Hello, I’m looking to run some integration tests with the helm distribution of datahub and I was wondering how I can run a ingest using “datahub-ingestion-cron” without having to visit the UI to generate a token.
Hey there! Make sure your message includes the following information if relevant, so we can help more effectively!
- Are you using UI or CLI for ingestion?
- Which DataHub version are you using? (e.g. 0.12.0)
- What data source(s) are you integrating with DataHub? (e.g. BigQuery)
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To help you effectively, I need a bit more information:
- Are you using the UI or CLI for ingestion?
- Which DataHub version are you using? (e.g., 0.12.0)?
- What data source(s) are you integrating with DataHub (e.g., BigQuery)?
Based on your initial question, it seems you want to run ingestion using the datahub-ingestion-cron
without having to visit the UI to generate a token. You can achieve this by using a Kubernetes ConfigMap to store your ingestion recipes and scheduling the ingestion via the Helm chart.
Here’s a general approach:
- Create a Kubernetes ConfigMap: Store your ingestion recipe in a ConfigMap.
- Configure
values.yaml
: Enable thedatahub-ingestion-cron
subchart and reference your ConfigMap and recipe file. - Use Environment Variables for Tokens: Instead of hardcoding tokens in your ConfigMap, use environment variables to inject them securely.
Example Configuration
ConfigMap:
apiVersion: v1
kind: ConfigMap
metadata:
name: recipe-config
data:
mysql_recipe.yml: |-
source:
type: mysql
config:
host_port: <MYSQL_HOST>:3306
database: dbname
username: root
password: example
sink:
type: datahub-rest
config:
server: http://<GMS_HOST>:8080
token: ${DATAHUB_TOKEN}
values.yaml:
datahub-ingestion-cron:
enabled: true
crons:
mysql:
schedule: "0 * * * *" # Every hour
recipe:
configmapName: recipe-config
fileName: mysql_recipe.yml
Injecting Environment Variables
You can inject the DATAHUB_TOKEN
environment variable into your Kubernetes pods using a Kubernetes Secret or directly in your deployment configuration.
For more detailed steps, you can refer to the <https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/schedule_docs/kubernetes.md|official documentation>.
Would you like more detailed steps or have any specific questions about this process?
Sources:
- <https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/schedule_docs/kubernetes.md|Using Kubernetes for Scheduling Ingestion>
- <Slack Discussion on Ingestion Scheduling>
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- CLI
- 0.13.2
- s3
<@U06TM7M40RK>
Great, thanks for the details! Given that you’re using the CLI for ingestion, DataHub version 0.13.2, and integrating with S3, here’s how you can set up and run ingestion using datahub-ingestion-cron
without visiting the UI to generate a token.
Steps to Schedule Ingestion Using datahub-ingestion-cron
- Create a Kubernetes ConfigMap: Store your ingestion recipe in a ConfigMap.
- Configure
values.yaml
: Enable thedatahub-ingestion-cron
subchart and reference your ConfigMap and recipe file. - Use Environment Variables for Tokens: Instead of hardcoding tokens in your ConfigMap, use environment variables to inject them securely.
Example Configuration
ConfigMap:
apiVersion: v1
kind: ConfigMap
metadata:
name: recipe-config
data:
s3_recipe.yml: |-
source:
type: s3
config:
bucket_name: <YOUR_S3_BUCKET>
aws_access_key_id: ${AWS_ACCESS_KEY_ID}
aws_secret_access_key: ${AWS_SECRET_ACCESS_KEY}
sink:
type: datahub-rest
config:
server: http://<GMS_HOST>:8080
token: ${DATAHUB_TOKEN}
values.yaml:
datahub-ingestion-cron:
enabled: true
crons:
s3:
schedule: "0 * * * *" # Every hour
recipe:
configmapName: recipe-config
fileName: s3_recipe.yml
Injecting Environment Variables
You can inject the AWS_ACCESS_KEY_ID
, AWS_SECRET_ACCESS_KEY
, and DATAHUB_TOKEN
environment variables into your Kubernetes pods using a Kubernetes Secret or directly in your deployment configuration.
