Did you know that nearly 60% of companies using application performance monitoring (APM) tools like New Relic fail to fully realize its potential within the first year? That’s a staggering waste of investment and opportunity. Are you making these common mistakes and leaving valuable insights on the table?
Key Takeaways
- Immediately configure alerts for critical transaction errors and response time breaches to proactively address performance issues.
- Tag and group your New Relic data using custom attributes, such as application version, environment, or customer segment, for better filtering and analysis.
- Regularly review and update your New Relic dashboards and queries, at least quarterly, to reflect changing application architectures and business priorities.
Ignoring Alerting Best Practices
One of the most pervasive issues I see with organizations using New Relic is a failure to set up proper alerting. A recent survey by the Dynatrace Research Group found that 67% of IT teams still struggle with alert fatigue. This often stems from either too many alerts (most of which are irrelevant) or alerts that are not actionable. What good is being notified if you don’t know what to do with the notification?
I once worked with a client, a large e-commerce company based here in Atlanta, near the intersection of Peachtree and Lenox, who had New Relic installed but only used the default alerts. They were drowning in notifications about minor CPU spikes on non-critical servers. Meanwhile, their checkout process was experiencing intermittent slowdowns that went completely unnoticed, costing them thousands of dollars in lost sales every day. We revamped their alerting strategy to focus on key performance indicators (KPIs) directly tied to revenue, such as transaction error rates and average response times for critical user flows. Within a week, they were able to proactively identify and resolve performance bottlenecks before they impacted customers.
Proper alerting in New Relic means defining clear thresholds based on historical data and business impact. Don’t just alert on everything; alert on what matters. Use New Relic’s anomaly detection features to automatically adjust thresholds based on changing traffic patterns. And, critically, ensure that each alert includes clear instructions on how to respond. For example, an alert for high error rates on the payment processing service should include a link to the relevant runbook and the contact information of the on-call engineer.
Failing to Leverage Custom Attributes
Data without context is just noise. According to a Gartner report, organizations that effectively use tagging and metadata with their APM tools see a 20% improvement in problem resolution times. New Relic provides powerful capabilities for adding custom attributes to your data, but many teams underutilize this feature.
Think about it: are you just monitoring “web servers” or are you monitoring “web servers running version 3.2 of the e-commerce application in the production environment for the premium customer segment”? The more context you add, the easier it is to slice and dice your data to identify the root cause of performance issues. Custom attributes can be used to tag transactions, events, logs, and metrics with any relevant information, such as application version, environment, customer ID, region, or feature flag. This allows you to filter and group your data in New Relic to quickly isolate problems and understand their impact.
For example, let’s say you’re rolling out a new feature. By tagging all transactions associated with that feature with a custom attribute, you can easily track its performance and identify any regressions. Or, if you’re experiencing performance issues for a specific customer segment, you can filter your data by customer ID to see if the problem is isolated to that group. Setting up custom attributes takes a little extra effort upfront, but it pays off big time in terms of improved visibility and faster troubleshooting and resolution. I suggest creating a standardized tagging taxonomy so everyone on the team is on the same page.
Neglecting Query Optimization
New Relic’s query language, NRQL, is incredibly powerful, but it can also be a performance bottleneck if not used correctly. A Splunk study found that poorly optimized queries can increase query execution time by as much as 500%. I’ve seen this firsthand. I recall working with a financial services firm downtown near Woodruff Park that was complaining about slow dashboard load times in New Relic. After investigating, we discovered that they were using inefficient NRQL queries that were scanning the entire dataset every time the dashboard refreshed. By optimizing the queries to use indexes and limit the scope of the search, we were able to reduce dashboard load times from minutes to seconds. Here’s what nobody tells you: simple is often better. Complex queries are rarely the answer.
One common mistake is using wildcard searches without proper filtering. For example, instead of using `SELECT FROM Transaction WHERE name LIKE ‘%payment%’`, use `SELECT FROM Transaction WHERE name LIKE ‘%payment%’ AND appName = ‘payment-service’`. This will significantly reduce the amount of data that needs to be scanned. Another mistake is using `TIMESERIES` without specifying a `SINCE` clause. This will cause New Relic to scan the entire historical dataset, which can be very slow. Always specify a `SINCE` clause to limit the time range of the query. Finally, make sure you’re using the correct data types. For example, if you’re querying for a numeric value, make sure the attribute is stored as a number, not a string. Otherwise, New Relic will have to perform a type conversion for every row, which can be very slow.
