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Cloudbench

Introduction

The Cloudbench tool, available at bin/cloudbench in the repository, launches one-off benchmarks in the AWS Scratch account.

Very little structure is imposed on the benchmarks scripts:

  • they must write a CSV file (with header) containing the results to a file named results.csv
  • they must (for now) be written in Python.
  • they must follow the Unix convention of exiting with code 0 on success, and non-zero otherwise.

Each row of the produced CSV file is interpreted as one benchmark run. For an example, see the avro_ingest.py script.

Prerequisites

Follow the instructions in the bin/scratch documentation to set up your machine for command-line AWS access to the Scratch account, and to learn about the basic commands for launching and querying individual machines.

Invocation

Launching benchmarks is done with the bin/cloudbench start subcommand. It takes the following options:

--profile: One of either basic or confluent. basic should be used if only the machine running the benchmark is required; confluent adds a separate machine running Kafka, Schema Registry, and Zookeeper.

--trials: How many separate clusters to run the benchmark on per Git revision

--revs: A comma-separated list of Git revisions to benchmark.

For example, the following command:

bin/cloudbench start --profile confluent --trials 3 --revs HEAD,'HEAD^' materialize.benches.avro_ingest -r 100000000 -n 10

launches 12 machines: two git revisions, three clusters per revision, and two machines per cluster. It then runs the module misc.benches.avro_ingest, defined in the file misc/python/materialize/benches/avro_ingest.py, with the arguments -r 100000000 -n 10 on 6 of those machines (one per cluster; the other machine is for the Confluent platform).

Checking results

Because benchmarks may in general be long-running, bin/cloudbench start does not need to stay running for the entire time it takes them to complete. After setting up the machines and launching the benchmark scripts, that tool exists, printing out a "benchmark ID". That benchmark ID may in turn be passed to the bin/benchmark check utility, like so:

bin/cloudbench check f4765a9a

This command checks every 60 seconds whether a benchmark has completed. Once it does complete, assuming all runs were successful, it gets their results, collates them into one CSV file, and prints it to stdout.

Cleaning up

Benchmark machines are automatically cleaned up after one day. If you need to run something for longer, ask how to disable the automated cleanup in #eng-infra on Slack.

If you want to clean up machines sooner, you may use the bin/scratch destroy tool.