Latest News & Updates on Datadog

Datadog and Cloudaware have integrated Cloudaware LogSight into the Datadog Marketplace, enhancing cloud log monitoring and compliance capabilities. This integration enables automated discovery and o...nboarding of unmonitored log sources, addressing security and compliance needs in multi-cloud environments. It strengthens Datadog's position as a central observability hub, appealing to enterprises managing complex cloud infrastructures.
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Datadog has introduced bring-your-own-cloud (BYOC) support, allowing customers to store observability data in their own cloud accounts. This shift aims to address the growing telemetry volumes driven... by AI and agentic workloads. Despite this architectural change, Datadog maintains a dependency on its proprietary agent for advanced features, preserving some level of vendor lock-in.
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Cloudaware and Datadog have partnered to integrate Cloudaware LogSight into the Datadog Marketplace. This integration helps customers ensure complete cloud log coverage by automatically discovering a...nd reconciling log sources with Datadog's ingestion. It provides continuous monitoring and compliance-ready evidence, enhancing Datadog's log management capabilities.
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The article discusses the development of a simple event-driven application using Datadog Workflows. The new setup replaces a more complex AWS-based system, simplifying event parsing and routing. Data...dog Workflows streamline the sales cycle automation by integrating with HubSpot, providing a low-maintenance, low-code solution suitable for moderate volume operations.
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Datadog introduced new AI product innovations at DASH2026, aimed at helping teams manage cloud complexity and enhance autonomous operations. These updates are part of Datadog's efforts to stay ahead ...in the observability and AI space.
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Datadog announced enhancements to its platform with expanded Bits AI agents, Agent Observability, and AI governance tools, highlighting its role in monitoring AI-heavy infrastructure. The company's f...irst-quarter revenue reached $1.01 billion, marking a 32% increase year-over-year, with significant growth in large customer relationships.
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Datadog has launched new AI security products, including AI Guard, as part of its recent announcements at the DASH event. This launch is part of Datadog's strategy to enhance its cybersecurity offeri...ngs through AI integration.
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Datadog unveiled over 100 new capabilities at its DASH 2026 event, focusing on AI-driven observability and security. Key updates include the "Bring Your Own Cloud" feature for data management, and en...hancements to Bits AI for autonomous operations. New tools like AI Guard protect AI agents from threats, while Bits Agent Builder allows custom AI agent creation within Datadog.
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Datadog launched over 100 new capabilities at DASH 2026, including making its Bits AI platform fully autonomous and introducing AI Guard for enhanced AI agent security. The new features allow for aut...omatic issue detection and remediation, and protection against AI agent attacks. Datadog also introduced Bring Your Own Cloud for data sovereignty and cost management, and tools for custom AI agent creation and monitoring.
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Datadog has expanded its AI framework, Bits, to enhance its observability platform, enabling DevOps teams to automatically discover and resolve issues. New features include Bits Code for remediation,... Bits Release for code change verification, and Bits Detection for extending observability. These tools aim to automate and improve the efficiency of software development and operations.
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Datadog has launched over 100 new capabilities at its DASH event, enhancing its AI-powered observability and security platform. Key updates include Bits AI for autonomous operations, AI Guard for pro...tecting AI agents, and Bring Your Own Cloud for data management. These innovations aim to improve visibility and operational control, addressing the challenges of AI-driven transformation and security complexity.
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Datadog introduced over 100 new features at its DASH conference, focusing on AI and security. Key products include Bits AI, which automates workflows and operates autonomously, and AI Guard, which se...cures AI agents. The Bring Your Own Cloud feature allows data processing in customers' cloud environments. The Bits Agent Builder enables teams to create AI agents for incident resolution.
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Datadog unveiled over 100 new features at its DASH 2026 conference, focusing on autonomous AI operations and security. Key updates include the expansion of Bits AI agents for development and security..., introducing modules like Bits Detection and AI Guard. These features enhance automation, threat detection, and operational control, positioning Datadog as a leader in AI-driven enterprise technology.
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Datadog introduced over 100 new tools at its DASH event to enhance AI and security management. Key updates include Bits AI, which now autonomously manages development and security workflows, and AI G...uard, which protects AI agents from attacks. The new "Bring Your Own Cloud" feature allows data processing in customers' environments, addressing data storage challenges.
