A lightweight, ultra-fast tool for building observability pipelines

Take control of your observability data

Collect, transform, and route all your logs and metrics with one simple tool.

Why Vector?

Ultra fast and reliable

Built in Rust, Vector is blistering fast, memory efficient, and designed to handle the most demanding workloads.

End to end

Vector strives to be the only tool you need to get observability data from A to B, deploying as a daemon, sidecar, or aggregator.

Unified

Vector supports logs and metrics, making it easy to collect and process all your observability data.

Vendor neutral

Vector doesn’t favor any specific vendor platforms and fosters a fair, open ecosystem with your best interests in mind. Lock-in free and future proof.

Programmable transforms

Vector’s highly configurable transforms give you the full power of programmable runtimes. Handle complex use cases without limitation.

Clear guarantees

Guarantees matter, and Vector is clear on which guarantees it provides, helping you make the appropriate trade-offs for your use case.

A complete, end-to-end platform.

Deploy Vector in a variety of roles to suit your use case.
Get data from point A to point B without patching tools together.

Learn more about the distributed deployment topology for Vector

Learn more about the centralized deployment topology for Vector

Learn more about the stream-based deployment topology for Vector

Easy to configure

A simple, composable format enables you to build flexible pipelines

/etc/vector/vector.yaml

sources: datadog_agent: type: "datadog_agent" address: "0.0.0.0:80"  transforms: remove_sensitive_user_info: type: "remap" inputs: ["datadog_agent"] source: | redact(., filters: ["us_social_security_number"])  sinks: datadog_backend: type: "datadog_logs" inputs: ["remove_sensitive_user_info"] default_api_key: "${DATADOG_API_KEY}"

sources: kafka_in: type: "kafka" bootstrap_servers: "10.14.22.123:9092,10.14.23.332:9092" group_id: "vector-logs" key_field: "message" topics: ["logs-*"]  transforms: json_parse: type: "remap" inputs: ["kafka_in"] source: | parsed, err = parse_json(.message) if err != null { log(err, level: "error") } . |= object(parsed) ?? {}  sinks: elasticsearch_out: type: "elasticsearch" inputs: ["json_parse"] endpoint: "http://10.24.32.122:9000" index: "logs-via-kafka"

sources: k8s_in: type: "kubernetes_logs"  sinks: aws_s3_out: type: "aws_s3" inputs: ["k8s_in"] bucket: "k8s-logs" region: "us-east-1" compression: "gzip" encoding: codec: "json"

sources: splunk_hec_in: type: "splunk_hec" address: "0.0.0.0:8080" token: "${SPLUNK_HEC_TOKEN}"  sinks: datadog_out: type: "datadog_logs" inputs: ["splunk_hec_in"] default_api_key: "${DATADOG_API_KEY}"

Configuration examples are in YAML but Vector also supports TOML and JSON

Installs everywhere

Packaged as a single binary. No dependencies, no runtime, and memory safe.

Single binary

X86_64, ARM64/v7

No runtime

Memory safe

Install with a one-liner:

For humans
For machines

curl --proto '=https' --tlsv1.2 -sSfL https://sh.vector.dev | bash

curl --proto '=https' --tlsv1.2 -sSfL https://sh.vector.dev | bash -s -- -y

Or choose your preferred method:

Highly flexible processing topologies

A wide range of sources, transforms, and sinks to choose from

Backed by a strong open source community

13k+ GitHub stars

300+ Contributors

30m+ Downloads

40 Countries

View GitHub repo

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