Anuncio • 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. Anuncio • May 02
Datadog, Inc., Annual General Meeting, Jun 15, 2026 Datadog, Inc., Annual General Meeting, Jun 15, 2026. Anuncio • 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. Anuncio • 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 Anuncio • 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. Anuncio • 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. Anuncio • 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. Anuncio • 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. Anuncio • Mar 02
Datadog, Inc., Annual General Meeting, Apr 21, 2026 Datadog, Inc., Annual General Meeting, Apr 21, 2026. Anuncio • 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. Anuncio • Jan 21
Datadog, Inc. to Report Q4, 2025 Results on Feb 10, 2026 Datadog, Inc. announced that they will report Q4, 2025 results Pre-Market on Feb 10, 2026 Anuncio • Nov 06
Datadog, Inc. Provides Earnings Guidance for the Fourth Quarter and Full Year 2025 Datadog, Inc. provided earnings guidance for the fourth quarter and full year 2025. For the fourth quarter 2025, the company expects revenue between $912 million and $916 million.
For the full year 2025, the company expects revenue between $3.386 billion and $3.390 billion. Anuncio • Oct 17
Datadog Reportedly Explores Takeover Bid for GitLab Datadog, Inc. (NasdaqGS:DDOG) is said to be working with bankers at Morgan Stanley (MS) to once again explore a potential takeover bid for GitLab Inc. (NasdaqGS:GTLB), a source reportedly told Street Insider. GitLab explored a potential sale with its own bankers and Datadog was one of the interested parties, Reuters previously reported. A new bid could be made for over $60 per share, according to Street Insider's source. Anuncio • Sep 12
Datadog, Inc. Appoints Ami Vora as Class I Director, Effective September 11, 2025 On September 11, 2025, the Board of Directors of Datadog, Inc. increased the size of the Board from nine to ten members and appointed Ami Vora as a Class I director of the company to fill the resulting vacancy, each effective September 11, 2025. Ms. Vora's term will expire at the Company's Annual Meeting of Stockholders to be held in 2026. Ms. Vora has not been, and is not currently expected to be, named to any committee of the Board at this time. Vora brings over 20 years of experience leading product and design teams for some of the most widely used products in the world. She was Chief Product Officer at Faire, a global wholesale marketplace for independent brands and retailers. Before that, Vora led product and design for WhatsApp, one of the most-used and most-loved apps in the world. She held several prior roles at Meta, including Vice President and Head of Product for Facebook Ads, scaling Instagram, and launching Facebook's developer platform. Vora began her career at Microsoft, building tools for developers. She holds a BA in Computer Science from Harvard University. Anuncio • Aug 07
Datadog, Inc. Provides Earnings Guidance for the Third Quarter and Full Year 2025 Datadog, Inc. provided earnings guidance for the third Quarter and full year 2025. For the quarter, company expected Revenue to be in range of $847 million and $851 million,
For the full year, company expected Revenue to in range of between $3.312 billion and $3.322 billion. Anuncio • Jul 18
Datadog, Inc. to Report Q2, 2025 Results on Aug 07, 2025 Datadog, Inc. announced that they will report Q2, 2025 results Pre-Market on Aug 07, 2025 Anuncio • May 08
Datadog, Inc. Provides Financial Guidance for the Second Quarter and Full Year 2025 Datadog, Inc. provided financial guidance for the second quarter and full year 2025. For the quarter, the company expects Revenue between $787 million and $791 million.
For the full year, the company expects Revenue between $3.215 billion and $3.235 billion. Anuncio • May 05
Datadog, Inc. (NasdaqGS:DDOG) acquired Eppo Data, Inc. Datadog, Inc. (NasdaqGS:DDOG) acquired Eppo Data, Inc. on May 5, 2025. Eppo will continue supporting existing customers and bringing on new customers as part of Eppo by Datadog.
Datadog, Inc. (NasdaqGS:DDOG) completed the acquisition of Eppo Data, Inc. on May 5, 2025. Anuncio • Apr 24
Datadog, Inc. (NasdaqGS:DDOG) acquired Metaplane, Inc. Datadog, Inc. (NasdaqGS:DDOG) acquired Metaplane, Inc. on April 23, 2025. The acquisition of Metaplane accelerates Datadog’s expansion into data observability—building on launches of related products like Data Jobs Monitoring and Data Streams Monitoring. Metaplane will continue to support its existing customer base and onboard new users under the Metaplane by Datadog brand.
Datadog, Inc. (NasdaqGS:DDOG) completed the acquisition of Metaplane, Inc. on April 23, 2025. Anuncio • Apr 16
Datadog, Inc. to Report Q1, 2025 Results on May 06, 2025 Datadog, Inc. announced that they will report Q1, 2025 results Pre-Market on May 06, 2025 Anuncio • Apr 07
Datadog, Inc., Annual General Meeting, Jun 03, 2025 Datadog, Inc., Annual General Meeting, Jun 03, 2025. Anuncio • Feb 13
Datadog, Inc. Provides Earnings Guidance for the First Quarter and Full Fiscal Year 2025 Datadog, Inc. provided earnings guidance for the first quarter and full fiscal year 2025. For the quarter, the company expected revenue between $737 million and $741 million.
