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The latest News and Information on Application Performance Monitoring and related technologies.

Scaling Java Web Applications: Choosing Between Microsoft Windows and Linux OS

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.

Transform and Migrate Logs with Datadog Custom Processor

See how Datadog’s new Custom Processor in Observability Pipelines helps you transform and migrate logs from platforms like Splunk and Sumo Logic with precision and control. This demo walks through real examples of using VRL (Vector Remap Language) to enrich log data, rewrite timestamps, apply quotas, and securely process archives.

Redefining Frontend Observability with Datadog RUM

Discover how Datadog is redefining frontend observability with Real User Monitoring (RUM). In this demo, see how RUM helps teams detect, investigate, and resolve frontend issues that directly impact user experience and business outcomes. With RUM Without Limits, you get full visibility into every user session, giving you an accurate and comprehensive view of your users’ experiences. Monitor performance, track errors, and understand how your application behaves in real time.

Monitoring Chaos Experiments with New Relic Probe in Harness

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.

External Request Monitoring: The Silent Pillar Every APM Needs

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.

Why Your APM Needs Observability - Metrics, Logs, and Traces Explained

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.

10 Proven APM Best Practices to Reducing Latency and Improving Response Time

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.

Top 11 Ruby APM Tools for 2025: A Performance-Driven Selection

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.

Datadog Cloud Cost Management: Make cost a key metric for engineers

See how Datadog Cloud Cost Management puts cost and efficiency KPIs directly in front of engineers in their daily workflows. In this short demo, you’ll learn how to: Datadog unifies cost, performance, and business metrics in one platform, so FinOps, engineering, and finance teams can make cost-aware decisions together.