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At Intuit one third of P1/P2 outages are caused by a change. As Intuit runs ~2500 services on K8s we need to quickly detect and resolve problems using AIOps. Our talk focuses on how we built a K8s native DAG-based streaming processing platform (Numaflow) and streaming ML platform (Numalogic) which is open-sourced under Numaproj to address this problem. We will show how we collect, process, and analyze in-cluster data in real-time and how our Numalogic computes anomaly scores for each deployment. This DAG-based ML platform has now been adopted by Intuit and helps our ML engineers focus on writing just the inference and pre/post-processing logic while the platform takes care of building the dynamic execution model, retries, buffering between the vertices, back-pressure, conditional-forwarding, and auto-scaling. We will also show how we integrated Observability into Argo CD so users can understand and remediate the behavior induced by change and how this is helping Intuit reduce MTTD/MTTR.
Amit is Director of Engineering at Intuit responsible for Observability and Analytics which covers Observability , Operational Data Lake and Platform Analytics. He is also responsible for open source projects Argo and Numaproj. He is currently working to deliver observability and... Read More →
Vigith is a Principal Software Engineer for the Intuit Observability and Analytics team in Mountain View, California. One of Vigith's current day-to-day focus areas is on the various challenges in building scalable, data and AIOps solutions for both batch and high throughput systems... Read More →
