The latest News and Information on Containers, Kubernetes, Docker and related technologies.
Making an Open Source Software with sensitive data and dozens of external integrations is a real challenge, here are feedbacks and tradeoffs we've made.
Back in May, we announced the Kubernetes integration to help users easily monitor and alert on core Kubernetes cluster metrics using the Grafana Agent, our lightweight observability data collector optimized for sending metric, log, and trace data to Grafana Cloud. Since then, we’ve made some improvements to help our customers go even further.
In this article, we’ll cover the three main challenges you may face when maintaining your own Prometheus LTS solution. In the beginning, Prometheus claimed that it wasn’t a long-term metrics storage, the expected outcome was that somebody would eventually create that long-term storage (LTS) for Prometheus metrics. Currently, there are several open-source projects to provide long-term storage (Prometheus LTS). These community projects are ahead of the rest: Cortex, Thanos, and M3.
Fast build times are great, which is why we aim for less than 5m between merging a PR and getting it into production. Not only is waiting on builds a waste of developer time — and an annoying concentration breaker — the speed at which you can deploy new changes has an impact on your shipping velocity. Put simply, you can ship faster and with more confidence when deploying a follow-up fix is a simple, quick change.
It’s that time again; we’re really happy to announce Calico v3.21! As always, thank you to everyone who contributed to this release! For detailed release notes, please go here. Alongside the usual-but-essential bug fixes and other improvements, there are some big new improvements to be aware of.
Cloud-native transformations come with many security and troubleshooting challenges. Real-time intrusion detection and the prevention of continuously evolving threats is challenging for cloud-native applications in Kubernetes. Due to the ephemeral nature of pods, it is difficult to determine source or destination endpoints and limit their blast radius. Traditional perimeter-based firewalls are not ideal fit for Kubernetes and containers.
Leveraging Terraform, which is an infrastructure-as-code platform, is a great match. Using both technologies together is becoming more mature and there have been some great pieces around the art of the possible between the two platforms. Though if you are unfamiliar with both, this guide will get you up and started with both Terraform and Shipa together. In this example will be using Terraform to create all of the necessary Shipa resources to deploy to a Kubernetes cluster.