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Datadog unveiled over 100 new capabilities at its DASH event, enhancing its AI-powered observability and security platform. Key updates include Bits AI, which automates operational workflows, and AI ...Guard, which protects AI agents from attacks. The platform now supports Bring Your Own Cloud, allowing data processing in customers' environments.
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Datadog launched over 100 new capabilities at its DASH event, enhancing its AI-powered observability and security platform. Key features include Bits AI for autonomous operations, AI Guard for AI age...nt protection, and Bring Your Own Cloud for data management. These updates aim to simplify complexity and improve operational control in AI-driven environments.
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Datadog introduced over 100 new products and capabilities at its DASH conference, enhancing its AI-powered observability and security platform. Key updates include Bits AI for autonomous operations, ...AI Guard for security, and Bring Your Own Cloud for data management. These innovations aim to improve visibility, operational control, and security in complex environments.
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Datadog launched over 100 new AI-powered observability and security capabilities at its DASH 2026 event. Key updates include Bits AI for autonomous operations, AI Guard for AI agent protection, and B...ring Your Own Cloud for processing data in customer environments. These enhancements aim to improve AI-driven complexity management and operational autonomy.
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Datadog and AWS have launched Datadog's full range of products in the AWS Asia-Pacific (Sydney) region, enhancing data residency and security compliance for Australian and New Zealand organizations. ...This integration supports local data storage and processing, crucial for regulated industries such as government and banking, and aligns with Australia's digital economy goals.
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Datadog has achieved FedRAMP High certification, allowing it to handle sensitive U.S. government data. This certification enables Datadog to support federal agencies requiring high-impact data protec...tion, such as law enforcement and emergency services. It reflects Datadog's investment in the U.S. public sector and strengthens its position in cloud security and compliance.
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Datadog has achieved FedRAMP High certification, confirming its platform meets stringent security standards for federal cloud environments. This certification enables Datadog to support U.S. governme...nt agencies and contractors handling sensitive data, enhancing its position in the regulated sector.
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Datadog has achieved FedRAMP High security certification, enhancing its compliance credentials for federal agencies. This certification allows Datadog to offer its cloud monitoring services to U.S. g...overnment agencies, ensuring high-level security and compliance standards.
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Datadog has achieved FedRAMP High certification, enhancing its capability to meet federal security standards. This certification allows Datadog to operate in sensitive federal environments, providing... U.S. government agencies with secure observability and faster incident response for critical information management.
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Datadog has released the Anomaly Reasoning Framework Benchmark (ARFBench), a time series question-answering dataset and evaluation suite. ARFBench, derived from Datadog's internal incident telemetry,... includes 750 questions from 142 time series. It evaluates models like GPT-5, which achieved 62.7% accuracy. The benchmark aims to enhance model performance in anomaly reasoning and incident response.
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Datadog launched a GPU Monitoring tool to optimize AI infrastructure costs by providing detailed insights into GPU usage, helping teams manage resources efficiently and reduce troubleshooting time.

Datadog launched a new GPU Monitoring tool to help organizations manage AI infrastructure costs. This product offers detailed insights into GPU usage, allowing teams to optimize resources and reduce ...costs associated with AI projects. The tool aims to improve AI delivery by minimizing troubleshooting time and enhancing decision-making regarding hardware procurement and resource allocation.
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Datadog has launched GPU Monitoring, a unified observability product designed to optimize GPU fleet health, performance, and cost management. Targeting platform engineering and ML teams, it provides ...fleet-wide visibility, identifies idle GPUs, and offers forecasting to reduce unnecessary purchases. This tool aims to address rising AI infrastructure costs by linking device metrics to workload and team ownership, enhancing capacity planning and financial governance.
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Datadog has introduced GPU monitoring to its observability platform, enabling organizations to track GPU usage and costs more effectively. This tool provides a unified view of GPU fleet health and pe...rformance, helping businesses optimize AI workloads and reduce expenses. The feature supports cloud, neocloud, and on-premises GPU environments, identifying inefficiencies and stalled processes to enhance cost management.
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Datadog has introduced GPU Monitoring, a tool designed to optimize GPU usage in AI workloads by providing a comprehensive view of GPU health, performance, and costs. This product helps organizations ...manage AI infrastructure expenses by identifying underutilized GPUs and bottlenecks. Hyperbolic, an AI cloud services provider, is an early adopter, using the tool for enhanced visibility in multi-tenant environments. The launch addresses the growing need for efficient AI operations and financial planning.
