Datadog | The Monitor blog

This Month in Datadog - July 2026

The July episode of *This Month in Datadog* introduces several new "Bits" AI features, including Bits Release for automated code validation and Bits Chat for interacting with Datad…

Prioritize security findings with the Datadog Runtime Prioritization Engine

The Datadog Runtime Prioritization Engine (RPE) addresses the challenges of managing security in dynamic cloud environments by using live telemetry to automatically identify resour…

A practical guide to React error monitoring

This article outlines strategies for implementing effective error handling in React applications by tracking errors at the render, business, and global levels. It emphasizes the im…

Engineering the Datadog Agent for FedRAMP High® Certification

To achieve FedRAMP High certification, Datadog had to move beyond its previous proxy-based architecture, which could not sufficiently enforce strict cryptographic boundaries and fa…

Investigate every security event with an AI agent, without the frontier bill

To enable cost-effective security monitoring at scale, a new two-stage pipeline uses a small state-space model called Mambark to act as an efficient retriever for massive event str…

Normalize security logs to Google SecOps UDM with Observability Pipelines

Google SecOps packs for Observability Pipelines automate the normalization of diverse security logs into a standardized Unified Data Model (UDM) before they reach Google SecOps. Th…

Efficient multi-provider agent environments with AI gateways: best practices

AI gateways provide a centralized interface for accessing multiple LLM providers through a single API, allowing organizations to efficiently route agentic tasks to the most cost-ef…

Provision Datadog on Stripe Projects

Datadog has partnered with Stripe Projects to allow developers to provision observability services directly from the terminal using simple CLI commands. This integration automates …

From zero to traces: Choosing the right APM instrumentation method for your stack

Datadog recommends using Single Step Instrumentation (SSI) as the default method for distributed tracing because it can deploy across an entire fleet in minutes by injecting tracer…

Unbiased Java CPU profiling with JFR in JDK 25

While traditional Java Flight Recorder (JFR) sampling can be biased and fail to accurately identify CPU-bound hotspots, developers have historically relied on unstable, unsupported…

Use OpenTelemetry-native observability with Datadog from ingestion to investigation

Following OpenTelemetry’s CNCF graduation, Datadog is expanding its support for OTel-native observability by enabling vendor-neutral data ingestion via standard OTLP exporters and …

Answer any cost question faster with the Cloud Cost skill in Bits Chat

Datadog’s Bits Chat Cloud Cost skill introduces a conversational interface that allows FinOps and engineering teams to manage cloud, AI, and SaaS expenditures using plain language.…