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fix(docs): add disk usage req (#3415)

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docs/quickstart.md
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@ -4,7 +4,9 @@
To deploy a new instance of DataHub, perform the following steps. To deploy a new instance of DataHub, perform the following steps.
1. Install [docker](https://docs.docker.com/install/) and [docker-compose](https://docs.docker.com/compose/install/) (if using Linux). Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs, 8GB RAM, 2GB Swap area. 1. Install [docker](https://docs.docker.com/install/) and [docker-compose](https://docs.docker.com/compose/install/) (if
using Linux). Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs,
8GB RAM, 2GB Swap area, and 10GB disk space.
2. Launch the Docker Engine from command line or the desktop app. 2. Launch the Docker Engine from command line or the desktop app.
@ -21,7 +23,8 @@ To deploy a new instance of DataHub, perform the following steps.
datahub version datahub version
``` ```
If you see "command not found", try running cli commands with the prefix 'python3 -m' instead: `python3 -m datahub version` If you see "command not found", try running cli commands with the prefix 'python3 -m'
instead: `python3 -m datahub version`
4. To deploy DataHub, run the following CLI command from your terminal 4. To deploy DataHub, run the following CLI command from your terminal
@ -29,14 +32,17 @@ To deploy a new instance of DataHub, perform the following steps.
datahub docker quickstart datahub docker quickstart
``` ```
Upon completion of this step, you should be able to navigate to the DataHub UI at [http://localhost:9002](http://localhost:9002) in your browser. You can sign in using `datahub` as both the username and password. Upon completion of this step, you should be able to navigate to the DataHub UI
at [http://localhost:9002](http://localhost:9002) in your browser. You can sign in using `datahub` as both the
username and password.
5. To ingest the sample metadata, run the following CLI command from your terminal 5. To ingest the sample metadata, run the following CLI command from your terminal
``` ```
datahub docker ingest-sample-data datahub docker ingest-sample-data
``` ```
That's it! To start pushing your company's metadata into DataHub, take a look at the [Metadata Ingestion Framework](../metadata-ingestion/README.md). That's it! To start pushing your company's metadata into DataHub, take a look at
the [Metadata Ingestion Framework](../metadata-ingestion/README.md).
## Resetting DataHub ## Resetting DataHub
@ -50,8 +56,8 @@ datahub docker nuke
### Command not found: datahub ### Command not found: datahub
If running the datahub cli produces "command not found" errors inside your terminal, your system may be defaulting to an older If running the datahub cli produces "command not found" errors inside your terminal, your system may be defaulting to an
version of Python. Try prefixing your `datahub` commands with `python3 -m`: older version of Python. Try prefixing your `datahub` commands with `python3 -m`:
``` ```
python3 -m datahub docker quickstart python3 -m datahub docker quickstart
@ -60,8 +66,8 @@ python3 -m datahub docker quickstart
### Miscellaneous Docker issues ### Miscellaneous Docker issues
There can be misc issues with Docker, like conflicting containers and dangling volumes, that can often be resolved by There can be misc issues with Docker, like conflicting containers and dangling volumes, that can often be resolved by
pruning your Docker state with the following command. Note that this command removes all unused containers, networks, images (both dangling and unreferenced), pruning your Docker state with the following command. Note that this command removes all unused containers, networks,
and optionally, volumes. images (both dangling and unreferenced), and optionally, volumes.
``` ```
docker system prune docker system prune