For the year, the company expected revenue between $3.175 billion and $3.195 billion. Anuncio • Jan 25
Datadog, Inc. to Report Q4, 2024 Results on Feb 13, 2025 Datadog, Inc. announced that they will report Q4, 2024 results Pre-Market on Feb 13, 2025 Anuncio • Dec 26
Datadog, Inc. Appoints Amit Agarwal as A Class II Director, Effective January 1, 2025 On December 22, 2024, the Board of Directors (the “Board”) of Datadog, Inc. (the “Company”) increased the size of the Board from eight to nine members and appointed Amit Agarwal as a Class II director of the Company to fill the resulting vacancy, each effective January 1, 2025 (the “Effective Date”). Mr. Agarwal's term will expire at the Company’s 2027 Annual Meeting of Stockholders. Mr. Agarwal has not been, and is not currently expected to be, named to any committee of the Board at this time. Anuncio • Nov 13
Datadog, Inc. Introduces Kubernetes Active Remediation to Provide Curated Guidance and End-To-End Management of Kubernetes Environments Datadog, Inc. announced the launch of Kubernetes Active Remediation, which builds on Datadog's automated troubleshooting capabilities to provide curated remediation guidance, best practices and end-to-end issue management for Kubernetes organizations. Traditional monitoring tools track health and performance based on metrics, but teams need deeper insights and guidance to navigate the complexities of Kubernetes environments. Teams are also often slowed down by the limited availability of their organization's internal Kubernetes experts. Without actionable recommendations, diagnosing the root cause of issues can be time consuming and resource intensive, leading to prolonged downtime and decreased operational efficiency. Kubernetes Active Remediation offers the deeper insights at scale that teams need by providing a comprehensive overview of cluster-level resource problems ranked by their importance and relevance. After a problematic cluster or workload has been identified, teams can view consolidated troubleshooting information, including root cause analysis and recommended fixes. They can then directly trigger deployment patches for the key issues from within the Datadog platform. Kubernetes Active Remediation helps organizations: Automate root-cause analysis and detection: Recommendations are automatically issued with full contextual data and triaged to the correct owner. Curated remediation actions can also be pre-approved by the DevOps or security teams to automate the process downstream. Directly repair Kubernetes environments: Explanations and suggestions are provided based on troubleshooting patterns that are commonly seen in Kubernetes environments. Once the user has the full context and recommended next steps, they can directly trigger deployment patches from within Datadog to remediate the issue. Improve troubleshooting and remediation speed: By accelerating a user's time to detect and resolve an issue, Datadog helps application development teams be more efficient, understand root causes and automate their remediation processes. Anuncio • Nov 08
Datadog, Inc. Provides Earnings Guidance for the Fourth Quarter and Full Year 2024 Datadog, Inc. provided earnings guidance for the fourth quarter and full year 2024. For the quarter, the company expected revenue between $709 million and $713 million.
For the full year, the company expected revenue between $2.656 billion and $2.660 billion. Anuncio • Oct 18
Datadog, Inc. to Report Q3, 2024 Results on Nov 07, 2024 Datadog, Inc. announced that they will report Q3, 2024 results Pre-Market on Nov 07, 2024 Anuncio • Aug 08
Datadog, Inc. Provides Earnings Guidance for the Third Quarter and for Full Year 2024 Datadog, Inc. provided earnings guidance for the third quarter and full year 2024. For the quarter, the company expected Revenue between $660 million and $664 million.
