공시 • May 28
Datadog Achieves FedRAMP High Certification For Its Observability And Security Platform Datadog for Government has achieved Federal Risk and Authorization Management Program (FedRAMP) High certification for its observability and security platform. Datadog’s AI-powered end-to-end observability and security platform delivers real-time visibility and actionable insights across agencies’ entire IT environments while complying with Federal Government’s most stringent security requirements. The platform enables agencies to strengthen their security posture by identifying and managing risk within a single, unified solution designed for high-impact systems. With comprehensive dashboards and intelligent alerts, Government teams can proactively detect and resolve issues before they disrupt mission-critical operations or impact citizen services. Carahsoft serves as Datadog’s Master Government Aggregator, providing ease of procurement for the company’s platform and solutions and access to services and training for the Public Sector through hundreds of contract vehicles. Datadog’s solutions are available through Carahsoft’s GSA Schedule No. 47QSWA18D008F, NASPO ValuePoint Master Agreement #AR2472, TIPS Contract #220105, OMNIA Partners Contract #R240303 and E&I Contract #EI00063~2021MA. 공시 • May 10
Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year 2026 Datadog, Inc. provided earnings guidance for the second quarter and full year 2026. For the second quarter. the company expects Revenue between $1.07 billion and $1.08 billion.
For the full year, the company expects revenue between $4.30 billion and $4.34 billion. 공시 • May 02
Datadog, Inc., Annual General Meeting, Jun 15, 2026 Datadog, Inc., Annual General Meeting, Jun 15, 2026. 공시 • Apr 24
Datadog Announces GPU Monitoring to Help Businesses Optimize Spend and Performance as They Aim to Scale AI Projects Datadog, Inc. announced that GPU Monitoring is available to customers everywhere. The new product addresses one of the most prevalent issues facing organizations as they look for a scalable and effective way to manage expanding AI costs. The launch of GPU Monitoring marks one of the first times a single solution provides unified visibility across the AI stack—giving customers a single view linking GPU fleet health, cost, and performance directly to the teams relying on them for faster troubleshooting of slow workloads and cost savings. Most GPU tools provide high-level device health metrics, but they don’t surface cross-functional resource contention issues, explain why training and inference workloads fail, or provide visibility into which devices are idle or ineffectively used. This lack of visibility slows down investigations and means that teams overprovision as the safest default—leading to wasted spend. GPU Monitoring streamlines this work by linking fleet telemetry directly to the workloads consuming those resources, and gives platform engineering and machine learning teams a shared view to investigate together, enabling them to: Scale AI without overspending: With visibility and forecasting based on the usage patterns of fleets and direct guidance on whether to buy new GPUs or free up existing ones, platform teams avoid expensive purchases and long procurement cycles, machine learning teams get capacity faster, and leadership gets better ROI with predictable spend. Accelerate AI delivery: Stalled workloads are correlated directly to the underlying GPUs, pods and processes running them so that teams can troubleshoot performance bottlenecks in minutes instead of hours, allowing engineers to focus on shipping AI projects. Avoid costly disruptions: Unhealthy GPUs are proactively identified before failures cascade across a cluster and cause training and inference delays. Maximize ROI on GPU spend: Teams are empowered and accountable for their GPU utilization and costs, and can easily pinpoint where they are overserving or underutilizing their GPUs. This allows teams to reclaim and reallocate resources in order to reduce wasted spend. GPU Monitoring is now generally available. 공시 • Apr 17
Datadog, Inc. to Report Q1, 2026 Results on May 07, 2026 Datadog, Inc. announced that they will report Q1, 2026 results Pre-Market on May 07, 2026 공시 • Apr 03
Datadog Inc. Announces Datadog Experiments Availability Datadog, Inc. announced that Datadog Experiments is available to customers everywhere. The new product enables teams to design, launch, and measure product experiments and A/B tests directly within the Datadog platform—giving teams the data and insights they need to understand how every change affects user behavior, application performance and business outcomes. Datadog solves this problem with the first experimentation platform that combines business metrics from a customer’s data warehouse with product analytics events and application observability. Powered by Datadog’s acquisition of Eppo, Datadog Experiments pairs best-in-class statistical methods with real-time observability guardrails so companies can test what matters, move quickly and ship with confidence. The product empowers every product manager, designer and engineer at a company to take a measured approach to change. Datadog Experiments enables teams to accelerate decisions without the overhead: Experimentation is self-serve and standardized, so teams can move from insight to decision without coordination overhead. Run safer, higher-quality experiments: Built-in guardrails, real-time feedback and shared standards help teams catch issues early, protect users and keep experiments valid. Make decisions leaders trust: Results are credible, reproducible and comparable by measuring impact directly against source-of-truth business metrics in native data warehouses, using consistent methodologies teams can audit and trust. By tying experiments to Real User Monitoring (RUM), Product Analytics, APM and logs, organizations can measure both business impact and performance implications to reduce risk without slowing innovation. Datadog Experiments is now generally available. 공시 • Mar 25
