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Eventum

Requirements

Supported platforms, Python version, and resource usage for running Eventum.

Eventum runs natively on Linux and in Docker on any host. Before installing, check the supported platforms, the required Python version, and the resources a running instance consumes.

Supported platforms

PlatformSupportNotes
LinuxNativeFull support — install from PyPI, from source, or run with Docker.
WSL2 (Windows)NativeRuns exactly as on Linux — the recommended way to run on a Windows host. Set up WSL2.
Docker (any OS)FullOfficial images run on Windows, macOS, and Linux hosts.
Windows / macOS (native)Not supportedUse Docker, or WSL2 on Windows.

Python

Eventum requires Python 3.14 or later. This applies to native installations (PyPI or source) — the Docker image already bundles Python.

For best performance, use the free-threaded build (Python 3.14t). It disables the GIL, allowing multiple generators to run truly in parallel across CPU cores. Install it with uv python install 3.14t.

Resource usage

Resource use depends on the run mode and your workload. The figures below are a baseline to size from.

ScenarioCPURAMNotes
Minimal1 vCPU1 GBCan run a single generator with eventum generate.
Recommended2 vCPU4 GBCan run the full application with eventum run — multiple generators plus the API and Studio.
Optimal4 vCPU8 GBCan run many generators at high throughput, with room to spare.
  • CPU — Driven mainly by the event stage, which is CPU-bound; how much it needs depends on the event plugin you choose, how you configure it, and your target throughput. Each generator runs three pipeline stages — input, event, and output — in parallel on the free-threaded build, so throughput scales with available cores.
  • RAM — Scales with the number of generators and their batching. Each generator buffers timestamp and event batches sized by batch.size and queue.*, so larger batches or more generators raise memory use.
  • Disk — Allow around 5 GB for the application, its caches, and logs.
  • Network — Used only when output plugins deliver over the network (Kafka, HTTP, OpenSearch, ClickHouse).

Batching, queue depth, and concurrency are configurable — tune them in eventum.yml to trade memory for throughput.

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