important to consider where your users will physically be when they access the QuickSight application. Provisioning QuickSight in a region closer to your end users will result in a snappier, more performative user experience.

The different feature packages offered in Amazon QuickSight differ drastically in price, and it can be difficult to tell which package is appropriate for your organization. Most of the time, this decision comes down to how you want to share the data visualizations you have created.

Standard Edition is the most basic QuickSight package, and it’s a great place to start dipping your toes into QuickSight. You pay $12 per author per month, and you cannot provision readers. This means that all visualizations will only be able to be accessed on the QuickSight application, and only by authors. This works great for small teams that only need to grant access to dashboards internally.

Enterprise edition costs $24 per author, but allows many more methods of sharing your dashboards and reports. With Enterprise edition, you can provision readers, embed dashboards into web applications, send out periodic email reports, and much more. You also get more robust and fine-grained features for data security and access to your data sources. Enterprise edition is great if you have tens or hundreds of readers: users you want to give access to view your data visualizations.

QuickSight also offers a myriad of add-on features, including Reader Session Capacity Pricing, Paginated Reports, and QuickSight Q. My general advice for these add-ons is to start with the most basic viable feature package you can, and only upgrade or add-on if you find the additional features are worth the price. It’s very easy to upgrade, but downgrading can cause complications with your existing dashboards.

Conclusion

Pay-as-you-go pricing is one of QuickSight’s greatest strengths, but it can also create more up-front work to understand your organization’s needs for your BI solution. This article should give you just enough information to get started with QuickSight, but there’s still the matter of connecting data sources, creating datasets, authoring visualizations, and sharing your visualizations!

To answer any and all questions you might have about using Amazon QuickSight, check out my course “Amazon QuickSight Deep Dive”. This course is designed for AWS administrators provisioning QuickSight, data analysts using QuickSight, or anyone who might fall between. 

Good luck on your journey for data insights, take care of each other, and keep being awesome!

Check out the list below to see what our talented tech gurus found the most useful, along with a brief summary of what each article covers.

1. What’s free at ACG

Let’s be honest, everybody loves free stuff. It’s honestly no surprise that this list of free courses was the most popular. We update this article every month, so check it out! This list often includes free courses for AWS, Azure, GCP, Linux, cloud security, Kubernetes, DevOps training, and more!

Read the article: What’s free at ACG

2. 8 AWS jobs you can get with an AWS certification

You know what people love almost as much as free stuff? Certifications — and at the top of that list is usually AWS certs. But after you get one, what then? This article answers just that, such as the jobs you might be qualified for and can land with your shiny new certificate, and how much you can expect to earn.

Read the article: 8 AWS jobs you can get with an AWS certification

Here at A Cloud Guru, we love us some Serverless! But between all the offerings — AWS Lambda, Azure Functions, and Google Cloud Functions — it can be hard to tell which one is the “King of Serverless” (Yes, this is an official title, and there’s a belt and everything). That’s why in this article, we pit these offerings against each other to determine which service reigns supreme. After all, there can only be one!

Read the article: Serverless showdown: AWS Lambda vs Azure Functions vs Google Cloud Functions

This was an incredibly popular article this year! In it, we share how you can schedule CloudWatch Event Rules to thaw AWS Lambda functions and help reduce response times from three seconds to a couple hundred milliseconds. However, the age of Lambda cold starts may be over given the latest news from AWS re:Invent 2022, where AWS released Lambda SnapStart. 

We’ve written up a summary of the details here on our blog at Lambda SnapStart: What we know from re:Invent 2022, and there’s a great blog detailing this release by Jeff Barr himself, titled Accelerate your Lambda Functions with Lambda SnapStart.

Read the article: How to keep your AWS Lambda functions warm

5. Microsoft certification renewals and expirations explained

In 2021, Microsoft made some big (and welcome) changes to the way they handle certification expirations and renewals. Our man on all things Microsoft, Lars Klint, explains everything you need to know about how it impacts your Azure certifications in this article. In his words, ‘What are you waiting for? Go on, read it!’

Read the article: Microsoft certification renewals and expirations explained

6. How to troubleshoot 5 common Terraform errors

Terraform was our most searched-for term in 2021, and it’s still plenty popular today. If you’ve got Terraform state and language errors, make sure to read this article by Jess Hoch. It covers the five most common Terraform errors you’re likely to encounter while managing infrastructure (and how to troubleshoot them).

