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Method

This document provides a detailed description of the QA process. It is intended to be used by engineers reproducing the experimental setup for future tests of CometBFT. The (first iteration of the) QA process as described in the RELEASES.md document was applied to version v0.34.x in order to have a set of results acting as benchmarking baseline. This baseline is then compared with results obtained in later versions. Out of the testnet-based test cases described in the releases document we focused on two of them: 200 Node Test, and Rotating Nodes Test.

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Software Dependencies

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Infrastructure Requirements to Run the Tests

  • An account at Digital Ocean (DO), with a high droplet limit (>202)
  • The machine to orchestrate the tests should have the following installed:

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Requirements for Result Extraction

  • Prometheus DB to collect metrics from nodes
  • Prometheus DB to process queries (may be different node from the previous)
  • blockstore DB of one of the full nodes in the testnet

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200 Node Testnet

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Running the test

This section explains how the tests were carried out for reproducibility purposes.
  1. [If you haven’t done it before] Follow steps 1-4 of the README.md at the top of the testnet repository to configure Terraform, and doctl.
  2. Copy file testnets/testnet200.toml onto testnet.toml (do NOT commit this change)
  3. Set the variable VERSION_TAG in the Makefile to the git hash that is to be tested.
    • If you are running the base test, which implies an homogeneous network (all nodes are running the same version), then make sure makefile variable VERSION2_WEIGHT is set to 0
    • If you are running a mixed network, set the variable VERSION2_TAG to the other version you want deployed in the network. Then adjust the weight variables VERSION_WEIGHT and VERSION2_WEIGHT to configure the desired proportion of nodes running each of the two configured versions.
  4. Follow steps 5-10 of the README.md to configure and start the 200 node testnet
    • WARNING: Do NOT forget to run make terraform-destroy as soon as you are done with the tests (see step 9)
  5. As a sanity check, connect to the Prometheus node’s web interface (port 9090) and check the graph for the cometbft_consensus_height metric. All nodes should be increasing their heights.
    • You can find the Prometheus node’s IP address in ansible/hosts under section [prometheus].
    • The following URL will display the metrics cometbft_consensus_height and cometbft_mempool_size: 
      http://<PROMETHEUS-NODE-IP>:9090/classic/graph?g0.range_input=1h&g0.expr=cometbft_consensus_height&g0.tab=0&g1.range_input=1h&g1.expr=cometbft_mempool_size&g1.tab=0
  6. You now need to start the load runner that will produce transaction load.
    • If you don’t know the saturation load of the version you are testing, you need to discover it.
      • Run make loadrunners-init. This will copy the loader scripts to the testnet-load-runner node and install the load tool.
      • Find the IP address of the testnet-load-runner node in ansible/hosts under section [loadrunners].
      • ssh into testnet-load-runner.
        • Edit the script /root/200-node-loadscript.sh in the load runner node to provide the IP address of a full node (for example, validator000). This node will receive all transactions from the load runner node.
        • Run /root/200-node-loadscript.sh from the load runner node.
          • This script will take about 40 mins to run, so it is suggested to first run tmux in case the ssh session breaks.
          • It is running 90-seconds-long experiments in a loop with different loads.
    • If you already know the saturation load, you can simply run the test (several times) for 90 seconds with a load somewhat below saturation:
      • set makefile variables LOAD_CONNECTIONS, LOAD_TX_RATE, to values that will produce the desired transaction load.
      • set LOAD_TOTAL_TIME to 90 (seconds).
      • run “make runload” and wait for it to complete. You may want to run this several times so the data from different runs can be compared.
  7. Run make retrieve-data to gather all relevant data from the testnet into the orchestrating machine
    • Alternatively, you may want to run make retrieve-prometheus-data and make retrieve-blockstore separately. The end result will be the same.
    • make retrieve-blockstore accepts the following values in makefile variable RETRIEVE_TARGET_HOST
      • any: (which is the default) picks up a full node and retrieves the blockstore from that node only.
      • all: retrieves the blockstore from all full nodes; this is extremely slow, and consumes plenty of bandwidth, so use it with care.
      • the name of a particular full node (e.g., validator01): retrieves the blockstore from that node only.
  8. Verify that the data was collected without errors
    • at least one blockstore DB for a CometBFT validator
    • the Prometheus database from the Prometheus node
    • for extra care, you can run zip -T on the prometheus.zip file and (one of) the blockstore.db.zip file(s)
  9. Run make terraform-destroy
    • Don’t forget to type yes! Otherwise you’re in trouble.