For the year, the company expected Revenue between $2.62 billion and $2.63 billion. Anuncio • Aug 06
Datadog, Inc. Appoints Yanbing Li as Chief Product Officer Datadog, Inc. announced that Yanbing Li is joining as Chief Product Officer, effective immediately. Li has more than 25 years of product, technology and engineering experience, having led global engineering, operations and infrastructure teams at Aurora, Google and VMware. Most recently, Li was Senior Vice President of Engineering at Aurora, where she led all software development efforts. Prior to Aurora, as Vice President of Product and Engineering at Google, Li was responsible for the commerce platform for cloud, and the operations and service infrastructure powering both Google Cloud and Google. Prior to Google, she was the Senior Vice President and General Manager for the Storage and Availability Business Unit at VMware. Li holds a Ph.D degree from Princeton University, a master's degree from Cornell University and a bachelor's degree from Tsinghua University. Anuncio • Jul 19
Datadog, Inc. to Report Q2, 2024 Results on Aug 08, 2024 Datadog, Inc. announced that they will report Q2, 2024 results Pre-Market on Aug 08, 2024 Anuncio • Jul 04
Datadog, Inc. Appoints David Galloreese as Chief People Officer Datadog, Inc. announced that David Galloreese joined as Chief People Officer. Galloreese has more than 20 years of human resources experience from roles at brands like Figma, Wells Fargo, Walmart, Medallia and Caesars Entertainment. Most recently, Galloreese was a Senior Advisor at McKinsey & Company, and advised companies like Karat, Guild and Gametime. Prior to his advisor roles, he held Chief Human Resources Officer positions at Figma and Wells Fargo, was the Chief People Officer at Sam's Club, and was the Head of People & Culture at Medallia. Anuncio • Jun 27
Datadog, Inc. On-Call Launches to Deliver Observability-Enriched Paging and Unified Incident Management Capabilities Datadog, Inc. announced Datadog On-Call, a modern on-call experience with observability-enriched paging and seamless incident management workflows. Datadog On-Call instantly coordinates teams with relevant context for faster issue resolution, better incident control and improved collaboration. DevOps, SRE, Security and IT Operations teams need to maintain high levels of service, but they face challenges such as overwhelming alerts, confusion over dynamically shifting service ownership, disjointed paging strategies, coverage gaps and scheduling issues that make it difficult to understand, prioritize and resolve issues quickly. Traditional on-call systems offer workflows only for paging, while point solutions do not offer observability context, workflows or data, resulting in information gaps that lengthen resolution times. By unifying observability and paging into one seamless platform, Datadog On-Call solves these issues and eliminates the inefficiencies of multiple disjointed tools, allowing engineers to focus on resolving incidents quickly and effectively without the added stress of switching contexts or missing critical information. Datadog On- Call helps DevOps, SRE, security and IT Operations teams: Act Quickly and Stay Informed: Paging with integrated observability and seamless incident management ensures critical insights and data are readily available within a single platform, eliminating the need for context switching. Connect with the Tools They Use Every Day: On-Call integrates with a rich ecosystem of third-party monitoring, alerting and service management tools so teams don't have to learn new workflows or spend resources on training. Ensure Clear Service and Team Ownership: Break down knowledge silos and avoid confusion by associating teams with their respective services to simplify configuration, address ownership gaps and ensure the right responders are paged during an alert. Instantly trace upstream and downstream services affected by an outage or issue. SaaS platform integrates and automates infrastructure monitoring, application performance monitoring, log management, user experience monitoring, cloud security and many other capabilities to provide unified, real-time observability and security for customers' entire technology stack. Datadog is used by organizations of all sizes and across a wide range of industries to enable digital transformation and cloud migration, drive collaboration among development, operations, security and business teams, accelerate time to market for applications, reduce time to problem resolution, secure applications and infrastructure, understand user behavior and track key business metrics. Anuncio • Jun 21
Datadog, Inc. Launches New Product to Observe, Troubleshoot and Optimize Data Processing Jobs Datadog, Inc. announced the general availability of Data Jobs Monitoring, a new product that helps data platform teams and data engineers detect problematic Spark and Databricks jobs anywhere in their data pipelines, remediate failed and long-running-jobs faster, and optimize overprovisioned compute resources to reduce costs. Data Jobs Monitoring immediately surfaces specific jobs that need optimization and reliability improvements while enabling teams to drill down into job execution traces so that they can correlate their job telemetry to their cloud infrastructure for fast debugging. Data Jobs Monitoring helps teams to: Detect job failures and latency spikes: Out-of-the-box alerts immediately notify teams when jobs have failed or are running beyond automatically detected baselines so that they can be addressed before there are negative impacts to the end user experience. Recommended filters surface the most important issues that are impacting job and cluster health, so that they can be prioritized. Pinpoint and resolve erroneous jobs faster: Detailed trace views show teams exactly where a job failed in its execution flow so they have the full context for faster troubleshooting. Multiple job runs can be compared to one another to expedite root cause analysis and identify trends and changes in run duration, Spark performance metrics, cluster utilization and configuration. Identify opportunities for cost savings: Resource utilization and Spark application metrics help teams identify ways to lower compute costs for overprovisioned clusters and optimize inefficient job runs. Data Jobs Monitoring is now generally available. Anuncio • Jun 18
