The Curious Engineer

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Datadog

datadoghq.com/blog

Check out The Monitor, Datadog's main blog, to learn more about new Datadog products and features, integrations, and more.

DevOps / SRE / infrastructure

Posts
107 from 1 Jul 2026 to 30 Oct 2026
Posting
weekly (105 in the last year)
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company blog
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https://www.datadoghq.com/blog/index.xml

2026 105

  1. How we use Insights to improve the agent behind Insights
  2. Datadog named a Leader in the Forrester Wave™: AIOps Platforms, Q4 2026
  3. Trace voice agents with Datadog Agent Observability
  4. Detect when your AI agent copies a self-replicating prompt injection
  5. Default to serverless for AI agents, then let production data decide what moves
  6. Match monitoring depth to workload needs with Infrastructure Basic
  7. Best practices for scaling A/B testing with experiment protocols
  8. Monitor Oracle AI Database across clouds with Datadog
  9. Optimize AI costs with Agent Observability
  10. Beyond container image signing: How we enforce software supply chain policies at Datadog
  11. Build better SLOs with RUM and synthetic SLIs
  12. Introducing Scout 1.0: A new SRE model powering Bits AI with frontier performance at a fraction of the cost
  13. Monitor the performance of critical steps in user journeys with RUM operations
  14. How Kubernetes DRA can improve GPU utilization and cut costs
  15. How Datadog defines service criticality at scale
  16. Unify data across Datadog BYOC with cross-cluster queries for teams and AI agents
  17. Define user actions on your web app with visual labeling in Product Analytics
  18. Run incident response in your FedRAMP High environment
  19. How we replaced our host vulnerability scanner with the Datadog Agent
  20. Ship faster, improve reliability, and control CI costs with Datadog CI/CD Optimization
  21. Process and route critical security logs to Exabeam with Observability Pipelines
  22. Key metrics for monitoring Databricks
  23. Databricks’ native monitoring resources
  24. Monitor Databricks with Datadog
  25. The first 72 hours of a ransomware attack: Why restored isn’t recovered
  26. How we extended Apache DataFusion to execute one query across many machines
  27. Monitor warehouse data quality beyond pipeline health
  28. Block malicious packages across your organization with Supply Chain Firewall and Datadog Code Security
  29. How we built an async-aware Python profiler
  30. Extend Datadog RUM and Product Analytics to Shopify and Salesforce
  31. Using TypeSafe’s Jev for evals in Datadog Agent Observability
  32. How we fine-tuned Qwen3.5-9B for change attribution in production alerts
  33. Find answers in your logs faster with Datadog’s Tap to Parse
  34. Configure RUM SDKs remotely from Datadog
  35. Cut AI agent cost and improve accuracy with Code Execution in the Datadog MCP Server
  36. When users don’t click thumbs up: Inferring agent feedback from Datadog telemetry
  37. Understand the top paths users take to convert or drop off with Journey Paths
  38. Enforce custom rules in Datadog IaC Security scanning
  39. From alert to resolution: Manage incidents with Bits Chat in Slack
  40. Transform and route security logs to Microsoft Sentinel tables using Observability Pipelines
  41. Monitor TAS and gang scheduling for AI training in Kubernetes
  42. How to operate shared platforms safely at agent scale
  43. Manage Cursor costs with Datadog Cloud Cost Management
  44. Datadog named the Company to Beat for observability platforms in 2026 Gartner® AI Vendor Race report
  45. Analyze your experiments in ChatGPT with the Datadog Experiments plugin
  46. Understanding NetFlow duplication: Why it happens, and how to deduplicate
  47. How we built Datadog Experiments
  48. Troubleshoot Kafka issues across every layer of your stack with Kafka Console
  49. How we built data-driven AI Golden Paths at Datadog
  50. Coordinate product launches with Datadog
  51. Stop runtime threats with Workload Protection response actions
  52. Build and run Datadog workflows from Bits Chat or AI agents
  53. Monitor prompt caching to optimize your token usage
  54. Making Rust observability reliable at scale with OpenTelemetry
  55. From traces to experiments: A loop for improving AI agents
  56. Visualize how CUPED adjusts experiment results with Datadog
  57. How Bits Database Optimization proves a query rewrite is faster
  58. Respond to security threats faster with Tines and Observability Pipelines
  59. Troubleshoot and secure your code faster with Datadog’s Bitbucket Cloud Source Code integration
  60. Reduce sensitive data exposure with build-time allowlists
  61. Debug live production code without redeploying with Datadog Live Debugger
  62. What we learned about AI agent security by monitoring our agents
  63. How Datadog saves over $1 million each month by optimizing AI usage
  64. Beyond the $1 AI era: How federal agencies can build the evidence for FY27 renewals
  65. Golden Paths for AI agents: What changes when platform users aren’t human?
  66. Monitor Azure Functions across every hosting plan with Datadog
  67. Control trace volume with OpenTelemetry tail-based sampling
  68. Detect vulnerabilities in LLM applications with Datadog’s AI-native SAST
  69. From signals to systemic risk: Building Risk AI
  70. How CISA’s BOD 26-04 changes vulnerability prioritization
  71. 20× the CI traffic without getting slower: How we rebuilt Git serving at Datadog
  72. Two ways to measure the cumulative impact of experiments
  73. Centralize human and agentic work with Datadog Work Management
  74. Trace AWS Lambda durable functions with Datadog
  75. Data pipeline monitoring 101: Tracking health and performance across the data stack
  76. Avoid Azure secret rotation with secretless authentication
  77. How we improved APM Java startup by encoding a prefix trie as a JVM constant
  78. Investigate account-level churn risk with Product Analytics account segments
  79. How to manage risk from unfixed Kubernetes CVEs
  80. Instrument serverless apps with agentic onboarding
  81. Find, analyze, and collaborate on user sessions in Datadog Session Replay
  82. This Month in Datadog - July 2026
  83. Prioritize security findings with the Datadog Runtime Prioritization Engine
  84. A practical guide to React error monitoring
  85. Investigate every security event with an AI agent, without the frontier bill
  86. Engineering the Datadog Agent for FedRAMP High® Certification
  87. Normalize security logs to Google SecOps UDM with Observability Pipelines
  88. Provision Datadog on Stripe Projects
  89. AI gateway best practices: Model routing, reliability, and budget controls for production agents
  90. Unbiased Java CPU profiling with JFR in JDK 25
  91. From zero to traces: Choosing the right APM instrumentation method for your stack
  92. Use OpenTelemetry-native observability with Datadog from ingestion to investigation
  93. How we brought agentic workflows to Cloud SIEM with the Datadog MCP Server
  94. Answer any cost question faster with the Cloud Cost skill in Bits Chat
  95. Monitor Apigee X API traffic and security with Datadog
  96. Datadog named Leader in 2026 Gartner® Magic Quadrant™ for Observability Platforms
  97. Making agentic token costs visible in production
  98. Protect AWS Strands Agents with Datadog AI Guard
  99. Monitor your .NET MAUI apps with Datadog RUM
  100. DASH 2026 recap: Product news, sessions, and highlights
  101. Monitor watchOS and visionOS apps with Datadog RUM
  102. Reduce SAST false positives with agentic evaluation and Bits Memories
  103. The effect distribution: The missing piece in experimentation programs
  104. How we measure data completeness at scale
  105. Three internal tools Datadog built with AI that improved developer experience and system performance

Undated 2

  1. Engineering
  2. AI