The webinar by Ram Lakshmanan focuses on using Java Flight Recorder (JFR) and AI to identify subtle performance signals during testing, which may indicate future production issues. It emphasizes moving beyond high-level metrics to a detailed, signal-based approach for analyzing JVM behavior, thereby allowing early detection and resolution of potential performance problems.
JAX London, an annual conference for Java and Software Architecture, will take place in October 2026. Architect Ram Lakshmanan will discuss using JFR and AI to detect subtle signals that indicate potential production issues, emphasizing the importance of identifying small metrics to prevent larger incidents in software performance.
JAX London, held annually in October, is a premier conference for Java and Software Architecture professionals. In 2026, architect Ram Lakshmanan presented on "LET'S FORECAST PRODUCTION OUTAGES USING MICRO-METRICS, PATTERNS & ML," sharing insights into advanced techniques for mitigating software production issues.
The webinar by Mahesh Devda focuses on troubleshooting unresponsive .NET applications. It emphasizes the importance of using thread dumps and diagnostic data to analyze runtime evidence, moving from symptoms to root causes. The session highlights that similar symptoms can stem from different issues, advocating for a systematic troubleshooting approach.
The recent webinar "Context Engineering with Spring AI," led by Boni García, emphasized the importance of context engineering beyond prompt engineering in developing reliable AI applications. It covered different context sources, practical architecture, and design patterns, demonstrating how Spring AI facilitates improved responses and maintainability for AI assistants.
The webinar "JFR ❤️ AI: Ultimate Combo for Troubleshooting" featured Ram Lakshmanan demonstrating how Java Flight Recorder (JFR) can enhance performance troubleshooting through AI. By using semantic parsing to structure JFR data, engineers can efficiently identify root causes in complex Java applications, streamlining the analysis process significantly.
Java heap dumps are crucial for troubleshooting memory issues in JVM applications. The recent yCrash webinar highlighted Object Query Language (OQL) as a powerful tool to analyze heap dumps efficiently through SQL-like queries. It discussed OQL's syntax, advanced features, and practical use cases for identifying memory leaks and optimizing performance.
Java Flight Recorder (JFR) captures essential Java application events but analyzing vast JFR recordings can be challenging. In a webinar, Ram Lakshmanan discusses how Deterministic AI enhances JFR analysis by converting complex data into structured facts, facilitating quicker and more accurate troubleshooting of JVM performance issues while ensuring data privacy.
Java thread dumps are one of the most powerful diagnostic artifacts for understanding application freezes, deadlocks, CPU spikes, and JVM unresponsiveness, but interpreting them accurately is rarely straightforward. Their size, complexity, and sheer volume can make manual analysis overwhelming, especially…
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