The latest News and Information on Containers, Kubernetes, Docker and related technologies.
Google Kubernetes Engine (GKE), a service on the Google Cloud Platform (GCP), is a hosted platform for running and orchestrating containerized applications. Similar to Amazon’s Elastic Container Service (ECS), GKE manages Docker containers deployed on a cluster of machines. However, unlike ECS, GKE uses Kubernetes, an increasingly popular open source orchestrator that can deploy, schedule, and scale containers on the fly.
As we’ve rolled out Loki internally at Grafana Labs, we wanted logs beyond just simple applications. Specifically while debugging outages due to config, Kubernetes, or node restarts, we’ve found Kubernetes events to be super useful. The Kubernetes events feature allows you to see all of the changes in a cluster, and you can get a simple overview by just retrieving them: This also captures when nodes go unresponsive and when a pod has been killed along with the reason.
If you have anything to do with the world of cloud computing or even programming for that matter, then I’m sure you’ve heard of different terms being tossed around such as “serverless computing” or “containers,” and even “monolithic architectures.” A lot of people who understand such computing methods can have a bad habit of using these terms without leaving any explanation as to what they are.
Harbor, developed by VMware and hosted by the CNCF, is an open source registry for container images and Helm charts. Hosting Harbor within your infrastructure gives you a number of advantages over using the default Docker registry, such as role-based access control, security scanning, and replication of resources between registry instances. Since a failed Harbor deployment can spell trouble for your containerized workloads, monitoring your self-hosted container registry is critical.
Developer teams and even operational teams often ignore monitoring applications. Deadlines, inexperience, company culture, and management can lead to poor or neglected monitoring inside developing platforms. Automating all monitoring tasks is an excellent way to avoid this scenario. Automation leads to lower costs, less time spent solving issues, and more efficient teams.
