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Datadog | The Monitor blog

Introducing our open source AI-native SAST Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog Not all index scans are equal: How we cut query latency by over 99% Platform engineering metrics: What to measure and what to ignore Integrate Recorded Future threat intelligence with Datadog Cloud SIEM CI/CD security: threat modeling using a MITRE-style threat matrix CI/CD security: How to secure your GitHub ecosystem Ingress NGINX is EOL: A practical guide for migrating to Kubernetes Gateway API Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA Introducing the Datadog Code Security MCP Capture and analyze custom heatmaps in Session Replay Understand session replays faster with AI summaries and smart chapters Monitor ClickHouse query performance with Datadog Database Monitoring How we designed empathetic alert sounds for on-call engineers Search and act across Datadog to resolve issues faster with Bits Assistant Measure the business impact of every product change with Datadog Experiments Analyzing round trip query latency Configuring JavaScript caches for better performance Introducing Bits AI Dev Agent for Code Security Datadog achieves ISO 42001 certification for responsible AI Monitor Nutanix clusters, hosts, and VMs with Datadog Monitor Juniper Mist in Datadog A new Host Map for modern infrastructure Annotate traces to improve LLM quality with Datadog LLM Observability What’s new in Cloud SIEM: AI-powered investigations, enhanced threat intelligence, and scalable security operations Explore Kubernetes with native OpenTelemetry data Monitor Oracle Fusion Cloud Applications with Datadog Announcing the Datadog Terraform provider v4.0.0 Scaling Kubernetes workloads on custom metrics How to design cloud environments for AI-powered threat analysis Monitor Aruba Central in Datadog How we centralize and remediate risks with Datadog Case Management Accelerate incident response with Datadog and ServiceNow Monitor your application and network load balancer logs Understanding Karpenter architecture for Kubernetes autoscaling Tools for collecting metrics and logs from Karpenter Monitor Karpenter with Datadog What your product data is actually saying Key metrics for monitoring Karpenter Securing Datadog’s platform in the AI age: The role of observability data Four ways engineering teams use the Datadog MCP Server to power AI agents Approaching your observability migration with the right mindset Meet the new Bits AI SRE: Deeper reasoning, twice as fast Key learnings from the 2026 State of DevSecOps study Use plain English to query your multi-cloud infrastructure in Resource Catalog Simplifying troubleshooting across the user journey with Datadog Synthetic Monitoring Protect your OCI resources with Datadog Cloud Security This Month in Datadog - February 2026 Amazon EC2 security: How misconfigured and public AMIs expand your cloud attack surface Enable end-to-end visibility into your Java apps with a single command Measure and improve mobile app startup performance with Datadog RUM Evaluating our AI Guard application to improve quality and control cost Identify untested code across every level of your codebase Make use of guardrail metrics and stop babysitting your releases Monitor Versa Networks SD-WAN performance in Datadog Improve performance and reliability with APM Recommendations Remediate transitive vulnerabilities faster with Datadog Software Composition Analysis Generate audit-ready vulnerability and compliance reports with Datadog Sheets Monitor Fortinet FortiManager performance in Datadog Improve test coverage across codebases with Datadog Code Coverage Move fast, don’t break things: Consistent testing standards at scale Enrich logs with ServiceNow CMDB context before routing to any SIEM or logging tool Monitor Lustre with Datadog Make faster, better product decisions with Datadog Product Analytics Surface and remediate runtime posture issues with Workload Protection Findings Protect agentic AI applications with Datadog AI Guard How to optimize JavaScript code with CSS Trace Google Pub/Sub workloads in Cloud Run with Datadog Detect human names in logs with ML in Sensitive Data Scanner How we cut our NLQ agent debugging time from hours to minutes with LLM Observability Debug PostgreSQL query latency faster with EXPLAIN ANALYZE in Datadog Database Monitoring Datadog acquires Propolis Unify and correlate frontend and backend data with retention filters Scale compliance across global frameworks with Datadog Cloud Security Monitor Arista VeloCloud SD-WAN performance with Datadog Building reliable dashboard agents with Datadog LLM Observability Simplify log collection and aggregation for MSSPs with Datadog Observability Pipelines Mitigation for Node.js denial-of-service vulnerability affecting Datadog APM Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization How we built an AI SRE agent that investigates like a team of engineers Datadog integrations 2025 recap: Observability for AI, security, and hybrid cloud Design effective executive dashboards with Datadog Implement dbt data quality checks with dbt-expectations Bring faster visibility into AWS Lambda functions with remote instrumentation Troubleshoot faster with the GitLab Source Code integration in Datadog How Cambia Health Solutions saved $30,000 monthly with Cloud Cost Management and the Datadog Resource Catalog Normalize any logs for Cloud SIEM with Datadog's OCSF processor Optimizing Datadog at scale: Cost-efficient observability at Zendesk Detect, diagnose, and resolve network issues easily with CNM Network Health Connect engineering errors to user impact in early-stage products Cilium configuration for Kubernetes operations at scale Designing feedback loops for progressive delivery Ship features faster and safer with Datadog Feature Flags Choosing the right OpenTelemetry Collector distribution Route your monitor alerts with Datadog monitor notification rules Automate Cloud SIEM investigations with Bits AI Security Analyst Cloud threat detection: How to identify risky activity across control and data planes Collecting Kafka performance metrics Monitoring Kafka with Datadog Monitoring Kafka performance metrics
Recapping Datadog Summit Denver 2022
Kirk Kaiser, Kaylyn Sigler · 2022-05-02 · via Datadog | The Monitor blog

