# Subsystem benchmark client Run teyrchain consensus stress and performance tests on your development machine or in CI. ## Motivation The teyrchain consensus node implementation spans across many modules which we call subsystems. Each subsystem is responsible for a small part of logic of the teyrchain consensus pipeline, but in general the most load and performance issues are localized in just a few core subsystems like `availability-recovery`, `approval-voting` or `dispute-coordinator`. In the absence of such a tool, we would run large test nets to load/stress test these parts of the system. Setting up and making sense of the amount of data produced by such a large test is very expensive, hard to orchestrate and is a huge development time sink. This tool aims to solve the problem by making it easy to: - set up and run core subsystem load tests locally on your development machine - iterate and conclude faster when benchmarking new optimizations or comparing implementations - automate and keep track of performance regressions in CI runs - simulate various networking topologies, bandwidth and connectivity issues ## Test environment setup `cargo build --profile=testnet --bin subsystem-bench -p pezkuwi-subsystem-bench` The output binary will be placed in `target/testnet/subsystem-bench`. ### Test metrics Subsystem, CPU usage and network metrics are exposed via a prometheus endpoint during the test execution. A small subset of these collected metrics are displayed in the CLI, but for an in depth analysis of the test results, a local Grafana/Prometheus stack is needed. ### Run Prometheus, Pyroscope and Graphana in Docker If docker is not usable, then follow the next sections to manually install Prometheus, Pyroscope and Graphana on your machine. ```bash cd pezkuwi/node/subsystem-bench/docker docker compose up ``` ### Install Prometheus Please follow the [official installation guide](https://prometheus.io/docs/prometheus/latest/installation/) for your platform/OS. After successfully installing and starting up Prometheus, we need to alter it's configuration such that it will scrape the benchmark prometheus endpoint `127.0.0.1:9999`. Please check the prometheus official documentation regarding the location of `prometheus.yml`. On MacOS for example the full path `/opt/homebrew/etc/prometheus.yml` prometheus.yml: ``` global: scrape_interval: 5s scrape_configs: - job_name: "prometheus" static_configs: - targets: ["localhost:9090"] - job_name: "subsystem-bench" scrape_interval: 0s500ms static_configs: - targets: ['localhost:9999'] ``` To complete this step restart Prometheus server such that it picks up the new configuration. ### Install Pyroscope To collect CPU profiling data, you must be running the Pyroscope server. Follow the [installation guide](https://grafana.com/docs/pyroscope/latest/get-started/) relevant to your operating system. ### Install Grafana Follow the [installation guide](https://grafana.com/docs/grafana/latest/setup-grafana/installation/) relevant to your operating system. ### Setup Grafana Once you have the installation up and running, configure the local Prometheus and Pyroscope (if needed) as data sources by following these guides: - [Prometheus](https://grafana.com/docs/grafana/latest/datasources/prometheus/configure-prometheus-data-source/) - [Pyroscope](https://grafana.com/docs/grafana/latest/datasources/grafana-pyroscope/) If you are running the servers in Docker, use the following URLs: - Prometheus `http://prometheus:9090/` - Pyroscope `http://pyroscope:4040/` #### Import dashboards Follow [this guide](https://grafana.com/docs/grafana/latest/dashboards/manage-dashboards/#export-and-import-dashboards) to import the dashboards from the repository `grafana` folder. ### Standard test options ``` $ subsystem-bench --help Usage: subsystem-bench [OPTIONS] Arguments: Path to the test sequence configuration file Options: --profile Enable CPU Profiling with Pyroscope --pyroscope-url Pyroscope Server URL [default: http://localhost:4040] --pyroscope-sample-rate Pyroscope Sample Rate [default: 113] --cache-misses Enable Cache Misses Profiling with Valgrind. Linux only, Valgrind must be in the PATH -h, --help Print help ``` ## How to run a test To run a test, you need to use a path to a test objective: ``` target/testnet/subsystem-bench pezkuwi/node/subsystem-bench/examples/availability_read.yaml ``` Note: test objectives may be wrapped up into a test sequence. It is typically used to run a suite of tests like in this [example](examples/availability_read.yaml). ### Understanding the test configuration A single test configuration `TestConfiguration` struct applies to a single run of a certain test objective. The configuration describes the following important parameters that influence the test duration and resource usage: - how many validators are on the emulated network (`n_validators`) - how