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Continuous Load Testing | A Developer's Guide

Continuous load testing is a powerful way of preparing for surges in traffic, without needing real users. Imagine you’re a software engineer working on a website that’s seen a recent surge in traffic. Despite initial testing indicating that the website should be capable of handling the increased load, the website crashes during peak hours. Load Testing is the process of simulating real-world usage of a website or application.

Building a Mock Server from User Traffic in Kubernetes

A mock server can prove useful in many circumstances. Imagine you’re an engineer working on optimizing a feature inside of an existing API that relies on multiple other microservices to function properly. To fully test the optimizations, you’ll have to set up test versions of all the dependencies, which quickly proves to be quite a task in and of itself. This is where a mocks—a server that simulates the behavior of a real server—can be very beneficial.
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Testing Kubernetes Ingress with Production Traffic

Testing Kubernetes Ingress resources can be tricky, and can lead to frustration when bugs pop up in production that weren't caught during testing. This can happen for a variety of reasons, but with Ingress specifically, it often has to do with a misalignment between the data used in testing and the traffic generated in production. Tools like Postman can be a great way of generating traffic, but they have the drawback of being manually created. Not only is this unlikely to create all the needed variations for a single endpoint (different headers, different request bodies, etc.), it would be almost impossible to create all the needed variations, for all possible endpoints.

Optimize Kubernetes Performance Part 2: Creating Comparisons

The main idea behind Kubernetes is to create a standardized approach to running containers in the cloud. Whether you’re running AKS on Azure or EKS on Amazon, your cluster should still behave in more or less the same way. But that’s not to say you’re locked in to doing things one way; Kubernetes still offers a lot of flexibility in many cases. This is what experienced engineers take advantage of when trying to optimize Kubernetes performance.

Optimize Kubernetes Performance Part 1: Cluster Configurations

Kubernetes is a powerful platform that comes with many features to help engineers run their applications more efficiently. However, as you gain more experience and deploy more workloads, you’ll inevitably start looking for ways to optimize Kubernetes performance. There are many ways to approach optimization. On one hand, you could work exclusively with the tools and configurations provided by Kubernetes itself; on the other, you could reap the benefits of third-party tools.

An Overview of Traffic Mirroring Options in Kubernetes

Testing in production carries a lot of risk, like possibly causing downtime for users. However, the advantages of using real user traffic are many, which has led to the popularity of traffic mirroring. Mirroring can be implemented as part of pre-deployment testing, as well as other parts of the developer experience like the development itself. But, how do you get started with it?

Kubernetes Preview Environments - Adoption, Use Cases & Implementations

No matter what application you’re building and who your target customers are, everyone can agree that it’s critical to avoid broken deployments. To aid in this goal, many tools and concepts have been invented, with Kubernetes preview environments being one of them. In this post, you’ll get a deeper understanding of how preview environments work, how organizations are using them, and how you can get started yourself.

The Role of Traffic Replay in Production Traffic Replication

Testing in production is one of the most effective—and risky—ways of testing. The ability to use real-world conditions ensures reliability of tests, as no bugs can appear as a result of misconfigurations of the environment. However, using the same environment as your users also has an obvious downside: any bugs discovered by testing will immediately affect users.