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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
Datadog’s AWS re:Invent 2020 guide
Waldo Grunenwald · 2020-11-24 · via Datadog | The Monitor blog

In Q4 of every year since 2012, AWS has flooded the Las Vegas strip with thousands of AWS staff, partners, and customers for a week of keynote sessions, announcements, workshops, and more. In a year like no other, we’re gearing up for a re:Invent like no other!

As a long-time AWS partner, we look forward to re:Invent every year. We enjoy meeting you face to face, sharing the latest in monitoring and security, and learning a thing or two in the process. Although we won’t be meeting you in person, we’re bringing lots of interactive content your way.

With the move to a virtual format, re:Invent will be spread across three weeks instead of just one, and sessions will be rebroadcast to serve multiple time zones.

As with any other re:Invent, we have engaging activities for you:

  • Three completely different Datadog demos, in four languages (English, Korean, Japanese, and Spanish)

  • 1:1 sessions with Datadog Technical Solutions team members

  • Daily raffle for an Xbox Series X

  • Swag Passport Program to earn Datadog shirts, stickers, and socks

  • Free trial sign up sweepstakes for a 1-in-10 chance to win an iPhone 12 or a Google Pixel 5

Devops Scavenger Hunt

Throughout the day on Tuesday, December 8, we’ll be hosting a virtual scavenger hunt through the Datadog platform. Attendees will troubleshoot an outage scenario using Datadog in a sandbox environment. The three highest scores win a Nintendo Switch, and the top score also wins a TV! Register for this event through December 4.

AWS Hack Jams

New for 2020 are AWS Hack Jams. Attendees will have the opportunity to compete to solve hands-on real-world challenges in live AWS environments. Four events will be taking place:

  • Security Jam, session 1: December 2 | 8:00 a.m.–noon EST

  • Security Jam, session 2: December 2 | 3:00–7:00 p.m. PST

  • Devops Jam, session 1: December 9 | 8:00 a.m.–noon EST

  • Devops Jam, session 2: December 9 | 3:00–7:00 p.m. PST

The Magic of Incident Response with PagerDuty, Datadog, and Slack

Join PagerDuty, Datadog, and Slack on Monday, December 14 for an interactive virtual magic experience featuring America’s Got Talent winner and featured performer at the LINQ in Las Vegas, Mat Franco.

This family-friendly experience will give you the opportunity to ask Mat some of your burning questions, and possibly be included in one of the “on stage” demonstrations.

Details and RSVP available at https://meet.pagerduty.com/magic

Sessions we’re looking forward to

re:Invent is usually so stuffed with keynotes, announcements, and sessions that it can be a challenge to get to the sessions that you’re most interested in. The format changes will make it easier for you to manage your re:Invent calendar! Here are some of the sessions we’re looking forward to:

Building the next generation of residential robots

Tuesday, December 1 12:00–12:20 a.m. EST

Robots are being used more widely in homes, and they are becoming increasingly advanced and include capabilities like artificial intelligence, data streaming, image recognition, voice activation, and remote monitoring. In this session, see how AWS RoboMaker and AWS IoT enable the development and testing of sophisticated robots that can autonomously navigate, communicate, comprehend, and learn. iRobot also discusses how it is using AWS to build intelligent robots that fit seamlessly into your life at home.

Datadog’s take: The promise of automata helping in our daily lives has always been ambitious, but the delivery of real-use capabilities has been somewhat limited and slow to arrive. We’ve seen improvements in the smart-home space that have allowed for viable products that everyday consumers can use, but we’re still excited to see what mundanities can be removed in the coming years. I want “sudo make me a sandwich” to be a statement that results in a sandwich being made from ingredients in my kitchen without human intervention between my statement and having said sandwich within reach!

Paving the way toward automated driving with BMW Group

Tuesday, December 8 4:00–4:30 p.m. EST

In this session, explore the AWS autonomous driving data lake reference architecture to learn how organizations manage the challenge of ingesting, transforming, labeling, and cataloging massive amounts of data to develop automated driving systems using Amazon EMR, Amazon S3, Amazon SageMaker Ground Truth, and more. See how BMW Group collects 1 billion+ km of anonymized perception data from its worldwide connected fleet of customer vehicles to develop safe and performant automated driving systems. This session explains the purpose of and approach to the data collection and discusses examples from analyzing this valuable dataset.

Datadog’s take: The act of entering an automobile and traveling among other vehicles is one of the most dangerous activities that most people engage in, and it’s the people themselves that are the most faulty component. There are a lot of philosophical arguments about behavior in extreme cases (like variants of the Trolley Problem), but humans are bad at the mundane parts. I look forward to the day when I can actively drive my car as an indulgence, rather than the norm.

Deep dive into AWS Lambda security: Function isolation

Thursday, December 17 3:45–4:15 p.m. EST

This session dives into the security model behind AWS Lambda functions, looking at how you can isolate workloads, build multiple layers of protection, and leverage fine-grained authorization. You learn about the implementation, the open-source Firecracker technology that provides one of the most important layers, and what this means for how you build on Lambda. You also learn about SaaS, customization, and safe patterns for running your own customer’s code in your Lambda functions.

Datadog’s take: While we use a lot of Lambda, security is an aspect that is too easy to overlook, and it’s vitally important to keep up on the latest security recommendations.

Testing resiliency using chaos engineering

Thursday, December 17 1:30–2:00 p.m. EST

In this session, you learn how to use chaos engineering to set up failure injection testing to validate the resiliency of your service. Referencing the AWS Well-Architected Framework, you learn about the design principles and AWS resources that help ensure a resilient architecture. Then, with a three-tier architecture, this session demonstrates how to implement automation to simulate various failures, from the loss of a single Amazon EC2 server to the loss of an entire Availability Zone. The session focuses on the impacts of these failures and the resources that AWS provides to maintain high service availability and short time to recovery.

Datadog’s take: Chaos engineering improves your resiliency, which directly affects your SLOs and can therefore be a powerful tool in the SRE arsenal. This session also introduces the Well-Architected Framework from AWS, which will help you deliver secure, performant products for the cloud. The combination of architecture, performance, and experimentation should be a great intro to the practice of chaos engineering.

Wednesday, December 18 6:00–6:30 a.m. PST

Adrian Cockcroft has a long history of being at the leading edge of industry trends, such as cloud computing, Devops, microservices, and chaos engineering. In this session, he highlights patterns that are emerging with some of the most advanced AWS customers, including serverless first, continuously tested resilience, and Wardley mapping for technology transitions. He covers an old topic that’s been emerging for a long time— architectures that take advantage of extremely large memory systems—and a new topic about optimizing architectures around sustainability concerns.

Datadog’s take: If there’s one session you should absolutely not miss, my money is on this one with Adrian Cockcroft. Adrian’s long been a voice in the cloud-native space and this talk is sure to open some eyes and some minds, and offer a great outlook of what’s to come next year.

Datadog is also delivering a session with one of our customers! Live at 3:15 p.m. EST on December 3, Dunelm’s Tom Hayman and our own Kirk Kaiser will present “Serverless Everything: Replatforming for Speed and Ownership at Dunelm.” Tom and Kirk will tell the story of how Dunelm drastically improved their deployment velocity and saw an average speed improvement of 472 percent across their entire platform! You’ll hear how they’ve decided to organize teams around core business domains, and see how observability is a core component of moving fast with Serverless.

These are just a handful of the sessions that we’re looking forward to. Take a look at the full schedule; I’m sure that there’s plenty for you to sink your teeth into!