Kubernetes Operational Intelligence

Kubernetes Operational Intelligence

Collect Metrics, Events, and Logs

Log structure and tagging

Log structure and tagging

Name space
Kubernetes supports multiple virtual clusters backed by the same physical cluster. These virtual clusters are called namespaces
Pod name
The group of containers for your application
UID
Every object created over the whole lifetime of a Kubernetes cluster has a distinct UID
Image name
The name of the container image
Container name
The container name
Metrics

Metrics

Cluster
Metrics aggregated over all nodes displayed in SPM overview
Host / node level
Metrics aggregated per node
Pod level
Metrics aggregated by pod name
Docker Container level
Metrics aggregated for a single container

Having these data extracted and structured makes it easy to slice and dice Kubernetes metrics and logs, build log analytics reports, and quickly narrow down to problematic pods while troubleshooting.

Alert rules can be created on both logs and Kubernetes / Docker metrics. All Kubernetes cluster nodes and containers are auto-discovered regardless of where you are running Kubernetes – Google Container Engine, Amazon ECS, Rancher, CoreOS, etc. are all supported.

Quick Start

  1. Sign up
  2. Create Logsene App for logs and SPM App for metrics
  3. Grab sematext-agent.yml and enter your SPM and Logsene App tokens
  4. Run Sematext Agent as Kubernetes DaemonSet:
    kubectl create -f sematext-agent.yml
  5. You’re done!
Kubernetes Cheat Sheet

Kubernetes Cheat Sheet

Kubernetes is an open source system for automating deployment, scaling and management of containerized applications that was originally designed by Google and donated to the Cloud Native Computing Foundation. It aims to provide a “platform for automating deployment, scaling, and operations of application containers across clusters of hosts”. It usually works with the Docker container tool and coordinates between a wide cluster of hosts running Docker.

Pygmalios

“We use docker containers for our applications so integration was very easy by creating a new Sematext docker container. Also integrating other applications was easy as Sematext supports them.” Read Case Study

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