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1 | 1 | # Docker Images
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| 2 | + |
| 3 | +## Prerequisites |
| 4 | +You need to install [docker](https://docs.docker.com/install/) and |
| 5 | +[docker-compose](https://docs.docker.com/compose/install/) (if using Linux; on Windows and Mac compose is included with |
| 6 | +Docker Desktop). |
| 7 | + |
| 8 | +Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs, 8GB RAM, 2GB Swap |
| 9 | +area. |
| 10 | + |
| 11 | +## Quickstart |
| 12 | + |
2 | 13 | The easiest way to bring up and test DataHub is using DataHub [Docker](https://www.docker.com) images
|
3 | 14 | which are continuously deployed to [Docker Hub](https://hub.docker.com/u/linkedin) with every commit to repository.
|
4 | 15 |
|
| 16 | +You can easily download and run all these images and their dependencies with our |
| 17 | +[quick start guide](../docs/quickstart.md). |
| 18 | + |
| 19 | +DataHub Docker Images: |
| 20 | + |
5 | 21 | * [linkedin/datahub-gms](https://cloud.docker.com/repository/docker/linkedin/datahub-gms/)
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6 | 22 | * [linkedin/datahub-frontend](https://cloud.docker.com/repository/docker/linkedin/datahub-frontend/)
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7 | 23 | * [linkedin/datahub-mae-consumer](https://cloud.docker.com/repository/docker/linkedin/datahub-mae-consumer/)
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8 | 24 | * [linkedin/datahub-mce-consumer](https://cloud.docker.com/repository/docker/linkedin/datahub-mce-consumer/)
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9 | 25 |
|
10 |
| -Above Docker images are created for DataHub specific use. You can check subdirectories to check how those images are |
11 |
| -generated via [Dockerbuild](https://docs.docker.com/engine/reference/commandline/build/) files or |
12 |
| -how to start each container using [Docker Compose](https://docs.docker.com/compose/). Other than these, DataHub depends |
13 |
| -on below Docker images to be able to run: |
| 26 | +Dependencies: |
14 | 27 | * [**Kafka and Schema Registry**](kafka)
|
15 |
| -* [**Elasticsearch**](elasticsearch) |
| 28 | +* [**Elasticsearch**](elasticsearch-setup) |
16 | 29 | * [**MySQL**](mysql)
|
17 | 30 |
|
18 |
| -Local-built ingestion image allows you to create on an ad-hoc basis `metadatachangeevent` with Python script. |
19 |
| -The pipeline depends on all the above images composing up. |
20 |
| -* [**Ingestion**](ingestion) |
| 31 | +### Ingesting demo data. |
21 | 32 |
|
22 |
| -## Prerequisites |
23 |
| -You need to install [docker](https://docs.docker.com/install/) and [docker-compose](https://docs.docker.com/compose/install/). |
| 33 | +If you want to test ingesting some data once DataHub is up, see [**Ingestion**](ingestion/README.md). |
24 | 34 |
|
25 |
| -## Quickstart |
26 |
| -If you want to quickly try and evaluate DataHub by running all necessary Docker containers, you can check |
27 |
| -[Quickstart Guide](quickstart). |
| 35 | +## Using Docker Images During Development |
| 36 | + |
| 37 | +See [Using Docker Images During Development](../docs/docker/development.md). |
| 38 | + |
| 39 | +## Building And Deploying Docker Images |
| 40 | + |
| 41 | +We use GitHub actions to build and continuously deploy our images. There should be no need to do this manually; a |
| 42 | +successful release on Github will automatically publish the images. |
| 43 | + |
| 44 | +### Building images |
| 45 | + |
| 46 | +To build the full images (that we are going to publish), you need to run the following: |
| 47 | + |
| 48 | +``` |
| 49 | +COMPOSE_DOCKER_CLI_BUILD=1 DOCKER_BUILDKIT=1 docker-compose -p datahub build |
| 50 | +``` |
| 51 | + |
| 52 | +This is because we're relying on builtkit for multistage builds. It does not hurt also set `DATAHUB_VERSION` to |
| 53 | +something unique. |
| 54 | + |
| 55 | +This is not our recommended development flow and most developers should be following the |
| 56 | +[Using Docker Images During Development](#using-docker-images-during-development) guide. |
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