# bits ai Published articles for bits ai. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## From alert to resolution: Manage incidents with Bits Chat in Slack DevFeed: [From alert to resolution: Manage incidents with Bits Chat in Slack]() Original publisher: [Read original article]() Author: Nancy Zhu; Evan Marcantonio; Nicole Parisi; Chris Miller Published: 2026-09-16T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [incident](), [Slack](), [Artificial Intelligence](), [telemetry](), [Code](), [Pull Request]() Tags: [ai](), [also](), [bits-ai](), [code](), [collaboration](), [ecommerce](), [incident](), [monitor](), [root-cause-analysis](), [slack](), [telemetry]() ### AI overview This tutorial explains how Bits Chat in Slack can support incident response by investigating alerts, analyzing telemetry, coordinating responders, generating a pull request for a fix, and tracking follow-up work within the incident channel. ### Source excerpt Use Bits Chat in Slack to investigate incidents, collaborate with responders, make code fixes, and capture follow-up work where your team communicates. ## Coordinate product launches with Datadog DevFeed: [Coordinate product launches with Datadog]() Original publisher: [Read original article]() Author: Milene Darnis; Adam Virani Published: 2026-09-08T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [Instrumentation](), [experiments]() Tags: [ai](), [bits-ai](), [digital-experience-monitoring](), [experimentation](), [experiments](), [feature-flags](), [instrumentation](), [launch](), [product-analytics](), [session-replay]() ### AI overview A tutorial on using Datadog Product Analytics Launches to plan product releases, define measurement questions, create tracking plans, and identify missing events and properties before rollout. ### Source excerpt Learn how to turn a product brief and feature flag into a connected launch workflow for instrumentation, experimentation, QA, and reporting. ## Build and run Datadog workflows from Bits Chat or AI agents DevFeed: [Build and run Datadog workflows from Bits Chat or AI agents]() Original publisher: [Read original article]() Author: Neha Haresh; Gabriel Margolis; Brianna Wang; David Robert-Ansart Published: 2026-09-03T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Bots](), [cursor](), [incident]() Tags: [ai](), [ai-agents](), [ai-coding](), [bits-ai](), [claude-code](), [codex](), [cursor](), [debug](), [incident-management](), [mcp](), [workflow-automation](), [workflows]() ### AI overview Datadog describes using Bits Chat and AI coding agents to create, run, and debug automated workflows with Datadog and development context. ### Source excerpt Build, debug, and run Datadog workflows from Bits Chat and AI coding agents using the operational and development context where you're working. ## Debug live production code without redeploying with Datadog Live Debugger DevFeed: [Debug live production code without redeploying with Datadog Live Debugger]() Original publisher: [Read original article]() Author: Eric Metaj; Sarah Stonehill Published: 2026-08-27T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [debugging](), [Instrumentation](), [AI-assisted coding](), [Code]() Tags: [agents](), [ai](), [apm](), [bits-ai](), [code](), [debug](), [debugger](), [debugging](), [developer](), [ide](), [instrumentation](), [production](), [root-cause-analysis](), [tracing]() ### AI overview Datadog Live Debugger helps developers investigate production bugs without changing, restarting, or redeploying application code. It captures runtime details through logpoints, including variable values, method arguments, execution context, and request paths. Bits AI can analyze linked source code, place non-breaking logpoints, interpret collected data, and suggest fixes grounded in production behavior. ### Source excerpt Learn how Live Debugger helps you investigate production code and debug faster using Bits AI. ## This Month in Datadog - July 2026 DevFeed: [This Month in Datadog - July 2026]() Original publisher: [Read original article]() Author: Datadog Published: 2026-08-05T00:00:00Z Content type: release Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Chat](), [releases](), [real user monitoring](), [C++]() Tags: [agentic](), [ai](), [ai-agents](), [bits-ai](), [c-plus-plus](), [mcp](), [mcp-server](), [product](), [production](), [pull-request](), [release](), [testing](), [validation](), [work]() ### AI overview A July 2026 Datadog roundup covering Bits Release, Bits Testing, Bits Chat, Bits Memories, and additional product updates. ### Source excerpt Watch July's This Month in Datadog for in-depth conversations with Datadog product leaders about Bits Release, Bits Testing, Bits Chat, and more. ## Investigate every security event with an AI agent, without the frontier bill DevFeed: [Investigate every security event with an AI agent, without the frontier bill]() Original publisher: [Read original article]() Author: Nicolas Grislain Published: 2026-07-28T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Bots]() Tags: [ai](), [ai-agent](), [ai-research](), [ai-security](), [bits-ai](), [cloud-siem](), [llm](), [logs](), [security]() ### AI overview Datadog describes a two-stage security detection pipeline in which Mambark scores audit-log events and routes only the most suspicious ones to an AI agent for deeper investigation. ### Source excerpt Learn how Datadog built Mambark, a small state-space model that scores every security event and enables heavier AI agents to investigate only the events that matter. ## Answer any cost question faster with the Cloud Cost skill in Bits Chat DevFeed: [Answer any cost question faster with the Cloud Cost skill in Bits Chat]() Original publisher: [Read original article]() Author: Dom Nguyen Published: 2026-07-17T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [cloud cost management](), [finops](), [observability](), [Artificial Intelligence](), [anthropic](), [OpenAI]() Tags: [ai](), [analysis](), [anthropic](), [bits-ai](), [cloud](), [cloud-cost-management](), [cost](), [finops](), [metrics](), [monitor](), [observability](), [openai](), [optimization](), [root-cause-analysis](), [saas]() ### AI overview This article introduces the Cloud Cost skill in Bits Chat, a conversational workflow for investigating cloud, SaaS, AI, custom, and Datadog costs. It explains how teams can ask cost questions in plain language, investigate anomalies, identify the teams or services driving spend, compare spending with budgets, and correlate cost changes with observability metrics to support root-cause analysis and optimization. ### Source excerpt Use the Cloud Cost skill in Bits Chat to investigate cost anomalies, perform root cause analysis on cost spikes, and get personalized savings. ## Reduce SAST false positives with agentic evaluation and Bits Memories DevFeed: [Reduce SAST false positives with agentic evaluation and Bits Memories]() Original publisher: [Read original article]() Author: Cole Maring Published: 2026-07-06T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Static code analysis](), [Application Security](), [Artificial Intelligence](), [bits ai](), [Vulnerabilities](), [Security]() Tags: [agentic](), [ai](), [analysis](), [application-security](), [bits-ai](), [code](), [code-security](), [developer](), [devsecops](), [learn](), [post](), [security](), [threat-detection](), [tools](), [vulnerabilities](), [vulnerability-management]() ### AI overview Datadog's Static Code Analysis uses Bits AI agentic evaluation to investigate SAST findings across a repository, combining related code paths, callers, and validators with organization-specific knowledge from Bits Memories. The goal is to distinguish true vulnerabilities from false positives and speed security triage. ### Source excerpt Learn how Bits AI in Datadog Static Code Analysis uses repository-wide reasoning and custom context to help make security triage faster and more accurate. ## Accelerate investigations with AI in Datadog Incident Response DevFeed: [Accelerate investigations with AI in Datadog Incident Response]() Original publisher: [Read original article]() Author: Curtis Maher; Sam Rodman; Daljeet Sandu Published: 2026-07-01T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Artificial Intelligence](), [Incident response](), [telemetry](), [Monitoring](), [Slack](), [Web app]() Tags: [ai](), [app](), [bits-ai](), [collaboration](), [google](), [incident-management](), [incident-response](), [microsoft](), [monitoring](), [root-cause-analysis](), [slack](), [telemetry](), [web](), [zoom]() ### AI overview Datadog Incident Response introduces three AI-powered capabilities: Bits Investigation acts as an active responder, AI generates summaries of active incidents in chat, and bridge discussions are captured in a unified incident timeline. Bits analyzes incident context such as telemetry, deployment history, chat discussions, and runbooks, then shares investigation updates, root-cause findings, and recommended next steps within existing workflows. ### Source excerpt Investigate incidents with Bits Investigation as a fellow responder, receive AI-generated summaries in chat, and capture critical decisions made on bridge calls. ## Three internal tools Datadog built with AI that improved developer experience and system performance DevFeed: [Three internal tools Datadog built with AI that improved developer experience and system performance]() Original publisher: [Read original article]() Author: Joe McGovern; Alex Zvorygin; Alex Bianchi; Colin Nichols Published: 2026-07-01T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [developer tooling](), [Deployment Tools](), [Orchestration](), [AI Bots](), [SDKs](), [sdlc]() Tags: [ai](), [bits-ai](), [deployment-tools](), [developer-experience](), [devops](), [internal-tools](), [orchestration](), [performance](), [platform-engineering](), [sdlc](), [software-delivery](), [testing]() ### AI overview Datadog describes internal AI-enabled tools intended to improve developer experience, deployment support, and backend performance. One example is an agent-orchestrated support application