February 2026 Summaries

Chalk has introduced a series of updates focused on enhancing system efficiency, scalability, and integration, aimed at improving the management of real-time data pipelines and workload automation. Notable advancements include the implementation of metaplanning and autosharding, which optimizes query shard counts automatically for large workloads, reducing operational overhead and improving runtime performance. Enhancements in planner caching and parallel resolver execution have decreased cold-start latency, ensuring a more consistent and smooth performance. Chalk has also introduced webhooks for real-time alerting and custom integrations, enabling teams to automate responses and maintain system reliability, and has expanded its ecosystem by supporting external vector databases for enhanced model capabilities. Additionally, the platform now offers extensive learning resources and customer success stories, such as its collaboration with Medely, to illustrate Chalk's practical applications in production machine learning stacks, and has provided a migration guide for teams transitioning from Tecton to Chalk.

ODSC's first San Francisco meetup of 2026 at their new Union Square office featured a talk by co-founder Elliot Marx on improving marketplace recommender systems by shifting from batch pipelines to real-time feature computation. The existing reliance on precomputed features often results in stale data and missed user interactions, whereas Elliot's approach involves computing features on demand, akin to a query execution engine, allowing for fresher, dynamically generated user-item data. During a live demo, Marx demonstrated the process of writing resolvers in Python to define and manage new features, generating efficient query plans, and ensuring temporal consistency to avoid data leakage. The session resonated with attendees facing similar challenges, leading to an extended Q&A session about query optimization and dynamic feature handling. The event, co-hosted by ODSC, marked the beginning of a series of planned events aimed at showcasing Chalk's capabilities for those working on production machine learning systems.