After a two-year hiatus, Datadog customer summits are back. And what better place to begin in-person again than in sunny Denver, Colorado!

This year, Datadog Summit included a series of technical talks, hands-on workshops, and small-group Q&A sessions. We discussed how to better scale container operations, how to improve processes like on-call, and how to create smoother feature releases. We introduced automated root cause analysis with Watchdog RCA, live container resource maps, and recent Log Management advances. In addition, Datadog users and partners shared their own diverse experiences: Scott Berke from Slice used Datadog to build out the infrastructure they needed to power their search, and Brian Lokey, Engineering Leader at Kandji, shared how they scaled their development teams during hyper-growth of their company.

You can watch some of the product announcements and talks below or see the entire playlist here.

Security is everyone’s job - Linux vulnerabilities in production infra

Security vulnerabilities can show up anywhere in production. Datadog’s Nick Davis discusses how security is everyone’s job, and how teams with more than security in their title worked together to mitigate the DirtyPipe vulnerability in the Linux kernel 5.8 and up. He goes through the vulnerability, how orgs could be at risk from it (with examples) and then how we mitigated the risk at Datadog.

Searching for a Slice: how we built a search pipeline to power a robust search experience (Slice)

In this talk, Scott Berke from Slice describes the process of building out the infrastructure to power the search at Slice. Along the way, we learn about the many details that become important in building a consistent search and some of the unexpected ways they reused search internally to drive growth.

CI & shift-left observability

Borja Burgos from Datadog talks about what shift-left observability means, some of its core principles, and the benefits you can get by implementing it.

Empowering developer teams during hyper-growth (Kandji)

Brian Lokey, Engineering Leader at Kandji, shows how they empower their developers to get things done while significantly scaling up the size of their team. Brian discusses infrastructure as code, GitOps and democratized deployments, observability, and more.

You build it, you own it - Microservices operations with Datadog Service Catalog

Managing microservices requires understanding many dependencies, both technical and operational. Brooke Chen of Datadog introduces the Service Catalog, a new view combining telemetry, performance, topology, and metadata to enable an at-a-glance understanding of even the most complex microservices architectures.

Sharing Safely - Build a modern compliance strategy for your observability data

Tori Teng of Datadog takes us through a real-world example of how a large financial services company was able to limit and mitigate the risk of leaking sensitive data by combining Sensitive Data Scanner with Log Management Role Based Access Control (RBAC).

Troubleshooting in serverless applications

In this talk, Alex Cuoci of Datadog explains the basics of serverless and shows recent data and research demonstrating that at least one-in-five organizations used serverless in 2021. He runs through an example of how to deploy a serverless application in AWS, including discussing API Gateway, AppSync, Lambda functions, synchronous and batch processing, and persisting data, and how this gives you a more holistic view for how your serverless workloads are behaving across the entire stack.

Kubernetes at Datadog scale

When Datadog adopted Kubernetes we discovered some of these boundaries the hard way, and we continuously challenge and modify our infrastructure decisions in order to fit our use case. Ara Pulido shares what we learned as we scaled our Kubernetes clusters, the contributions to Kubernetes we made along the way, and how you can apply those learnings when growing your Kubernetes clusters from a handful to hundreds or thousands of nodes.

Simplify scaling your container operations with kubernetes

Our most recent container report showed that the average number of pods deployed by Kubernetes organizations is doubling. Watch Datadog’s John Kendall cover how to simplify the scaling of your container operations and cut through this increasing complexity with the new Live Container Resource Map.

Datadog’s own Omri Sass covers the ways in which our Application Performance Monitoring (APM) suite can help remediate problems faster. Learn more about the components that make up the suite as well as updates to Watchdog, with Impact Analysis and Root Cause Analysis.

Thanks to everyone who came to Datadog Summit Denver, and thanks to everyone who shared their wisdom! We look forward to meeting you at a future Summit if we missed you this time. You can view the entire playlist for the event here.