Performance Benchmarking Across Regions with New Relic

Question

Pulumi · Accepted Answer

To perform performance benchmarking across regions with New Relic using Pulumi, you'll need to utilize New Relic's capabilities to monitor and gather data on your applications deployed in various regions. You can then define and track performance metrics such as response times, error rates, and throughput to compare the performance across different regions.

The following are the broad steps you will take in the Pulumi program:
1. Establish New Relic as the monitoring tool.
2. Set up New Relic integrations for the cloud services where your applications are deployed.
3. Define Service Level Indicators (SLIs) and Service Level Objectives (SLOs) to monitor the aspects of performance that are meaningful for your use case.
4. Create a New Relic dashboard to visualize and compare the performance across different regions.

Here's how a Pulumi program in Python can help you set up the performance benchmarking:

1. **New Relic Provider**: Make sure to have the New Relic provider configured in your Pulumi program, so you can interact with the resources made available by New Relic.

2. **Cloud Integration Resources**: Integrate with cloud services (like AWS, GCP, or Azure) using New Relic's cloud integrations to collect telemetry data from the applications you want to benchmark.

3. **OneDashboard Resource**: Create dashboards using the `newrelic.OneDashboard` resource to get a visual representation of your application's performance. Inside these dashboards, you can create widgets that query your application data for specific metrics, allowing you to compare performance across regions.

Now let's write the Pulumi program to create a New Relic dashboard that helps with comparing performance metrics across regions. This example assumes you already have an application instrumented with New Relic and are already collecting data.

First, install the required Pulumi New Relic package (if not already installed):

```sh
pip install pulumi_newrelic
```

Now, let's write the Pulumi Python program:

```python
import pulumi
import pulumi_newrelic as newrelic

# Assume the New Relic account ID is already known and applications are being monitored.
new_relic_account_id = "YOUR_NEW_RELIC_ACCOUNT_ID"

# Create New Relic one dashboard for performance monitoring across regions.
performance_dashboard = newrelic.OneDashboard("performanceDashboard",
    name="Performance Across Regions",
    account_id=new_relic_account_id,
    permissions="public_read_only",  # Set appropriate permissions
    pages=[
        newrelic.OneDashboardPageArgs(
            name="Overview",
            widgets=[
                # Add widgets as needed to compare application performance.
                # For example, let's add a widget showing the comparison of average response times across regions.
                newrelic.OneDashboardWidgetAreaArgs(
                    title="Average Response Time (by Region)",
                    nrql_queries=[
                        newrelic.OneDashboardWidgetNrqlQueryArgs(
                            # NRQL (New Relic Query Language) to fetch the average response time broken down by region.
                            query="SELECT average(duration) FROM Transaction FACET region TIMESERIES",
                            account_id=new_relic_account_id
                        )
                    ]
                )
                # Add more widgets as needed for other performance metrics like error rate, throughput, etc.
            ]
        )
    ],
    # Add additional configurations such as variables and linked entity GUIDs if needed.
)

# Export the dashboard URL so you can easily access it from the Pulumi outputs.
pulumi.export("performance_dashboard_url", performance_dashboard.permalink)
```

In the NRQL query within the widget definition, replace `Transaction` with the relevant event type for your application, and `region` with the attribute that identifies the region in your telemetry data. This example uses a fictional `region` attribute, so you'd need to replace it with your actual attribute name.

This Pulumi program defines a simple New Relic dashboard with one widget designed to display average response time broken down by region. By adding more widgets and queries, you can extend the dashboard to display a wide range of performance metrics for benchmarking. After running this Pulumi program, you can visit the provided permalink to view your dashboard and start analyzing the performance of your applications across different regions.