Kubernetes Monitoring: Top 5 Tools & Methodologies
A crucial part of Kubernetes monitoring is about choosing the right tool and methodology. This post introduces 5 popular options.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
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Mock APIs: Testing in Agile Environments
Testing in agile environments require many parts coming together, with mock APIs being a crucial part of this.
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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. The continuous version is when you integrate it into your development process as part of a CI/CD pipeline.
Test Automation Streamlines Software Development
Test automation has a variety of advantages, and in this post you'll see how it can streamline software development.
Data & Traffic Are Key to Kubernetes Preview Environments
Preview environments are temporary environments where developers can test code changes before deploying them to production, also called ephemeral environments, they’re temporary and should be discarded after testing changes. Carrying out tests using accurate data is a major challenge when creating and destroying environments. Put differently, you need realistic data and traffic in the preview environment to reflect the performance of code changes in production.
How to Create a Kubernetes Preview Environment
A Kubernetes preview environment is an isolated environment that allows developers to test their code at any time without worrying about how others may be affected. While implementations and use cases may vary, simulating a production environment as closely as possible is the main goal. Imagine you’re part of a team developing a complex API, and you’ve been tasked with adding a new endpoint that relies on features within the codebase currently being optimized by one of your team members.
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.
Optimize Kubernetes Performance Part 3: Streamlining Development
In this third and final part, you’ll get to see a few examples that aren’t strictly related to configuration changes or new tools, but rather ways that traffic replay can help streamline the development process for those deploying in Kubernetes.
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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. But to put it simply: preview environments allow teams to deploy a version of their applications during the development process, interacting with it as if it was deployed in production.
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.