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Vector

Vector is an open source high-performance observability data pipeline from Datadog for collecting, transforming, and routing logs, metrics, and traces. Built in Rust for performance and reliability, Vector supports 50+ sources, 20+ transforms, and 80+ sinks. It provides a built-in API for health monitoring and component inspection, plus Vector Remap Language (VRL) for powerful data transformation.

3 APIs 8 Features
Data PipelineLogsMetricsObservabilityOpen SourceRustTraces

APIs

Vector Observability API

The Vector Observability API provides HTTP endpoints for health monitoring of running Vector instances and gRPC endpoints for component inspection and event streaming. Enable vi...

Vector Remap Language (VRL)

Vector Remap Language (VRL) is a purpose-built expression language for transforming observability data in Vector. Provides 100+ built-in functions for parsing, filtering, enrich...

Vector Helm Charts

Official Helm charts for deploying Vector on Kubernetes as a DaemonSet (agent mode) or Deployment (aggregator mode).

Features

High-Performance Pipeline

Built in Rust with benchmarks showing 86+ MiB/s throughput for log pipeline workloads.

Unified Data Plane

Single binary handles logs, metrics, and traces from collection through routing.

50+ Sources

Native integrations for files, Kafka, Kubernetes, AWS S3/CloudWatch, Splunk, and more.

80+ Sinks

Route data to Elasticsearch, Datadog, S3, BigQuery, Splunk, Loki, and many more destinations.

Vector Remap Language (VRL)

Purpose-built expression language with 100+ functions for transforming observability data.

Observability API

Built-in HTTP/gRPC API for health checks and component inspection (must be explicitly enabled).

Kubernetes Native

Deploy as DaemonSet (agent) or Deployment (aggregator) with official Helm charts.

Agent and Aggregator Modes

Run as a lightweight agent on each node or as a centralized aggregator for fan-in routing.

Use Cases

Log Pipeline Unification

Replace multiple log shippers with a single Vector pipeline for all log collection and routing.

Observability Cost Reduction

Filter, sample, and transform data before sending to expensive SaaS observability platforms.

Vendor Switching

Route observability data to multiple backends simultaneously to facilitate migration.

Kubernetes Log Collection

Deploy Vector as a DaemonSet to collect container logs from all Kubernetes nodes.

Log Enrichment

Parse, enrich, and normalize log events using VRL before routing to downstream systems.

Metrics Collection

Collect host and service metrics using Vector's built-in sources and forward to Prometheus or DataDog.

Splunk Cost Reduction

Use Vector to filter and route Splunk data to reduce indexing volume and licensing costs.

Integrations

Datadog

Native Datadog logs and metrics sink; Vector was created and is maintained by Datadog.

Elasticsearch

Elasticsearch sink for forwarding logs and metrics to Elasticsearch clusters.

Splunk HEC

Splunk HTTP Event Collector sink for sending data to Splunk Enterprise and Cloud.

Kafka

Kafka source and sink for consuming and producing observability data streams.

AWS S3

S3 sink for archiving logs and metrics to Amazon S3 for long-term storage.

Grafana Loki

Loki sink for forwarding logs to Grafana's log aggregation system.

Prometheus

Prometheus remote write sink and scrape source for metrics pipelines.

Kubernetes

Kubernetes source for collecting container logs, pod metadata, and events.

Semantic Vocabularies

Vector Observability Api Context

1 classes · 1 properties

JSON-LD

API Governance Rules

Vector API Rules

16 rules · 9 errors 7 warnings

SPECTRAL

JSON Structure

Example Payloads

Resources

🔗
Website
Website
🔗
Documentation
Documentation
👥
GitHubOrganization
GitHubOrganization
👥
GitHubRepository
GitHubRepository
📄
ReleaseNotes
ReleaseNotes
📰
Blog
Blog
🔗
Forum
Forum
👥
StackOverflow
StackOverflow
🔗
SpectralRules
SpectralRules
🔗
Vocabulary
Vocabulary

