#Java file monitor example download
jarįirst, download the jar file containing the agent from the New Relic website, and unzip the download.
#Java file monitor example code
New Relic uses an agent-based monitoring approach, which means you don’t need to make any code changes at all unless you want to use advanced features like custom instrumentation. Specifically, we’ll be adding New Relic monitoring to a Spring Boot service which is running in Heroku. Let’s look at how you’d go about adding this sort of monitoring to your own Java services. Set Up New Relic for a Java-based Web Service This brief detective story shows how a monitoring tool like New Relic allowed Brandy to understand current state and past state for key performance metrics, and then slice and dice those metrics to gain understanding. The production incident is resolved, and the team can dig into the specifics of why that feature was causing a performance regression at their leisure. Looks like that did the trick – service latencies are back where they ought to be. She can clearly see that requests with the feature flag on have a p95 of around 600ms, while requests with the feature flag off have a much lower p95, around 100ms.īrandy asks Tray to turn the feature back down to 0%, and keeps an eye on the production graphs. Brandy investigates by graphing service response time grouped by the state of that feature flag, and finds a smoking gun: Tray the Product Manager raises his hand, telling her that he turned up a new feature flag to 50% at around that time. She opens up the New Relic dashboard for her service to understand what’s happening, and immediately sees that 95th percentile (p95) latencies are up dramatically, starting around 2:30pm:īrandy doesn’t see any deployments happening around that time, so she pings her team in chat to see if there were any other changes.
She’s just been informed that response times seem slow in production. She’s currently on call, “wearing the pager” for production support of that service. Let’s explore this concept in more detail with a concrete example.īrandy is a product engineer who works on a Java-based web service. When responding to an incident, we want to start with what, when and why: what is the issue, when did it start happening, and why is it happening. Why would we want to add monitoring to a service? The primary motivation is to detect and respond to issues with that service in production, often referred to as an incident.
Unpack a Production Incident in Your Java Application with New Relic In this post, we’ll take a quick look at using New Relic to sleuth through a production incident, and then walk through setting it up for a Spring Boot web service. New Relic also provides a sophisticated set of additional capabilities that you can grow into over time. New Relic is a product you can use to add monitoring to a Java service in a matter of minutes. One aspect of that is monitoring: tracking runtime performance metrics such as response latencies, error rates, and memory usage. Beyond implementing and testing new product features, more and more engineers are also expected to play a hand in production operations. The modern Java developer is expected to shoulder a lot of responsibilities.
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