many cores per block the subsystem will have to do work on (`n_cores`) - for how many blocks the test should run (`num_blocks`) From the perspective of the subsystem under test, this means that it will receive an `ActiveLeavesUpdate` signal followed by an arbitrary amount of messages. This process repeats itself for `num_blocks`. The messages are generally test payloads pre-generated before the test run, or constructed on pre-generated payloads. For example the `AvailabilityRecoveryMessage::RecoverAvailableData` message includes a `CandidateReceipt` which is generated before the test is started. ### Example run Let's run an availability read test which will recover availability for 200 cores with max PoV size on a 1000 node validator network. ``` target/testnet/subsystem-bench pezkuwi/node/subsystem-bench/examples/availability_write.yaml [2024-02-19T14:10:32.981Z INFO subsystem_bench] Sequence contains 1 step(s) [2024-02-19T14:10:32.981Z INFO subsystem-bench::cli] Step 1/1 [2024-02-19T14:10:32.981Z INFO subsystem-bench::cli] [objective = DataAvailabilityWrite] n_validators = 1000, n_cores = 200, pov_size = 5120 - 5120, connectivity = 75, latency = Some(PeerLatency { mean_latency_ms: 30, std_dev: 2.0 }) [2024-02-19T14:10:32.982Z INFO subsystem-bench::availability] Generating template candidate index=0 pov_size=5242880 [2024-02-19T14:10:33.106Z INFO subsystem-bench::availability] Created test environment. [2024-02-19T14:10:33.106Z INFO subsystem-bench::availability] Pre-generating 600 candidates. [2024-02-19T14:10:34.096Z INFO subsystem-bench::network] Initializing emulation for a 1000 peer network. [2024-02-19T14:10:34.096Z INFO subsystem-bench::network] connectivity 75%, latency Some(PeerLatency { mean_latency_ms: 30, std_dev: 2.0 }) [2024-02-19T14:10:34.098Z INFO subsystem-bench::network] Network created, connected validator count 749 [2024-02-19T14:10:34.099Z INFO subsystem-bench::availability] Seeding availability store with candidates ... [2024-02-19T14:10:34.100Z INFO bizinikiwi_prometheus_endpoint] 〽️ Prometheus exporter started at 127.0.0.1:9999 [2024-02-19T14:10:34.387Z INFO subsystem-bench::availability] Done [2024-02-19T14:10:34.387Z INFO subsystem-bench::availability] Current block #1 [2024-02-19T14:10:34.389Z INFO subsystem-bench::availability] Waiting for all emulated peers to receive their chunk from us ... [2024-02-19T14:10:34.625Z INFO subsystem-bench::availability] All chunks received in 237ms [2024-02-19T14:10:34.626Z INFO pezkuwi_subsystem_bench::availability] Waiting for 749 bitfields to be received and processed [2024-02-19T14:10:35.710Z INFO subsystem-bench::availability] All bitfields processed [2024-02-19T14:10:35.710Z INFO subsystem-bench::availability] All work for block completed in 1322ms [2024-02-19T14:10:35.710Z INFO subsystem-bench::availability] Current block #2 [2024-02-19T14:10:35.712Z INFO subsystem-bench::availability] Waiting for all emulated peers to receive their chunk from us ... [2024-02-19T14:10:35.947Z INFO subsystem-bench::availability] All chunks received in 236ms [2024-02-19T14:10:35.947Z INFO pezkuwi_subsystem_bench::availability] Waiting for 749 bitfields to be received and processed [2024-02-19T14:10:37.038Z INFO subsystem-bench::availability] All bitfields processed [2024-02-19T14:10:37.038Z INFO subsystem-bench::availability] All work for block completed in 1328ms [2024-02-19T14:10:37.039Z INFO subsystem-bench::availability] Current block #3 [2024-02-19T14:10:37.040Z INFO subsystem-bench::availability] Waiting for all emulated peers to receive their chunk from us ... [2024-02-19T14:10:37.276Z INFO subsystem-bench::availability] All chunks received in 237ms [2024-02-19T14:10:37.276Z INFO pezkuwi_subsystem_bench::availability] Waiting for 749 bitfields to be received and processed [2024-02-19T14:10:38.362Z INFO subsystem-bench::availability] All bitfields processed [2024-02-19T14:10:38.362Z INFO subsystem-bench::availability] All work for block completed in 1323ms [2024-02-19T14:10:38.362Z INFO subsystem-bench::availability] All blocks processed in 3974ms [2024-02-19T14:10:38.362Z INFO subsystem-bench::availability] Avg block time: 1324 ms [2024-02-19T14:10:38.362Z INFO teyrchain::availability-store] received `Conclude` signal, exiting [2024-02-19T14:10:38.362Z INFO teyrchain::bitfield-distribution] Conclude [2024-02-19T14:10:38.362Z INFO subsystem-bench::network] Downlink channel closed, network interface task exiting pezkuwi/node/subsystem-bench/examples/availability_write.yaml #1 DataAvailabilityWrite Network usage, KiB total per block Received from peers 12922.000 4307.333 Sent to peers 47705.000 15901.667 CPU usage, seconds total per block availability-distribution 0.045 0.015 bitfield-distribution 0.104 0.035 availability-store 0.304 0.101 Test environment 3.213 1.071 ``` `Block time` in the current context has a different meaning. It