Datadog（DDOG19）株式概要Datadog, Inc.は、クラウド・アプリケーション向けの観測可能性とセキュリティのプラットフォームを米国内外で運営している。 詳細DDOG19 ファンダメンタル分析スノーフレーク・スコア評価1/6将来の成長4/6過去の実績2/6財務の健全性5/6配当金0/6報酬当社が推定した公正価値より4.2%で取引されている 収益は年間31.83%増加すると予測されています リスク分析TH市場と比較して、過去 3 か月間の株価の変動が非常に大きい利益率(3.7%)は昨年より低い(5.8%) すべてのリスクチェックを見るDDOG19 Community Fair Values Create NarrativeSee what others think this stock is worth. Follow their fair value or set your own to get alerts.Your Fair Value฿Current Price฿7.5099.9% 割安 内在価値ディスカウントGrowth estimate overAnnual revenue growth rate5 Yearstime period%/yrDecreaseIncreasePastFuture-84m8b2016201920222025202620282031Revenue US$8.1bEarnings US$301.0mAdvancedSet Fair ValueView all narrativesDatadog, Inc. 競合他社SynopsysSymbol: NasdaqGS:SNPSMarket cap: US$88.2bIntuitSymbol: NasdaqGS:INTUMarket cap: US$77.7bCadence Design SystemsSymbol: NasdaqGS:CDNSMarket cap: US$106.2bAdobeSymbol: NasdaqGS:ADBEMarket cap: US$94.3b価格と性能株価の高値、安値、推移の概要Datadog過去の株価現在の株価US$7.5052週高値US$9.0552週安値US$3.08ベータ1.551ヶ月の変化16.28%3ヶ月変化82.93%1年変化n/a3年間の変化n/a5年間の変化n/aIPOからの変化106.04%最新ニュースお知らせ • May 28Datadog Achieves FedRAMP High Certification For Its Observability And Security PlatformDatadog 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.お知らせ • May 10Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year 2026Datadog, 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.お知らせ • May 02Datadog, Inc., Annual General Meeting, Jun 15, 2026Datadog, Inc., Annual General Meeting, Jun 15, 2026.お知らせ • Apr 24Datadog Announces GPU Monitoring to Help Businesses Optimize Spend and Performance as They Aim to Scale AI ProjectsDatadog, 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.お知らせ • Apr 17Datadog, Inc. to Report Q1, 2026 Results on May 07, 2026Datadog, Inc. announced that they will report Q1, 2026 results Pre-Market on May 07, 2026お知らせ • Apr 03Datadog Inc. Announces Datadog Experiments AvailabilityDatadog, 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.最新情報をもっと見るRecent updatesお知らせ • May 28Datadog Achieves FedRAMP High Certification For Its Observability And Security PlatformDatadog 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.お知らせ • May 10Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year 2026Datadog, 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.お知らせ • May 02Datadog, Inc., Annual General Meeting, Jun 15, 2026Datadog, Inc., Annual General Meeting, Jun 15, 2026.お知らせ • Apr 24Datadog Announces GPU Monitoring to Help Businesses Optimize Spend and Performance as They Aim to Scale AI ProjectsDatadog, 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.お知らせ • Apr 17Datadog, Inc. to Report Q1, 2026 Results on May 07, 2026Datadog, Inc. announced that they will report Q1, 2026 results Pre-Market on May 07, 2026お知らせ • Apr 03Datadog Inc. Announces Datadog Experiments AvailabilityDatadog, 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.お知らせ • Mar 25Datadog, Inc. Announces Availability of Bits AI Security AnalystDatadog, 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.お知らせ • Mar 10Datadog, Inc. Launches MCP Server For AI Agents With Secure, Real-Time Access To Unified Observability DataDatadog, 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.お知らせ • Mar 03Datadog, Inc. Appoints Dominic Phillips to its Board of DirectorsDatadog, 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.お知らせ • Mar 02Datadog, Inc., Annual General Meeting, Apr 21, 2026Datadog, Inc., Annual General Meeting, Apr 21, 2026.お知らせ • Feb 10Datadog, Inc. Provides Earnings Guidance for the First Quarter and Fiscal Year 2026Datadog, 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.株主還元DDOG19TH SoftwareTH 市場7D-8.5%-7.5%-1.4%1Yn/a-17.1%40.4%株主還元を見る業界別リターン: DDOG19がTH Software業界に対してどのようなパフォーマンスを示したかを判断するにはデータが不十分です。リターン対市場: DDOG19 TH市場に対してどのようなパフォーマンスを示したかを判断するにはデータが不十分です。価格変動Is DDOG19's price volatile compared to industry and market?DDOG19 volatilityDDOG19 Average Weekly Movement14.0%Software Industry Average Movement7.3%Market Average Movement4.3%10% most volatile stocks in TH Market10.4%10% least volatile stocks in TH Market2.1%安定した株価: DDOG19の株価は、 TH市場と比較して過去 3 か月間で変動しています。時間の経過による変動: 過去 1 年間のDDOG19のボラティリティの変化を判断するには データが不十分です。会社概要設立従業員CEO（最高経営責任者ウェブサイト20108,100Olivier Pomelwww.datadoghq.comDatadog, Inc.は、クラウドアプリケーション向けの観測性とセキュリティのプラットフォームを米国内外で運営している。