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Result Extraction

The method for extracting the results described here is highly manual (and exploratory) at this stage. The CometBFT team should improve it at every iteration to increase the amount of automation.

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Steps

  1. Unzip the blockstore into a directory
  2. To identify saturation points
    1. Extract the latency report for all the experiments.
      • Run these commands from the directory containing the blockstore.db folder.
      • It is advisable to adjust the hash in the go run command to the latest possible.
      • mkdir results
go run github.com/cometbft/cometbft/test/loadtime/cmd/report@3003ef7 --database-type goleveldb --data-dir ./ > results/report.txt
    2. File report.txt contains an unordered list of experiments with varying concurrent connections and transaction rate. You will need to separate data per experiment.
      • Create files report01.txt, report02.txt, report04.txt and, for each experiment in file report.txt, copy its related lines to the filename that matches the number of connections, for example 
        for cnum in 1 2 4; do echo "$cnum"; grep "Connections: $cnum" results/report.txt -B 2 -A 10 > results/report$cnum.txt;  done
      • Sort the experiments in report01.txt in ascending tx rate order. Likewise for report02.txt and report04.txt.
      • Otherwise just keep report.txt, and skip to the next step.
    3. Generate file report_tabbed.txt by showing the contents report01.txt, report02.txt, report04.txt side by side
      • This effectively creates a table where rows are a particular tx rate and columns are a particular number of websocket connections.
      • Combine the column files into a single table file:
        • Replace tabs by spaces in all column files. For example, sed -i.bak 's/\t/ /g' results/report1.txt.
      • Merge the new column files into one: paste results/report1.txt results/report2.txt results/report4.txt | column -s $'\t' -t > report_tabbed.txt
  3. To generate a latency vs throughput plot, extract the data as a CSV 
    •  go run github.com/cometbft/cometbft/test/loadtime/cmd/report@3003ef7 --database-type goleveldb --data-dir ./ --csv results/raw.csv
    • Follow the instructions for the latency_throughput.py script. This plot is useful to visualize the saturation point.
    • Alternatively, follow the instructions for the latency_plotter.py script. This script generates a series of plots per experiment and configuration that may help with visualizing Latency vs Throughput variation.

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Extracting Prometheus Metrics

  1. Stop the prometheus server if it is running as a service (e.g. a systemd unit).
  2. Unzip the prometheus database retrieved from the testnet, and move it to replace the local prometheus database.
  3. Start the prometheus server and make sure no error logs appear at start up.
  4. Identify the time window you want to plot in your graphs.
  5. Execute the prometheus_plotter.py script for the time window.