Sources

Raw ↑
aid: vector
name: Vector
description: >-
  Vector is an open source high-performance observability data pipeline from Datadog for collecting, transforming, and
  routing logs, metrics, and traces. Built in Rust for performance and reliability, Vector supports 50+ sources, 20+
  transforms, and 80+ sinks. It provides a built-in API for health monitoring and component inspection, plus Vector
  Remap Language (VRL) for powerful data transformation.
type: Index
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg
tags:
  - Data Pipeline
  - Logs
  - Metrics
  - Observability
  - Open Source
  - Rust
  - Traces
url: https://raw.githubusercontent.com/api-evangelist/vector/refs/heads/main/apis.yml
created: '2026-03-25'
modified: '2026-05-19'
specificationVersion: '0.19'
apis:
  - aid: vector:vector-observability-api
    name: Vector Observability API
    description: >-
      The Vector Observability API provides HTTP endpoints for health monitoring of running Vector instances and gRPC
      endpoints for component inspection and event streaming. Enable via api.enabled: true in Vector configuration.
      Binds to 127.0.0.1:8686 by default. Note: the API does not support authentication and should only be used in
      isolated environments.
    humanURL: https://vector.dev/docs/reference/api/
    baseURL: http://127.0.0.1:8686
    tags:
      - Health Monitoring
      - Observability
      - Pipeline Management
    properties:
      - type: Documentation
        url: https://vector.dev/docs/reference/api/
      - type: OpenAPI
        url: openapi/vector-observability-api-openapi.yml
      - type: JSONSchema
        url: json-schema/vector-observability-api-health-response-schema.json
        title: Health Response Schema
      - type: JSONStructure
        url: json-structure/vector-observability-api-health-response-structure.json
        title: Health Response Structure
      - type: Example
        url: examples/vector-observability-api-health-response-example.json
        title: Health Response Example
      - type: JSONLD
        url: json-ld/vector-observability-api-context.jsonld
  - aid: vector:vector-vrl
    name: Vector Remap Language (VRL)
    description: >-
      Vector Remap Language (VRL) is a purpose-built expression language for transforming observability data in Vector.
      Provides 100+ built-in functions for parsing, filtering, enriching, and transforming logs, metrics, and traces
      without leaving the Vector pipeline.
    humanURL: https://vector.dev/docs/reference/vrl/
    tags:
      - Data Transformation
      - Expression Language
      - VRL
    properties:
      - type: Documentation
        url: https://vector.dev/docs/reference/vrl/
      - type: GitHubRepository
        url: https://github.com/vectordotdev/vrl
  - aid: vector:vector-helm
    name: Vector Helm Charts
    description: >-
      Official Helm charts for deploying Vector on Kubernetes as a DaemonSet (agent mode) or Deployment (aggregator
      mode).
    humanURL: https://vector.dev/docs/setup/installation/package-managers/helm/
    tags:
      - Helm
      - Kubernetes
      - Deployment
    properties:
      - type: Documentation
        url: https://vector.dev/docs/setup/installation/package-managers/helm/
      - type: GitHubRepository
        url: https://github.com/vectordotdev/helm-charts
common:
  - type: Website
    url: https://vector.dev
  - type: Documentation
    url: https://vector.dev/docs/
  - type: GitHubOrganization
    url: https://github.com/vectordotdev
  - type: GitHubRepository
    url: https://github.com/vectordotdev/vector
  - type: ReleaseNotes
    url: https://vector.dev/releases/
  - type: Blog
    url: https://vector.dev/blog/
  - type: Forum
    url: https://discord.com/invite/n2yjjZR
  - type: StackOverflow
    url: https://stackoverflow.com/questions/tagged/vector-dev
  - type: SpectralRules
    url: rules/vector-spectral-rules.yml
  - type: Vocabulary
    url: vocabulary/vector-vocabulary.yaml
  - type: Features
    data:
      - name: High-Performance Pipeline
        description: Built in Rust with benchmarks showing 86+ MiB/s throughput for log pipeline workloads.
      - name: Unified Data Plane
        description: Single binary handles logs, metrics, and traces from collection through routing.
      - name: 50+ Sources
        description: Native integrations for files, Kafka, Kubernetes, AWS S3/CloudWatch, Splunk, and more.
      - name: 80+ Sinks
        description: Route data to Elasticsearch, Datadog, S3, BigQuery, Splunk, Loki, and many more destinations.
      - name: Vector Remap Language (VRL)
        description: Purpose-built expression language with 100+ functions for transforming observability data.
      - name: Observability API
        description: Built-in HTTP/gRPC API for health checks and component inspection (must be explicitly enabled).
      - name: Kubernetes Native
        description: Deploy as DaemonSet (agent) or Deployment (aggregator) with official Helm charts.
      - name: Agent and Aggregator Modes
        description: Run as a lightweight agent on each node or as a centralized aggregator for fan-in routing.
  - type: UseCases
    data:
      - name: Log Pipeline Unification
        description: Replace multiple log shippers with a single Vector pipeline for all log collection and routing.
      - name: Observability Cost Reduction
        description: Filter, sample, and transform data before sending to expensive SaaS observability platforms.
      - name: Vendor Switching
        description: Route observability data to multiple backends simultaneously to facilitate migration.
      - name: Kubernetes Log Collection
        description: Deploy Vector as a DaemonSet to collect container logs from all Kubernetes nodes.
      - name: Log Enrichment
        description: Parse, enrich, and normalize log events using VRL before routing to downstream systems.
      - name: Metrics Collection
        description: Collect host and service metrics using Vector's built-in sources and forward to Prometheus or DataDog.
      - name: Splunk Cost Reduction
        description: Use Vector to filter and route Splunk data to reduce indexing volume and licensing costs.
  - type: Integrations
    data:
      - name: Datadog
        description: Native Datadog logs and metrics sink; Vector was created and is maintained by Datadog.
      - name: Elasticsearch
        description: Elasticsearch sink for forwarding logs and metrics to Elasticsearch clusters.
      - name: Splunk HEC
        description: Splunk HTTP Event Collector sink for sending data to Splunk Enterprise and Cloud.
      - name: Kafka
        description: Kafka source and sink for consuming and producing observability data streams.
      - name: AWS S3
        description: S3 sink for archiving logs and metrics to Amazon S3 for long-term storage.
      - name: Grafana Loki
        description: Loki sink for forwarding logs to Grafana's log aggregation system.
      - name: Prometheus
        description: Prometheus remote write sink and scrape source for metrics pipelines.
      - name: Kubernetes
        description: Kubernetes source for collecting container logs, pod metadata, and events.
maintainers:
  - FN: Kin Lane
    email: kin@apievangelist.com