Hey VS kubernetes

We can reproduce the failure with curl or hey tool, so that we have many failed UpdateProduct Lambda functions.

Then I sent several hundreds create product requests via the hey tool like :

As in the previous article we use hey tool to perform the load test like this

The results of the experiment below were based on reproducing approximately 100 cold starts for the duration of our experiment which ran for approximately 1 hour. For it (and all experiments from my previous articles) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman

The results of the experiment to retrieve the existing product from the database by its id see GetProductByIdViaAuroraServerlessV2DataApiHandler with Lambda function with 1024 MB memory setting were based on reproducing more than 100 cold and approximately 10.000 warm starts with experiment which ran for approximately 1 hour. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. We won't enable SnapStart on the Lambda function first.

The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts with experiment which ran for approximately 1 hour. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. I ran all these experiments for all 3 scenarios using 2 different compilation options in template.yaml each:

In our experiment we'll re-use the application introduced in part 9 for this. There are basically 2 Lambda functions which both respond to the API Gateway requests and retrieve product by id received from the API Gateway from DynamoDB. One Lambda function GetProductByIdWithPureJava21Lambda can be used with and without SnapStart and the second one GetProductByIdWithPureJava21LambdaAndPriming uses SnapStart and DynamoDB request invocation priming. We'll measure cold and warm starts using the following memory settings in MBs : 256, 512, 768, 1024, 1536 and 2048. I also put the cold starts measured in the part 12 into the tables to see both cold and warm starts in one place. The results of the experiment below were based on reproducing more than 100 cold and approximately 100.000 warm starts for the duration of our experiment which ran for approximately 1 hour. Here is the code for the sample application. For it (and experiments from my previous article) I used the load test tool hey, but you can use whatever tool you want, like Serverless-artillery or Postman. Abbreviation c is for the cold start and w is for the warm start.

Por último, podemos executar os testes de carga usando hey.

For running our experiments to provoke anomalies we'll use the stress test tool. You can use the tool of your choice (like Gatling, JMeter, Fiddler or Artillery), I personally prefer to use the tool hey as it is easy to use and similar to curl. On Linux this tool can be installed by executing

Containers package applications and their dependencies, ensuring consistency across environments. Using Docker makes it easy to "build once, run anywhere." Kubernetes manages multiple containers to keep complex apps running smoothly.

By 2025, these languages are expected to see wider adoption as cloud technologies continue to evolve. Additionally, tools like Kubernetes, an open-source container management platform, will become even more vital, helping developers efficiently deploy and manage cloud platforms. These technologies contribute significantly to supporting large-scale data processing and simplifying the management and operation of cloud infrastructure.

Kubernetes

Containerization: Technologies like Docker, ModelKits, and Kubernetes to standardize and automate deployments in a controlled, scalable way.

One of those great revolutionary technologies that have transformed how developers think of and Interact with cloud infrastructure is Kubernetes. Initially Developed at Google, Kubernetes, also known as K8s, is an open source system for automating deployment, scaling, and management of containerized applications. It is Designed on the same principles that allow Google to run billions of containers a week, Kubernetes can scale without increasing your operations team.

In the ever-evolving landscape of modern software development, Kubernetes and Terraform stand out as two essential tools for managing infrastructure and applications. While both are critical for modern DevOps and cloud-native ecosystems, they serve different purposes and operate in distinct domains. Understanding the differences between Kubernetes and Terraform is key to leveraging them effectively. Let’s dive deeper into what these tools are and how they compare.

This blog series will walk you through what Kubernetes and Amazon Web Services (AWS) are, how they complement each other, and how you can use them to build internet-scale applications. Part 0 (this post) will introduce the basics. Future posts will include boilerplate code to help you set up your own Kubernetes cluster in AWS and practical examples of building scalable services. Onward!

Example: Kubernetes, a widely used system for managing and organizing software containers, relies heavily on its extensive documentation. Non-developers contribute to its clarity, ensuring that even newcomers can understand how to use the platform.

12. Kubernetes

Kubernetes (K8s) is currently the most popular container orchestrator, originally developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF). It provides a robust platform for automating deployment, scaling, and operations of containerized applications.