Vector Components

Collect events from AMQP 0.9.1 compatible brokers like RabbitMQ

Collect metrics from Apache’s HTTPD server

Collect Docker container stats for tasks running in AWS ECS and AWS Fargate

Collect logs from AWS Kinesis Firehose

Collect logs from AWS S3

Collect logs from AWS SQS

Receive logs, metrics, and traces collected by a Datadog Agent

Generate fake log events, which can be useful for testing and demos

Collect DNS logs from a dnstap-compatible server

Collect logs from Docker

Receive metrics from collected by a EventStoreDB

Collect output from a process running on the host

Collect logs from files

Collect logs from a file descriptor

Collect logs from a Fluentd or Fluent Bit agent

Fetch observability events from GCP’s PubSub messaging system

Collect logs from Heroku’s Logplex, the router responsible for receiving logs from your Heroku apps

Collect metric data from the local system

Pull observability data from an HTTP server at a configured interval

Receive observability data from an HTTP client request

Expose all log and trace messages emitted by the running Vector instance

Access to the metrics produced by Vector itself and process them in your Vector pipeline

Collect logs from JournalD

Collect observability data from Apache Kafka topics

Collect logs from Kubernetes Nodes

Collect logs from a Logstash agent

Collect metrics from the MongoDB database

Receive logs from an MQTT broker

Read observability data from subjects on the NATS messaging system

Collect metrics from NGINX

Receive OTLP data through gRPC or HTTP.

Collect metrics from the PostgreSQL database

Collect metrics from Prometheus

Collect metrics from Prometheus

Collect metrics via the Prometheus client

Collect observability events from Apache Pulsar topics

Collect observability data from Redis.

Collect logs using the socket client

Receive logs from Splunk

Publish statically configured metrics on an interval

Collect metrics emitted via StatsD protocol

Collect logs sent via stdin

Collect logs sent via Syslog

Collect observability data from another Vector instance

Modify your observability data as it passes through your topology using Vector Remap Language (VRL)

Aggregate metrics passing through a topology

Parse metadata emitted by AWS EC2 instances

Deduplicate logs passing through a topology

Routes events from one or more streams to unique sub-streams based on a set of user-defined conditions.

Filter events based on a set of conditions

Convert log events to metric events

Modify event data using the Lua programming language

Convert metric events to log events

Collapse multiple log events into a single event based on a set of conditions and merge strategies

Split a stream of events into multiple sub-streams based on user-supplied conditions

Sample events from an event stream based on supplied criteria and at a configurable rate

Limit the cardinality of tags on metrics events as a safeguard against cardinality explosion

Rate limit logs passing through a topology

A variant of ring buffer or backtrace logging implemented as a sliding window

Send events to AMQP 0.9.1 compatible brokers like RabbitMQ

Deliver events to AppSignal

Publish log events to AWS Cloudwatch Logs

Publish metric events to AWS Cloudwatch Metrics

Publish logs to AWS Kinesis Data Firehose topics

Publish logs to AWS Kinesis Streams topics

Store observability events in the AWS S3 object storage system

Publish observability events to Simple Notification Service topics

Publish observability events to Simple Queue Service topics

Deliver log events to Axiom

Store your observability data in Azure Blob Storage

Publish log events to the Azure Monitor Logs service

Send observability events nowhere, which can be useful for debugging purposes

Deliver log data to the ClickHouse database

Display observability events in the console, which can be useful for debugging purposes

Deliver log data to the Databend database

Publish observability events to the Datadog Events API

Publish log events to Datadog

Publish metric events to Datadog

Publish traces to Datadog

Index observability events in Elasticsearch

Output observability events into files

Store unstructured log events in Google Chronicle

Deliver metrics to GCP’s Cloud Monitoring system

Store observability events in GCP Cloud Storage

Deliver logs to GCP’s Cloud Operations suite

Publish observability events to GCP’s PubSub messaging system

Writes logs to GreptimeDB

Writes metrics to GreptimeDB

Deliver log events to Honeycomb

Deliver observability data to an HTTP server

Deliver log event data to Humio

Deliver metric event data to Humio

Deliver log event data to InfluxDB

Deliver metric event data to InfluxDB

Publish observability data to Apache Kafka topics

Deliver log events to Keep

Deliver log event data to the Loki aggregation system

Deliver log event data to Mezmo

Deliver observability event data to an MQTT broker

Publish observability data to subjects on the NATS messaging system

Deliver events to New Relic

Send OTLP data through HTTP.

Deliver log events to Papertrail from SolarWinds

Deliver observability data to the PostgreSQL database

Output metric events to a Prometheus exporter running on the host

Deliver metric data to a Prometheus remote write endpoint

Publish observability events to Apache Pulsar topics

Publish observability data to Redis.

Publish log events to Sematext

Publish metric events to Sematext

Deliver logs to a remote socket endpoint

Deliver log data to Splunk’s HTTP Event Collector

Deliver metric data to Splunk’s HTTP Event Collector

Deliver metric data to a StatsD aggregator

Relay observability data to another Vector instance

Output observability events into WebHDFS

Deliver observability event data to a websocket listener

Deliver observability event data to websocket clients