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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
Join us at Datadog Summit Sydney
2022-07-01 · via Datadog | The Monitor blog

Datadog is built on community—from the engineers and SREs whose feedback helps us constantly improve, to the developers who share integrations that broaden the Datadog ecosystem. Datadog Summit is our celebration of community.

We’re excited to be back in person! Our next Datadog Summit will be held on August 16 in Sydney. We hope you’ll join us to meet and learn from others in the community, as well as from the Datadog team.

Sharing knowledge

At the summit you’ll hear from engineers and developers who were able to transform their organizations by building cultures of observability. This is an opportunity for you to learn from other users, such as ones from Australian companies Canva and SEEK. You’ll also receive practical advice from community members who use data and insights from Datadog to improve system performance, security, and reliability.

At Datadog Summit Denver, 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.

The Datadog team will be there to show off our latest product features and answer your questions so that you can get even more from the Datadog platform.

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 mere handful to hundreds or thousands of nodes.

Hands-on workshops

Datadog Summit will feature hands-on workshops covering infrastructure monitoring, distributed tracing, log management, and more—giving you real-world insights that allow you to understand how your systems are performing, and how to quickly find and resolve issues.

Datadog Summit workshops include:

  • Intro to Datadog - SRE: Our introductory training workshop will take you from Datadog novice to Datadog pro. We’ll show you the essential features of Datadog and how to get the most out of them. This course focuses on scenarios most relevant to SREs.
  • Using Log Management with Metrics and Traces to Improve Developer Productivity: Become an expert in building observability with log data. This workshop will walk you through best practices for log collection, processing, and retention. We’ll then dive into scenarios that will help you analyze data from multiple sources by using Log Management’s powerful search and analytics capabilities.
  • Delivering High Quality Software with APM and Distributed Tracing: In this workshop, you will instrument an application with Datadog APM. You’ll then identify the source of performance issues within Datadog. Once you’ve discovered these issues, you’ll release a new version of the application, and ensure the application performance improves.
  • Measuring Core Web Vitals in Production: Core Web Vitals (CWVs) have become the standard measurement of UX quality and search engine ranking across the web. CWVs are central to monitoring an application’s frontend performance in production, and they can also provide crucial insight into the user experience. This workshop will help you understand the fundamental set of CWVs, monitor standard CWVs for a web application, mitigate issues that create poor CWV scores, and set up automated alerts to notify your team if a CWV score falls below an acceptable threshold.
Get hands-on training from Datadog engineers in workshops.
Get hands-on training from Datadog engineers in workshops.
Get hands-on training from Datadog engineers in workshops.

See you in Sydney

Datadog Summit will be held at the Four Seasons Sydney. Although the Summit is a free event, space is limited, so RSVP now to reserve your seat!