‘Advanced Heap Dump Analysis Techniques’ Webinar

In September, a webinar titled “Advanced Heap Dump Analysis Techniques” gathered developers and JVM enthusiasts to discuss efficient strategies for analyzing memory issues through heap dumps. Topics covered included querying with OQL, using APIs for automation, and correlating data to quickly identify memory leaks, ultimately promoting healthier Java applications.

‘The Hidden Battle: Troubleshooting Issues in On-Prem Customer Deployments’ webinar

The recent webinar focused on troubleshooting performance issues in customer-managed, on-premise environments. Experts discussed challenges like limited visibility and communication delays, emphasizing the need for essential artifacts for diagnosis. Participants learned practical strategies, including automation workflows and effective communication techniques, to enhance resolution accuracy and reduce turnaround times.

Key Challenges in Troubleshooting Customer On-Premise Applications

Troubleshooting on-premise application issues is complicated due to limited access to customer systems and reliance on their support staff for vital diagnostic data. Challenges include incomplete information, security concerns, miscommunication, and environmental instabilities. Implementing the yc-360 Script can streamline artifact collection, improving diagnosis and reducing resolution times.

‘Micro-Metrics Every Performance Engineer Should Validate Before Sign-Off’ webinar

The June webinar focused on performance testing, emphasizing the importance of micro-metrics like garbage collection behavior, object creation rates, and thread patterns. These critical indicators can reveal potential issues before they escalate. Participants learned strategies to enhance JVM performance validation and reduce post-deployment problems, highlighting that macro-metrics alone are insufficient.

Performance Lab Tests Say Green. Production Says Otherwise. Why? 

The post addresses challenges faced in performance testing, including discrepancies between test and production environments, reliance on synthetic data, and the absence of long-running tests. To improve detection of performance issues, it suggests enhancing testing with Micro-Metrics, implementing chaos engineering, and recording production traffic for realistic simulations.

Best Practices for Capturing the Micro-Metrics Labs Often Miss

To accurately forecast production performance issues, validating Micro-Metrics is essential. Key best practices include enabling Garbage Collection Logs, triggering 'yc-360 Script' midway and at the end of tests, and utilizing self-trigger M3 mode for endurance tests. Comparing new and previous baseline incident reports helps identify performance degradation trends effectively.

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