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Plotly Charts in New Relic: A Comprehensive Guide

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Plotly Charts in New Relic: A Comprehensive Guide

Introduction

Monitoring and understanding application performance is crucial for any development team. New Relic, a popular application performance monitoring (APM) platform, provides a wealth of data that can be used to gain insights into application behavior. However, the raw data itself can be difficult to interpret. This is where visualization comes in. Plotly, a powerful open-source charting library, offers an elegant way to transform New Relic data into insightful and interactive charts.

By combining New Relic's data with Plotly's visualization capabilities, you can gain a deeper understanding of your application's performance, pinpoint areas for improvement, and proactively prevent issues before they impact users. This guide provides a comprehensive overview of how to integrate Plotly charts into your New Relic dashboards, enabling you to effectively visualize and analyze your application data.

Key Concepts

New Relic Insights

New Relic Insights is a data exploration and visualization tool within the New Relic platform. It allows you to query and analyze your New Relic data using a powerful query language called NRQL (New Relic Query Language).

Plotly

Plotly is a versatile and interactive charting library that offers a wide range of chart types, from basic line graphs to complex 3D visualizations. It's designed to be highly customizable and interactive, enabling users to create visually appealing and insightful charts that can be easily shared and embedded.

Plotly.js

Plotly.js is the JavaScript library that powers Plotly's interactive charts. It can be used to create charts within web applications, as well as to generate static images. Plotly.js is also compatible with other JavaScript frameworks like React, Angular, and Vue.js.

Integrating Plotly Charts into New Relic

There are several ways to integrate Plotly charts into your New Relic dashboards:

Using Plotly's New Relic Integration

Plotly offers a dedicated integration with New Relic, enabling you to create and embed Plotly charts directly within your New Relic dashboards. This integration is streamlined and easy to use, allowing you to quickly visualize your data without needing to write any custom code.

To use this integration, you need to:

Obtain your New Relic API Key: Navigate to your New Relic account settings and copy your API key.
Install the Plotly package: If you haven't already, install the Plotly package in your project using npm or yarn: npm install plotly
Create a Plotly chart: Use Plotly's library to create the desired chart, specifying the data and visualization options. The code will need to fetch the data from New Relic using the API key.
Embed the chart into your New Relic dashboard: The integration allows you to directly embed the created Plotly chart into your New Relic dashboard using a dedicated widget or through custom code.

This method offers a simple and efficient way to bring Plotly charts into your New Relic environment. You can find detailed documentation and examples on Plotly's website.

Creating Custom Visualizations with NRQL and Plotly.js

For more advanced customization, you can leverage the power of NRQL to retrieve data from New Relic and then use Plotly.js to create interactive charts within your New Relic dashboards.

Here's a basic example of how you can create a line chart visualizing CPU usage over time:

// Import Plotly.js
import * as Plotly from 'plotly.js/dist/plotly';

// Define your NRQL query
const nrqlQuery = `SELECT average(system.cpu.user) FROM SystemSample WHERE entityGuid='${entityGuid}' SINCE 1 day AGO`;

// Fetch data from New Relic API
fetch(`https://api.newrelic.com/v2/accounts/${accountId}/query?nrql=${encodeURIComponent(nrqlQuery)}`, {
  headers: {
    'Authorization': `Api-Key ${apiKey}`
  }
})
.then(response =&gt; response.json())
.then(data =&gt; {
  // Extract the data from the response
  const timestamps = data.results[0].data.map(d =&gt; d[0]);
  const cpuUsage = data.results[0].data.map(d =&gt; d[1]);

  // Create a Plotly line chart
  const chartData = [{
    x: timestamps,
    y: cpuUsage,
    type: 'line'
  }];

  // Define chart layout options
  const layout = {
    title: 'CPU Usage',
    xaxis: {
      title: 'Time'
    },
    yaxis: {
      title: 'CPU Usage (%)'
    }
  };

  // Create the Plotly chart
  Plotly.newPlot('chartContainer', chartData, layout);
});

This code fetches CPU usage data from New Relic using an NRQL query, extracts the timestamps and values, and then creates a line chart using Plotly.js. The chart can then be displayed in your New Relic dashboard using the "Custom HTML" widget.

