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posthog/plugin-server
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bin feat: Plugin server services refactor - take 2 (#24737) 2024-09-03 11:00:50 +02:00
functional_tests refactor(group-analytics): Add project field to group type (#25600) 2024-11-01 00:12:28 +01:00
patches
src refactor(ingestion): Make group type project-based (read/write) (#25876) 2024-11-12 14:35:47 +01:00
tests refactor(ingestion): Make group type project-based (read/write) (#25876) 2024-11-12 14:35:47 +01:00
.babelrc
.editorconfig
.eslintrc.js chore: warn on switch with fall through (#25355) 2024-10-03 08:30:36 +00:00
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jest.config.functional.js
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package.json feat(cdp): hog to JS transpiler (#26143) 2024-11-18 13:38:25 +00:00
pnpm-lock.yaml feat(cdp): hog to JS transpiler (#26143) 2024-11-18 13:38:25 +00:00
README.md
tsconfig.eslint.json
tsconfig.json

PostHog Plugin Server

npm package MIT License

This service takes care of processing events with plugins and more.

Get started

Let's get you developing the plugin server in no time:

  1. Have virtual environment from the main PostHog repo active.

  2. Install dependencies and prepare for takeoff by running command pnpm i.

  3. Start a development instance of PostHog - instructions here. After all, this is the PostHog Plugin Server, and it works in conjuction with the main server.

  4. Make sure that the plugin server is configured correctly (see Configuration). The following settings need to be the same for the plugin server and the main server: DATABASE_URL, REDIS_URL, KAFKA_HOSTS, CLICKHOUSE_HOST, CLICKHOUSE_DATABASE, CLICKHOUSE_USER, and CLICKHOUSE_PASSWORD. Their default values should work just fine in local development though.

  5. Start the plugin server in autoreload mode with pnpm start:dev, or in compiled mode with pnpm build && pnpm start:dist, and develop away!

  6. Prepare for running tests with pnpm setup:test, which will run the necessary migrations. Run the tests themselves with pnpm test:{1,2}.

  7. Prepare for running functional tests. See notes below.

Running Functional Tests

Functional tests are provided located in functional_tests. They provide tests for high level functionality of the plugin-server, i.e. functionality that any client of the plugin-server should be able to use. It attempts to assume nothing of the implementation details of the plugin-server.

At the time of writing it assumes:

  1. that events are pushed into Kafka topics.
  2. that side-effects of the plugin-server are updates to ClickHouse table data.
  3. that the plugin-server reads certain data from Postgres tables e.g. posthog_team, posthog_pluginsource etc. These would ideally be wrapped in some implementation detail agnostic API.

It specifically doesn't assume details of the running plugin-server process e.g. runtime stack.

See bin/ci_functional_tests.sh for how these tests are run in CI. For local testing:

  1. run docker docker compose -f docker-compose.dev.yml up (in posthog folder)
  2. setup the test DBs pnpm setup:test
  3. start the plugin-server:
    APP_METRICS_FLUSH_FREQUENCY_MS=0 \
        CLICKHOUSE_DATABASE='default' \
        DATABASE_URL=postgres://posthog:posthog@localhost:5432/test_posthog \
        PLUGINS_DEFAULT_LOG_LEVEL=0 \
        RELOAD_PLUGIN_JITTER_MAX_MS=0 \
        PLUGIN_SERVER_MODE=functional-tests \
        pnpm start:dev
    
  4. run the tests:
    CLICKHOUSE_DATABASE='default' \
        DATABASE_URL=postgres://posthog:posthog@localhost:5432/test_posthog \
        pnpm functional_tests --watch
    

CLI flags

There are also a few alternative utility options on how to boot plugin-server. Each one does a single thing. They are listed in the table below, in order of precedence.

