Chalk's recent release introduces a variety of enhancements aimed at improving workflows, observability, and integrations. The update expands Chalk expressions to facilitate feature engineering and performance through static analysis and C++ compilation, and introduces a broader chalk.functions library for logical expressions and feature transformations. Dashboard improvements include comprehensive metrics, enhanced monitoring with warning banners, and detailed visibility into Kubernetes pod resources, alongside a SQL explorer for faster data exploration. Offline queries now support flexible input and execution parameters, allowing for improved integration and storage options. The @features decorator offers caching options for null or default feature values in online stores like DynamoDB or Redis, while the ChalkClient supports integration testing, enabling CI/CD pipeline execution. Additional features include a new chalk usage command, healthcheck capabilities, support for managing dependencies with Poetry, Pub/Sub as a streaming source, and an idempotency key to prevent duplicate job executions.