Datadog, Inc. Launches New App Builder for DevSecOps Teams Datadog, Inc. announced the general availability of Datadog App Builder, a low-code development tool that helps teams rapidly create self-service applications and integrate them securely into their monitoring stacks. These customized apps help accelerate issue remediation at scale by enabling both technical and business users to take action on incidents, all within Datadog. Having separate tools for monitoring and remediation can lead to slower response times and longer downtime for companies. When responding to an issue, teams need reliable, well-maintained tooling that's painless to use and minimizes context switching so that, when an issue arises, responders aren't spending time combing through monitoring data for context, connecting to hosts and other infrastructure resources, or pivoting betweenoles in order to remediate. Datadog App Builder enables the integration of customized, secure and scalable apps directly into teams' monitoring stacks, empowering organizations to take action on observability insights. Teams can also create self-service apps so anyone in the organization can perform remediation tasks quickly and without context switching. The low-code product allows teams to build apps in hours instead of weeks due to its UI components, templates called blueprints, data integrations called connections and support for custom JavaScript code. The connections include Datadog sources like metrics, logs and monitors, 550+ out-of-the-box actions for key tools and platforms (including GitHub, PagerDuty, Jira, CloudFlare, OpenAI and a host of AWS, Azure and GCP services). Anuncio • Apr 21
Datadog, Inc., Annual General Meeting, Jun 05, 2024 Datadog, Inc., Annual General Meeting, Jun 05, 2024, at 11:00 US Eastern Standard Time. Agenda: To consider and approve election of Director; to consider and approve ratification of Deloitte and Touche as independent accounting firm; and to consider and approve any other matters. Anuncio • Apr 17
Datadog, Inc. to Report Q1, 2024 Results on May 07, 2024 Datadog, Inc. announced that they will report Q1, 2024 results Pre-Market on May 07, 2024 Anuncio • Feb 06
Datadog, Inc. Welcomes Sara Varni as Chief Marketing Officer Datadog, Inc. announced that Sara Varni is joining as Chief Marketing Officer (CMO), effective immediately. Varni brings more than 15 years of marketing experience centered around enterprise software products—including leadership positions at Attentive, Twilio and Salesforce—to her role at Datadog. Varni was most recently CMO at Attentive. Prior to Attentive, she was CMO at Twilio where she grew the marketing function and helped scale annual company revenue as part of the leadership team. Before joining Twilio, Varni held multiple senior marketing roles at Salesforce. She holds a BS in Business Administration from Bucknell University and an MBA from The Anderson School of Management at UCLA. Anuncio • Jan 17
Datadog, Inc. to Report Q4, 2023 Results on Feb 13, 2024 Datadog, Inc. announced that they will report Q4, 2023 results Pre-Market on Feb 13, 2024 Anuncio • Nov 08
Datadog, Inc. Provides Earnings Guidance for the Fourth Quarter and Full Year 2023 Datadog, Inc. provides earnings guidance for the fourth quarter and Full Year 2023. For the quarter, the company expects Revenue between $564 million and $568 million.For the year the company expects, Revenue between $2.103 billion and $2.107 billion. Anuncio • Oct 18
Datadog, Inc. to Report Q3, 2023 Results on Nov 07, 2023 Datadog, Inc. announced that they will report Q3, 2023 results Pre-Market on Nov 07, 2023 Anuncio • Aug 10
Datadog, Inc. Provides Revenue Guidance for the Third Year and Full Year 2023 Datadog, Inc. provided revenue guidance for the third year and full year 2023. For the quarter, the company expect Revenue between $521 million and $525 million.For the period, the company expect Revenue between $2.05 billion and $2.06 billion. Anuncio • Jul 14
Datadog, Inc. to Report Q2, 2023 Results on Aug 08, 2023 Datadog, Inc. announced that they will report Q2, 2023 results at 9:30 AM, US Eastern Standard Time on Aug 08, 2023 Anuncio • May 05
Datadog, Inc. Provides Revenue Guidance for the Second Quarter and Full Year of 2023 Datadog, Inc. provided revenue guidance for the second quarter and full year of 2023. For the second quarter, the company expects revenue between $498 million and $502 million.For the full year, the company expects revenue between $2.08 billion and $2.10 billion. Anuncio • Feb 18
Datadog, Inc. Provides Financial Guidance for the First Quarter and Full Year of 2023 Datadog, Inc. provided financial guidance for the first quarter and full year of 2023. For the first quarter of 2023, the company expects revenue between $466 million and $470 million. For the fiscal year 2023, the company expects revenue between $2.07 billion and $2.09 billion. Anuncio • Jan 20
Datadog, Inc. to Report Q4, 2022 Results on Feb 16, 2023 Datadog, Inc. announced that they will report Q4, 2022 results Pre-Market on Feb 16, 2023 Anuncio • Nov 30
Datadog, Inc Launches Universal Service Monitoring Datadog, Inc. announced the general availability of Universal Service Monitoring, which automatically detects all microservices across an organization's environment and provides instant visibility into their health and dependencies—all without any code changes. Services are independent units of code that perform specific business functions and are accessible through an API. Visibility into these services is essential for organizations to monitor and assess the overall health of the applications that depend on them. However, if these services cannot be instrumented, either because their source code is unavailable, they are built by third parties or they are developed using unsupported programming languages, it can create blind spots that limit teams' ability to monitor these services and react if something goes wrong. Universal Service Monitoring provides complete visibility into first- and third-party services and their dependencies, regardless of programming language they use. The product complements Datadog's foundational Infrastructure Monitoring and Application Performance Monitoring capabilities and seamlessly integrates with Service Catalog, so that teams can view the health of their entire technology stack alongside ownership and other critical information about their services. Universal Service Monitoring helps teams to - Discover and map services: Automatically discover first- and third-party services to reduce mean-time-to-detection through out-of-the-box dependency mapping. Monitor service health: Gain instant visibility into the health of every service and deployment through real-time request rate, error and duration (RED) metrics and correlated infrastructure metrics and application logs. Centralize dispersed service information: Instantly populate DatadogService Catalog and enrich services with relevant owners, runbooks, on-call contact information and more to improve collaboration during incidents. Expand monitoring to root cause analyses: Resolve issues faster by adding end-to-end distributed traces that are correlated with observability data from across Datadog's unified platform. Anuncio • Oct 14
