Send artifact information to Harness SEI
This topic provides step-by-step instructions on how you can set up a GitHub Actions workflow to allow SEI to ingest the data for the artifacts and environment variables from GitHub Actions.
Prerequisites
- A GitHub repository for your project
- SEI API Key & SEI Integration ID
- Access to GitHub Actions for the repository.
- Familiarity with environment variables and GitHub Actions configuration.
Set up the workflow
Follow these steps to set up the workflow:
-
Create an SEI API Key
- Go to your SEI account and create an API Key.
- Give the API Key a Name and Description.
- Set the role as
Ingestion
.
-
Create Organization/Repository Secret
- To securely store the SEI API Key, you can create a GitHub secret in either your organization or your repository, depending on your preference.
- For Organization Secret, go to creating secrets in an organization Give the secret a name (e.g.,
SEI_API_KEY
) and store the SEI API Key value. - For Repository Secret, go to creating secrets in a repositoryGive the secret a name (e.g.,
GITHUB_SECRETS
) and store the SEI API Key value.
-
Create the GitHub Actions Integration and make a note of the Integration ID, which you will need in the next steps. For more information, go to configure the integration on the cloud.
-
Append the following steps to your existing GitHub Actions workflow configuration:
- name: Push artifacts to SEI Endpoint
id: push_artifacts
env:
base_url: "https://app.harness.io/gateway/sei/api/v1"
# Change the URL based on your environment (e.g., eu1, asia1, etc.)
payload: '{"integration_id":"<INTEGRATION_ID>","repository":"${{ github.repository }}","job_run_number":"${{ github.run_number }}","job_name":"${{ github.workflow }}","artifacts":[{"name":"<ADD_IMAGE_NAME>", "location":"<ADD_LOCATION>", "tag":"<ADD_TAG>", "digest":"<ADD_DIGEST>","type":"<ADD_TYPE>", "artifact_created_at":"<ADD_ARTIFACT_CREATED_AT>"}]}'
run: curl '${{ env.base_url }}/v1/cicd/push_artifacts' -H 'accept:application/json' -H 'authorization:Apikey ${{ secrets.SEI_API_KEY }}' -H 'content-type:application/json' --data-raw '${{ env.payload }}' --compressed --globoff
- name: Push params to SEI Endpoint
id: push_params
env:
base_url: "https://app.harness.io/gateway/sei/api/v1"
# Change the URL based on your environment (e.g., eu1, asia1, etc.)
payload: '{"integration_id":"<INTEGRATION_ID>","repository":"${{ github.repository }}","job_run_number":"${{ github.run_number }}","job_name":"${{ github.workflow }}","params":[{"name":"<ADD_NAME>","type":"<ADD_TYPE>","value":"<ADD_VALUE>"}]}'
run: curl '${{ env.base_url }}/v1/cicd/push_job_run_params' -H 'accept:application/json' -H 'authorization:Apikey ${{ secrets.SEI_API_KEY }}' -H 'content-type:application/json' --data-raw '${{ env.payload }}' --compressed --globoff
-
Make sure to update the
INTEGRATION_ID
in the workflow step with your actual SEI Integration ID. Also, update theBASE_URL
according to your environment:- Base URL (PROD2): https://app.harness.io/gratis/sei/api/v1/
- Base URL (PROD1): https://app.harness.io/prod1/sei/api/v1/
-
If there is an issue with the SEI endpoint (e.g., if the endpoint is down, 500 Internal Server Error), and you want the workflow run to fail if artifacts are not sent to SEI, use the -f flag in the curl command.
curl -f <REQUEST>
- Refer to the metadata below to request and ingest the artifact data from GitHub Actions into SEI.
Description | |
---|---|
name | Image name of the artifact (e.g., ghcr.io/organization/repository:v0.1.1 where the repository is the image name) |
location | Location of the artifact (e.g., ghcr.io/organization) |
tag | Tag of the image (e.g., ghcr.io/organization/repository:v0.1.1 where v0.1.1 is the tag/qualifier). |
digest | Digest/Hash of the generated artifact (e.g., sha256.). |
type | Type of the generated artifact (optional). If CD is Harness, set type as "container" for correlation. |
artifact_created_at | Creation time of the artifact in UTC format (optional). |
name
,location
,tag
, anddigest
of the artifact are required fields.- If
type
,artifact_created_at
, ordigest
are not available you can remove those fields from the object. type
andartifact_created_at
are optional fields.