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Datadog has launched its new GPU Monitoring product, designed to optimize AI infrastructure by providing unified visibility across GPU fleet health, cost, and performance. This tool helps businesses ...manage AI costs effectively by linking GPU telemetry to workloads, enabling faster troubleshooting, and preventing resource wastage. It offers detailed insights into GPU utilization, facilitating better resource allocation and cost savings.
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Datadog has introduced GPU Monitoring to help organizations manage AI compute costs effectively. This tool provides a unified view of GPU usage, enabling developers and machine learning engineers to ...identify idle resources, trace bottlenecks, and link hardware metrics to application behavior. It aims to address cost pressures by improving visibility and efficiency in AI infrastructure management. Hyperbolic, a user of the product, benefits from enhanced operational insights and streamlined incident investigations.
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Datadog has launched GPU Monitoring, a new product that provides unified visibility across the AI stack, helping businesses optimize GPU usage and reduce costs. It offers real-time insights into GPU ...fleet health, cost, and performance, enabling teams to troubleshoot issues quickly and manage AI projects efficiently. The tool is now generally available.
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Datadog's AI engineering report reveals that capacity limits cause nearly 60% of AI failures in production, highlighting operational complexity as a major challenge. The report emphasizes the need fo...r AI observability and operational control as businesses transition from AI trials to live use. Datadog's findings indicate that infrastructure constraints, rather than model performance, are the primary bottlenecks in AI deployment.
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Datadog has launched GPU Monitoring, a new product offering unified visibility across AI stacks, helping businesses optimize GPU usage and reduce costs. This tool provides detailed insights into GPU ...fleet health, cost, and performance, enabling teams to manage AI projects more efficiently and avoid overspending. It is now generally available.
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Datadog's State of AI Engineering 2026 report reveals that nearly 5% of AI requests fail in production, primarily due to capacity limits. The report highlights that 69% of companies use three or more... AI models, increasing operational complexity. Datadog emphasizes the need for AI observability to manage these challenges effectively.
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Datadog has launched Datadog Experiments, a new platform designed to enhance product development by enabling teams to conduct A/B tests and measure product experiments. This platform integrates busin...ess metrics with product analytics, improving decision-making efficiency and reducing risks associated with rapid feature releases. The launch is expected to boost Datadog's market competitiveness and align with the growing demand for integrated solutions in product development.
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Datadog launched two new tools: Datadog Experiments, a product testing tool that provides insights into user behavior and app performance, and Bits AI Security Analyst, an AI-driven security agent th...at accelerates threat investigation and remediation. These tools address market needs for improved product experimentation and faster security responses.
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Datadog has launched Datadog Experiments, a new service that allows product teams to conduct and measure A/B tests and other experiments within its platform. This tool integrates business metrics, pr...oduct analytics, and application observability data, aiming to streamline the assessment of product changes. Built on technology from the acquired startup Eppo, it connects with Datadog's existing observability products, enhancing decision-making by providing a unified dataset and measurement methods.
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Datadog has launched Datadog Experiments, a new product that integrates experimentation into its observability platform. This tool allows teams to conduct A/B tests and measure product changes' impac...t on user behavior and business outcomes. It combines business metrics with product analytics and application observability, enhancing decision-making and innovation in AI-driven environments.
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Datadog has launched Datadog Experiments, a new product that integrates experimentation and A/B testing directly into its platform. This tool allows teams to measure the impact of changes on user beh...avior, application performance, and business outcomes in real time. It aims to streamline testing processes and improve decision-making by consolidating insights within a single platform, leveraging technology from Datadog's acquisition of Eppo.
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Datadog has introduced Experiments, a new feature for A/B testing. This tool is designed to help businesses optimize their applications by providing insights into user interactions and performance me...trics.
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Datadog has launched Datadog Experiments, a new feature designed to help teams connect product changes with business outcomes. This tool enables teams to experiment with product features and assess t...heir impact, enhancing decision-making and product development efficiency.
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Datadog has launched Datadog Experiments, a new product that integrates experimentation into its observability platform. This tool allows teams to design, launch, and measure product experiments and ...A/B tests, connecting product changes to business outcomes. It combines business metrics with product analytics and application observability, enhancing decision-making and innovation in AI-driven environments.
