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workload

README.md

Workload

This workload is used to test connection latency. It uses apache benchmark as workload generator.

We want to test kube-proxy performance on different service workloads, at the same time we want to minimize the impact of client/server performance. To achieve that, we will use the exact same amount of service backends and the same configuration for clients. The main tests parameters are (set in the env file):

  • number of services (SERVICES, using the same amount of backends)
  • number of clients (CLIENTS, when number of services is more than number of clients, each client will ping its own service by picking equally distributed service ips, e.g. for 10 clients and 100 services, client-1 pings service-10, client-2 pings service-20, etc.)
  • number of requests per client (CONN_PER_CLIENT, ab -n value)
  • client concurrency (CLIENT_CONCURRENCY, number of parallel connections per client, ab -c value)

The total number of requests = CONN_PER_CLIENT * CLIENTS

Running

  1. Install kube-burner v1.9.0+

    1.1 You can download kube-burner from https://github.com/cloud-bulldozer/kube-burner/releases

    1.2 You can build it from source kube-burner with make build

  2. Set test parameters in the env file, make sure to set KUBECONFIG either in the env file or in the terminal itself.

  3. source ./env && kube-burner init -c ./kube-burner.yaml

kube-burner cleans up automatically, but if you interrupted the run, use kubectl delete ns -l kube-burner-job to clean up.

Results

Check grafana dashboard for the results. ab results are stored in the ./results folder (created during the test run). You will find connect and total time distributions reported by the client pods in results/connect_time.jpg and results/total_time.jpg. results/quantiles shows quantiles calculated for the reported measurements from ab.

NOTE: times reported by ab are always higher than results reported by the conntrack-metrics and the dashboard as it includes ab's send and receive delay.

The easiest way to have fresh results for every experiment is to just restart the conntrack-metrics pods.