Analyzing & Troubleshooting CPU Spike Using JFR

Java Flight Recorder (JFR) enables low-overhead profiling to diagnose CPU spikes, which occur when threads excessively consume CPU resources, often due to infinite loops or inefficient code. This blog outlines causes, simulates the issue, captures JFR data, and analyzes it to identify performance bottlenecks, specifically within the CPUSpikerThread class.

Troubleshooting Memory Leaks in Jenkins

Memory leaks in Jenkins can severely degrade performance, causing delays and unresponsiveness. Such leaks occur when memory is retained beyond its usefulness, leading to increased garbage collection efforts. The article discusses symptoms, root causes, and diagnostic tools for identifying and fixing memory leaks, emphasizing the importance of regular monitoring to prevent issues.

AI-Powered RCA Summary: Instantly Understand What Went Wrong

yCrash enhances AI-powered root cause analysis by integrating structured JSON outputs from extensive diagnostics with Large Language Models (LLMs). This allows for clearer executive summaries and interactive reports, improving accessibility for technical and non-technical users. Key benefits include precise metrics, historical analysis, visualizations, and cost efficiency, ensuring effective incident troubleshooting.

“GC Log Analysis Using Deterministic AI” webinar

GC logs are essential for JVM performance analysis, but their complexity complicates interpretation. In a recent webinar, Ram Lakshmanan discussed how Deterministic AI can refine GC log analysis, enhancing accuracy and safety while addressing the limitations of traditional AI methods. This approach enables faster, reliable insights for troubleshooting performance issues.

‘Troubleshooting .NET Production problems using AI’ Webinar

The session led by Ram Lakshmanan and Mahesh Devda focuses on utilizing AI to enhance troubleshooting in .NET applications. They emphasize that traditional methods are time-consuming and ineffective. AI-driven approaches streamline the diagnosis of production issues, improve resolution speed, and ultimately protect user experience, revenue, and trust.

Production is Secure. Is Troubleshooting Process Secure?

Enterprises have invested heavily in cybersecurity, yet the production troubleshooting process still faces significant risks, including untrusted tools, data leakage, and unauthorized access to sensitive information. The yCrash solution addresses these gaps by securely managing troubleshooting artifacts, implementing robust authentication, and sanitizing data to ensure compliance and protect confidential information.

Securing Production Troubleshooting with yCrash Audit Logs

yCrash has introduced an audit trail feature, addressing enterprise security gaps by logging user actions. This enhancement enables tracking of who accesses sensitive production data, ensuring compliance and accountability. With SSO integration, the logs provide detailed user activity, fostering a culture of security awareness among engineers and improving overall troubleshooting security.

‘Analyzing Application Logs Using AI’ Webinar

In a recent webinar, experts discussed how AI can enhance application log analysis, addressing challenges in manual reviews amidst growing log volumes. Key topics included anomaly detection, error pattern identification, and event correlation across systems, all aimed at accelerating root cause analysis and improving incident response while maintaining engineering judgment.

‘Java 25 is out! Selection of my favorite features’ Webinar

Java 25 has launched, introducing significant enhancements aimed at modernizing Java applications. A recent webinar featuring expert Michael Inden focused on practical features such as pattern matching, string templates, structured concurrency, and unnamed classes. Attendees gained hands-on experience and insights into adopting these changes for improved code quality and productivity.

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