that investigates deployment requests, drafts responses for approval, and can open a pull request when it identifies a potential fix. ### Source excerpt At Datadog, we don't just use AI to ship customer products. It also enables internal projects and performance wins that help our engineers and systems do their jobs better and faster. Learn more in this blog. ## Preparing for OMB M-26-14: How Datadog supports federal logging maturity DevFeed: [Preparing for OMB M-26-14: How Datadog supports federal logging maturity]() Original publisher: [Read original article]() Author: Chris Leffler; Sophie Wang Published: 2026-06-29T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [SIEM, Security, Observability](), [log management](), [Monitoring](), [threat detection](), [incident](), [Incident response](), [observability](), [Security](), [Security Operations Center](), [Resilience](), [Cybersecurity]() Tags: [bits-ai](), [cloud-siem](), [compliance](), [cybersecurity](), [fedramp](), [govcloud](), [incident-response](), [log-management](), [logging](), [monitoring](), [observability](), [resilience](), [security](), [security-operations-center](), [soc](), [systems](), [telemetry](), [threat-detection](), [workflow-automation]() ### AI overview This article explains how OMB Memorandum M-26-14 changes federal logging guidance from prescriptive requirements to a risk- and maturity-based model. It describes continuous event monitoring and threat hunting, investigation, response, and forensics, including centralized security telemetry, visibility across IT, OT, and IoT environments, threat detection, searchable and retrievable logs, cross-source correlation, incident response, and forensic analysis. It also presents Datadog as a unified observability and security platform for helping agencies meet these requirements. ### Source excerpt Learn how Datadog helps federal agencies prepare for OMB M-26-14 by providing centralized telemetry data, threat detection, and automated incident response. ## DASH 2026: Guide to Datadog's newest announcements DevFeed: [DASH 2026: Guide to Datadog's newest announcements]() Original publisher: [Read original article]() Author: Datadog Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [bits ai](), [Artificial Intelligence](), [Monitoring](), [observability](), [agent observability](), [MCP]() Tags: [agent-observability](), [ai](), [ai-agents](), [bits-ai](), [dash](), [mcp](), [monitoring](), [observability](), [telemetry]() ### AI overview Datadog's DASH 2026 keynote roundup covers Bits AI capabilities for developer and operations workflows, including autonomous detection and remediation, AI-assisted release validation and testing, operational memory, and observability features. It also highlights MCP Apps, Agent Observability, and Journey Monitoring. ### Source excerpt A roundup of everything we announced at DASH 2026, from Bits AI and MCP Apps to Agent Observability and Journey Monitoring. ## Turn Datadog findings into automated code fixes with Bits Code DevFeed: [Turn Datadog findings into automated code fixes with Bits Code]() Original publisher: [Read original article]() Author: Mike Leach; Eric Metaj Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI-assisted coding](), [telemetry](), [error tracking](), [ci]() Tags: [agent](), [ai](), [bits-ai](), [ci](), [code](), [devops](), [error-tracking](), [github](), [logs](), [pull-request](), [software-delivery](), [telemetry](), [traces]() ### AI overview Bits Code investigates Datadog findings using available telemetry and service context, proposes code fixes with unit tests, and opens GitHub pull requests after addressing CI failures. ### Source excerpt Learn how Bits Code can turn high-impact findings into reviewable code changes for engineers. ## Ship code safely at AI speed with Bits Release DevFeed: [Ship code safely at AI speed with Bits Release]() Original publisher: [Read original article]() Author: Ala Shiban; Guillaume Turbat Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [CI/CD](), [AI Bots](), [AI Chat]() Tags: [agents](), [ai](), [bits-ai](), [ci-cd](), [code](), [coding](), [deployment](), [developer](), [devops](), [engineering](), [feature-flags](), [github](), [logs](), [production](), [pull-request](), [release](), [telemetry](), [testing](), [validation](), [workflow]() ### AI overview Bits Release is presented as a preview release-validation system that follows pull requests into production, continuously checks changes with telemetry and testing, and surfaces evidence in engineering workflows. ### Source excerpt Bits Release continuously validates every change from pull request to production, catching silent regressions and helping engineering teams ship at AI speed. ## DASH 2026 Harnessing AI: Guide to Datadog's newest announcements DevFeed: [DASH 2026 Harnessing AI: Guide to Datadog's newest announcements]() Original publisher: [Read original article]() Author: Datadog Published: 2026-06-09T00:00:00Z Content type: release Language: en Sources: [Datadog | The Monitor blog]() Topics: [AI Chat](), [dashboards]() Tags: [agentic](), [ai](), [ai-observability](), [announcements](), [autonomous](), [bits-ai](), [coding](), [conversational-ai](), [dash](), [dashboards](), [incident](), [logs](), [mcp](), [metrics](), [observability](), [telemetry](), [traces]() ### AI overview A DASH 2026 release roundup covering Datadog AI features, including Bits Chat for natural-language search, incident investigation, and dashboard generation. ### Source excerpt A roundup of everything we announced at DASH 2026, including Datadog MCP Apps, Bits Code, AI Observability, and Pup CLI. ## Datadog MCP Apps: Interactive experiences in AI workflows DevFeed: [Datadog MCP Apps: Interactive experiences in AI workflows]() Original publisher: [Read original article]() Author: Amy Zhou; Bowen Chen Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Model Context Protocol](), [MCP Server](), [Artificial Intelligence](), [observability](), [telemetry](), [incident](), [Latency](), [Extension](), [product analytics](), [Claude](), [ChatGPT](), [cursor]() Tags: [ai](), [ai-tools](), [bits-ai](), [chatgpt](), [claude](), [codex](), [cursor](), [extension](), [incident](), [latency](), [mcp](), [mcp-server](), [observability](), [openai](), [telemetry]() ### AI overview Datadog MCP Apps extend the Datadog MCP Server with interactive UI elements inside AI conversations. They let developers inspect live graphs, monitors, Product Analytics widgets, and other visual context while investigating incidents, user behavior, and latency without switching to Datadog. ### Source excerpt Learn how the Datadog MCP Server supports live Datadog graphs, monitors, and other UI elements directly within AI tools such as Cursor, ChatGPT, Claude, and Codex. ## Investigate Kubernetes resources with Datadog MCP tools DevFeed: [Investigate Kubernetes resources with Datadog MCP tools]() Original publisher: [Read original article]() Author: Allie Rittman; Christine Chun Alias Yang Published: 2026-06-09T00:00:00Z Content type: tutorial Language: en Sources: [Datadog | The Monitor blog]() Topics: [MCP Server](), [Kubernetes](), [AI Agent](), [Protocol (disambiguation)](), [context window]() Tags: [ai](), [ai-agents](), [bits-ai](), [containers](), [context-window](), [infrastructure-monitoring](), [kubernetes](), [mcp](), [mcp-server](), [root-cause-analysis](), [tools]() ### AI overview Datadog MCP Server's Kubernetes toolset gives MCP-compatible AI agents read-only, cross-cluster access to Kubernetes resource context in Datadog. The article explains how its tools support resource searches, manifest inspection, issue investigation, metadata enrichment, scoped structured responses, pagination, and context-window management. ### Source excerpt Use Datadog MCP Server Kubernetes tools to help AI agents search resources, inspect manifests, and investigate Kubernetes issues. ## Get reliable answers to business questions with Bits Data Analysis DevFeed: [Get reliable answers to business questions with Bits Data Analysis]() Original publisher: [Read original article]() Author: Jonathan Morin; Jonathan Parisot; Harel Shein Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Data analysis](), [data observability](), [semantic-layer](), [SIEM, Security, Observability](), [Model Context Protocol](), [ai-coding]() Tags: [ai](), [ai-coding](), [analytics](), [bits-ai](), [data-analytics](), [data-engineering](), [data-observability](), [digital-experience-monitoring](), [mcp](), [observability](), [root-cause-analysis](), [semantic-layer]() ### AI overview Bits Data Analysis, now in Preview, helps teams answer business questions with governed context from their data stack and Datadog telemetry. It uses metric definitions, lineage, freshness, quality signals, application telemetry, and source code to select appropriate data and provide confidence indicators with links to the definitions and tables used. ### Source excerpt Learn how Bits Data Analysis answers business questions using governed data context from Datadog. ## Automatically optimize database queries with Datadog Database Monitoring DevFeed: [Automatically optimize database queries with Datadog Database Monitoring]() Original publisher: [Read original article]() Author: Nenad Noveljić; Alex Weisberger; Eden Gorevoy; Jake Martin Published: 2026-06-09T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [database monitoring](), [Optimization](), [Database](), [Pull Request](), [bits ai](), [Deployment](), [telemetry]() Tags: [bits-ai](), [code](), [database](), [database-monitoring](), [deployment](), [devops](), [monitoring](), [optimization](), [performance](), [pull-request](), [telemetry]() ### AI overview Datadog Database Monitoring's Bits Database Optimization automatically identifies slow-query candidates, validates rewrites against a simulated copy of the schema, and opens pull requests with simulation evidence for the code that generated the query. ### Source excerpt Learn how you can automatically detect, validate, and fix slow queries with Datadog Database Monitoring, closing the loop from optimization to deployment.