Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations.
The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network outages or service restarts. Its schema-agnostic processing model allows for dynamic field manipulation and enrichment, enabling users to normalize telemetry data from disparate sources without requiring rigid, predefined schemas.
The platform supports a wide range of deployment topologies, operating as a lightweight edge agent on individual hosts or as a centralized aggregator for high-volume data processing. It provides extensive integration capabilities for cloud-native environments, including automated log collection from containers and native support for various cloud storage and monitoring services.
Vector is configured via a declarative engine that validates pipeline definitions and supports dynamic reloads without service interruptions. The software is distributed as a pre-compiled binary and can be installed via standard system package managers or containerized deployment methods.