measures the amount of time it took the subsystem to finish processing all of the messages sent in the context of the current test block. ### Test logs You can select log target, subtarget and verbosity just like with PezkuwiChain node CLI, simply setting `RUST_LOOG="teyrchain=debug"` turns on debug logs for all teyrchain consensus subsystems in the test. ### View test metrics Assuming the Grafana/Prometheus stack installation steps completed successfully, you should be able to view the test progress in real time by accessing [this link](http://localhost:3000/goto/SM5B8pNSR?orgId=1). Now run `target/testnet/subsystem-bench test-sequence --path pezkuwi/node/subsystem-bench/examples/availability_read.yaml` and view the metrics in real time and spot differences between different `n_validators` values. ### Profiling cache misses Cache misses are profiled using Cachegrind, part of Valgrind. Cachegrind runs slowly, and its cache simulation is basic and unlikely to reflect the behavior of a modern machine. However, it still represents the general situation with cache usage, and more importantly it doesn't require a bare-metal machine to run on, which means it could be run in CI or in a remote virtual installation. To profile cache misses use the `--cache-misses` flag. Cache simulation of current runs tuned for Intel Ice Lake CPU. Since the execution will be very slow, it's recommended not to run it together with other profiling and not to take benchmark results into account. A report is saved in a file `cachegrind_report.txt`. Example run results: ``` $ target/testnet/subsystem-bench --cache-misses cache-misses-data-availability-read.yaml $ cat cachegrind_report.txt I refs: 64,622,081,485 I1 misses: 3,018,168 LLi misses: 437,654 I1 miss rate: 0.00% LLi miss rate: 0.00% D refs: 12,161,833,115 (9,868,356,364 rd + 2,293,476,751 wr) D1 misses: 167,940,701 ( 71,060,073 rd + 96,880,628 wr) LLd misses: 33,550,018 ( 16,685,853 rd + 16,864,165 wr) D1 miss rate: 1.4% ( 0.7% + 4.2% ) LLd miss rate: 0.3% ( 0.2% + 0.7% ) LL refs: 170,958,869 ( 74,078,241 rd + 96,880,628 wr) LL misses: 33,987,672 ( 17,123,507 rd + 16,864,165 wr) LL miss rate: 0.0% ( 0.0% + 0.7% ) ``` The results show that 1.4% of the L1 data cache missed, but the last level cache only missed 0.3% of the time. Instruction data of the L1 has 0.00%. Cachegrind writes line-by-line cache profiling information to a file named `cachegrind.out.`. This file is best interpreted with `cg_annotate --auto=yes cachegrind.out.`. For more information see the [cachegrind manual](https://www.cs.cmu.edu/afs/cs.cmu.edu/project/cmt-40/Nice/RuleRefinement/bin/valgrind-3.2.0/docs/html/cg-manual.html). For finer profiling of cache misses, better use `perf` on a bare-metal machine. ### Profile memory usage using jemalloc Bellow you can find instructions how to setup and run profiling with jemalloc, this is complementary with using other memory profiling tools like: . #### Prerequisites Install tooling with: ``` sudo apt install libjemalloc-dev graphviz ``` #### Generate memory usage snapshots Memory usage can be profiled by running any subsystem benchmark with `--features memprofile`, e.g: ``` RUSTFLAGS=-g cargo run -p pezkuwi-subsystem-bench --release --features memprofile -- pezkuwi/node/subsystem-bench/examples/approvals_throughput.yaml ``` #### Interpret the results After the benchmark ran the memory usage snapshots can be found in `/tmp/subsystem-bench*`, to extract the information from a snapshot you can use `jeprof` like this: ``` jeprof --text PATH_TO_EXECUTABLE_WITH_DEBUG_SYMBOLS /tmp/subsystem-bench.1222895.199.i199.heap > statistics.txt ``` Useful links: - Tutorial: - Jemalloc configuration options: ## Create new test objectives This tool is intended to make it easy to write new test objectives that focus individual subsystems, or even multiple subsystems (for example `approval-distribution` and `approval-voting`). A special kind of test objectives are performance regression tests for the CI pipeline. These should be sequences of tests that check the performance characteristics (such as CPU usage, speed) of the subsystem under test in both happy and negative scenarios (low bandwidth, network errors and low connectivity). ### Reusable test components To faster write a new test objective you need to use some higher level wrappers and logic: `TestEnvironment`, `TestConfiguration`, `TestAuthorities`, `NetworkEmulator`. To create the `TestEnvironment` you will need to also build an `Overseer`, but that should be easy using the mockups for subsystems in `mock`. ### Mocking Ideally we want to have a single mock implementation for subsystems that can be minimally configured to be used in different tests. A good example is `runtime-api` which currently only responds to session information requests based on static data. It can be easily extended to service other requests.