同社の製品は、インフラストラクチャおよびアプリケーション・パフォーマンス・モニタリング、ログ管理、デジタル・エクスペリエンス・モニタリング、継続的プロファイラ、データベース・モニタリング、データ観測可能性、ユニバーサル・サービス・モニタリング、ネットワーク・モニタリング、エラー追跡、インシデント管理、ワークフロー自動化、観測可能性パイプライン、クラウド・コストおよびクラウド・セキュリティ管理、アプリケーション・セキュリティ管理、クラウドSIEM、機密データ・スキャナ、イベント管理、CIおよびLLMの可視化で構成されている。Datadog, Inc.は2010年に法人化され、ニューヨーク州ニューヨークに本社を置いている。もっと見るDatadog, Inc. 基礎のまとめDatadog の収益と売上を時価総額と比較するとどうか。DDOG19 基礎統計学時価総額฿2.67t収益（TTM）฿4.47b売上高(TTM)฿120.99b597.2xPER（株価収益率22.1xP/SレシオDDOG19 は割高か？公正価値と評価分析を参照収益と収入最新の決算報告書（TTM）に基づく主な収益性統計DDOG19 損益計算書（TTM）収益US$3.67b売上原価US$737.86m売上総利益US$2.93bその他の費用US$2.80b収益US$135.67m直近の収益報告Mar 31, 2026次回決算日該当なし一株当たり利益（EPS）0.38グロス・マージン79.91%純利益率3.69%有利子負債／自己資本比率24.7%DDOG19 の長期的なパフォーマンスは？過去の実績と比較を見るView Valuation企業分析と財務データの現状データ最終更新日（UTC時間）企業分析2026/06/11 02:55終値2026/06/11 00:00収益2026/03/31年間収益2025/12/31データソース企業分析に使用したデータはS&P Global Market Intelligence LLC のものです。本レポートを作成するための分析モデルでは、以下のデータを使用しています。データは正規化されているため、ソースが利用可能になるまでに時間がかかる場合があります。パッケージデータタイムフレーム米国ソース例会社財務10年損益計算書キャッシュ・フロー計算書貸借対照表SECフォーム10-KSECフォーム10-Qアナリストのコンセンサス予想+プラス3年予想財務アナリストの目標株価アナリストリサーチレポートBlue Matrix市場価格30年株価配当、分割、措置ICEマーケットデータSECフォームS-1所有権10年トップ株主インサイダー取引SECフォーム4SECフォーム13Dマネジメント10年リーダーシップ・チーム取締役会SECフォーム10-KSECフォームDEF 14A主な進展10年会社からのお知らせSECフォーム8-K* 米国証券を対象とした例であり、非米国証券については、同等の規制書式および情報源を使用。特に断りのない限り、すべての財務データは1年ごとの期間に基づいていますが、四半期ごとに更新されます。これは、TTM（Trailing Twelve Month）またはLTM（Last Twelve Month）データとして知られています。詳細はこちら。分析モデルとスノーフレーク本レポートを生成するために使用した分析モデルの詳細は当社のGithubページでご覧いただけます。また、レポートの使用方法に関するガイドやYoutubeのチュートリアルも掲載しています。シンプリー・ウォールストリート分析モデルを設計・構築した世界トップクラスのチームについてご紹介します。業界およびセクターの指標私たちの業界とセクションの指標は、Simply Wall Stによって6時間ごとに計算されます。アナリスト筋Datadog, Inc. 45 これらのアナリストのうち、弊社レポートのインプットとして使用した売上高または利益の予想を提出したのは、 。アナリストの投稿は一日中更新されます。58 アナリスト機関Adam ShepherdArete Research Services LLPWilliam PowerBairdRaimo LenschowBarclays55 その他のアナリストを表示
お知らせ • May 28Datadog Achieves FedRAMP High Certification For Its Observability And Security PlatformDatadog 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.
お知らせ • May 10Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year 2026Datadog, 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.
お知らせ • May 02Datadog, Inc., Annual General Meeting, Jun 15, 2026Datadog, Inc., Annual General Meeting, Jun 15, 2026.
お知らせ • Apr 24Datadog Announces GPU Monitoring to Help Businesses Optimize Spend and Performance as They Aim to Scale AI ProjectsDatadog, 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.
お知らせ • Apr 17Datadog, Inc. to Report Q1, 2026 Results on May 07, 2026Datadog, Inc. announced that they will report Q1, 2026 results Pre-Market on May 07, 2026
お知らせ • Apr 03Datadog Inc. Announces Datadog Experiments AvailabilityDatadog, 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.
お知らせ • May 28Datadog Achieves FedRAMP High Certification For Its Observability And Security PlatformDatadog 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.
お知らせ • May 10Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year 2026Datadog, 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.
お知らせ • May 02Datadog, Inc., Annual General Meeting, Jun 15, 2026Datadog, Inc., Annual General Meeting, Jun 15, 2026.
お知らせ • Apr 24Datadog Announces GPU Monitoring to Help Businesses Optimize Spend and Performance as They Aim to Scale AI ProjectsDatadog, 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.
お知らせ • Apr 17Datadog, Inc. to Report Q1, 2026 Results on May 07, 2026Datadog, Inc. announced that they will report Q1, 2026 results Pre-Market on May 07, 2026
お知らせ • Apr 03Datadog Inc. Announces Datadog Experiments AvailabilityDatadog, 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.
お知らせ • Mar 25Datadog, Inc. Announces Availability of Bits AI Security AnalystDatadog, 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.
お知らせ • Mar 10Datadog, Inc. Launches MCP Server For AI Agents With Secure, Real-Time Access To Unified Observability DataDatadog, 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.
お知らせ • Mar 03Datadog, Inc. Appoints Dominic Phillips to its Board of DirectorsDatadog, 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.
お知らせ • Mar 02Datadog, Inc., Annual General Meeting, Apr 21, 2026Datadog, Inc., Annual General Meeting, Apr 21, 2026.
お知らせ • Feb 10Datadog, Inc. Provides Earnings Guidance for the First Quarter and Fiscal Year 2026Datadog, 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.
