Operations | Monitoring | ITSM | DevOps | Cloud

New Relic probes in Harness Chaos Engineering let you automatically validate system performance against defined SLOs during chaos experiments, transforming subjective testing into objective, metrics-driven resilience validation. By querying New Relic metrics in real-time and comparing results against your success criteria, you can programmatically verify that your systems maintain acceptable performance levels even under failure conditions.

When engineering teams evaluate observability tools, the "Datadog vs. Grafana" debate is one of the most common. The choice is difficult because they represent two fundamentally different philosophies. Datadog is a comprehensive, all-in-one, managed SaaS platform. It offers a "buy" solution where you get a unified experience for metrics, logs, and traces out of the box. Grafana is an open-source, highly flexible visualization layer.

Java is one of the most widely used platforms for supporting web applications. According to RedMonk and TIOBE rankings, Java has consistently remained in the top 4 most popular programming languages worldwide, with millions of developers actively using it. Industry-standard application servers such as WebLogic, WebSphere, Tomcat, and JBoss all run on Java and power a large share of enterprise workloads and Java web applications.

The global market for application performance monitoring (APM) is growing fast. Market research shows the industry is expected to rise from about USD 7.52 billion in 2023 to nearly USD 19.62 billion by 2030, with a compound annual growth rate (CAGR) of around 15.1%. This rapid expansion reflects how digital transformation, hybrid cloud adoption, and third-party integrations are reshaping performance monitoring needs. It’s no longer enough to track just internal code paths and database queries.

Modern software applications are increasingly complex. Microservices, cloud infrastructure, and distributed architectures make it challenging for developers, DevOps engineers, and SREs to maintain high performance and a seamless user experience. Traditional Application Performance Monitoring (APM) provides critical insights into how applications perform, but alone, it often leaves blind spots when it comes to diagnosing issues or understanding the full system behavior.

Speed defines user loyalty. Recent market research indicates that organizations adopting advanced application performance monitoring (APM) tools are achieving measurable gains in user engagement, retention, and revenue. “ A 2025 performance study found that businesses tracking latency and response time proactively reduced customer churn by up to 30%. ” As applications expand across distributed architectures, microservices, and cloud environments, performance gaps become harder to diagnose.

Observability has become a core part of running Ruby applications at scale. Knowing how your app performs — from request latency to background job execution — helps catch slowdowns early and improve reliability. This blog walks through some of the most useful APM tools for Ruby in 2025. Each section highlights what the tool does well, where it fits best, and what kind of visibility it brings to your application's performance.