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Quickstart: Docker

The whole DFE stack under Docker Compose on one host: a laptop, a demo box or a proof of concept. It runs the same images as a Kubernetes deployment, just packaged differently.

You need Docker Engine 26.0 or later with Compose 2.34.0 or later.

docker compose -f oci://ghcr.io/hyperi-io/dfe-docker:compose up -d

Point your browser to http://localhost:3000 and log in as admin with password dfe-first-login. The console makes you change it at first login. Every port listens on 127.0.0.1 only. docker compose -f oci://ghcr.io/hyperi-io/dfe-docker:compose down stops the stack and keeps its data.

ProfileTransportRuns
slim-grpcgRPC, low latencyThe core path alone: receiver, loader and ClickHouse, with the engine and the console.
slim-kafkaKafka message busThe same core path over Kafka, plus a Kafka UI.
single-grpcgRPC, low latencyThe core path plus the fetcher and the transforms.
single-kafkaKafka message busThe core path over Kafka, plus the archiver, the fetcher and the transforms. The default.

Then send it an event of your own:

curl -X POST http://localhost:8080/ingest \
  -H 'Content-Type: application/json' \
  -d '{"_source":"main","message":"hello dfe"}'

_source routes it, so "main" lands in dfe.main a couple of seconds later.

Coming from Splunk or Elastic? You didn't create an index or a mapping first, and you won't need to. main takes whatever fields you send and they all work straight away, so a sender adding or changing a field breaks nothing. You tune the fields that matter later. More in what's different.

Where to find it: the console is at http://localhost:3000, ClickHouse HTTP at http://localhost:8123 and the engine API at http://localhost:8003. single-kafka adds the Kafka UI at http://localhost:8081. The ingest ports listen on every interface, and everything else on this host only.

Next:

  1. The full first look, including reading the event back: Taking DFE for a first look.
  2. What each profile runs: profiles.
  3. Set the deployment's configuration: configuration.
  4. Deploy, and move to a newer release: deploying.
  5. Run it day to day: operating.
  6. When something does not come up: troubleshooting.