dapp-runner is a utility that allows you to run decentralized applications on Golem.
It uses simple application descriptors expressed in yaml, similar to those used by
tools like docker-compose.
dapp-runner runs alongside the Golem daemon
and uses yapapi, Golem's Python high-level API
to communicate with it. As opposed to using plain yapapi though, deployment of
applications on Golem using dapp-runner requires no code and no experience in Python.
In its present form, the dapp-runner constitutes an initial reference implementation
of the multi-service application deployment framework described in
GAP-16.
Following features of the framework are currently supported:
- Descriptor "Apply" operation
- Single-YAML package support
- Merging descriptor files
- GAOM explicit dependency syntax
- GAOM object dependency graph [currently limited to the services' explicit dependency syntax]
While the dapp-runner is perfectly capable of running decentralized apps on its own, we are also
providing a separate tool to facilitate running and managing multiple applications on a single
machine, namely, the dapp-manager.
dApp Manager keeps track of the launched apps and allows you to easily query their output streams.
It uses the dapp-runner as its back-end and both require the yagna daemon to communicate with the
rest of the Golem Network.
To run Golem apps, dapp-runner requires a properly configured yagna daemon.
In the future, you'll be able to provision apps using external supervisor machines
which will run a yagna daemon on your behalf.
For now, please follow the "Requestor development: a quick primer"
tutorial and ensure that your yagna is up and running. Only the first part of this
tutorial is required - you don't need to run the blender example.
Most importantly, make sure you have set the YAGNA_APPKEY in your evironment, e.g. with:
export YAGNA_APPKEY=insert-your-32-char-app-key-hereor, on Windows:
set YAGNA_APPKEY=insert-your-32-char-app-key-hereand if you don't know what your app-key is, you can always query yagna with:
yagna app-key listFirst, ensure you have Python 3.8 or later:
python3 --version[ depending on the platform, it may be just python instead of python3 ]
If your Python version is older, consider using pyenv.
Once your python interpreter reports a version 3.8 or later, you can set-up your virtual environment:
python3 -m venv ~/.envs/dapp-runner
source ~/.envs/dapp-runner/bin/activateor, if you're on Windows:
python -m venv --clear %HOMEDRIVE%%HOMEPATH%\.envs\dapp-runner
%HOMEDRIVE%%HOMEPATH%\.envs\dapp-runner\Scripts\activate.batgit clone --recurse-submodules https://github.com/golemfactory/dapp-runner.gitcd dapp-runner
pip install -U pip poetry
poetry installMake sure your yagna daemon is running,
you have initialized the payment driver with yagna payment init --sender,
and that you have set the YAGNA_APPKEY environment variable.
Then run:
dapp-runner start --config configs/default.yaml dapp-store/apps/webapp.yamlYou should see the application being deployed on the Golem Network and once it's up, you'll be greeted with:
{"http": {"local_proxy_address": "http://localhost:8080"}}You can connect to this address using your local browser, and you'll see our minimalistic web application example running.
Press Ctrl-C in the terminal where you ran dapp-runner to initiate its shutdown.
As mentioned above, the decentralized applications that are deployed on Golem by the
dapp-runner are described in yaml files, conforming to the schema
described in GAP-16.
