Are you struggling to get actionable insights from your New Relic implementation? Many companies invest in this powerful
Key Takeaways
- Implement custom attributes to enrich your New Relic data with business-relevant context, going beyond default metrics.
- Configure alerting thresholds carefully, using historical data and anomaly detection to minimize false positives and alert fatigue.
- Regularly review and refine your New Relic dashboards to ensure they are displaying the most relevant and actionable information for your team.
- Utilize New Relic’s workload feature to group related services and applications for a holistic view of system health and performance.
The Problem: Data Overload, Insight Underload
Many organizations, especially those in the Atlanta metro area with its booming tech scene, face a common problem with New Relic: they collect tons of data but struggle to extract meaningful insights. It’s like trying to find a specific grain of sand on the beach at Tybee Island. The tool is powerful, but without a clear strategy, you end up with dashboards full of charts that don’t tell a story. I’ve seen it time and again: teams drowning in metrics, unable to pinpoint the root cause of performance issues or identify opportunities for improvement.
What happens? Developers and operations teams get overwhelmed. Important alerts are missed amidst the noise. Performance bottlenecks remain hidden. Decision-making suffers. Ultimately, the investment in New Relic fails to deliver the expected return. This is especially painful for startups near Tech Square who are counting on every dollar to make an impact.
The Solution: A Structured Approach to New Relic Configuration
The solution lies in a structured approach to New Relic configuration, focusing on clear objectives, thoughtful instrumentation, and actionable dashboards. It’s about transforming raw data into a coherent narrative that guides your team towards better performance and improved business outcomes.
Step 1: Define Clear Objectives
Before you even log in to New Relic, ask yourself: What are you trying to achieve? What are the key performance indicators (KPIs) that matter most to your business? Are you trying to reduce page load times, improve transaction success rates, or optimize database query performance? I had a client last year who wanted to reduce customer churn. We used New Relic to track the performance of critical user flows and identified slow API calls that were causing frustration. Defining clear objectives upfront will guide your instrumentation efforts and ensure you’re collecting the right data.
Without those objectives, you’re just collecting data for data’s sake. That’s a waste of time and resources.
Step 2: Implement Custom Attributes
New Relic provides a wealth of default metrics, but these are often not enough to provide the contextual information you need to understand the “why” behind performance issues. This is where custom attributes come in. Custom attributes allow you to enrich your data with business-relevant context, such as user IDs, product names, order values, or campaign IDs. According to New Relic’s documentation, attributes can be added to transactions, events, logs, and spans.
For example, if you’re an e-commerce company, you might add custom attributes to track the performance of different product categories. This would allow you to identify which product categories are experiencing the most performance issues and prioritize your optimization efforts accordingly. Or, if you’re running a marketing campaign, you could add a custom attribute to track the performance of different campaign variations. This would allow you to see which campaigns are driving the most traffic and conversions.
Here’s how you can implement custom attributes:
- Identify the relevant context: What business-related information would help you better understand your New Relic data?
- Choose the appropriate data type: Custom attributes can be strings, numbers, or booleans. Choose the data type that best represents your data.
- Implement the attribute in your code: Use the New Relic agent API to add the attribute to your transactions, events, or logs. For example, in Java, you might use the
NewRelic.addCustomParameter()method. - Verify the attribute is being collected: Check the New Relic UI to ensure your custom attributes are being collected and displayed correctly.
Step 3: Configure Alerting Thresholds Carefully
Alerting is a critical component of any monitoring solution. However, poorly configured alerts can lead to alert fatigue and missed incidents. The key is to configure alerting thresholds carefully, based on historical data and anomaly detection. Don’t just set arbitrary thresholds based on gut feeling. I’ve seen that fail spectacularly.
Here’s how to configure effective alerting thresholds:
- Establish baseline performance: Use New Relic’s historical data to establish baseline performance metrics for your applications and services.
- Set thresholds based on deviations from the baseline: Configure alerts to trigger when performance deviates significantly from the established baseline. Consider using New Relic’s anomaly detection features to automatically adjust thresholds based on changing traffic patterns.
- Define clear escalation policies: Who should be notified when an alert is triggered? What are the steps they should take to investigate and resolve the issue? Make sure your escalation policies are well-defined and communicated to your team.
- Avoid overly sensitive thresholds: Setting thresholds too low will result in a flood of false positives, leading to alert fatigue. Be realistic about what constitutes a significant performance issue.
- Iterate and refine: Regularly review your alerting thresholds and adjust them as needed based on your experience. The goal is to minimize false positives while ensuring that you’re alerted to genuine performance issues.
Creating a stable tech environment is crucial to avoid constant firefighting.
Step 4: Create Actionable Dashboards
Dashboards are your window into your New Relic data. But a dashboard cluttered with irrelevant charts is worse than no dashboard at all. The goal is to create dashboards that are clear, concise, and actionable. This means focusing on the metrics that matter most to your business and presenting them in a way that makes it easy to identify trends and anomalies. We ran into this exact issue at my previous firm. We had so many dashboards, nobody knew which ones to trust.
