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Published: Aug 20, 2022 License: Apache-2.0

README

Istio Performance Benchmarking

This directory contains Python scripts to benchmark Istio's data plane performance.

See the Istio Performance and Scalability Guide for performance data against the latest Istio release.

For instructions on how to run these scripts with Linkerd, see the linkerd/ directory.

Prerequisites

  1. Python3
  2. pipenv
  3. helm

Setup

  1. Create a Kubernetes cluster.

    We provide a GKE cluster-create script in this repo, refer to GKE Cluster Setup.

    If you are using your own cluster, see resource requirment for machine type recommendations.

  2. Install Istio

    See Setup Istio.

  3. Deploy the workloads to measure performance against. The test environment is two Fortio pods (one client, one server), set to communicate over HTTP1, using mutual TLS authentication. By default, the client pod will make HTTP requests with a 1KB payload.

    export NAMESPACE=twopods-istio
    export INTERCEPTION_MODE=REDIRECT
    export ISTIO_INJECT=true
    export LOAD_GEN_TYPE=nighthawk
    export DNS_DOMAIN=v104.qualistio.org
    ./setup_test.sh
    

Note: We are currently supporting two types of load generators: nighthawk and fortio. Please specify the LOAD_GEN_TYPE environment variable to your desired one.

Prepare Python Environment

Here, pipenv shell will create a local Python3 virtual environment, and pipenv install will install all the Python packages needed to run the benchmarking scripts and graph_plotter via Pipfile:

cd perf/benchmark
pipenv --three
pipenv shell
pipenv install

Run performance tests

The benchmarking script is located at runner.py. This script runs a set of Fortio or Nighthawk performance tests depending on the kind of LOAD_GEN_TYPE you set before.

The different sidecar modes and telemetry configurations of performance tests are described in the Istio performance dashboard site.

How to run:

  1. run with CLI argument directly
python runner/runner.py --conn <conn> --qps <qps> --duration <duration> --OPTIONAL-FLAGS
  1. run with config yaml
python runner/runner.py --config_file ./configs/istio/telemetryv2_stats/latency.yaml

Required fields to specified via CLI or config file:

  • conn = number of concurrent connections
  • qps = queries per second for each connection
  • duration = number of seconds to run each test for (the minimum value for duration should be: 92 seconds)
  • load_gen_type = the traffic load generator type
  • telemetry_mode = the telemetry mode you enabled while installing Istio (none or telemetryv2)
optional arguments:
  -h, --help            show this help message and exit
  --headers HEADERS     a list of `header:value` should be separated by comma, e.g. --headers="foo:bar,foo1:bar1,foo2:bar2"
  --conn CONN           number of connections, comma separated list
  --qps QPS             qps, comma separated list
  --duration DURATION   duration in seconds of the extract
  --load_gen_type LOAD_GEN_TYPE
                        traffic load generator type, can be either Fortio or Nighthawk
  --jitter JITTER       to enable or disable jitter for load generator
  --size SIZE           size of the payload
  --mesh MESH           istio or linkerd
  --telemetry_mode TELEMETRY_MODE
                        run with different telemetry configurations:
                        none, telemetryv2
  --client CLIENT       where to run the test from
  --server SERVER       pod ip of the server
  --perf PERF           also run perf and produce flame graph
  --frequency FREQUENCY sampling frequency of generating flame graph
  --ingress INGRESS     run traffic through ingress, should be a valid URL
  --extra_labels EXTRA_LABELS
                        extra labels
  --protocol_mode PROTOCOL_MODE
                        http, tcp or grpc
  --config_file CONFIG_FILE
                        config yaml file
  --cacert CACERT       path to the cacert for the fortio client inside the
                        container
  --baseline            run baseline for all
  --no_baseline         do not run baseline for all
  --serversidecar       run serversidecar-only for all
  --no_serversidecar    do not run serversidecar-only for all
  --clientsidecar       run clientsidecar-only for all
  --no_clientsidecar    do not run clientsidecar-only for all
  --bothsidecar         run both clientsidecar and serversidecar
  --no_sidecar          do not run clientsidecar and serversidecar

Note:

  • runner.py will run all combinations of the parameters given. However, in order to reduce ambiguity when generating the graph, it would be better to change one parameter at a time and fix other parameters
  • if you want to run with --perf flag to generate a flame graph, please make sure you have the permission to gather perf data, please refer to step 2 of this README
  • to test your system's maximum qps before choosing the range of qps you want to measure by passing --qps 0

For example:

