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The latest News and Information on Containers, Kubernetes, Docker and related technologies.

Environment variables and Secrets for Qovery v2 released

I am super excited to announce that we released the support of Environment Variables and Secrets. Watch the video to see those features in action. Environment Variables and Secrets are similar. The main difference is that the Secrets are encrypted and the value can’t be revealed. Both are injected at the build and runtime of your applications. Give it a try now! Resources: I am eager to have your feedback. Put a comment here. ‍

Terraform meets AppOps

The growing adoption of microservices and Kubernetes gave rise to the need to efficiently manage, schedule, and control Kubernetes clusters, where tools like Terraform are helping many organizations address those challenges today. Terraform is a popular choice among DevOps and Platform Engineering teams as engineers can use the tool to quickly spin up and edit environments directly from their CI/CD pipelines.

Unlimited Preview Environments with Kubernetes Namespaces

In our big series of Kubernetes anti-patterns, we briefly explained that static test environments are no longer needed if you are using Kubernetes. They are expensive, hard to maintain, and hard to clean up. Instead, we suggested the adoption of temporary environments that are created on demand when a pull request is opened. In this article, we will see the practical explanations on how to achieve unlimited temporary environments using Kubernetes namespaces.

Monitor containerized ASP.NET Core applications with Datadog APM

ASP.NET Core is an open source web development framework that enables you to develop .NET applications on macOS, Linux, and Windows machines. The introduction of .NET Core in 2016 dramatically increased the number of ways to build and deploy .NET applications. This means that you need the ability to easily monitor application performance across a wide variety of platforms, such as Docker containers.

How to Move Kubernetes Logs to S3 with Logstash

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.