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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 London 2024
2024-04-12 · via Datadog | The Monitor blog

In the last week of March 2024, Datadog hosted its latest Datadog Summit in London to celebrate our community. As Jeremy Garcia, Datadog’s VP of Technical Community and Open Source, mentioned during his welcome remarks, London is the first city that has seen two Datadog Summits, with the first one in 2018. It was great to be able to see how our community there has grown over the past six years.

Datadog Summit London included talks from Datadog product managers and our customers, hands-on workshops, product demos, and a couple of fun interactive challenges (AWS Gameday and CoTerm Battle)

You can watch the talks below or see the entire playlist here.

Leveraging observability for enhanced IoT development at Electrolux

Kicking off the day’s talks, Kristina Kondrashevich from Electrolux, shared the very interesting story of how her team introduced chaos engineering practices to Electrolux’s software engineering organization. Thanks to these techniques, teams started to own their own services in production, understand infrastructure related incidents, and resolve them faster.

Security at the speed of cloud

Securing applications in a world where we are releasing code to production several times per day can be overwhelming. Max Hedouin, senior product manager for App and API Protection at Datadog, shared how security, development, and operations teams need to collaborate and work together to be successful in this challenging task.

Serving up loyalty one dish at a time

Toli Apostolidis, principal software engineer at Flipdish, explained how Flipdish was able to deliver a full new product from scratch in just four months while also modernizing their technical stack and their team processes. He covered how a new way of organizing their teams was as important as any technical decision they made throughout the project.

And what about my user experience?

When monitoring applications, teams might start by covering their infrastructure and backend services. But your users interact with your application through your frontend services, so they are usually the first ones to find errors there. How can we improve this? Maël Lilensten of Datadog talked through some of the ways that Datadog frontend engineers use Datadog RUM products to improve the user experience of our customers.

Managing a complex distributed payment system across 185 locations and 110k of transactions per day

Devices on the edge represent a whole new set of problems when it comes to observability. Usman Niazi, head of SRE at Dunelm, shared how the company eliminated the blind spots they had in a third-party vendor application with a smart in-house solution involving AWS Lambda and Datadog.

What is an anomaly?

Is this an anomaly? This simple question started a lot of conversations during Datadog Principal Product Manager Nils Bunge’s talk. Nils explained how Datadog had to make some important decisions when designing Watchdog in 2017 to avoid false positives, and how they plan to improve it in the future.

Aviva’s journey to carbon net zero, one EC2 instance at a time

In March 2021, Aviva officially announced that the company aims to achieve net-zero carbon emissions by 2040. The first milestone on that journey is a 25 percent reduction in carbon intensity of assets by 2025. Leo Earl, cloud sustainability specialist at Aviva, shared very practical tips on how their engineering teams are using observability to identify waste and reduce the overall energy consumption of their infrastructure.

Thanks for coming

Thanks to everyone who came to Datadog Summit London, and thanks to everyone who shared their knowledge! We look forward to meeting you at a future summit if we missed you this time.