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Datadog has introduced Datadog Experiments, a new feature within its platform that enables product and engineering teams to run reliable experiments directly. This tool integrates behavioral analytic...s, application performance telemetry, and business metrics, allowing teams to design, launch, and analyze experiments without external dependencies. It aims to accelerate learning, prevent costly restarts, and optimize AI applications by providing real-time insights and performance monitoring.
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Datadog has launched the Bits AI Security Analyst within its Cloud SIEM platform. This AI agent automates security investigations, reducing mean-time-to-resolution by over 90%. It processes data from... various security tools, addressing alert fatigue and enhancing threat detection. The move underscores Datadog's expansion into security operations, leveraging AI to combat sophisticated threats and support security teams.
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Datadog has released the Terraform provider v4.0.0, enhancing infrastructure-as-code reliability. Key updates include improved monitor governance, a unified AWS integration resource, and stronger cre...dential security. The upgrade to Terraform protocol v6 facilitates future enhancements. These changes aim to provide a more secure and efficient observability-as-code experience for enterprise-scale platform engineering.
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Datadog has launched its MCP Server, enhancing AI-driven observability by connecting real-time data to AI agents for automated incident response. The company plans a new UK data center to meet compli...ance needs in regulated sectors like finance and healthcare. These moves aim to strengthen Datadog's position in AI operations and compliance-focused markets, competing with Dynatrace and New Relic.
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Datadog has launched a new solution for autonomous code optimization using LLMs, Unicron, and BitsEvolve. This innovation integrates formal verification and live traffic validation, aiming to streaml...ine deployment cycles by minimizing human intervention. The solution enhances productivity by ensuring robustly tested code fit for live environments, reinforcing Datadog's focus on AI and operational excellence.
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Datadog has launched AI Guard and Feature Flags to enhance its data observability offerings. AI Guard aims to protect AI applications, while Feature Flags facilitate safer software releases. These up...dates are part of Datadog's strategy to integrate AI-driven safeguards and improve performance monitoring, reinforcing its position in infrastructure monitoring and application performance solutions.
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Datadog has launched the MCP Server, designed to provide AI agents with secure, real-time access to observability data. This tool integrates live telemetry into AI coding agents and IDEs, allowing de...velopers to debug production issues efficiently. It supports autonomous AI operations on live systems by enabling secure access to production data, enhancing incident response capabilities.
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Datadog has launched its MCP Server, a new interface designed to enhance AI agent capabilities by providing secure, real-time access to unified observability data. This integration aims to improve de...veloper debugging efficiency in cloud applications by allowing AI agents to resolve production issues quickly. The server also supports automated incident response while ensuring compliance with corporate security requirements.
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Datadog has launched the MCP Server for secure, real-time observability in AI agent workflows and announced an integration with Cohesity to enhance AI agent resilience and recovery. These initiatives... aim to deepen Datadog's role in AI-centric enterprise environments, focusing on monitoring, security, and reliability in AI-driven operations.
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Datadog has launched its MCP Server for AI agent observability, now generally available, and announced an integration with Cohesity for automated incident recovery in AI environments. This partnershi...p enhances Datadog's platform by connecting AI operations with observability, data governance, and recovery, positioning it as a control plane for production AI.
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Datadog has launched its MCP Server, now generally available, to enhance AI workflows by providing secure, real-time access to unified observability data. This new product aims to streamline debuggin...g, automate operations, and ensure compliance, allowing AI agents to operate seamlessly within development environments.
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Datadog introduces the MCP Server, enhancing live observability for AI agents. This new product feature allows real-time monitoring and insights, improving AI operations and performance.

Datadog has launched its MCP Server, now generally available, to enhance AI agent workflows with real-time observability and security. It integrates with AI coding agents, providing live logs, metric...s, and traces to streamline debugging and secure AI operations. This release aims to simplify AI-native development by offering secure data access and reducing integration complexity.
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Datadog has announced the general availability of its MCP Server, designed to enhance AI workflow integration by providing real-time observability data access. This new server allows developers to de...bug using AI coding agents while maintaining security and governance controls. The MCP Server aims to streamline AI development by integrating Datadogs observability capabilities, enhancing operational efficiency and compliance.