Example Kubernetes Secret:
apiVersion: v1
kind: Secret
metadata:
name: datahub-secrets
type: Opaque
data:
AWS_ACCESS_KEY_ID: <base64_encoded_access_key>
AWS_SECRET_ACCESS_KEY: <base64_encoded_secret_key>
DATAHUB_TOKEN: <base64_encoded_token>
Referencing the Secret in Your Deployment:
apiVersion: apps/v1
kind: Deployment
metadata:
name: datahub-ingestion
spec:
template:
spec:
containers:
- name: datahub-ingestion
envFrom:
- secretRef:
name: datahub-secrets
Running the Ingestion
Once you have your ConfigMap and values.yaml configured, and your secrets set up, you can deploy the Helm chart to schedule the ingestion.
helm upgrade --install datahub datahub/datahub -f values.yaml
This setup will ensure that your ingestion runs as per the schedule defined in the values.yaml
without needing to visit the UI to generate a token.
Would you like more detailed steps or have any specific questions about this process?
Sources:
- <https://github.com/datahub-project/datahub/blob/master/metadata-ingestion/schedule_docs/kubernetes.md|Using Kubernetes for Scheduling Ingestion>
- <Slack Discussion on Ingestion Scheduling>
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Where does the token environment variable come from? <@U06TM7M40RK>
The token environment variable (DATAHUB_TOKEN
) can be generated and managed programmatically without needing to visit the UI. Here’s how you can achieve this:
Generating a Personal Access Token Programmatically
- Enable Metadata Service Authentication: Ensure that metadata service authentication is enabled in your DataHub deployment.
- Generate the Token: Use the DataHub API to generate a personal access token.
Step-by-Step Process
1. Enable Metadata Service Authentication
Ensure that the METADATA_SERVICE_AUTH_ENABLED
environment variable is set to true
for the datahub-gms
container or pod. This enables token-based authentication.
apiVersion: apps/v1
kind: Deployment
metadata:
name: datahub-gms
spec:
template:
spec:
containers:
- name: datahub-gms
env:
- name: METADATA_SERVICE_AUTH_ENABLED
value: "true"
2. Generate the Token
You can generate a personal access token programmatically using the DataHub API. Here’s an example using curl
:
curl -X POST "http://<GMS_HOST>:8080/api/authentication/token" \
-H "Content-Type: application/json" \
-d '{
"username": "<your-username>",
"password": "<your-password>"
}'
This will return a JSON response containing the token. You can then store this token securely in a Kubernetes Secret.
Example Kubernetes Secret
apiVersion: v1
kind: Secret
metadata:
name: datahub-secrets
type: Opaque
data:
DATAHUB_TOKEN: <base64_encoded_token>
Referencing the Secret in Your Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: datahub-ingestion
spec:
template:
spec:
containers:
- name: datahub-ingestion
envFrom:
- secretRef:
name: datahub-secrets
Using the Token in Your Ingestion Recipe
In your ingestion recipe, reference the DATAHUB_TOKEN
environment variable:
sink:
type: datahub-rest
config:
server: http://<GMS_HOST>:8080
token: ${DATAHUB_TOKEN}
Summary
By following these steps, you can generate and manage the DATAHUB_TOKEN
programmatically, ensuring that your ingestion process is automated and secure.
Would you like more detailed steps or have any specific questions about this process?
Sources:
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/personal-access-tokens.md|Personal Access Tokens>
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/introducing-metadata-service-authentication.md|Metadata Service Authentication>
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<@U06TM7M40RK> I get a 401 when I try and curl that service here is how I’m curling:
-H "Content-Type: application/json" \
-d '{
"username": "datahub",
"password": "datahub"
};'```
The 401 Unauthorized error indicates that the authentication request is not being accepted. Here are a few steps to troubleshoot and resolve this issue:
1. Ensure Metadata Service Authentication is Enabled
First, double-check that the METADATA_SERVICE_AUTH_ENABLED
environment variable is set to true
for the datahub-gms
container or pod. This is crucial for enabling token-based authentication.
apiVersion: apps/v1
kind: Deployment
metadata:
name: datahub-gms
spec:
template:
spec:
containers:
- name: datahub-gms
env:
- name: METADATA_SERVICE_AUTH_ENABLED
value: "true"
2. Verify Credentials
Ensure that the username and password you are using are correct. The default credentials are often datahub
for both username and password, but these might have been changed in your setup.