Read the article: How to troubleshoot 5 common Terraform errors

7. CDK vs Terraform vs CloudFormation: A guide to IaC on AWS

Another comparison article, this time by Jared Short! He compares CDK against Terraform and CloudFormation, and answers which one is best for you when it comes to Infrastructure as Code (IaC) tools on AWS. He even provides a handy chart on the situations you should consider using each offering.

Read the article: CDK vs Terraform vs CloudFormation: A guide to IaC on AWS

8. How to build a multi-region active-active architecture on AWS

This is a great article, not only because it starts with a quote from Arthur C. Clarke. It explains the why and how of designing a multi-region active-active architecture in AWS. It’s worth noting this is the second entry in a series on building this kind of architecture (The first of which you can find here).

Read the article: How to build a multi-region active-active architecture on AWS

9. Serverless browser automation with AWS Lambda and Puppeteer

Programmatically controlling a web browser enables you to automate many useful tasks with code. For many of these, you can use Lambda to minimize infrastructure overhead and simplify scaling. This handy blog post shows how to deploy an example application that uses a headless browser to take periodic screenshots of a webpage.

Read the article: Serverless browser automation with AWS Lambda and Puppeteer

10. An Inside Look At AWS Secrets Manager vs AWS Systems Manager Parameter Store

AWS Secrets Manager is a service that helps you protect access to your apps, services, and IT resources. In this article, Craig Arcuri explains how it compares to Parameter Store, including the similarities and differences between the two.

Read the article: An Inside Look At AWS Secrets Manager vs AWS Systems Manager Parameter Store

It’s hard for us to pick out the best articles of 2022 — if we don’t like them, we don’t publish them! But with great effort, we’ve made a list of the stand-out articles we feel you should check out. 

1. Cloud Adventures: 5 Fun, Free Cloud Computing Courses To Try

Remember how I said everyone loves free stuff? Or, okay, you might have skimmed that line, but I’m not the reading police. Well, five Cloud Adventures courses are among those free things you can take! Cloud Adventures are not your average cloud computing training. These courses combine learning science with active engagement to help you master cloud technology — that means bite-sized courses with comics, animations, and just generally interesting stuff.

There’s over 20 Cloud Adventures courses in total for everything from AWS, Azure, Linux, Terraform, Kubernetes, Vim, SDS, and more. For the full list, check out the article!

Read the article: Cloud Adventures: 5 Fun, Free Cloud Computing Courses To Try

2. What is multicloud: Understanding the multicloud strategy

2023 is going to be all about multicloud! According to Gartner, more than 80% of organizations use more than one cloud provider, with 75% of organizations defaulting to multicloud environments. But what is a multicloud strategy and how do you know if it’s right for your organization? This article answers that question and more.

Read the article: What is multicloud: Understanding the multicloud strategy

3. Multicloud Fluency: 6 reasons you should learn multiple clouds

Learning multiple clouds makes a lot of sense from a career standpoint, even if your organization only uses one cloud provider. Mattias Andersson explains it best in this article, and also shares his own experience on how hard it is to become multicloud proficient.

Read the article: Multicloud Fluency: 6 reasons you should learn multiple clouds

4. 7 Ways to Jump-Start Your Cloud Computing Career

It’s the entry-level conundrum as baffling as the chicken and the egg. You need a job to get experience, but you need experience to land a job. Most “entry-level” cloud computing jobs ask for years of prior experience, making it difficult to break into the field. Ryan Kroonenburg explains how you can break this vicious cycle.

Read the article: 7 Ways to Jump-Start Your Cloud Computing Career

5. Our “What Certification is right for you?” series

Okay, so this is a bit of a cheat, since it’s not one article, but three. Our gurus have written some handy guides on how to pick the right cloud certification for you from popular providers like AWS, Azure, and GCP. 

6. Tech worker burnout: What it is, and how to deal with it

Are you feeling burned out? It’s not uncommon at all — two in five IT professionals are at high risk of burnout, and if you’re working in cybersecurity, it’s more than half. Whether you’re a manager or a staff member, this guide will help you identify the signs of burnout (in yourself and others), as well as share what you can do to fight it.

Read the article: Tech worker burnout: What it is, and how to deal with it

7. Can I shift my SQL language skills from on-prem to Azure?

This one makes the list simply because Amy Coughlin is a hilarious writer, and it compares popular Azure solutions to dog breeds. If you need any more reasons than that, I’m sorry, I can’t help you. Just kidding: It does offer great advice on how you can transfer your SQL language skills from on-prem to Azure.

Read the article: Can I shift my SQL language skills from on-prem to Azure?