Name Description CLI flags
Help Show plugin server configuration options -h, --help
Version Only show currently running plugin server version -v, --version
Migrate Migrate Graphile Worker --migrate

Alternative modes

By default, plugin-server is responsible for and executes all of the following:

  1. Ingestion (calling plugins and writing event and person data to ClickHouse and Postgres, buffering events)
  2. Scheduled tasks (runEveryX type plugin tasks)
  3. Processing plugin jobs
  4. Async plugin tasks (onEvent plugin tasks)

Ingestion can be split into its own process at higher scales. To do so, you need to run two different instances of plugin-server, with the following environment variables set:

Env Var Description
PLUGIN_SERVER_MODE=ingestion This plugin server instance only runs ingestion (1)
PLUGIN_SERVER_MODE=async This plugin server processes all async tasks (2-4). Note that async plugin tasks are triggered based on ClickHouse events topic

If PLUGIN_SERVER_MODE is not set the plugin server will execute all of its tasks (1-4).

Configuration

There's a multitude of settings you can use to control the plugin server. Use them as environment variables.

Name Description Default value
DATABASE_URL Postgres database URL 'postgres://localhost:5432/posthog'
REDIS_URL Redis store URL 'redis://localhost'
BASE_DIR base path for resolving local plugins '.'
WORKER_CONCURRENCY number of concurrent worker threads 0 all cores
TASKS_PER_WORKER number of parallel tasks per worker thread 10
REDIS_POOL_MIN_SIZE minimum number of Redis connections to use per thread 1
REDIS_POOL_MAX_SIZE maximum number of Redis connections to use per thread 3
SCHEDULE_LOCK_TTL how many seconds to hold the lock for the schedule 60
PLUGINS_RELOAD_PUBSUB_CHANNEL Redis channel for reload events 'reload-plugins'
CLICKHOUSE_HOST ClickHouse host 'localhost'
CLICKHOUSE_OFFLINE_CLUSTER_HOST ClickHouse host to use for offline workloads. Falls back to CLICKHOUSE_HOST null
CLICKHOUSE_DATABASE ClickHouse database 'default'
CLICKHOUSE_USER ClickHouse username 'default'
CLICKHOUSE_PASSWORD ClickHouse password null
CLICKHOUSE_CA ClickHouse CA certs null
CLICKHOUSE_SECURE whether to secure ClickHouse connection false
KAFKA_HOSTS comma-delimited Kafka hosts null
KAFKA_CONSUMPTION_TOPIC Kafka incoming events topic 'events_plugin_ingestion'
KAFKA_CLIENT_CERT_B64 Kafka certificate in Base64 null
KAFKA_CLIENT_CERT_KEY_B64 Kafka certificate key in Base64 null
KAFKA_TRUSTED_CERT_B64 Kafka trusted CA in Base64 null
KAFKA_PRODUCER_MAX_QUEUE_SIZE Kafka producer batch max size before flushing 20
KAFKA_FLUSH_FREQUENCY_MS Kafka producer batch max duration before flushing 500
KAFKA_MAX_MESSAGE_BATCH_SIZE Kafka producer batch max size in bytes before flushing 900000
LOG_LEVEL minimum log level 'info'
SENTRY_DSN Sentry ingestion URL null
DISABLE_MMDB whether to disable MMDB IP location capabilities false
INTERNAL_MMDB_SERVER_PORT port of the internal server used for IP location (0 means random) 0
DISTINCT_ID_LRU_SIZE size of persons distinct ID LRU cache 10000
PISCINA_USE_ATOMICS corresponds to the piscina useAtomics config option (https://github.com/piscinajs/piscina#constructor-new-piscinaoptions) true
PISCINA_ATOMICS_TIMEOUT (advanced) corresponds to the length of time (in ms) a piscina worker should block for when looking for tasks - instances with high volumes (100+ events/sec) might benefit from setting this to a lower value 5000
HEALTHCHECK_MAX_STALE_SECONDS 'maximum number of seconds the plugin server can go without ingesting events before the healthcheck fails' 7200
KAFKA_PARTITIONS_CONSUMED_CONCURRENTLY (advanced) how many kafka partitions the plugin server should consume from concurrently 1
PLUGIN_SERVER_MODE (advanced) see alternative modes section null

Releasing a new version

Just bump up version in package.json on the main branch and the new version will be published automatically, with a matching PR in the main PostHog repo created.

