This Month in Datadog - February 2026
Watch February’s This Month in Datadog to learn about Data Observability, AI Guard, Feature Flags, five new Incident Management releases, and more.
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23 项更新 · 2026年2月
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Watch February’s This Month in Datadog to learn about Data Observability, AI Guard, Feature Flags, five new Incident Management releases, and more.
The article highlights the risks associated with improper sourcing and lifecycle management of Amazon EC2 AMIs (Amazon Machine Images) and their impact on cloud security. It emphasizes that poorly man…
Learn how to capture RUM and APM telemetry data without making any code changes.
Learn how you can monitor mobile app launch performance on iOS and Android by using startup metrics and launch-type context in Datadog RUM.
Learn how Datadog used LLM Observability internally to build and test AI Guard, so that teams can protect their Bits AI Agents by detecting and blocking unsafe model behavior.
Learn how Datadog Code Coverage helps you easily detect untested code and track test coverage over time.
Learn how guardrail metrics automate rollouts with built-in safety checks, and how Datadog Feature Flags connects releases to your observability data.
Monitor Versa SD-WAN health, link/tunnel SLA performance, interface utilization, and application traffic in Datadog.
APM Recommendations helps you identify, prioritize, and act on performance and reliability issues by using telemetry data from across the Datadog platform.
Trace transitive vulnerabilities to root dependencies and apply safe upgrades with guided remediation.
Learn how Datadog Sheets helps security teams generate audit-ready vulnerability and compliance reports from a single, unified view.
Monitor edge device health, link quality, SLA compliance and application performance with Datadog's Fortinet FortiManager SD-WAN integration.
Datadog Code Coverage surfaces coverage insights in CI and PRs, helping teams apply consistent testing standards and review overall and diff coverage.
See how Datadog Code Coverage unifies test coverage across repositories, helps enforce testing standards, and generates tests for untested code paths.
Datadog Observability Pipelines uses Reference Tables to enrich logs with ServiceNow CMDB data to help you prioritize events and investigate incidents.
Learn how Datadog’s Lustre integration correlates file system, job, and infrastructure metrics to troubleshoot HPC bottlenecks and optimize I/O performance.
Datadog Workload Protection Findings provides a dedicated view for risky runtime behavior, helping teams improve security posture and respond effectively to urgent threats.
Learn how you can easily define user actions, analyze journeys without SQL, and save and share charts for faster decisions.
Learn how Datadog AI Guard evaluates prompts, responses, and tool calls in real time to help you defend agentic AI applications against emerging threats.
Learn how to optimize inefficient JavaScript code with CSS to improve rendering performance, accessibility, Core Web Vitals, and frontend user experience.
Get producer-aware distributed tracing for Google Pub/Sub, including Cloud Run push subscriptions, batch fan-out visibility, and async acknowledgments.
Learn how you can discover human names in your logs at scale and support compliance efforts without having to write and maintain regex patterns.