Set Up SAP Leonardo Environment
- Ensure you have access to SAP Cloud Platform, particularly the SAP Leonardo services that you plan to use (e.g., IoT, Machine Learning).
- Verify your SAP Cloud Platform account credentials and ensure you have the necessary permissions to create instances and applications.
- Set up your Leonardo project in the SAP Cloud Platform Cockpit by navigating to the 'Instances and Subscriptions' section and selecting the appropriate services.
Prepare Datadog Account
- Create a Datadog account if you do not have one already. Ensure your account has the necessary permissions to ingest external data.
- Navigate to the Datadog API Keys section found in the account settings to create and copy an API Key, which will be necessary for integration.
- Set up a Datadog project or dashboard where you want the data from SAP Leonardo to be displayed.
Leverage SAP Leonardo APIs
- Access the SAP Leonardo API documentation for information on available endpoints and required authentication methods.
- Use the provided API services to programmatically access the data you wish to monitor in Datadog. Ensure you have the correct endpoint URLs and authentication tokens set up in your environment configuration.
- Test the API connection using tools like Postman or CURL to ensure you can successfully retrieve the data from SAP Leonardo.
Integrate with Datadog Using Agent
- Install the Datadog Agent on your application server that interacts with SAP Leonardo. Refer to the Datadog Agent installation documentation for platform-specific instructions.
- Configure the Datadog Agent by editing the
datadog.yaml file. Input your API Key from the Datadog account settings.
api_key: <YOUR_DATADOG_API_KEY>
- Create a custom check in Datadog for handling SAP Leonardo data by placing a custom Python script in the Agent's checks.d directory. This script will call SAP Leonardo APIs and push data to your Datadog account.
import requests
import logging
def check_data():
url = "https://<SAP_ENDPOINT>"
headers = {"Authorization": "Bearer <YOUR_ACCESS_TOKEN>"}
response = requests.get(url, headers=headers)
if response.status_code == 200:
data = response.json()
# Process data and send metrics to Datadog
else:
logging.error(f"Failed to fetch data from SAP Leonardo: {response.status_code}")
check_data()
Create Metrics and Dashboards in Datadog
- Use the collected data to create custom metrics in Datadog. These can involve counts, averages, or any relevant information necessary for monitoring the performance of your SAP Leonardo resources.
- Create dashboards to visualize the collected data and set up alerts to monitor specific key performance indicators based on your SAP Leonardo data.
Validate Integration
- Verify that data from SAP Leonardo is flowing into Datadog via the custom check script and that it appears correctly in the dashboards you created.
- Simulate data changes in SAP Leonardo and ensure that they reflect accurately and promptly within your Datadog metrics and dashboards.
Maintain and Troubleshoot Integration
- Regularly update your Datadog Agent and integration scripts to maintain compatibility with both SAP Leonardo's and Datadog’s API changes.
- Monitor the logs of the Datadog Agent to troubleshoot any issues related to data ingestion or API connectivity from SAP Leonardo.
