Cloud computing, containerization, and container orchestration are the most important trends in DevOps. Whether you’re a data scientist, software developer, or product manager, it’s good to know Docker and Kubernetes basics. Both technologies help you collaborate with others, deploy your projects, and increase your value to employers. In this article, we’ll cover essential Kubernetes concepts. There are a lot of Kubernetes terms, which can make it intimidating.

If you’re thinking about using containers to manage an application, there are a lot of options for technologies to use. It can be difficult to even know where to begin to make a decision. One common question is whether someone should use Docker vs Kubernetes for managing their application containers. This is a misleading question. In truth, Docker and Kubernetes aren’t competing technologies. There’s no need for them to face off.

We’ve all read those op-eds in the Smarter Living section of NYT about impostors syndrome. After all, they have been getting more and more traction as a new generation enters the associate-level in their career.

In the last post, Samuell (from the og-aws Slack group) figured out his negative TTL problems in Cloudfront. During that session, we actually solved two different problems. This post is to finish off that conversation and address the other problem, which was how to use the default error page in Cloudfront.

Welcome to the second edition of Serverless from the Trenches, our series of bite-sized blog posts aimed at developers and DevOps working in serverless. Each article will focus on a different technique or tool to solve a real-world problem and – hopefully – help make your work in serverless more productive. This week we look at how to add Cognito to your integration tests flow, making for true black box testing.

Canary releases are a powerful technique for updating large-scale production environments safely. The idea is simple: deploy the update to a subset of your environment, pause and monitor to ensure everything is healthy, and then deploy to the next subset. But implementing these staged releases can be challenging, as you’ll need to retool your deployment pipeline and build programmatic health checks to validate the success of each canary release.

Last month, members of the Datadog community convened in Seattle for our customer summit. There, they discussed new developments in monitoring dynamic infrastructure and applications, learned about the latest updates to the Datadog platform, and shared tips, tools, and techniques from their own experiences.