Datadog

For Arlei Roberto Francioli Junior, Executive Manager of Technology at Elo, reliability isn't just an engineering goal—it's a business imperative. As Elo continues to modernize its technology platform, the team has built a more proactive approach to operating its payment services. With real-time visibility across applications, infrastructure, and transactions, Command Center Elo can identify emerging issues early, collaborate faster, and help prevent disruptions before they reach cardholders. That shift has led to a 70% reduction in mean time to resolution, while improving platform availability and reducing operational costs through smarter infrastructure management. For a company where every second matters, observability has become the foundation for delivering the speed, resilience, and trust customers expect. See what other customers are doing to lead change with Datadog: https://lnkd.in/ewaZj6hY

Building enterprise AI requires more than powerful models—it requires the confidence to operate them in production. That's what Kenta Ishida, Site Reliability Engineer at LayerX, is helping his team achieve with AI Workforce, LayerX's enterprise AI platform. By bringing application performance and AI workflow visibility together, LayerX has transformed how teams investigate, validate, and release AI features. Engineers, QA, and SREs now work from a shared view of every AI workflow, making it easier to understand what happened, respond to customer issues, and safely roll out new capabilities. One of the biggest improvements has been in troubleshooting. LayerX has reduced LLM provider triage time by approximately 95%, turning investigations that once took hours into work that can often be completed in minutes. For LayerX, observability isn't just about monitoring systems—it's about giving enterprise customers the reliability, transparency, and trust they expect from AI. Check out what other customers are doing to lead change with Datadog: https://lnkd.in/ewaZj6hY

We’ve got a jam-packed schedule at #DatadogSummit San Francisco! ✨ Scott Gonyea: AI-Trace, Figma's internal debugging assistant, built on Datadog's MCP server plus Figma's own repos and engineering conventions ✨ Cansu Berkem: An end-to-end incident response workflow that combines people, automation, and AI to cut MTTR and kill repetitive follow-up ✨ Nick Isaacs: Decomposing Datadog's monolith with Claude, GPT-5, and LangGraph, plus tips for more reliable, accurate code ✨ Ala Shiban: AI writes code 10x faster, so why aren't we shipping 10x faster? What an agentic harness looks like when the SDLC is the harness Join us: https://bit.ly/4i80KSi

When PUBG Corporation: Battlegrounds has an incident, millions of players feel it. Krafton PUBG Studio's SRE team knew that and decided their patchwork of manual workflows and disconnected tools wasn't good enough. So they did something ambitious: they designed a formal five-stage incident response process from scratch and built it entirely on Datadog. ✅ The outcome speaks for itself: MTTD down to 3.89 minutes, false positives eliminated, and AI-generated postmortems that turn every incident into a learning opportunity. See how they did it: https://lnkd.in/eXpe-9bU

The next episode of This Month in Datadog is about to drop 👀 Datadog’s Omar Nema gives us a sneak peek at what's coming — including a closer look at how Automated Dashboard Investigation helps you make sense of your metrics.

Meet the people behind Datadog Tokyo – a team building together in one of the most exciting markets in the world. We're hiring across Commercial and Enterprise Sales, Customer Success, Technical Support, Sales Engineering, and more. ようこそ、Datadog Tokyoへ！ 東京駅に隣接するJPタワー内にあるDatadogの東京オフィスからは、皇居や東京の街並みを一望できます。 セールス、マーケティング、テクニカルサポート、セールスエンジニアリングなど、さまざまなチームが集まり、世界各地のチームと協力しながら働いています。 Join the pack: 🔗 https://bit.ly/4xLP2RV #DatadogLife

Not all risks are created equal, and treating them that way means missing the ones that matter most. Datadog's Risk Engineering team built a Systemic Risk Detection Pipeline and a set of Risk AI Agents that go beyond individual finding severity to understand how vulnerabilities, misconfigurations, and identity risks interact — surfacing "risk paths" that show how small exposures can combine into major organizational impact. Read how we're rethinking risk prioritization internally here at Datadog: https://bit.ly/4qG1LDE

2x throughput. 50% lower infrastructure costs. ✅ Go behind the scenes with Ben Gotthold, Mary Pat Gravely and the team at AssemblyAI to see how they use Datadog to operate Voice AI across thousands of GPUs — improving performance, resolving incidents faster, and continuing to ship new models at speed. Watch the full video → https://lnkd.in/eQcVPTyW Read the full case study → https://lnkd.in/eygn2_sA

9+ TB of daily logs. Migrated in just 6 weeks. 🤯 See how Michael Pearce and the team at Contentful moved their logs to Datadog, expanded self-service access from 200 to 500+ users, and accelerated troubleshooting with Flex Logs— all while unifying logs with the rest of their observability data. Read the full story: https://bit.ly/3Smp4pe

Datadog has been named a Leader in the June 2026 Gartner Magic Quadrant™ for Observability Platforms for the sixth year in a row! To us, that’s six years of commitment to solving customer challenges and providing unified observability and security. 💜 Read more: https://bit.ly/4zuFWe7