Compare tools & learn the best methodologies for efficient Kubernetes load testing, and see how to ensure performance of your app under load.

Managing container environments, such as Kubernetes data planes and ECS requires more than achieving cost savings. Yes, this is a vital component of optimizing your containers. But you also need to optimize for availability and usage, all while having a clear visualization of how your costs break down across compute, network, and storage.

When it comes to choosing the right AWS container optimization solution, building a DIY suite of free optimizer tools may seem like a great idea, but will it provide everything you need? The hidden, total cost of ownership (TCO) for open-source tools can quickly build up, making it a less manageable option when compared to a third-party optimizer. Our helpful list of what you need to consider will help you decide which AWS container optimization solution is right for you: a DIY toolset or a managed suite.

A Docker container is a portable software package that holds an application’s code, necessary dependencies, and environment settings in a lightweight, standalone, and easily runnable form. When running an application in Docker, you might need to perform some analysis or troubleshooting to diagnose and fix errors. Rather than recreating the environment and testing it separately, it is often easier to SSH into the Docker container to check on its health.

Multi-cloud seems like an obvious path for most organizations, but what isn’t obvious is how to implement it, especially with a DevOps centric approach. For Cycle users, multi-cloud is just something they do. It’s a native part of the platform and a standardized experience that has led to 70+% of our users consuming infrastructure from more than 1 provider.

Software development, agility and efficiency are paramount. Continuous Integration and Continuous Deployment (CI/CD) practices have revolutionised the way we build, test, and deploy software. When coupled with the power of Kubernetes, an open-source container orchestration platform, organisations can achieve a level of deployment excellence that was once only a dream.

The rise of containerization has precipitated an unprecedented shift in the software development landscape, with Kubernetes emerging as the de facto standard for managing large-scale containerized applications. One of the more nuanced aspects of Kubernetes that is gaining attention is multi-cluster orchestration. This approach to cluster management offers several compelling advantages that reshape how businesses operate and innovate in a cloud-native context.