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Datadog's State of DevSecOps Report 2026 reveals that 87% of organizations run services with known vulnerabilities, highlighting risks from outdated software and rapid release cycles. The report emph...asizes the security challenges posed by aging dependencies, rapid adoption of third-party updates, and insufficient build pipeline configurations. Datadog's executives stress the need for improved clarity and governance in security practices, particularly in complex environments.
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Datadog has integrated Google's Agent Development Kit into its LLM Observability platform. This integration provides automatic instrumentation for AI-driven agentic systems, offering deeper insights ...into performance and cost. It helps developers monitor complex AI workflows, improving reliability and operational confidence. This enhancement bridges a gap in AI agent deployment by providing tailored monitoring and governance tools.
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Datadog has introduced pg_tracing, a PostgreSQL extension for distributed tracing. It generates server-side spans for queries and supports PostgreSQL versions 14 to 16. The extension provides various... methods for span output and trace context propagation. It is in early development and may be unstable.
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In 2025, Datadog expanded its integrations ecosystem, surpassing 1,000 integrations and adding over 110 new technology partners. Key integrations include AI observability tools like GitHub Copilot an...d Microsoft Copilot, security enhancements with Wiz and Falco, and hybrid cloud solutions with Proxmox and Cisco Meraki. These integrations enhance visibility and performance across AI, security, and hybrid cloud environments.
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Datadog has launched Bits AI SRE, an AI agent for incident resolution, enhancing its AI-powered monitoring suite. This agent autonomously investigates alerts, identifies root causes, and provides ins...ights to reduce response times. It includes enterprise security features and is now generally available to all users. The launch aligns with Datadog's AI strategy expansion.
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Datadog has launched a new Storage Management tool aimed at optimizing cloud storage costs. This product provides granular visibility, proactive anomaly detection, and targeted recommendations to red...uce cloud storage waste, focusing on Amazon S3, with previews for Google Cloud Storage and Azure Blob Storage. It helps teams manage data-intensive workloads by identifying cost drivers and offering actionable insights to optimize storage usage.
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Datadog has expanded its cloud cost management capabilities to include Oracle Cloud Infrastructure, offering users daily cost visibility, allocation, and optimization features similar to those for AW...S and Microsoft Azure. This move enhances Datadog's position in managing hybrid and multi-cloud environments, providing a unified approach to cloud cost analysis for businesses using OCI.
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Datadog has enhanced its observability and security platform on Oracle Cloud Infrastructure (OCI) with new integrations for GPU Monitoring, Cloud Cost Management, and Cloud SIEM. These features aim t...o optimize AI workloads, manage costs, and improve security threat detection. The expanded support provides comprehensive monitoring capabilities, helping organizations manage AI and machine learning workloads efficiently across OCI and other cloud platforms.
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Anthropic and Datadog have formed a partnership to integrate trusted AI solutions, enhancing Datadog's cloud monitoring capabilities with AI-driven insights.

MegazoneCloud and Datadog have signed a Strategic Collaboration Agreement to enhance AI operations management in the Asia Pacific and Japan region. This partnership will integrate MegazoneCloud's AI ...and cloud capabilities with Datadog's observability technology, focusing on supporting generative AI services. The collaboration aims to expand market presence and strengthen their partnership through joint marketing and technical seminars.
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Datadog has significantly expanded its partner ecosystem, particularly in the Asia Pacific region, by quadrupling its channel team size since 2024. This growth aligns with its focus on AI and observa...bility as core business capabilities. The company has invested in resources, including appointing Renee Mitsis as head of channel and alliances for Australia and New Zealand, to support partners in navigating AI economics and governance.
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Critical Cloud has become the first "Powered by Datadog" partner, embedding Datadog into its managed services for AWS and Azure. This accreditation reflects Critical Cloud's technical excellence and ...ability to enhance customer operations with Datadog's observability platform, improving reliability and reducing downtime.
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Cohesity and Datadog have partnered to enhance AI agent resilience through enterprise-grade observability and rapid recovery. This integration combines Datadog's real-time monitoring capabilities wit...h Cohesity's automated data recovery, enabling enterprises to detect anomalies and restore data efficiently. The collaboration aims to strengthen AI-driven systems' reliability and trust by providing continuous telemetry, anomaly detection, and automated recovery across various environments.
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Datadog and Cohesity have partnered to integrate AI observability with data recovery solutions. This collaboration aims to enhance monitoring and recovery capabilities for businesses, leveraging Data...dog's cloud monitoring expertise and Cohesity's data management technology.
