May 2026 monthly summary for ai-dynamo/dynamo: Enhanced test infrastructure and deployment documentation to boost reliability, efficiency, and maintainability of AI workloads. Key changes targeted testing organization, CI performance, and accurate Kubernetes deployment guidance. Key features delivered: - Component-based test markers added across vLLM, SGLang, and TRT-LLM to improve test organization and enable selective CI execution by backend component. - Documentation update for Kubernetes deployment with Volcano, correcting links and directing users to the appropriate Volcano installation guide. Major bugs fixed: - No standalone customer-facing bugs reported this month; improvements focused on CI reliability, test stability, and documentation accuracy to reduce deployment and test friction. Overall impact and accomplishments: - Faster, more reliable CI feedback loops with component-level test selection, leading to reduced CI time and maintenance overhead. - Clear, up-to-date deployment guidance for AI workloads, enabling smoother Kubernetes-based deployments with Volcano. - Strengthened code health and collaboration through explicit test categorization and documentation improvements. Technologies/skills demonstrated: - Test frameworks and CI/CD optimization, component-based testing, and test markers. - Kubernetes deployment practices with Volcano integration. - Documentation authoring and cross-team collaboration.