Ignoring the Power of Dashboards
Dashboards are your window into your application’s performance, but many teams treat them as an afterthought. A survey by the Tableau Research Institute found that 70% of business users report that they don’t regularly use the dashboards available to them, often because they are outdated or irrelevant. This is a huge missed opportunity. New Relic dashboards can be customized to display the metrics that are most important to your business, providing a real-time view of your application’s health. However, dashboards are not a “set it and forget it” kind of thing.
Dashboards should be regularly reviewed and updated to reflect changing business priorities and application architectures. I recommend reviewing your dashboards at least quarterly to ensure that they are still relevant and providing valuable insights. In fact, I make it a point to block time on my calendar every quarter to do just that. Also, don’t be afraid to experiment with different dashboard layouts and visualizations. New Relic offers a wide range of chart types and widgets that can be used to display your data in different ways. Find what works best for you and your team. A well-designed dashboard can help you quickly identify and resolve performance issues, improve collaboration, and make data-driven decisions.
Chasing Every Single Error (Counterpoint)
Here’s where I’ll disagree with some conventional wisdom. Many APM “experts” preach relentlessly about achieving a zero-error state. While striving for stability is admirable, obsessively chasing down every single, infrequent error can be a massive time sink with minimal return. Sometimes, the cost of fixing a rare, non-critical error outweighs the benefit. It’s like trying to fix a tiny scratch on your car that only you notice; is it really worth the expense and effort?
Instead of aiming for perfection, focus on the errors that have the biggest impact on your users and your business. Prioritize errors that are frequent, widespread, or affect critical functionality. Use New Relic’s error tracking features to identify the root cause of these errors and implement fixes that prevent them from recurring. And don’t be afraid to ignore the occasional, harmless error that doesn’t affect anyone. Sometimes, the best thing you can do is nothing at all. This isn’t laziness; it’s strategic resource allocation. It’s about making smart choices about where to invest your time and effort. This is not to say you should ignore errors altogether, but rather to be pragmatic and prioritize based on impact.
For example, we had a client last year who was spending hours every week investigating a rare error that occurred only when a user tried to upload a file larger than 1GB via a very old browser. The error had no impact on the vast majority of users, and the workaround was simple: use a modern browser. After analyzing the cost of fixing the error (which would have required a significant code refactoring), we decided to simply document the workaround and move on. This saved the client a significant amount of time and money, which they were able to invest in more important projects.
Thinking strategically about tech investments and measuring true ROI can significantly impact your bottom line.
What is the best way to set up alerts in New Relic?
Focus on alerting for critical transaction errors and response time breaches. Use anomaly detection to dynamically adjust thresholds and include clear instructions in each alert for quicker resolution.
How often should I review my New Relic dashboards?
Review and update your dashboards at least quarterly to ensure they reflect current business priorities and application architecture changes.
What are custom attributes and why are they important?
Custom attributes are tags you add to your data for better filtering and analysis, such as application version, environment, or customer segment. They provide context and help isolate the root cause of performance issues faster.
How can I optimize my NRQL queries?
Use indexes, limit the scope of searches with a `SINCE` clause, and ensure you’re using the correct data types. Avoid wildcard searches without proper filtering.
Is it necessary to fix every single error in New Relic?
No, focus on errors that have the biggest impact on users and the business. Prioritize frequent, widespread errors affecting critical functionality over rare, harmless ones.
Don’t let your investment in New Relic technology go to waste. By avoiding these common pitfalls – neglecting alerts, ignoring custom attributes, writing inefficient queries, and letting dashboards stagnate – you can unlock the full potential of New Relic and gain valuable insights into your application’s performance. Start by auditing your current New Relic setup and implementing these recommendations today to see immediate improvements. For a broader look, consider whether tech is even reliable in the first place.