3. Check API Endpoint
Ensure that the API endpoint URL is correct and accessible. You can test the endpoint by accessing it directly in a browser or using a simple curl
command without authentication to see if it responds.
4. Correct Curl Command
Ensure that your curl
command is correctly formatted. Here is a corrected version of your command:
curl -X POST "http://10.42.0.22:8080/api/authentication/token" \
-H "Content-Type: application/json" \
-d '{
"username": "datahub",
"password": "datahub"
}'
5. Check Logs
Check the logs of the datahub-gms
service for any errors or warnings that might provide more context on why the authentication is failing.
Example of Correct Configuration
Here is a complete example of how to enable metadata service authentication and generate a token:
Enable Metadata Service Authentication
apiVersion: apps/v1
kind: Deployment
metadata:
name: datahub-gms
spec:
template:
spec:
containers:
- name: datahub-gms
env:
- name: METADATA_SERVICE_AUTH_ENABLED
value: "true"
Generate Token Using Curl
curl -X POST "http://10.42.0.22:8080/api/authentication/token" \
-H "Content-Type: application/json" \
-d '{
"username": "datahub",
"password": "datahub"
}'
If you continue to face issues, please provide more details about your setup and any error messages from the logs.
Would you like more detailed steps or have any specific questions about this process?
Sources:
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/personal-access-tokens.md|Personal Access Tokens>
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/introducing-metadata-service-authentication.md|Metadata Service Authentication>
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METADATA_SERVICE_AUTH_ENABLED
is enabled by default in the helm chart deployment <@U06TM7M40RK>
If METADATA_SERVICE_AUTH_ENABLED
is enabled by default in your Helm chart deployment and you are still receiving a 401 error, there are a few additional steps you can take to troubleshoot and resolve the issue.
1. Verify Helm Chart Configuration
Ensure that the Helm chart values are correctly set to enable authentication. Specifically, check the values.yaml
file for the datahub-gms
subchart to confirm that METADATA_SERVICE_AUTH_ENABLED
is set to true
.
2. Check for Correct Credentials
Ensure that the credentials you are using (username
and password
) are correct. If you have customized these credentials, make sure they match what is configured in your DataHub deployment.
3. Inspect Logs for Errors
Check the logs of the datahub-gms
service for any errors or warnings that might provide more context on why the authentication is failing. This can often provide clues about misconfigurations or other issues.
4. Correct Curl Command
Ensure that your curl
command is correctly formatted and does not contain any syntax errors. Here is a corrected version of your command:
curl -X POST "<http://10.42.0.22:8080/api/authentication/token>" \
-H "Content-Type: application/json" \
-d '{
"username": "datahub",
"password": "datahub"
}'
Example Configuration
Here is a complete example of how to enable metadata service authentication and generate a token:
Enable Metadata Service Authentication
Ensure that the values.yaml
file for your Helm chart includes the following configuration:
datahub-gms:
env:
METADATA_SERVICE_AUTH_ENABLED: "true"
Generate Token Using Curl
curl -X POST "<http://10.42.0.22:8080/api/authentication/token>" \
-H "Content-Type: application/json" \
-d '{
"username": "datahub",
"password": "datahub"
}'
Additional Resources
For more detailed steps and troubleshooting, you can refer to the following resources:
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/personal-access-tokens.md|Personal Access Tokens>
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/introducing-metadata-service-authentication.md|Metadata Service Authentication>
If you continue to face issues, please provide more details about your setup and any error messages from the logs.
Would you like more detailed steps or have any specific questions about this process?
Sources:
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/personal-access-tokens.md|Personal Access Tokens>
- <https://github.com/datahub-project/datahub/blob/master/docs/authentication/introducing-metadata-service-authentication.md|Metadata Service Authentication>
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