Datadog, Inc. to Report Q3, 2022 Results on Nov 03, 2022 Datadog, Inc. announced that they will report Q3, 2022 results Pre-Market on Nov 03, 2022 Anuncio • Jul 15
Datadog, Inc. to Report Q2, 2022 Results on Aug 04, 2022 Datadog, Inc. announced that they will report Q2, 2022 results Pre-Market on Aug 04, 2022 Anuncio • Jun 17
Datadog Launches Observability Pipelines to Help Organizations Collect, Manage and Route Observability Data Datadog, Inc. announced the launch of Datadog Observability Pipelines—a new product that enables organizations to take greater control of their data so they can reliably scale their observability practices. Datadog Observability Pipelines is powered by Vector, an open source and high-performance framework for building telemetry pipelines. Organizations are tasked with managing many applications, which are powered by hundreds of services and result in the creation of trillions of logs, metrics and traces per month. The vast amount of data involved and the resulting complexity at both the application and organization levels can lead to reliability issues, technology lock-in, security risks and runaway costs. Datadog Observability Pipelines provides customers with a unified view to control and monitor the flow of all their infrastructure and application metrics, logs and traces. Users can now seamlessly collect, enrich, transform, sanitize and route observability data from any source to any destination—before data leaves their environment. This unified view gives enterprises enhanced visibility into how much they are spending and where, what tools they are leveraging and who has access to what data. This enables them to more precisely manage costs, reduce technology lock-in, improve compliance and standardization of data quality and ultimately scale their observability practices. Datadog Observability Pipelines helps IT and security teams in their goals to affordably manage and scale observability with complete flexibility and control over how their logs, metrics and traces are collected, transformed and routed. This helps organizations: Control Costs: Aggregate, filter and route all observability data based on use case without compromising visibility; Simplify Migrations and Reduce Lock-In: Orchestrate and monitor data processing from any source to any destination in one unified view; Protect Sensitive Data: Filter, redact and monitor sensitive data before it leaves network in order to better meet compliance requirements; Enforce Data Quality: Standardize the format of logs, metrics and traces to improve observability across teams; Scale with Confidence: Scale seamlessly with a product powered by Vector, a vendor-agnostic, open source project and engaged community with millions of monthly downloads that is deployed in production by enterprises processing petabytes of data every month; Easily Collect and Route Data: Observability Pipelines comes with more than 80 out-of-the-box integrations so organizations can quickly and easily collect and route data to any of the tools their teams already use, without disrupting existing workflows. Anuncio • Jun 03
Datadog, Inc. Appoints Titi Cole to its Board of Directors Datadog, Inc. announced the appointment of Titi Cole to its Board of Directors. Cole is Citigroup's CEO of Legacy Franchises, overseeing the bank's consumer business in Asia, Europe, Middle East, Africa and Mexico. She is a member of Citigroup's Executive Management Team and also serves as a Member of the Board of Grupo Financiero Citibanamex, S.A. de C.V. and Banco Nacional de México, S.A. Prior to her current role, Cole served as Citigroup's Head of Global Operations and Fraud Prevention and the Chief Client Officer for Personal Banking and Wealth Management (PBWM). Cole also served as the Global Diversity & Inclusion Champion for PBWM. Cole has more than 25 years of experience in the financial services industry and has held senior leadership roles at several large global banks and McKinsey & Company. She earned a bachelor of economics degree from the University of Ibadan in Nigeria and a master of business administration degree from Northwestern University's Kellogg School of Management. Cole serves on the Board of Trustees for Queens University of Charlotte. Anuncio • Apr 21
Datadog, Inc., Annual General Meeting, Jun 02, 2022 Datadog, Inc., Annual General Meeting, Jun 02, 2022, at 14:00 US Eastern Standard Time. Agenda: To consider election of three Class III directors to hold office until Annual Meeting of Stockholders in 2025; to approve the compensation of executive officers, as disclosed in this proxy statement; to ratify the selection by the audit committee of board of directors of Deloitte & Touche LLP as independent registered public accounting firm for the fiscal year ending December 31, 2022; and to conduct any other business properly brought before the Annual Meeting. Anuncio • Apr 15
Datadog, Inc. to Report Q1, 2022 Results on May 05, 2022 Datadog, Inc. announced that they will report Q1, 2022 results Pre-Market on May 05, 2022 Anuncio • Apr 14
