New York, New York--(Newsfile Corp. - July 9, 2025) -  Datadog, Inc. (NASDAQ: DDOG), the monitoring and security platform for cloud applications, announced its inclusion on the S&P 500 Index, effective prior to the opening of trading today. The S&P 500 is widely regarded as the best single gauge of large-cap U.S. equities, tracking the stock performance of 500 leading US companies. Datadog's addition comes as it continues to innovate across its product portfolio in AI, observability, security, log manageme ...

作 者 | APAC Investment News 编译 | 华尔街大事件 Datadog（ NASDAQ： DDOG ）于6月举办了 DASH 2025 活动，重点介绍了其用于监控和保 护AI工作负载的技术 。分析师相信该公司将继续在AI能力方面进行投资，并重申"强力买入"评 级，其合理价值为每股145美元。 在 DASH 2025 大会上， Datadog 展示了其面向基础设施监控平台的全新 AI 功能，重点关注 AI 工作负载的观察、分析、响应和自动化。如下图所示，得益于与 OpenAI、Anthropic 和 ServiceNow 等主要 AI 和应用程序提供商的合作，Datadog 平台能够为所有 AI 代理提供全面 的可观察性。这些可观察性功能可使企业客户通过集中式界面监控其 AI 训练和相关的 AI 工作负 载。 此外，Datadog 平台还可以为 AI 基础设施提供 GPU 优化和故障排除功能。借助其 GPU 监控功 能，客户可以实时了解其 AI 集群的部署和性能。 6月10日， Datadog 发布了 其AI代理，这些代理可以进行事件响应、产品开发和安全方面的训 练。这些AI代理涵盖全天候 ...

Core Insights - Datadog has introduced new capabilities for monitoring agentic AI, including AI Agent Monitoring, LLM Experiments, and AI Agents Console, aimed at providing organizations with end-to-end visibility and governance over AI investments [1][4][8] Industry Context - The rise of generative AI and autonomous agents is changing software development, but many organizations struggle with visibility into AI system behaviors and their business value [2][3] - A study indicates that only 25% of AI initiatives are currently delivering promised ROI, highlighting the need for better accountability in AI investments [4] Company Developments - Datadog's new observability features allow companies to monitor agentic systems, run structured experiments, and evaluate usage patterns, facilitating quicker and safer deployment of LLM applications [3][4] - The AI Agent Monitoring tool provides an interactive graph mapping each agent's decision path, enabling engineers to identify issues like latency spikes and incorrect tool calls [4][6] - LLM Experiments enable testing of prompt changes and model swaps against real production data, allowing users to quantify improvements in response accuracy and throughput [6][7] - The AI Agents Console helps organizations maintain visibility into both in-house and third-party agent behaviors, measuring usage, impact, and compliance risks [7]

Core Insights - Datadog has expanded its AI security capabilities to address critical security risks in AI environments, enhancing protection from development to production [1][2][3] AI Security Landscape - The rise of AI has created new security challenges, necessitating a reevaluation of existing threat models due to the autonomous nature of AI workloads [2] - AI-native applications are more vulnerable to security risks, including prompt and code injection, due to their non-deterministic behavior [3] Securing AI Development - Datadog Code Security is now generally available, enabling teams to detect and prioritize vulnerabilities in custom code and open-source libraries, utilizing AI for remediation [5] - The integration with developer tools like IDEs and GitHub allows for seamless vulnerability remediation without disrupting development processes [5] Hardening AI Application Security - Organizations need stronger security controls for AI applications, including separation of privileges and data classification, to mitigate new types of attacks [6] - Datadog LLM Observability monitors AI model integrity and performs toxicity checks to identify harmful behaviors [7] Runtime Security Measures - The complexity of AI applications complicates the task of security analysts in identifying and responding to threats [9] - The Bits AI Security Analyst, integrated into Datadog Cloud SIEM, autonomously triages security signals and provides actionable recommendations [10] Continuous Monitoring and Protection - Datadog's Workload Protection continuously monitors interactions between LLMs and their host environments, with new isolation capabilities to block exploitation of vulnerabilities [11] - The Sensitive Data Scanner helps prevent sensitive data leaks during AI model training and inference [8] Recent Announcements - New security capabilities were announced during the DASH conference, including Code Security, Cloud Security tools, and enhancements in LLM Observability [12]