It's advised to use bump patch/minor/major label on PRs - that way the above will be done automatically when the PR is merged.

Courtesy of GitHub Actions.

Walkthrough

The story begins with pluginServer.ts -> startPluginServer, which is the main thread of the plugin server.

This main thread spawns WORKER_CONCURRENCY worker threads, managed using Piscina. Each worker thread runs TASKS_PER_WORKER tasks (concurrentTasksPerWorker).

Main thread

Let's talk about the main thread first. This has:

  1. pubSub Redis powered pub-sub mechanism for reloading plugins whenever a message is published by the main PostHog app.

  2. hub Handler of connections to required DBs and queues (ClickHouse, Kafka, Postgres, Redis), holds loaded plugins. Created via hub.ts -> createHub. Every thread has its own instance.

  3. piscina This used to be a manager of tasks that were delegated to threads. It is now a shim over normal JS function calls that will be removed in the future.

  4. pluginScheduleControl Controller of scheduled jobs. Responsible for adding Piscina tasks for scheduled jobs, when the time comes. The schedule information makes it into the controller when plugin VMs are created.

    Scheduled tasks are controlled with Redlock (redis-based distributed lock), and run on only one plugin server instance in the entire cluster.

  5. jobQueueConsumer The internal job queue consumer. This enables retries, scheduling jobs in the future (once) (Note: this is the difference between pluginScheduleControl and this internal jobQueue). While pluginScheduleControl is triggered via runEveryMinute, runEveryHour tasks, the jobQueueConsumer deals with meta.jobs.doX(event).runAt(new Date()).

    Jobs are enqueued by job-queue-manager.ts, which is backed by Postgres-based Graphile-worker (graphile-queue.ts).

  6. queue Event ingestion queue. This is a Celery (backed by Redis) or Kafka queue, depending on the setup (EE/Cloud is Kafka due to high volume). These are consumed by the queue above, and sent off to the Piscina workers (src/main/ingestion-queues/queue.ts -> ingestEvent). Since all of the actual ingestion happens inside worker threads, you'll find the specific ingestion code there (src/worker/ingestion/ingest-event.ts). There the data is saved into Postgres (and ClickHouse via Kafka on EE/Cloud).

    It's also a good idea to see the producer side of this ingestion queue, which comes from posthog/posthog/api/capture.py. The plugin server gets the process_event_with_plugins Celery task from there, in the Postgres pipeline. The ClickHouse via Kafka pipeline gets the data by way of Kafka topic events_plugin_ingestion.

  7. mmdbServer TCP server, which works as an interface between the GeoIP MMDB data reader located in main thread memory and plugins ran in worker threads of the same plugin server instance. This way the GeoIP reader is only loaded in one thread and can be used in all. Additionally this mechanism ensures that mmdbServer is ready before ingestion is started (database downloaded from http-mmdb and read), and keeps the database up to date in the background.

Note: An organization_id is tied to a company and its installed plugins, a team_id is tied to a project and its plugin configs (enabled/disabled+extra config).

Patching node-rdkafka

We carry a node-rdkafka patch that adds cooperative rebalancing. To generate this patch:

# setup a local node-rdkafka clone
git clone git@github.com:PostHog/node-rdkafka.git
cd node-rdkafka
git remote add blizzard git@github.com:Blizzard/node-rdkafka.git
git fetch blizzard

# generate the diff
git diff blizzard/master > ~/node-rdkafka.diff

# in the plugin-server directory, this will output a temporary working directory
pnpm patch node-rdkafka@2.17.0

# enter the temporary directory from the previous command
cd /private/var/folders/b7/bmmghlpx5qdd6gpyvmz1k1_m0000gn/T/6082767a6879b3b4e11182f944f5cca3

# if asked, skip any missing files
patch -p1 < ~/node-rdkafka.diff

# in the plugin-server directory, target the temporary directory from the previous command
pnpm patch-commit /private/var/folders/b7/bmmghlpx5qdd6gpyvmz1k1_m0000gn/T/6082767a6879b3b4e11182f944f5cca3