Real-time AI Application Performance Monitoring with Dynatrace

Question

Pulumi · Accepted Answer

Application Performance Monitoring (APM) is critical for ensuring that your applications are running efficiently and for identifying any issues that may affect user experience. Dynatrace is a popular APM tool that provides real-time observability and AI-powered insights into your applications, infrastructure, and user experiences. By using Pulumi, you can automate the configuration and deployment of Dynatrace monitoring capabilities within your infrastructure.

Here's a Pulumi program in Python that sets up basic application performance monitoring using Dynatrace. I'll provide explanations for each part of the code and the resources being used.

In this example, we will set up Dynatrace resources such as monitoring policies and settings relevant to specific monitored technologies. For instance, we may want to enable host monitoring and monitor technologies like IIS (Internet Information Services) or OpenTracing, set up anomaly detection settings for services, and perhaps configure auto-tagging for better categorization of our monitored entities.

Please note that before executing this code, you need to have access to a Dynatrace environment and the necessary permissions to create or configure resources. Also, this code assumes you have the `pulumi-dynatrace` plugin installed and the Pulumi CLI set up. The Dynatrace provider is expected to be configured with the appropriate API token and environment details.

Let's begin by writing a simple Pulumi program using the available Dynatrace Pulumi resources:

```python
import pulumi
import pulumi_dynatrace as dynatrace

# Create Dynatrace Host Monitoring Configuration: This enables monitoring on a specific host.
# Replace `hostId` with the actual ID of the host you wish to monitor.
host_monitoring = dynatrace.HostMonitoring("exampleHostMonitoring",
    hostId="YOUR_HOST_ID",   # Replace with your host ID
    enabled=True,
    fullStack=True,
    autoInjection=True
)

# Create Dynatrace Monitored Technologies Configuration for IIS: Enable monitoring of the IIS technology.
# Replace `hostId` with the actual ID of the host where IIS is running.
iis_monitoring = dynatrace.MonitoredTechnologiesIis("exampleIisMonitoring",
    hostId="YOUR_HOST_ID",   # Replace with your host ID
    enabled=True
)

# Create Dynatrace Monitored Technologies Configuration for OpenTracing: Enable OpenTracing monitoring 
# if you're using distributed tracing in your applications.
# Replace `hostId` with the actual ID of the host you'd like to monitor.
opentracing_monitoring = dynatrace.MonitoredTechnologiesOpentracing("exampleOpenTracingMonitoring",
    hostId="YOUR_HOST_ID",   # Replace with your host ID
    enabled=True
)

# Create Dynatrace Anomaly Detection Policy for Services: Set up custom anomaly detection thresholds/rules.
# Here we're creating a dummy configuration, replace with your real monitoring needs.
service_anomalies = dynatrace.ServiceAnomalies("exampleServiceAnomalies",
    load= {
        "drops": {
            "minutes": 5,
            "percent": 50
        },
        "spikes": {
            "minutes": 5,
            "percent": 50
        }
    },
    failureRates= {
        "auto": {
            "absolute": 3,
            "relative": 5
        }
    },
    responseTimes= {
        "auto": {
            "load": "medium",
            "percent": 75,
            "milliseconds": 1000
        }
    }
)

# Create Dynatrace Autotag Rule: Automatically tag entities to facilitate fine-grained filtering and reporting.
auto_tag = dynatrace.Autotag("exampleAutoTag",
    name="Environment-Tag",
    rules=[
        {
            "type": "SERVICE",
            "enabled": True,
            "conditions": [
                {
                    "key": {
                        "attribute": "SERVICE_NAME"
                    },
                    "value": {
                        "operator": "CONTAINS",
                        "value": "production"
                    }
                }
            ]
        }
    ]
)

# Export relevant resource attributes, such as IDs or URLs if applicable for any of the above resources.
pulumi.export("host_monitoring_id", host_monitoring.id)
pulumi.export("iis_monitoring_id", iis_monitoring.id)
pulumi.export("opentracing_monitoring_id", opentracing_monitoring.id)
pulumi.export("service_anomalies_id", service_anomalies.id)
pulumi.export("auto_tag_id", auto_tag.id)
```

In this Pulumi program, each block creates a different Dynatrace resource for APM:

- **Host Monitoring**: This resource explicitly enables full-stack monitoring on a designated host. You must replace `YOUR_HOST_ID` with the specific host you're targeting.

- **Monitored Technologies IIS**: This resource sets up the monitoring for the IIS web server technology on the specified host.

- **Monitored Technologies OpenTracing**: Similar to IIS monitoring, this resource will enable OpenTracing technology monitoring if your applications use distributed tracing.

- **Service Anomalies**: This resource allows you to define anomaly detection settings for your services. The example above sets thresholds for load drops, load spikes, failure rates, and response times.

- **Auto Tag**: The AutoTag resource automatically tags services based on specified conditions, which aids in organizing and filtering your APM data for better analysis.

At the end of the program, we export the IDs of these resources so that they can be referenced or used in other infrastructure as code setups.

To deploy this configuration, you would run `pulumi up` in a directory with this code saved as a Python file (e.g., `main.py`). This will apply the configuration to your Dynatrace environment. Remember to replace placeholders such as `YOUR_HOST_ID` with actual values from your environment.