Datadog, Inc. Announces Availability of Bits AI Security Analyst Datadog, Inc. announced that Bits AI Security Analyst is available to customers everywhere. As part of Datadog’s Cloud SIEM, the AI agent reduces investigations that can take analysts hours down to as little as 30 seconds. Bits AI Security Analyst solves these issues by pairing the expertise of a senior SOC analyst with machine scale and speed, enabling investigation analysis across a breadth and volume of data sources that would be unachievable by a human, while still delivering high-accuracy verdicts backed by real-world context. This allows analysts to scale their investigation expertise so they can focus more time on high-impact defense priorities. When using other SIEMs, it can take teams hours to acknowledge alerts, run investigations, gather evidence, analyze results and escalate if needed. With Bits AI Security Analyst, teams using Datadog Cloud SIEM can autonomously complete all those steps in minutes, reducing the mean-time-to-resolution by more than 90%. Bits AI Security Analyst helps security teams: Detect and resolve issues faster: Autonomous investigations reduce alert fatigue, mean-time-to-detection and mean-time-to-resolution, all of which are critical to responding to attacks happening at machine speed. Gain comprehensive coverage: With a unified view of the entire attack surface across clouds, identities, EDRs and more—along with built-in observability telemetry—teams can identify and resolve critical threats and attacks. Scale at enterprise-grade speed: Native to Cloud SIEM, SOC teams can scale their use of AI by deploying faster with thousands of integrations, a unified user experience, and security controls like RBAC, giving teams enterprise-grade visibility, security and control. Bits AI Security Analyst is now generally available. 공시 • Mar 10
Datadog, Inc. Launches MCP Server For AI Agents With Secure, Real-Time Access To Unified Observability Data Datadog, Inc. announced that its MCP Server is generally available. For developers embedding AI agents into development and operational workflows, the Datadog MCP Server provides access to live observability data—so teams can debug in their preferred choice of AI coding agents or Integrated Development Environment with real-time telemetry and take action within established security and governance controls. As embedding AI agents into workflows becomes standard practice at companies across all industries, engineering teams are being tasked with operationalizing AI agents and navigating the intense complexity of this process. To do this, they need secure, governed access to production data, reduced integration overhead and compatibility with compliance requirements. Datadog MCP Server is a purpose-built interface designed for agentic systems, extending Datadog’s unified observability platform directly into AI workflows so that engineering teams can: Debug and act quickly without context switching: Feeds live logs, metrics and traces directly into AI coding agents like Claude Code, Cursor, Codex, Github Copilot, Cognition and Visual Studio Code when investigating production issues. Give custom AI agents direct access to real-time observability and intelligence: Empowers agents to leverage Datadog’s proactive detection and remediation signals so they can investigate and respond to issues automatically. Simplify data access for AI workflows: Reduces the risk of breaking changes by providing a dynamic, purpose-built protocol for agent communication. Datadog MCP Server is now generally available. 공시 • Mar 03
Datadog, Inc. Appoints Dominic Phillips to its Board of Directors Datadog, Inc. announced the appointment of Dominic Phillips to its Board of Directors. Dominic brings more than two decades of financial leadership in the technology space to Datadog. As EVP and Chief Financial Officer at Samsara, he leads the company's global financial operations, including strategic finance, accounting, procurement, tax, treasury, corporate development, investor relations, IT, and security. Prior to Samsara, Dominic served as Vice President of Finance and Head of Corporate Development at ServiceNow, where he led FP&A, investor relations, treasury, and corporate development, supporting the company’s significant growth. Earlier in his career, Dominic was a Vice President in Morgan Stanley’s technology investment banking group, advising technology companies on complex financings and strategic transactions. Dominic holds a BS in Business from Cal Poly, San Luis Obispo, and an MBA from UC Berkeley. 공시 • Mar 02
Datadog, Inc., Annual General Meeting, Apr 21, 2026 Datadog, Inc., Annual General Meeting, Apr 21, 2026. 공시 • Feb 10
Datadog, Inc. Provides Earnings Guidance for the First Quarter and Fiscal Year 2026 Datadog, Inc. provided earnings guidance for the First quarter and Fiscal year 2026. For the quarter, the company expects revenue between $951 million and $961 million.
For the year, the company expects revenue between $4.06 billion and $4.10 billion. 