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Rotating Node Testnet

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Running the test

This section explains how the tests were carried out for reproducibility purposes.
  1. [If you haven’t done it before] Follow steps 1-4 of the README.md at the top of the testnet repository to configure Terraform, and doctl.
  2. Copy file testnet_rotating.toml onto testnet.toml (do NOT commit this change)
  3. Set variable VERSION_TAG to the git hash that is to be tested.
  4. Run make terraform-apply EPHEMERAL_SIZE=25
    • WARNING: Do NOT forget to run make terraform-destroy as soon as you are done with the tests
  5. Follow steps 6-10 of the README.md to configure and start the “stable” part of the rotating node testnet
  6. As a sanity check, connect to the Prometheus node’s web interface and check the graph for the tendermint_consensus_height metric. All nodes should be increasing their heights.
  7. On a different shell,
    • run make runload LOAD_CONNECTIONS=X LOAD_TX_RATE=Y LOAD_TOTAL_TIME=Z
    • X and Y should reflect a load below the saturation point (see, e.g., this paragraph for further info)
    • Z (in seconds) should be big enough to keep running throughout the test, until we manually stop it in step 9. In principle, a good value for Z is 7200 (2 hours)
  8. Run make rotate to start the script that creates the ephemeral nodes, and kills them when they are caught up.
    • WARNING: If you run this command from your laptop, the laptop needs to be up and connected for the full length of the experiment.
    • This is an example Prometheus URL you can use to monitor the test case’s progress
  9. When the height of the chain reaches 3000, stop the make runload script.
  10. When the rotate script has made two iterations (i.e., all ephemeral nodes have caught up twice) after height 3000 was reached, stop make rotate
  11. Run make stop-network
  12. Run make retrieve-data to gather all relevant data from the testnet into the orchestrating machine
  13. Verify that the data was collected without errors
    • at least one blockstore DB for a CometBFT validator
    • the Prometheus database from the Prometheus node
    • for extra care, you can run zip -T on the prometheus.zip file and (one of) the blockstore.db.zip file(s)
  14. Run make terraform-destroy
Steps 8 to 10 are highly manual at the moment and will be improved in next iterations.

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Result Extraction

In order to obtain a latency plot, follow the instructions above for the 200 node experiment, but the results.txt file contains only one experiment. As for prometheus, the same method as for the 200 node experiment can be applied.

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Vote Extensions Testnet

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Running the test

This section explains how the tests were carried out for reproducibility purposes.
  1. [If you haven’t done it before] Follow steps 1-4 of the README.md at the top of the testnet repository to configure Terraform, and doctl.
  2. Copy file varyVESize.toml onto testnet.toml (do NOT commit this change).
  3. Set variable VERSION_TAG in the Makefile to the git hash that is to be tested.
  4. Follow steps 5-10 of the README.md to configure and start the testnet
    • WARNING: Do NOT forget to run make terraform-destroy as soon as you are done with the tests
  5. Configure the load runner to produce the desired transaction load.
    • set makefile variables ROTATE_CONNECTIONS, ROTATE_TX_RATE, to values that will produce the desired transaction load.
    • set ROTATE_TOTAL_TIME to 150 (seconds).
    • set ITERATIONS to the number of iterations that each configuration should run for.
  6. Execute steps 5-10 of the README.md file at the testnet repository.
  7. Repeat the following steps for each desired vote_extension_size
    1. Update the configuration (you can skip this step if you didn’t change the vote_extension_size)
      • Update the vote_extensions_size in the testnet.toml to the desired value.
      • make configgen
      • ANSIBLE_SSH_RETRIES=10 ansible-playbook ./ansible/re-init-testapp.yaml -u root -i ./ansible/hosts --limit=validators -e "testnet_dir=testnet" -f 20
      • make restart
    2. Run the test
      • make runload This will repeat the tests ITERATIONS times every time it is invoked.
    3. Collect your data
      • make retrieve-data Gathers all relevant data from the testnet into the orchestrating machine, inside folder experiments. Two subfolders are created, one blockstore DB for a CometBFT validator and one for the Prometheus DB data.
      • Verify that the data was collected without errors with zip -T on the prometheus.zip file and (one of) the blockstore.db.zip file(s).
  8. Clean up your setup.
    • make terraform-destroy; don’t forget that you need to type yes for it to complete.

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Result Extraction

In order to obtain a latency plot, follow the instructions above for the 200 node experiment, but:
  • The results.txt file contains only one experiment
  • Therefore, no need for any for loops
As for Prometheus, the same method as for the 200 node experiment can be applied.