Manual Distributed Task Execution on GitLab
Using Nx Agents is the easiest way to distribute task execution, but it your organization may not be able to use hosted Nx Agents. You can set up distributed task execution on your own CI provider using the recipe below.
Run Agents on GitLab
Run agents directly on GitLab with the workflow below:
1image: node:18
2
3# Creating template for DTE agents
4.dte-agent:
5 interruptible: true
6 cache:
7 key:
8 files:
9 - yarn.lock
10 paths:
11 - '.yarn-cache/'
12 script:
13 - yarn install --cache-folder .yarn-cache --prefer-offline --frozen-lockfile
14 - yarn nx-cloud start-agent
15
16# Creating template for a job running DTE (orchestrator)
17.base-pipeline:
18 interruptible: true
19 only:
20 - main
21 - merge_requests
22 cache:
23 key:
24 files:
25 - yarn.lock
26 paths:
27 - '.yarn-cache/'
28 before_script:
29 - yarn install --cache-folder .yarn-cache --prefer-offline --frozen-lockfile
30 - NX_HEAD=$CI_COMMIT_SHA
31 - NX_BASE=${CI_MERGE_REQUEST_DIFF_BASE_SHA:-$CI_COMMIT_BEFORE_SHA}
32
33 artifacts:
34 expire_in: 5 days
35 paths:
36 - dist
37
38# Main job running DTE
39nx-dte:
40 stage: affected
41 extends: .base-pipeline
42 script:
43 - yarn nx-cloud start-ci-run --distribute-on="manual" --stop-agents-after=e2e-ci
44 - yarn nx-cloud record -- nx format:check --base=$NX_BASE --head=$NX_HEAD
45 - yarn nx affected --base=$NX_BASE --head=$NX_HEAD -t lint,test,build,e2e-ci --parallel=2
46
47# Create as many agents as you want
48nx-dte-agent1:
49 extends: .dte-agent
50 stage: affected
51nx-dte-agent2:
52 extends: .dte-agent
53 stage: affected
54nx-dte-agent3:
55 extends: .dte-agent
56 stage: affected
57This configuration is setting up two types of jobs - a main job and three agent jobs.
The main job tells Nx Cloud to use DTE and then runs normal Nx commands as if this were a single pipeline set up. Once the commands are done, it notifies Nx Cloud to stop the agent jobs.
The agent jobs set up the repo and then wait for Nx Cloud to assign them tasks.
The agents and the --parallel flag both parallelize tasks, but in different ways. The way this workflow is written, there will be 3 agents running tasks and each agent will try to run 2 tasks at once. If a particular CI run only has 2 tasks, only one agent will be used.
Rerunning jobs with DTE
Rerunning only failed jobs results in agent jobs not running, which causes the CI pipeline to hang and eventually timeout. This is a common pitfall when using a CI providers "rerun failed jobs", or equivalent, feature since agent jobs will always complete successfully.
To enforce rerunning all jobs, you can set up your CI pipeline to exit early with a helpful error. For example:
You reran only failed jobs, but CI requires rerunning all jobs. Rerun all jobs in the pipeline to prevent this error.
At a high level:
- Create a job that always succeeds and uploads an artifact on the pipeline with the run attempt number of the pipeline.
- The main and agent jobs can read the artifact file when starting and assert they are on the same re-try attempt.
- If the reattempt number does not match, then error with a message stating to rerun all jobs. Otherwise, the pipelines are on the same rerun and can proceed as normally.