Example 1
python runner/runner.py --config_file ./configs/istio/telemetryv2_stats/latency.yaml
  • This will run with configuration specified in the ./configs/istio/telemetryv2_stats/latency.yaml
  • Run with telemetry v2 stats filter on and measure the latency
Example 2
python runner/runner.py --conn 2,4,8,16,32,64 --qps 1000 --duration 240 --baseline --load_gen_type=fortio --telemetry_mode=v2-nullvm
  • This will run separate tests for the both and baseline modes with fortio as the load generator and testing telemetryv2 enabled scenario
  • Separate tests for 2 to 64 concurrent connections
  • Each connection will send 1000 QPS
  • Each test will run for 240 seconds
Example 3
python runner/runner.py --conn 16,64 --qps 1000,4000 --duration 180 --serversidecar --baseline --load_gen_type=nighthawk --telemetry_mode=none
  • 12 tests total, each for 180 seconds, with all combinations of:
  • 16 and 64 connections
  • 1000 and 4000 QPS
  • both, serversidecar, and baseline modes
Example 4

Example 1 and 2 is to gather the latency results by increasing the number of connections. If you want to gather CPU and memory related results, you should increasing the number of QPS, like:

python runner/runner.py --conn 10  --qps 100,500,1000,2000,4000 --duration 240 --load_gen_type=fortio --telemetry_mode=v2-nullvm
Example 5: CPU flame graph
python runner/runner.py --conn 10  --qps 100,500,1000,2000,4000 --duration 240 --load_gen_type=fortio --telemetry_mode=v2-nullvm --perf=true

This will generate corresponding .svg flame graph in the perf/benchmark/flame/flameoutput repo. Here is the sample output

Example 6
python runner/runner.py --conn 2,4,8,16,32,64 --qps 1000 --duration 240 --baseline --load_gen_type=fortio --protocol_mode=tcp
  • This will run separate tests for the both and baseline modes with fortio tcp load test
  • Separate tests for 2 to 64 concurrent connections
  • Each connection will send 1000 QPS
  • Each test will run for 240 seconds

Gather Result Metrics

Once runner.py has completed, extract the results from Fortio and Prometheus.

  1. Set FORTIO_CLIENT_URL to the fortioclient Service's EXTERNAL_IP:

    kubectl get svc -n $NAMESPACE fortioclient
    NAME           TYPE           CLUSTER-IP   EXTERNAL-IP     PORT(S)                                                       AGE
    fortioclient   LoadBalancer   xxxx          xxxx       8080:31759/TCP,8079:30495/TCP,8078:31107/TCP,8077:31034/TCP   16h
    
    export FORTIO_CLIENT_URL=http://$(kubectl get services -n $NAMESPACE fortioclient -o jsonpath="{.status.loadBalancer.ingress[0].ip}"):9076
    

    or if you don't have an external IP:

    kubectl -n $NAMESPACE port-forward svc/fortioclient 9076:9076 &
    export FORTIO_CLIENT_URL=http://localhost:9076
    
  2. Set PROMETHEUS_URL:

    This command can be used if you installed Prometheus over the ./setup_istio.sh script. Otherwise your Prometheus maybe in a different namespace and differently named.

    kubectl -n istio-prometheus port-forward svc/istio-prometheus 9090:9090 &
    export PROMETHEUS_URL=http://localhost:9090
    
  3. Run fortio.py:

    python ./runner/fortio.py $FORTIO_CLIENT_URL --prometheus=$PROMETHEUS_URL --csv StartTime,ActualDuration,Labels,NumThreads,ActualQPS,p50,p90,p99,p999,cpu_mili_avg_istio_proxy_fortioclient,cpu_mili_avg_istio_proxy_fortioserver,cpu_mili_avg_istio_proxy_istio-ingressgateway,mem_Mi_avg_istio_proxy_fortioclient,mem_Mi_avg_istio_proxy_fortioserver,mem_Mi_avg_istio_proxy_istio-ingressgateway
    

    This script will generate two output files (one JSON, one CSV), both containing the same result metrics: Queries Per Second (QPS) attained, latency, and CPU/Memory usage.

Visualize CSV Results

Please refer to graph_plotter README

Add new config to benchmark pipeline

Currently we are running benchmark test towards different configs as prow job

To add a new config to this pipeline, we need to add a new directory under configs folder, where we can define config parameters structured as below:

  • installation.yaml: install Istio with this IstioOperator overlay file on top of istioctl built-in default profile and perf testing default overlay
  • cpu_mem.yaml: if provided, run cpu, memory test with this config
  • latency.yaml: if provided, run latency test with this config
  • prerun.sh: prerun hook we want to run before test
  • postrun.sh: postrun hook we want to run after test

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