❏ It’s built in Rust! Therefore it’s fast and memory efficient

❏ End-to-End, meaning only one service needed to get data from A to B

❏ 100% open source

❏ Easy to configure and transform data

❏ Great documentation

❏ Sources

Where vector gets its data from.

• Examples: Journald, Docker, File.

❏ Transforms

Used to transform an input into an output by parsing, filtering, sampling, or aggregating.

• Examples: Filter, Remove Fields, Add Fields.

❏ Sinks

The destination for an event.

• Examples: AWS Cloudwatch Logs, AWS S3, File.

1. Logs: A structured representation of a point-in-time event. It contains an arbitrary set of fields that describe the log event. Vector is schema neutral therefore it supports legacy and future schemas.
2. Metrics: Represents a numerical operation performed on a time series.

A component can either be a Metric or Log event type component. Components can only interact with other components of the same event type.

apache_metrics (M)

aws_ecs_metrics (M)

aws_kinesis_firehose (L)

aws_s3 (L)

docker_logs (L)

file (L)

generator (L)

heroku_logs (L)

host_metrics (M)

http (L)

internal_logs (L)

internal_metrics (M)

internal_logs (L)

internal_metricsjour

journald (L)

kafka (L)

kubernetes_logs (L)

mongodb_metrics (M)

nginx_metrics (M)

prometheus_remote_write (M)

prometheus_scrape (M)

socket (L)

splunk_hec (L)

statsd (M)

stdin (L)

syslog (L)

vector (L)

add_fields (L)

add_tags (M)

ansi_stripper (L)

aws_cloudwatch_logs_subscription_parser (L)

aws_ec2_metadata (L)

coercer (L)

concat (L)

dedupe (L)

filter (M, L)

geoip (L)

grok_parser (L)

json_parser (L)

key_value_parser (L)

log_to_metric (M, L)

logfmt_parser (L)

lua (M)

merge (L)

metric_to_log (M)

reduce (L)

regex_parser (L)

remap (M)

remove_fields (L)

remove_tags (M)

rename_fields (L)

sampler (L)

split (L)

swimlanes (L)

tag_cardinality_limit (M)

tokenizer (L)

wasm (L)

aws_cloudwatch_logs (L)

aws_cloudwatch_metrics (M)

aws_kinesis_firehose (L)

aws_kinesis_streams (L)

aws_s3 (L)

aws_sqs (L)

azure_monitor_logs (L)

blackhole (L)

clickhouse (L)

console (M, L)

datadog_logs (L)

datadog_metrics (M)

elasticsearch (L)

file (L)

gcp_cloud_storage (L)

gcp_pubsub (L)

gcp_stackdriver_logs (L)

honeycomb (L)

http (L)

humio_logs (L)

humio_metrics (M)

influxdb_logs (L)

influxdb_metrics (M)

kafka (L)

logdna (L)

loki (L)

nats (L)

new_relic_logs (L)

papertrail (L)

prometheus_exporter (M)

prometheus_remote_write (M)

pulsar (L)

sematext_logs (L)

sematext_metrics (M)

socket (L)

splunk_hec (L)

statsd (M)

vector (M, L)

❏ Two transforms available called log_to_metric and metric_to_log allow converting events to the other types. Enables sending one event type component to and opposite event type component after transformation.

❏ Internal sources for logs and metrics, allows monitoring of vector itself.

❏ Sends events from sinks to downstream services in batch payloads. This can be configured in each sink.