Summary of Datadog Conference Call Company Overview - **Company**: Datadog - **Industry**: Enterprise Software, specifically in observability and security for cloud environments - **CEO**: Olivier Pomel Key Points Industry Position and Growth - Datadog is one of only four enterprise software companies with over $3 billion in revenue and mid-20% growth, alongside Palantir, CrowdStrike, and Snowflake [3][4] - The company serves over 30,000 customers, primarily engineering teams, helping them manage application performance and security [7][4] Core Trends Driving Growth - Major trends fueling Datadog's growth include digital transformation, cloud migration, and AI transformation [4][11] - The complexity of modern systems is increasing, leading to a demand for observability solutions [5][6] Market Dynamics - Cloud migration remains strong, with expectations for long-term growth despite short-term fluctuations [10][11] - Datadog has only penetrated 45% of the Fortune 500, indicating significant growth potential [18][19] Customer Behavior and Spending - Customers are increasingly investing in cloud solutions as part of their IT budgets, viewing it as transformative rather than a cost [19][24] - Datadog's sales capacity has increased, leading to a notable rise in bookings and backlog growth, with an acceleration of 30% in CRPO [17][18] AI Integration - AI natives now account for 8.5% of Datadog's Annual Recurring Revenue (ARR) [29] - The company is positioned to benefit from the growth of AI applications, particularly in the inferencing stage rather than model training [33][34] Competitive Landscape - There is a growing trend among companies in the EU and Canada to seek local cloud providers, but Datadog sees limited immediate impact due to the lack of viable alternatives [12][13] - The AI landscape is evolving, with more companies able to innovate without massive investments, leading to a more diverse ecosystem [61][62] Future Outlook - Datadog anticipates that the trends seen in AI natives will eventually influence larger enterprises, similar to the past with cloud migration [49][52] - The company is committed to investing in engineering and sales capacity, maintaining a focus on organic growth and innovation [64][66] Observability and AI Models - Datadog offers LLM observability to help companies monitor AI models, ensuring they are functioning correctly and providing business value [42][43] - The company sees a significant opportunity in understanding how AI applications behave in production environments [55] Investment Strategy - Datadog has increased headcount by 25% to support growth, focusing on engineering and market coverage [64] - The company maintains a disciplined approach to pricing and product development, ensuring transparency and customer feedback drives innovation [66][67] Additional Insights - Datadog's growth is insulated from broader economic pressures, as its services are part of transformational investments rather than operational costs [25][28] - The company is leveraging AI to improve its own operations, enhancing coding efficiency and support processes [56][58] This summary encapsulates the key insights from the Datadog conference call, highlighting the company's strategic positioning, growth drivers, and future outlook in the enterprise software industry.

Core Viewpoint - Datadog is experiencing a frustrating stock performance despite strong growth momentum in the cloud-computing sector, particularly in observability and monitoring solutions driven by AI demand [1][2]. Group 1: AI-Powered Growth Opportunity - Datadog serves as a central data hub, providing real-time visibility across technology stacks, integrating data from over 900 software applications to enhance efficiency [4]. - The rise of data-intensive AI workflows is a significant growth driver, with Datadog actively integrating AI tools, including its Bits AI generative assistant, to enhance automation and intelligent analysis [5]. - The public cloud services market is valued at $600 billion and is expected to nearly double by 2028, with a 20% compound annual growth rate (CAGR), presenting substantial opportunities for Datadog [6]. Group 2: Robust Operating Tailwinds - In the first quarter, Datadog's revenue grew by 25% year over year to $762 million, exceeding Wall Street's expectations of $741.5 million, with adjusted earnings per share (EPS) of $0.46 also surpassing estimates [7]. - The company has around 30,500 customers, with 3,770 generating over $100,000 in annual recurring revenue (ARR), and a notable 110% dollar-based net retention rate indicates increased customer spending [8]. - Demand for AI solutions is strong, with the number of customers using its large language model (LLM) Observability product more than doubling in six months, supported by strategic acquisitions like Metaplane and Eppo [9]. Group 3: Free-Cash-Flow Momentum - For the full year 2025, Datadog targets revenue between $3.215 billion and $3.235 billion, reflecting a growth rate of 20% to 21% from the prior year, with EPS estimates of $1.67 to $1.71 indicating strong profitability [10]. - Free cash flow reached $833 million over the past year, surging 39% from year-end 2023, supporting the stock's premium valuation [10]. Group 4: Competitive Positioning - Datadog shares trade at a forward price-to-earnings (P/E) ratio of 64, which is high compared to the broader market but attractive relative to other high-growth software infrastructure peers [11]. - Compared to peers like CrowdStrike and Cloudflare, which have a forward P/E above 100, Datadog's unique blend of observability and cybersecurity capabilities offers broader use cases [12]. Final Thoughts - Datadog's AI-driven growth aligns with high-level themes in technology and cloud computing, making it a compelling addition to diversified portfolios [14].