Datadog Expands Its Watchdog AI Engine with Root Cause Analysis and Log Anomaly Detection Datadog, Inc. announced two new capabilities for Watchdog, its AI engine: Log Anomaly Detection and Root Cause Analysis. In today's highly dynamic application environments, it is impossible for engineers to anticipate and develop rules to detect all possible anomalous application behavior that could impact performance and availability. Embedded across Datadog's observability platform, Watchdog analyzes billions of events and learns what "normal" behavior looks like in order to proactively provide insight to users for anomalies they didn't anticipate. The two new capabilities of Watchdog take this one step further. Log Anomaly Detection automatically understands and baselines normal patterns in logs, and proactively discovers abnormalities such as new text patterns, meaningful changes in data volumes of existing patterns and error outliers. With this new capability, Datadog Log Management users are able to quickly see and address hidden issues before they turn into critical incidents. Root Cause Analysis works with Datadog's APM products to automatically identify causal relationships between symptoms of an issue across an organization's services. By doing so, it pinpoints the precise service where an issue originated. Additionally, this capability identifies the business impact of an issue when Datadog's Real Using Monitoring (RUM) is deployed in the environment. This unique new capability often solves in minutes the problems of causality and real user impact, each of which often take hours or days to solve with manual troubleshooting. Both Root Cause Analysis and Log Anomaly Detection require no additional configuration and are available to Datadog APM and Log Management users out of the box. Anuncio • Dec 10
Datadog, Inc. Announces Launch of Sensitive Data Scanner Datadog, Inc. announced the launch of Sensitive Data Scanner. When configured for a customer's environment, this new service provides customers with an easy solution to detect, classify and protect sensitive data found in their application logs, helping them comply with regulatory requirements (such as GDPR, HIPAA, CCPA), industry standards and business policies. Logs are often a major source of unintentional sensitive data exposure and leaks in enterprise and consumer applications. This opens organizations to legal, financial and privacy risks, and protecting such data requires significant financial and time investments. The company’s Sensitive Data Scanner mitigates these risks through an easy-to-use, stream-based pattern-matching service that uncovers, classifies and redacts sensitive information in real time and at any scale. Users can also build alerts and dashboards to easily identify and rapidly respond to sensitive data exposure. Sensitive Data Scanner delivers: identification of sensitive data in customer logs using a library of preconfigured and user-defined rules for dozens of sensitive data patterns, including cloud provider secret keys and credit card information; classification of sensitive data with searchable tags, as well as the ability to create custom classification strategies; and protection of sensitive data through data scrubbing and hashing for correlation or auditing purposes. Sensitive Data Scanner is generally available on December 9, 2021 for Log Management customers. Anuncio • Aug 18
Datadog, Inc. Announces Deep Database Monitoring Datadog, Inc. announced the general availability of Database Monitoring (DBM). With insights into query performance and explain plans, as well as automatic correlation of query metrics with application and infrastructure metrics, Database Monitoring provides engineers and database administrators the visibility they need to quickly find and fix application performance issues that arise from slow running database queries. Database queries are often the root cause of incidents and application performance issues. When applications make unnecessary queries or fail to use indices, they burden the entire database, causing performance degradation for all applications using the database. Databases do not store historical query performance metrics, which makes it extremely difficult to understand the context around an issue and identify trends. This becomes even harder as engineers typically need to dig into each database individually to investigate, which prolongs downtime and exacerbates the impact on the customer experience. Datadog Database Monitoring builds on the existing ability to monitor the general health and availability of the database and underlying infrastructure by allowing users to pinpoint the exact queries that impact application performance and user experience. With DBM, users can see the performance of database queries, troubleshoot slow queries with detailed execution breakdowns, and analyze historical trends in query latencies and overhead. This allows organizations to unlock improvements not only in database performance, but also in the performance of the upstream applications, APIs, and microservices that the database underpins. DBM users are also able to automatically correlate query performance data with Datadog infrastructure metrics to easily identify resource bottlenecks. This allows engineers to quickly understand whether performance issues are at the database or infrastructure level, without needing to manually export and reconcile information from multiple, disconnected point solutions. Datadog's unified data model makes it easy to search and filter information at scale with the same tags that are used everywhere in Datadog. Datadog DBM delivers deep visibility into databases and enables organizations to: Quickly detect and isolate drops in performance. Users can track the performance of normalized queries across their entire fleet of databases, see which types of queries are executed the most and where they run, and get alerts for long running or expensive queries. For each query, they can drill down further to the hosts that are running that query, and leverage log and network information to understand host performance. Pinpoint the root cause of performance drops. DBM provides quick access to explain plans, so users can view the sequence of steps that make up a query. This allows them to localize bottlenecks and identify opportunities to optimize performance and resource efficiency. Improve and maintain database health, preventing incidents and saving costs. DBM enables organizations to keep historical query performance data for up to three months, so they can understand changes over time and prevent regressions. Provide engineers access to database performance telemetry, without compromising data security. DBM offers a centralized view of database performance data, automatically correlated with infrastructure and application metrics, without requiring direct user access to database instances. Datadog DBM for Postgres and MySQL starts at $70 per database server. Anuncio • Aug 06