- Refer to the metadata below to ingest the environment variables data from GHA into SEI.
Note that all the keys mentioned are required fields.
Keys | Description |
---|---|
name | The environment variable name |
type | The type of the environment variable (string/integer) |
value | The associated value for the environment variable |
Here's a sample Github Actions workflow:
name: Creating artifacts
run-name: ${{ github.actor }} is creating artifacts
on:
push:
branches:
- main
workflow_dispatch:
jobs:
check_env:
runs-on: ubuntu-latest
env:
integration_id: 1
sample: ${{ github.run_id }}
steps:
- name: Check artifacts
run: echo 'Integration ID - ${{ env.integration_id }}'
running-resuable-workflow:
runs-on: ubuntu-latest
env:
check_run_id: 0
modulo: 1
steps:
- name: Workflow Step 1
run: echo 'Hello World';echo ${{ github.run_id }};echo ${{ env.modulo }}
- name: Workflow Step 2 - If condition
run: echo 'Exiting successfully'
deploy-to-docker:
runs-on: ubuntu-latest
steps:
- name: Configure Python in Ubuntu Environment
run: |
python3 -m pip install requests
docker -v
- uses: actions/checkout@v4
- name: List files
run: |
pwd
ls
- name: Execute Python script
run: |
python3 sample_script.py
ls /tmp/
working-directory: ./temp/
- name: Docker Login
uses: docker/login-action@v1
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Build docker image
run: |
echo "Building image"
docker system info | grep -E 'Username|Registry'
docker build -t username/repo:tag .
working-directory: ./temp/
- name: Push Docker Image
id: docker_deploy
run: |
docker push username/repo:tag
echo "digest=$(docker inspect --format='{{index .RepoDigests 0}}' username/repo:tag | cut -d'@' -f2)" >> "$GITHUB_OUTPUT"
working-directory: ./temp/
- name: Logout Docker
run: |
echo "${{steps.docker_deploy.outputs.digest}}"
docker logout
outputs:
docker_digest: ${{ steps.docker_deploy.outputs.digest }}
push_artifacts_to_sei:
runs-on: ubuntu-latest
needs: deploy-to-docker
steps:
- name: Push artifacts to SEI Endpoint
id: push_artifacts
env:
base_url: "https://app.harness.io/gateway/sei/api/v1"
# change the URL based on environment e.g. eu1, asia1, etc.
integration_id: 155
docker_image: "username/repo"
tag: v1.18.0
type: "Test_repo2"
payload: '{"integration_id":"155","repository":"${{ github.repository }}","job_run_number":"${{ github.run_number }}","job_name":"${{ github.workflow }}","artifacts":[{"name":"temp-test_rep01", "location":"registry.hub.docker.com/username", "tag":"v1.18.0", "type":"container", "digest": "${{needs.deploy-to-docker.outputs.docker_digest}}","artifacts_created_at": "2023-01-01T12:00:00.000+00:00"}]}'
run: |
curl '${{ env.base_url }}/v1/cicd/push_artifacts' -H 'accept:application/json' -H 'authorization:Apikey ${{ secrets.SEI_API_KEY }}' -H 'content-type:application/json' --data-raw '${{ env.payload }}' --compressed --globoff
- name: Push params to SEI Endpoint
id: push_params
env:
base_url: "https://app.harness.io/gateway/sei/api/v1"
# change the URL based on environment e.g. eu1, asia1, etc.
payload: '{"integration_id":"155","repository":"${{ github.repository }}","job_run_number":"${{ github.run_number }}","job_name":"${{ github.workflow }}","params":[{"name":"docker_image","type":"string","value":"username/repo"}, {"name":"tag","type":"string","value":"v1.18.0"}, {"name":"artifacts_created_at","type":"string","value":"2023-01-01T12:00:00.000+00:00"}]}'
run: curl '${{ env.base_url }}/v1/cicd/push_job_run_params' -H 'accept:application/json' -H 'authorization:Apikey ${{ secrets.SEI_API_KEY }}' -H 'content-type:application/json' --data-raw '${{ env.payload }}' --compressed --globoff
- If the SEI API fails, the workflow will not be able to send the artifacts or the job run parameters. In such cases, you will need to re-execute the Github Actions workflow.
- Artifacts data from existing/previous workflow executions cannot be ingested into SEI.
- Ensure that the tag names of images are unique to maintain the correct correlation between CI and CD stages.