Here’s how to create actionable dashboards:
- Focus on key metrics: Include only the metrics that are most relevant to your objectives. Avoid cluttering your dashboards with unnecessary information.
- Use clear and concise visualizations: Choose visualizations that effectively communicate the data. Use charts, graphs, and tables to present your data in a visually appealing and easy-to-understand format.
- Add context: Include annotations and comments to provide context and explain trends. This will help your team understand the “why” behind the data.
- Make it interactive: Use New Relic’s interactive features to allow users to drill down into the data and explore different perspectives.
- Regularly review and refine: Dashboards are not set-and-forget. Regularly review your dashboards and refine them as needed based on your experience and changing business needs.
Step 5: Leverage Workloads
New Relic’s workload feature allows you to group related services and applications into logical units. This provides a holistic view of system health and performance, making it easier to identify dependencies and troubleshoot issues. This is especially useful for complex microservices architectures. If you have multiple services running on AWS across different availability zones, workloads can help you visualize the overall health of your application.
To give a more concrete example, imagine you’re running an e-commerce platform with separate services for product catalog, shopping cart, order processing, and payment gateway. With workloads, you can group these services together and monitor their overall performance as a single unit. This allows you to quickly identify if there’s a problem affecting the entire e-commerce platform, even if the individual services appear to be healthy.
What Went Wrong First: Failed Approaches
Before we landed on this structured approach, we tried a few things that didn’t work. First, we tried a “collect everything” approach, hoping that we could sort it out later. This resulted in a massive influx of data that was difficult to analyze and manage. Second, we tried relying solely on default metrics, which didn’t provide enough context to understand the root cause of performance issues. Finally, we tried setting arbitrary alerting thresholds, which resulted in a flood of false positives. These failures taught us the importance of a structured approach, focusing on clear objectives, thoughtful instrumentation, and actionable dashboards.
Measurable Results: A Case Study
Let’s look at a fictional, but realistic, case study. “Acme Corp,” a SaaS provider located near Perimeter Mall, was struggling with slow response times and frequent outages. They implemented New Relic but initially saw little improvement. After following the structured approach outlined above, they achieved the following results:
- Reduced average response time by 30%: By implementing custom attributes to track the performance of different user segments, they identified a performance bottleneck affecting a specific group of users. After optimizing the code for that segment, they saw a significant reduction in average response time.
- Decreased the number of critical incidents by 50%: By configuring alerting thresholds based on historical data and anomaly detection, they reduced the number of false positives and ensured that they were alerted to genuine performance issues. This allowed them to proactively address issues before they escalated into critical incidents.
- Improved team collaboration: By creating actionable dashboards that provided a clear view of system health and performance, they improved communication and collaboration between development and operations teams. This allowed them to resolve issues more quickly and efficiently.
Within three months, Acme Corp saw a significant return on their investment in New Relic. They were able to improve application performance, reduce the number of incidents, and improve team collaboration. All this from better understanding and implementing their New Relic
Effective performance bottleneck identification is critical for achieving results like Acme Corp.
Thinking about performance testing? This could help prevent the issues Acme Corp faced.
What are custom events in New Relic and how do I use them?
Custom events allow you to capture specific actions or occurrences within your application that are not automatically tracked by New Relic. You can use the New Relic agent API to create and report custom events, adding relevant attributes to provide context. This is useful for tracking business-specific metrics or user behavior.
How do I troubleshoot high CPU usage reported by New Relic?
High CPU usage can be caused by various factors, such as inefficient code, excessive database queries, or resource-intensive tasks. New Relic provides tools to identify the specific code or transactions that are consuming the most CPU. You can then use this information to optimize your code or adjust resource allocation.
What is the difference between APM and infrastructure monitoring in New Relic?
APM (Application Performance Monitoring) focuses on the performance of your applications, tracking metrics such as response time, error rate, and throughput. Infrastructure monitoring focuses on the health and performance of your underlying infrastructure, such as servers, databases, and networks. Both are important for a complete view of your system.
How can I integrate New Relic with my CI/CD pipeline?
You can integrate New Relic with your CI/CD pipeline to automatically monitor the performance of new deployments. This allows you to quickly identify and address any performance regressions introduced by code changes. New Relic provides APIs and integrations for popular CI/CD tools like Jenkins and CircleCI.
How do I create a New Relic dashboard for monitoring database performance?
To create a dashboard for database performance, focus on metrics such as query execution time, database connections, and slow query count. Use New Relic’s query builder to create custom charts and graphs that visualize these metrics. You can also add alerts to notify you of any performance issues.
Don’t let your New Relic implementation become another shelfware statistic. Take the time to configure it properly, and you’ll unlock its full potential. Start with a single, well-defined objective, and build from there. The insights you gain will be well worth the effort.
