Top updates from 2026
October 2026
- Featuredatadoghq.com
Ship faster, improve reliability, and control CI costs with Datadog CI/CD Optimization
Datadog introduced CI/CD Optimization to help teams reduce CI feedback loops, improve build reliability, and control compute costs. The feature targets engineering teams seeking faster deployments and…
- Integrationdatadoghq.com
Process and route critical security logs to Exabeam with Observability Pipelines
Datadog introduced a new integration enabling Observability Pipelines Packs to process and reduce security log volume before forwarding to Exabeam, ensuring parser compatibility. This streamlines secu…
- Contentdatadoghq.com
Datadog Technical Training | Foundation Enablement
Datadog launched new technical training sessions covering AI-Powered Observability and Security, Datadog Bits AI, and expanded offerings in APM, Logs, Real User Monitoring, and Synthetics. New session…
- Contentdatadoghq.com
The first 72 hours of a ransomware attack: Why restored isn’t recovered
Datadog’s blog post highlights that server restoration alone does not equate to full business recovery during ransomware attacks. It emphasizes the need for ransomware recovery planning and leveraging…
- Integrationdatadoghq.com
Monitor Databricks with Datadog
Datadog introduced a new integration enabling users to monitor performance, data quality, and costs of Databricks analytics and AI/ML workloads directly within Datadog. This expands Datadog’s observab…
- Contentdatadoghq.com
Key metrics for monitoring Databricks
Datadog released a blog post outlining key metrics for monitoring Databricks data engineering, analytics, and Model Serving workloads. The guide aims to help users optimize health, performance, and co…
- Featuredatadoghq.com
Monitor warehouse data quality beyond pipeline health
Datadog introduced a new capability to monitor data quality at rest in warehouses, identifying issues that persist even when pipelines succeed. The feature enables tracing problems to their source, ad…
- Featuredatadoghq.com
How we extended Apache DataFusion to execute one query across many machines
Datadog introduced Distributed DataFusion, an extension enabling Apache DataFusion queries to run across multiple machines. This addresses scalability challenges for interactive queries in large-scale…
September 2026
- Featuredatadoghq.com
How we built an async-aware Python profiler
Datadog introduced an async-aware Python profiler that reduces overhead while preserving context across asyncio tasks. The tool is designed to improve debugging and performance monitoring for Python a…
- Integrationdatadoghq.com
Extend Datadog RUM and Product Analytics to Shopify and Salesforce
Datadog announced integrations enabling its Real User Monitoring (RUM) and Product Analytics to track checkout journeys on Shopify and customer experiences in Salesforce Experience Cloud. The move exp…
- Featuredatadoghq.com
Using TypeSafe’s Jev for evals in Datadog Agent Observability
Datadog announced the integration of TypeSafe’s Jev into its Agent Observability platform, enabling both online evals on live spans and offline evals within Datadog experiments using a single rubric. …
- Featuredatadoghq.com
Configure RUM SDKs remotely from Datadog
Datadog introduced RUM Remote Configuration, enabling teams to adjust SDK sampling rates, privacy settings, and data collection remotely without app updates. This decouples configuration changes from …
- Featuredatadoghq.com
Find answers in your logs faster with Datadog’s Tap to Parse
Datadog introduced Tap to Parse, a feature enabling users to extract searchable fields from unstructured logs directly within Log Explorer, Log Pipelines, and Observability Pipelines. This aims to sim…
- Featuredatadoghq.com
Teaching a 9B model to investigate production alerts
Datadog fine-tuned the Qwen3.5-9B model into a specialized agent for production alert investigation, achieving 87% of GLM-5.3’s Recall@5 at roughly 5% of the investigation cost. This update enhances D…
- Featuredatadoghq.com
Cut AI agent cost and improve accuracy with Code Execution in the Datadog MCP Server
Datadog introduced Code Execution in its MCP Server to reduce AI agent costs and improve accuracy by enabling multisignal investigations with fewer tool calls and less model context. This update targe…
- Featuredatadoghq.com
Understand the top paths users take to convert or drop off with Journey Paths
Datadog introduced Journey Paths in its Product Analytics suite, enabling teams to quantify user conversion paths, identify drop-off points, and analyze friction between funnel steps. This tool target…
- Featuredatadoghq.com
Enforce custom rules in Datadog IaC Security scanning
Datadog introduced the ability to create, test, and publish custom Infrastructure-as-Code (IaC) Security rules directly within its platform. This allows organizations to enforce organization-specific …
- Featuredatadoghq.com
From alert to resolution: Manage incidents with Bits Chat in Slack
Datadog introduced Bits Chat in Slack, enabling teams to investigate incidents, collaborate with responders, make code fixes, and track follow-up work directly within Slack. The feature integrates Dat…
- Integrationdatadoghq.com
Transform and route security logs to Microsoft Sentinel tables using Observability Pipelines
Datadog introduced Observability Pipelines Packs to transform and route security logs to Microsoft Sentinel tables, enabling schema mapping and ingest volume control. This integration streamlines log …
- Integrationdatadoghq.com
Manage Cursor costs with Datadog Cloud Cost Management
Datadog launched a new integration with Cursor, enabling users to analyze AI coding spend by user and model, detect unexpected cost changes, and manage these costs alongside existing cloud and SaaS sp…
Top 20 shown. Click a month above for the full archive of Datadog.
Track Datadog on autopilot
- · Weekly AI brief: narrative summary of what shipped, every Monday 9 AM
- · Email or Slack alerts, or chat with the archive in your dashboard
- · Add Datadog + up to 2 more competitors free, no credit card