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Datadog and Sakana AI have announced a strategic partnership to enhance AI innovation and observability for enterprises. This collaboration will focus on research, product development, and go-to-mark...et strategies, initially targeting large enterprise customers in Japan. The partnership aims to bridge the gap between AI innovation and production readiness, leveraging Datadog's observability platform and Sakana AI's research capabilities.
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Contrast Security has integrated its Application Detection and Response (ADR) product with Datadog Cloud SIEM to improve alert accuracy and reduce noise in security operations. This integration allow...s verified runtime threat data from Contrast ADR to feed into Datadog's platform, enhancing the ability to automate triage and response workflows. The collaboration aims to reduce mean time to respond to application-layer threats, offering a more efficient security solution for joint customers.
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Datadog has acquired Adaptive ML, an AI startup specializing in reinforcement learning operations, to enhance its observability and security platform. This acquisition aims to integrate Adaptive ML's... technology into Datadog's existing offerings, potentially improving alerting, anomaly detection, and security workflows. The move aligns with Datadog's strategy to deepen AI capabilities and maintain a competitive edge in the observability market.
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Datadog acquired Adaptive ML, a startup specializing in Reinforcement Learning Operations platforms. This acquisition will bolster Datadog's AI research, particularly in world models and agentic LLM ...post-training for observability. Adaptive ML's technology will enhance Datadog's ability to provide enterprises with AI-driven productivity improvements.
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Datadog is acquiring Adaptive ML to enhance its AI capabilities, focusing on enterprise-grade AI agent development and reinforcement learning operations. This move aims to expand Datadog's AI researc...h and development, integrating Adaptive ML's technology to offer customized, self-improving AI agents for enterprises. The acquisition highlights Datadog's commitment to advancing AI-powered observability and automation solutions.
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Datadog has acquired Adaptive ML, a startup specializing in Reinforcement Learning Operations (RLOps), to enhance its AI research in observability and security. Adaptive ML will integrate into Datado...g AI Research, focusing on developing specialized agents and models. This acquisition supports Datadog's investment in AI and aims to improve its end-to-end observability and security solutions.
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Datadog has acquired Adaptive ML to enhance its AI research and development capabilities. Adaptive ML will join Datadog's AI lab to build advanced AI infrastructure, focusing on observability and sec...urity challenges. This acquisition aligns with Datadog's strategy to leverage AI for improved observability and security solutions, enhancing its offerings for enterprise clients.
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Datadog has acquired Propolis, an autonomous QA testing platform. This acquisition aims to enhance Datadog's capabilities by integrating Propolis's goal-oriented testing with Datadog's monitoring too...ls, creating a comprehensive solution for automated end-to-end testing. This integration will allow for continuous quality assurance embedded in CI/CD and runtime processes.
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Datadog reported strong Q1 2026 financial results, with revenue increasing 32% year-over-year to $1 billion and non-GAAP EPS rising 30% to $0.60, surpassing analyst expectations. The company has gain...ed new AI-oriented customers and launched a GPU Monitoring product, enhancing its AI capabilities. Datadog's Q2 revenue guidance of $1.07-$1.08 billion also exceeded forecasts, indicating continued growth driven by AI demand.
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Datadog reported a strong Q1 2026, achieving its first billion-dollar quarter with $1.006 billion in revenue, a 32% YOY increase. The company saw significant growth in AI-native customer adoption and... multi-product usage. Datadog's AI-driven tools are becoming essential as enterprises manage complex digital environments. The company forecasts continued revenue growth and profitability improvements, reinforcing its position in the AI infrastructure space.
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Datadog reported significant revenue growth, driven by its AI offerings and legacy business, resulting in a 31% stock gain. This performance highlights Datadog's strong position in the enterprise sof...tware market, particularly in cloud monitoring and security.
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Datadog reported record first-quarter 2026 financial results, surpassing $1 billion in quarterly revenue for the first time, marking a 32% year-over-year increase. The company expanded its customer b...ase to 4,550 clients with annual recurring revenue over $100,000. Datadog's new GPU monitoring product enhances its AI infrastructure offerings, positioning it as a key provider amid global semiconductor supply chain disruptions.