Datadog, Inc. Launches Cloud Security Platform to Provide Security Teams with Unprecedented Observability Capabilities Datadog, Inc. announced the launch of the Datadog Cloud Security Platform, adding full-stack security context to Datadog's deep observability capabilities. This new offering enables organizations to use a single platform to correlate security insights with monitoring data across infrastructure, network and application tiers, providing Security teams with the visibility they need to understand and respond to potential threats faster. In recent years, security attacks have increasingly focused on the application level, prompting DevOps and Security teams to work more closely together to "shift left" and infuse security into the full software development life cycle. Traditionally, this has been difficult because of siloed tools and processes, which has been further exacerbated as organizations move to the cloud and security teams are left with even less visibility. Datadog's Cloud Security Platform addresses these challenges by enabling DevOps and Security teams to access a shared source of truth supported by a common data model. With Datadog, in parallel to detecting potential threats, Security leaders now have access to the underlying infrastructure, network and application data at the time of an attack, meaning they have deeper insights that enable more accurate threat detection and accelerated incident response. And, unlike point solutions, Datadog's platform approach ensures that this data is automatically correlated and presented in context, without requiring manual analysis. Anuncio • Jul 23
Datadog, Inc. Achieves AWS Government Competency Status Datadog, Inc. announced that it has achieved Amazon Web Services (AWS) Government Competency status. This designation reflects Datadog's deep experience working with government customers to deliver mission-critical workloads and applications on AWS. Datadog's cloud monitoring platform brings together infrastructure metrics, application traces, log data and synthetic monitoring, allowing government agencies to scale their cloud environments, troubleshoot potential issues and provide superlative citizen experiences. Datadog supports a wide range of AWS services and is a member of the Amazon Partner Network (APN). Anuncio • May 25
Datadog Extension for AWS Lambda Now Generally Available Datadog, Inc. announced the general availability of Datadog's AWS Lambda extension. This feature enables engineering teams to send their metrics, traces, and logs securely to Datadog with minimal overhead to their business-critical serverless applications. AWS Lambda extensions, a new feature from Amazon Web Services (AWS), represent a major step forward, allowing developers to run monitoring and security tools alongside their function code without complex installation processes or configuration management. For teams using Datadog's AWS Lambda extension, this can translate to saved time and money. Anuncio • May 07
Datadog, Inc. Provides Earnings Guidance for the Second Quarter and Full Year of 2021 Datadog, Inc. provided earnings guidance for the second quarter and full year of 2021. For the quarter, the company expects revenue between $211 million and $213 million.
For the year, the company expects revenue between $880 million and $890 million. Anuncio • Feb 18
Moogsoft Joins the Datadog Marketplace to Instantly Deliver Actionable Insights About It Incidents Moogsoft announced a new integration with Datadog. Available through the Datadog Marketplace, this new integration enables IT Ops, DevOps, and SRE teams to easily start ingesting events and metrics from Datadog into the Moogsoft Observability Cloud. Datadog’s monitoring and security platform provides metrics, traces, logs, and more to provide observability for modern environments. This new integration allows SREs, IT Ops, and DevOps pros to instantly see context-rich Moogsoft-generated incidents from across the full stack in either platform, boosting service availability. Put simply, it slashes the time an SRE must spend sifting through data to get to the cause of a service outage. Using this integration, Datadog users can use both platforms to: Achieve more context across incidents: Joint customers can use Moogsoft and Datadog to enrich telemetry from Metrics, Events and Logs APIs, as well as CI data from Datadog’s Topology APIs, with other data from across their environments including configuration database management systems (CMDBs), asset management databases, discovery systems and more. Accelerate identification of root cause: Moogsoft automatically adds key incident information such as location, department, business criticality, service relationships, runbooks and escalation processes. Minimize the impact and time spent on service-impacting outages:Moogsoft and Datadog algorithms automatically surface anomalies to Datadog customers, helping them address incidents before they introduce service impacts. Accelerate Monitoring Transformation:Moogsoft and Datadog automate event correlation across legacy on-premises systems and modern multi-cloud environments in one place, eliminating duplicates and effectively reducing the overall number of incidents across the full stack. Anuncio • Feb 10
Mendix Selects Datadog for Monitoring Multi-Cloud Microservices Environment Datadog, Inc. announced that Mendix, a Siemens business and global leader in low-code application development for the enterprise, has selected Datadog as the company's exclusive cloud observability platform for monitoring its multi-cloud microservices environment. Mendix engineers have adopted Datadog to ensure superior reliability for their enterprise customers and also to devote more time to innovation, rather than triage and troubleshooting. Mendix is fundamentally reinventing the way applications are built in the digital enterprise with its low-code platform. The Mendix platform uses a model-based, graphic interface for software development, to promote intense collaboration between business and IT teams and dramatically accelerate application development cycles, while maintaining the highest standards of security, quality, and governance. Mendix needed to ensure their platform is highly performant, available, and reliable for its customers, so they can quickly and easily build modern business applications. With a complex environment built on multiple clouds utilizing a microservices architecture, the monitoring challenges are manifold. To maintain the performance of its platform, Mendix needed to correlate critical data across multiple cloud providers, and numerous microservices, so that issues can be managed and resolved within a single pane of glass. Datadog's cloud monitoring platform has helped the Mendix operations team gain end-to-end visibility, with intuitive dashboards and targeted alerting, so engineers can spend time innovating instead of troubleshooting. Anuncio • Jan 22
