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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
Introducing this year’s new Datadog Ambassadors
2025-05-13 · via Datadog | The Monitor blog
Arielle Mella

Arielle Mella

Datadog Ambassadors share their expertise through blog posts, conference talks, open source contributions, and community leadership, helping developers around the world understand observability, DevOps, security, and more. From leading community events to building custom integrations, our Ambassadors have been hard at work showcasing their Datadog chops.

What we’ve been up to

Over the past year, our Ambassador community has continued to grow—not only in size, but also in impact. From publishing technical blog posts to giving conference talks and growing local communities, our Ambassadors have been at the forefront of thought leadership in the observability space.

Whether it’s community organizing or sharing real-world experiences on cloud migrations and platform engineering, our Ambassadors continue to produce thoughtful, hands-on content. Some standout contributions from this year include:

Several Ambassadors have taken on leadership roles within their local communities, scaling User Groups into thriving hubs of learning and collaboration. From meetups to workshops, they’re helping foster strong regional ecosystems that support ongoing learning and connection.

  • Ichiro Kano has played a key role in growing the Datadog Japan User Group (JDDUG) into a vibrant community, regularly organizing in-person meetups and technical sessions that bring together engineers across Japan to share observability best practices.
  • Changhyeon Yoon has been instrumental in growing the Datadog Korea User Group (DDKruG), helping organize meetups that highlight real-world use cases, foster community-driven learning, and build a stronger network of Datadog users across Korea.

Meet the 2025 Datadog Ambassadors

This year, the Ambassador program is expanding with a new cohort of builders, security experts, educators, and community leaders—and we’re excited to welcome them to the community.

Kelly Bettendorf

Kelly Bettendorf

Kelly is a Staff Security Engineer at Stavvy, focused on building practical, scalable security programs. His expertise spans detection engineering, cloud security, SIEM, and security automation—driving initiatives like detection as code, incident response, and compliance enablement. At DASH 2024, he shared a “crawl, walk, run” framework for detection as code, helping teams bring structure and scale to their detection efforts. A passionate problem solver and active member of the Datadog Slack community, Kelly brings high energy and curiosity to everything he does—whether it’s architecting security solutions or diving into technical challenges in his home lab.

Rebecca Cottignies

Rebecca Cottignies

Rebecca is a Cybersecurity Engineer at AssessFirst, where she leads efforts in governance, SOC, Purple Team operations, and ISO 27001 compliance. She’s particularly committed to cybersecurity governance and awareness-raising, with the passion of making this complex field accessible to everyone on her Medium blog. As a member of CESIN, she’s also passionate about sharing knowledge and disseminating best practices, contributing to the development of the cybersecurity community in France.

Shogo Hasunuma

Shogo Hasunuma

Shogo Hasunuma is based in Japan and serves as the head of the Managed Service Provider (MSP) Section at iret, Inc. He joined the company in 2015 with no prior experience in IT engineering and has steadily built his career—from an entry-level monitoring operator to roles in infrastructure design and implementation—before being appointed as a team leader in 2019. Currently, he is committed to enhancing managed services by advancing incident response automation, adopting generative AI, and implementing comprehensive observability strategies centered around Datadog. He also supports end users in fostering autonomous DevOps practices by offering guidance on effective usage of Datadog.

YoungJin Jung

YoungJin Jung

YoungJin is a DevOps Engineer driving infrastructure modernization at LG UPlus. He specializes in solving complex challenges that emerge in enterprise-scale environments, focusing on building scalable, resilient systems through modern DevOps practices. With a strong emphasis on observability and performance tuning, he utilizes Datadog to instrument services, analyze performance metrics, and proactively improve system reliability and the overall user experience. He is an active AWS Community Builder, contributing to the growth of cloud-native practices within the community, and also serves as a HashiCorp Ambassador, advocating for infrastructure as code and automation across large-scale deployments. You can read more about his DevOps adventures on his blog.

Yubin Kim

Yubin Kim

Yubin is a site reliability engineer at Karrot, focused on building resilient, scalable systems that internal developers can trust. She’s passionate about improving reliability through comprehensive monitoring, thoughtful CI/CD design, and pragmatic incident management. Yubin is a dedicated community member, always eager to share and learn alongside fellow engineers. She regularly publishes a number of blog posts on her personal blog on Datadog, Kubernetes, and observability events in Korea.

Michael Levan

Michael Levan

Michael is a Kubernetes and platform engineering expert, author, consultant, and CNCF Ambassador. With a knack for turning complexity into clarity, he helps companies around the world level up their infrastructure—and regularly shares his expertise through blogs, books, courses, podcasts, and conference talks.

Jon Lindeheim

Jon Lindeheim

Jon is an Engineering Manager at Axis Communications, overseeing the core services team for Axis Cloud Connect. With a background in architecture and DevOps, he brings a strategic and technical lens to platform engineering. Jon has shared his insights at events like DASH 2024 and AWS Summits, covering topics like platform engineering, cloud transformation, and DevOps practices in real-world settings.

Logan Rohloff

Logan Rohloff

Logan is a cloud and observability lead at RapDev, a Datadog Premier Partner. With experience spanning cloud automation, network engineering, and system administration, Logan plays a key role in helping organizations implement and optimize their observability strategies in the most automated and scalable fashion possible. He’s deployed nearly every Datadog product and written more than a dozen custom integrations. Logan also contributed to an open source utility for managing secrets with the Datadog Agent, which was donated to Datadog in 2024. Check out more of his work on RapDev’s blog.

Nilton Kazuyuki Ueda

Nilton Kazuyuki Ueda

Nilton is a Senior Data Executive in Business Intelligence, Data Engineering, Machine Learning and Generative AI at Deloitte, with over a decade of experience in multinational and global companies, leading large-scale corporate strategic initiatives. A longtime advocate of knowledge sharing, he actively contributes to the Brazilian tech community through technical talks, blog posts, and open discussions on cloud-native best practices.

You can check out the full list of Datadog Ambassadors and read more about the program here.

Thank you, Ambassadors!

The Datadog Ambassadors program continues to grow as a vibrant community of technical leaders, content creators, and practitioners who are shaping how teams around the world think about observability, reliability, and performance. We’re excited to see how this year’s Ambassadors will continue to inspire others in the year ahead.

Want to be an Ambassador? Learn more about the program here.