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Datadog reported a 32% year-over-year revenue growth for Q1 2026, reaching $1,006 million. The company launched several new products, including MCP Server, Bits AI Security Agent, GPU Monitoring, and... Datadog Experiments. Datadog also achieved FedRAMP High certification, enhancing its service offerings for U.S. government agencies.
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Datadog reported Q1 2026 revenue of $1.006 billion, a 32% increase year-over-year. The company achieved a GAAP operating income of $7 million and a non-GAAP operating income of $223 million. Datadog ...also launched several products, including MCP Server and Bits AI Security Analyst, and secured FedRAMP High certification. They added approximately 4,550 customers with $100k+ ARR, marking a 21% growth.
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The article discusses Datadog's upcoming Q1 2026 earnings report, highlighting the company's AI observability features as a potential growth catalyst. Analysts expect $0.06 EPS on $960 million revenu...e, with focus on customer retention and AI-driven product adoption. Despite valuation concerns, the consensus remains bullish, emphasizing Datadog's competitive position and market leadership in cloud monitoring.
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Datadog reported a 29% year-over-year revenue growth to $953.2 million, surpassing market expectations. Despite a 5.08% drop in stock price, the company's strong operating margin of 24.1% highlights ...its resilience amid market challenges. However, conservative revenue guidance for 2026 raises concerns about long-term growth potential.
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Datadog reported its fourth quarter and fiscal year 2025 financial results, highlighting a 29% year-over-year revenue growth to $953 million in Q4 and a 28% increase to $3.43 billion for the year. Th...e company also launched new products including Bits AI SRE Agent and expanded its collaboration with AWS. Datadog anticipates revenue between $4.06 billion and $4.10 billion for fiscal year 2026.
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Datadog Q4 Earnings & Revenues Surpass Estimates, Both Increase Y/Y - Yahoo Finance

Datadog's CTO, Alexis Le-Quoc, sold 32,300 shares of the company's stock, valued at approximately $3.76 million. This transaction, part of a pre-arranged trading plan, reduced his ownership by 5.73%.... The sale was disclosed in a legal filing with the SEC.
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Datadog has appointed Renee Mitsis, formerly of AWS, as head of channel and alliances for Australia and New Zealand. Mitsis will focus on enhancing partnerships within Datadog's ecosystem to drive cu...stomer success in AI and security. Her experience aligns with Datadog's strategy of collaboration with cloud providers and integrators.
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Datadog has appointed Renee Mitsis as Head of Channel and Alliances for Australia and New Zealand, aiming to enhance collaboration with partners and customers in the region. Mitsis will focus on inte...grating security, AI, and DevOps expertise to optimize customer outcomes and expand Datadog's partnership strategy. Her extensive experience with AWS and HPE positions her to scale Datadog's partner-led growth model, particularly in regulated industries.
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Datadog has appointed Renee Mitsis as Head of Channel and Alliances for Australia and New Zealand, focusing on enhancing partner-led growth in the region. Mitsis will manage relationships with partne...rs and customers, emphasizing early engagement in security, AI, and DevOps. This move aligns with Datadog's strategy to leverage partners for advisory services and managed operations, addressing the complexities of hybrid and multi-cloud environments.
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Datadog has appointed Dominic Phillips to its Board of Directors. Phillips, with extensive experience in scaling high-growth tech companies, aims to support Datadog's vision of enhancing AI-driven ob...servability and security. His background includes leadership roles at Samsara and ServiceNow.
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Datadog has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Observability Platforms, marking its sixth consecutive year in this position. This accolade highlights Datadog's ca...pabilities in helping customers manage AI-native applications and complex systems with its unified observability and security platform.
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Datadog has been named a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms for the sixth year in a row, ranking highest in Ability to Execute. This recognition highlights Datadog'...s significant R&D investments and its AI-powered features that enhance customer success.
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Datadog has been added to Wedbush Securities' AI 30 list, highlighting its potential to benefit from the AI expansion. Known for its observability and security tools, Datadog is positioned to capital...ize on the growing need for monitoring AI workloads. The company reported a 32% year-over-year revenue growth, reaching a $4 billion annual revenue run rate.
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Datadog has been named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the fifth consecutive year. This recognition highlights Datadog's strong execution and strategic vis...ion in the application performance monitoring and observability market. Customers praise Datadog's innovative features like APM, USM, and Watchdog for proactive alerting, underscoring its competitive advantage in the cloud monitoring space.
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