Docker

Have you ever been tasked with pipelining out an existing application in a new tool? This can be a long and daunting task. Especially if your application is multi-service, and mono-repo. I’m not going to get into all of hows and whys of multi-repo vs mono-repo today, but there is always a use case or operational model for each. One of the biggest issues I have run into with multi-serivce mono-repo apps is getting the container builds to work the first time.

In a previous blog we discussed the configuration and use of fluentbit with AWS elasticsearch. https://medium.com/@bahubalishetti/configuring-fluentbit-on-kubernetes-for-aws-elasticsearch-bec486bcc727 It helped provide a basic configuration of “logging” from a Kubernetes cluster. “Logging” is one aspect of “Observability” in Kubernetes. Lets review: Observability for the cluster and the application covers three areas: Monitoring metrics — Pulling metrics from the cluster, through cAdvisor, metrics server, and/or prometheus, along with application data which can be aggregated across clusters in Wavefront by VMware.

As noted in one of my earlier blogs, one of the key issues with managing Kubernetes is observability. Observability is the ability to gain insight into multiple data points/sets from the Kubernetes cluster and analyze this data in resolving issues. As review, observability for the cluster and application covers three areas: Monitoring metrics — Pulling metrics from the cluster, through cAdvisor, metrics server, and/or prometheus, along with application data which can be aggregated across clusters in Wavefront by VMware.