May 27, 2020
When 2 years ago Datadog decided to move its infrastructure platform to Kubernetes we didn’t expect to find so many roadblocks, but ingesting trillions of datapoints per day in a reliable fashion requires pushing the limits of cloud computing.
Creating and managing dozens of clusters, with thousands of nodes each and operating in several clouds was a challenging but rewarding learning experience. In this session Ara Pulido, Developer Advocate, will chat with Laurent Bernaille, Staff Engineer at Datadog and part of the team that created Datadog’s Kubernetes platform. We’ll cover the challenges we found creating and scaling Datadog’s Kubernetes platform and how we overcame them. The discussion will include scaling the control plane, security, certificates, networking, our open source contributions, and more!
Datadog on Building Reliable Distributed Applications Using Temporal →
Datadog on OpenTelemetry →
Datadog on Secure Remote Updates →
Datadog on Stateful Workloads on Kubernetes →
Datadog on Data Science →
Datadog on Kubernetes Autoscaling →
Datadog on Kubernetes Node Management →
Datadog on Caching →
Datadog on Data Engineering Pipelines: Apache Spark at Scale →
Datadog on Site Reliability Engineering →
Datadog on Building an Event Storage System →
Datadog on gRPC →
Datadog on Gamedays →
Datadog on Chaos Engineering →
Datadog on Serverless →
Datadog on Kubernetes Monitoring →
Datadog on Software Delivery →
Datadog on Incident Management →