Here's an example application descriptor (http-proxy.yaml), that provisions a single
instance of a simple, static website served with nginx:
payloads:
nginx:
runtime: "vm"
params:
image_hash: "16ad039c00f60a48c76d0644c96ccba63b13296d140477c736512127"
nodes:
http:
payload: "nginx"
init:
- ["/docker-entrypoint.sh"]
- ["/bin/chmod", "a+x", "/"]
- ["/bin/sh", "-c", 'echo "Hello from inside Golem!" > /usr/share/nginx/html/index.html']
- ["/bin/rm", "/var/log/nginx/access.log", "/var/log/nginx/error.log"]
- ["/usr/sbin/nginx"]
http_proxy:
ports:
- "80" # specify just the remote port, allow the local port to be automatically chosenAnd here's an example of a slightly more complex application (webapp.yaml), that uses
two kinds of services and explicitly connects them within a specified network:
payloads:
db:
runtime: "vm"
params:
image_hash: "85021afecf51687ecae8bdc21e10f3b11b82d2e3b169ba44e177340c"
http:
runtime: "vm"
params:
image_hash: "c37c1364f637c199fe710ca62241ff486db92c875b786814c6030aa1"
nodes:
db:
payload: "db"
init:
- ["/bin/run_rqlite.sh"]
network: "default"
ip:
- "192.168.0.2"
http:
payload: "http"
init:
- ["/bin/bash", "-c", "cd /webapp && python app.py --db-address 192.168.0.2 --db-port 4001 initdb"]
- ["/bin/bash", "-c", "cd /webapp && python app.py --db-address 192.168.0.2 --db-port 4001 run > /webapp/out 2> /webapp/err &"]
http_proxy:
ports:
- "5000" # specify just the remote port, allow the local port to be automatically chosen
network: "default"
ip:
- "192.168.0.3"
depends_on:
- "db"
networks:
default:
ip: "192.168.0.0/24"As can be seen in the http_proxy example above, the networks definition can be omitted.
Adding a http_proxy element to a nodes entry, causes the dapp-runner to implicitly
add the networks object with a default of a single IPv4 network. Additionally, it adds
the vpn capability to the requested parameters of the deployed vm runtime.
Note: The networks and capabilities objects will only be implicitly added if
they are not already present in the descriptor. If the application specifies any of
those objects, it is assumed that the application authors know what they're doing.
Similarly, specifying the payload as vm/manifest implicitly adds manifest-support to
the requested capabilities for the runtime.
Note: Again, this is only done if the payload.params doesn't already contain the
capabilities object.
Currently, the dapp-runner implements a single CLI command, start:
Usage: dapp-runner start [OPTIONS] DESCRIPTORS...which allows the following options:
-d, --data PATH Path to the data file.
-l, --log PATH Path to the log file.
-s, --state PATH Path to the state file.
--stdout PATH Redirect stdout to the specified file.
--stderr PATH Redirect stderr to the specified file.
-c, --config PATH Path to the file containing yagna-specific config.
[required]
--silent
--help Show this message and exit.The --data, --log, --state, --stdout, and --stderr arguments specify the
locations of files to which the respective streams are written. If unspecified, all
streams are written to the console which the dapp-runner is invoked from.
The data stream consists of JSON-formatted output of specific components that are run
as part of the services. Currently it carries the command execution events from
exescript commands, e.g.:
{
"db": {
"0": [
{
"command": {
"run": {
"entry_point": "/bin/run_rqlite.sh",
"args": [],
"capture": { "stdout": { "stream": {} }, "stderr": { "stream": {} } }
}
},
"success": true,
"stdout": null,
"stderr": null
}
]
}
}and the parameters of any started instances of Local HTTP proxies:
{ "http": { "local_proxy_address": "http://localhost:8080" } }The keys in the outermost dictionaries refer to names of service cluster as specified in
the yaml descriptor file. For exescript commands, the secondary layer's keys refer to
indices of instances within the specific cluster.
The state stream consists of JSON-formatted descriptions of the state of the dapp
after each state change, e.g.:
{ "db": { "0": "running" }, "http": { "0": "starting" } }Here, again, the keys in the topmost dictionary refer to the names of service clusters
defined in the yaml descriptor file and the secondary layer's keys refer to indices
of specific instances.
The log stream is a text stream of log messages emitted from dapp-runner.
Finally, stdout and stderr refer to the standard output streams of the dapp-runner
script.
This is a mandatory argument, specifying a path to a yaml file containing a
description of a configuration to connect to your yagna daemon, e.g.:
yagna:
app_key: "$YAGNA_APPKEY"
subnet_tag: "devnet-beta"
payment:
budget: 1.0 # GLM
driver: "erc20"
network: "holesky"One or more application descriptors, as specified in the "Application descriptor" section above.
If more than one yaml descriptor file is given, all of the yaml files are merged
into one descriptor before being processed further by the dapp-runner. The files
are merged using a deep-merge strategy with contents of each subsequent yaml file
overriding the colliding keys of the former ones.