Using a Plotly Plugin for New Relic

There are various third-party plugins available for New Relic that provide easier integration with Plotly. These plugins often streamline the process of connecting to New Relic data, formatting the data for Plotly, and embedding the chart into your dashboard. Some popular options include:

New Relic Charts: Offers a wide variety of chart types with predefined templates for easy integration with New Relic.
Plotly for New Relic: Provides a dedicated widget for directly embedding Plotly charts into your dashboards.
Plotly NRQL: Enables you to create custom NRQL queries and visualize the results with Plotly charts directly in your New Relic dashboards.

These plugins provide a more simplified approach compared to manually coding the integration, but they may have their own limitations in terms of customization and features. You can research and choose the plugin that best fits your needs and project requirements.

Types of Plotly Charts for New Relic Data

Plotly offers a vast array of chart types, allowing you to visualize your New Relic data in various ways. Some of the most commonly used charts for application performance monitoring include:

Line Charts

Line charts are ideal for visualizing trends over time. In New Relic, they can be used to track metrics like CPU usage, response times, error rates, and transaction throughput over time. This helps you identify performance bottlenecks, detect anomalies, and understand the overall health of your application.

Bar Charts

Bar charts effectively display categorical data, making them suitable for comparing metrics across different time periods, environments, or application components. In New Relic, they can be used to visualize metrics like the number of errors per application component, average response times across different environments, or user activity in different geographical regions.

Scatter Plots

Scatter plots are used to visualize the relationship between two variables. In New Relic, they can be used to analyze correlations between different metrics. For example, you can create a scatter plot to show the relationship between CPU usage and response times. This can help you identify potential bottlenecks and understand how different resources impact each other.

Heatmaps

Heatmaps are useful for visualizing data with multiple dimensions. In New Relic, they can be used to represent data points by their intensity using color gradients. This can help you identify areas of high or low activity, understand trends across different regions, or visualize data points within a specific time frame.

Histograms

Histograms provide a visual representation of the distribution of data. In New Relic, they can be used to understand the distribution of response times, error rates, or other performance metrics. This helps you identify outliers, understand the spread of your data, and identify potential performance issues.

Best Practices

To create effective and insightful charts, consider these best practices:

Choose the Right Chart Type

Select the chart type that best reflects the data you want to visualize and the message you want to convey. A line chart is ideal for showing trends over time, while a bar chart is better for comparing different categories.

Keep Charts Simple and Clear

Avoid overcrowding charts with too much information. Focus on conveying key insights in a concise and easy-to-understand manner. Use clear labels, appropriate colors, and a consistent style to improve readability.

Focus on Relevance

Only include relevant data points that support the insights you want to convey. Avoid including too many metrics or data points that obscure the main message.

Make Charts Interactive

Take advantage of Plotly's interactive capabilities to enable users to explore data in greater depth. Allow users to zoom, pan, and hover over data points to uncover hidden insights.

Share Insights, Not Just Data

Visualizations are not merely about presenting data; they are about communicating insights. Use charts to tell a story and highlight the key takeaways from your data.

Conclusion

Integrating Plotly charts into your New Relic dashboards is a powerful way to gain a deeper understanding of your application's performance. By leveraging Plotly's versatile charting capabilities and the insights provided by New Relic data, you can create visually appealing and interactive dashboards that inform decision-making, streamline troubleshooting, and improve overall application performance.

From simple line charts to complex heatmaps, Plotly offers a wide range of chart types to suit any monitoring need. By following the best practices outlined in this guide, you can create insightful visualizations that help you understand your data, identify performance issues, and ultimately improve the user experience of your applications.