Datadog | The Monitor blog

Give your AI agents live Datadog access from the command line

Pup CLI is a single-binary tool that provides AI agents and automation pipelines with secure, OAuth-scoped access to over 33 Datadog product domains. It optimizes agent workflows t…

Introducing Bits Agent Builder: Build agentic workflows for alert response and remediation

Datadog has launched Bits Agent Builder, a new tool that enables users to create custom, hosted AI agents capable of analyzing observability data and executing automated actions. B…

When failover isn’t safe: Building high-availability PostgreSQL on Kubernetes

During a simulated "gameday" failure, Datadog discovered that network latency caused PostgreSQL replication lag to exceed safety thresholds, preventing the system from safely promo…

From single pull requests to full software packages: Detecting malicious code at scale

The article describes the expansion of BewAIre, an LLM-based security system, from analyzing pull requests to scanning entire dependency packages for malicious code. The updated sy…

A deep dive into surfacing and fixing gaps in AWS data perimeter policies

This article examines the security gaps that arise when organizations rely on per-resource controls rather than organization-level policies to establish AWS data perimeters. Using …

How we cut Spark compute costs by 44% with agentic AI and Datadog Jobs Monitoring

To optimize a massive, high-cost Spark job, Datadog engineers developed an AI agent using Claude and Jobs Monitoring to bridge the gap between execution plans and application code.…

Migrate to Azure Managed Redis with Datadog and Eden

To mitigate the risks of migrating from Azure Cache for Redis to Azure Managed Redis, the article proposes a strategy using Datadog and Eden. Datadog provides the observability nee…

Monitor LLM routing with the Kubernetes Inference Extension

The Kubernetes Gateway API’s Inference Extension optimizes LLM serving by replacing generic HTTP load balancing with "inference-aware" routing that evaluates backend signals like K…

How a unified data model improves feature flag rollout decisions

The article argues that fragmented, "stitched-together" tool stacks create significant operational friction and decision-making delays by forcing teams to navigate disconnected dat…

Instrument LangGraph agents with Datadog: a practical guide

Datadog's AI Agent Monitoring addresses the "black box" nature of AI agents by providing end-to-end visibility into workflows, tool executions, and performance metrics like latency…

Monitor Azure Managed Redis with Datadog

Datadog’s agentless integration for Azure Managed Redis provides comprehensive visibility into critical metrics like cache efficiency, latency, and resource utilization through aut…

Deploy Datadog Kubernetes Autoscaling at scale

Datadog Kubernetes Autoscaling helps platform teams reduce idle costs by centrally managing workload rightsizing through in-app setup, GitOps cluster profiles, and AI-assisted onbo…