kube-profefe

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Published: Jan 8, 2020 License: MIT

README

Profefe is a project developed by @narqo. I was looking for a solution to do continuous profiling and I realized his code was well abstracted and comfortable to extend. The API server was already done and I decided to write an integration with Kubernetes.

kube-profefe

This project is a bridge between profefe and Kubernetes. At the moment it serves two different binaries:

  • kubectl-profefe a kubectl plugin that helps you to caputre pprof profiles, storing them locally or in pprofefe. It uses port-forwarding to expose the pprof port locally.
  • kprofefe is a cli that you can run as a cronjob in your kubernetes cluster. It discovers running pods in your clusters, it downloads profiles and it pushes them in profefe.

NB: if your configuration does not allow you to do kubectl port-forward the kubectl plugin will not work.

How it works

Golang has an http handler that exposes pprof over http, via annotation we can specify if a pod has profiles to capture and with other annotations we can configure path and port.

The annotations are:

  • profefe.com/enable=true is the annotation that tells kube-profefe to capture profiles from that pod.
  • profefe.com/port=8085 tells kube-profefe where to look for a pprof http server. By default it is 6060.
  • profefe.com/service=frontend tells kube-profefe the name of the service usable to lookup the profile. If the annotation is not specified it uses the pod name. My suggestion is to set this annotation because pods are ephemeral and lookup by pod name may be hard to do.
  • profefe.com/path=/debug/pprof tells kube-profefe where to look for a pprof http server. By default it is /debug/pprof.

Install kubectl-profefe

kubectl-profefe is a kubectl plugin designed to gather profiles from your local laptop and store them locally or in profefe.

In the release page in github we push binaries and containers (thanks goreleaser), you can download the tar.gz for your architecture and move the kubectl-profefe in your PATH. In this way it will work as kubectl plugin:

kubectl profefe --help

Getting Started with kubectl-profefe

Start minikube and deploy this pod:

apiVersion: v1
kind: Pod
metadata:
  name: influxdb-v2
  annotations:
    "profefe.com/enable": "true"
    "profefe.com/port": "9999"
spec:
  containers:
  - name: influxdb
    image: quay.io/influxdb/influxdb:2.0.0-alpha
    ports:
    - containerPort: 9999

Now you can capture the profiles:

kubectl profefe capture influxdb-v2

The profiles are stored inside your /tmp directory (you can change it with --output-dir), so you can read it with go tool pprof:

go tool pprof /tmp/profile-goroutine-influxdb-v2-1575552135.pb.gz

If you have a profefe up and running you can push your profiles there other than locally:

kubectl profefe capture influxdb-v2 --profefe-hostport http://localhost:10100

Directories

Path Synopsis
cmd
pkg
cmd

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