December 10, 2020
The Datadog Security Platform team leverages Serverless to ingest security events across many different cloud providers, deployment platforms, and devices. These security events are then transformed and shipped to a data lake to help defend and protect the platform as a whole. Once there, these ingested events are used to drive internal investigations, create internal security alerts, and reason about security incidents.
In this episode of Datadog on Serverless, David Huie, Team Lead - Security Engineering and Andrew Krug, Technical Evangelist - Security, will join Kirk Kaiser, Technical Evangelism Team Lead. They will talk about the tradeoffs we’re making within the Serverless ecosystem and platform. From deciding when to use Fargate or Lambda, to how well lambda fits within a larger open source ecosystem, we’ll touch upon real world lessons learned from shipping Serveress systems at scale.
Datadog on Building Reliable Distributed Applications Using Temporal →
Datadog on OpenTelemetry →
Datadog on Secure Remote Updates →
Datadog on LLMs: From Chatbots to Autonomous Agents →
Datadog on Stateful Workloads on Kubernetes →
Datadog on Data Science →
Datadog on Kubernetes Autoscaling →
Datadog on Kubernetes Node Management →
Datadog On Maintaining eBPF at Scale →
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 Rust →
Datadog on Profiling in Production →
Datadog on Gamedays →
Datadog on Chaos Engineering →
Datadog on Agent Integration Development →
Datadog on eBPF →
Datadog on Kubernetes Monitoring →
Datadog on Software Delivery →
Datadog on Kubernetes →