Datadog, Inc. to Report Q4, 2020 Results on Feb 11, 2021 Datadog, Inc. announced that they will report Q4, 2020 results After-Market on Feb 11, 2021 Anuncio • Dec 19
Datadog Releases Capabilities to Correlate User Sessions with Backend Application Traces Datadog, Inc. announced new capabilities connecting user experience data with application traces, bridging the gap between frontend and backend performance monitoring. This new capability enables on-call engineering teams to pinpoint the root cause of issues impacting customer experience on mobile and web-based applications to backend services. Traditional Real User Monitoring (RUM) and Application Performance Monitoring (APM) solutions are siloed, requiring separate workflows to troubleshoot across the stack. This makes connecting user experience data from browsers and mobile applications with backend traces, metrics, and logs a complex and tedious task. These manual correlation efforts slow down on-call engineering teams when trying to remediate issues, as they struggle to pinpoint which part of the application stack is responsible for revenue impacting incidents. Datadog’s automatic two-way correlation for frontend user sessions in RUM and backend traces in APM eliminates these blind spots, allowing on-call teams to quickly identify root causes and thus maintain robust user-experience on browser and mobile applications. Datadog’s new APM and RUM capabilities automatically correlate critical application performance data, providing teams with; Full-Stack Correlation: connecting every user request to all backend services to cut down MTTD and MTTR with a unified view across the application stack, Frontend/Backend Comparison: comparing frontend and backend durations on every request, enabling engineering teams to identify and optimize slow user experiences and Trace Search and Analytics by User Journey Tags: slicing and dicing backend traces by location, device, operating system, and more to provide context for impacted customers. Anuncio • Dec 18
Datadog Announces Integration Between Compliance Monitoring and the AWSWell-Architected Tool Datadog, Inc. announced a new integration for Datadog Compliance Monitoring with the Amazon Web Services (AWS) Well-Architected Tool. The AWS Well-Architected Tool enables customers to review the state of their workloads and compare them to the latest AWS architecture best practices. Datadog’s Compliance Monitoring now integrates with the AWS Well-Architected Tool, enabling customers to monitor that their workloads comply with AWS best practices. Directly within the Security Pillar section of the AWS Well-Architected Review (WAR) interactive tool, customers can query for all Datadog discovered misconfigurations that indicate drift or lack of adherence. Anuncio • Dec 13
Datadog, Inc. and Snyk Launch Github Integration to Help Customers Identify and Prioritize Code-Level Security Fixes Datadog, Inc. announced the Datadog Vulnerability Analysis GitHub Action, Datadog’s first action listed on the GitHub Marketplace. GitHub Actions provide powerful, flexible CI/CD with the ability to automate any software development workflow. The Datadog action continuously monitors dependency and version information of code being deployed. By integrating this data with Datadog’s Continuous Profiler and Snyk’s Vulnerability database, this provides a real-time view of what code is actually accessible and vulnerable in production. Scanning applications for known vulnerabilities often yields a long list of issues that are difficult to prioritize and subsequently fix. With the data collected by the new action, vulnerability analysis will be performed by the Datadog Continuous Profiler based on Snyk vulnerability metadata. This allows engineering teams to immediately detect when and how often vulnerable methods are invoked in live environments and prioritize their security fixes based on real-world application behavior. The Datadog Vulnerability Analysis GitHub Action can be found and installed directly from the GitHub Marketplace without needing to manage scripts or infrastructure. Anuncio • Oct 15
BigPanda and Datadog Form Partnership for Integration and Go-to-Market BigPanda, Inc. announced it has teamed with Datadog. The partnership includes powerful new integrations for out-of-the-box data-sharing between the two platforms, including alert, topology and change data. The integration provides support for all eight of Datadog's monitoring tools, and it’s the first integration to utilize Datadog's rich topology datasets out of the box. Datadog will offer an in-product "integration tile" to make integration with BigPanda fast and intuitive, allowing users to feed machine learning-driven root-cause changes back to Datadog. For Datadog users, BigPanda allows them to correlate alerts collected from all Datadog monitoring modules, including Infrastructure, Log Management, and APM. BigPanda also gives Datadog users the ability to collect alerts from other third-party tools along with Datadog alerts into context-rich incidents. This significantly reduces alert noise in users' environments while reducing Mean Time To Respond (MTTR) and other MTTx metrics. For BigPanda users, the integration lets them tap into Datadog's new service-to-service topology map to drive event enrichment, correlation, impact analysis and prioritization. Combined with CMDB data ingested from IT Service Management systems, this integration allows users to visualize the relationship between services in Datadog and other services. For joint customers such as United Airlines, the BigPanda and Datadog alliance ensures their ability to unlock additional value as the companies introduce new technology integrations that deliver on United’s mission to serve the needs of their customers in today's world and maintain IT service excellence their customers expect. 
