Datadog is the essential monitoring and security platform for cloud applications. The Datadog SaaS platform integrates and automates infrastructure monitoring, application performance monitoring and log management to provide unified, real-time observability of our 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.
APMdigest Blogs and News
Datadog announced that GPU Monitoring is available to customers everywhere.
Datadog announced that Datadog Experiments is available to customers everywhere.
Datadog announced plans for a new UK data center presence.
Resilience can no longer be defined by how quickly an organization recovers from an incident or disruption. The effectiveness of any resilience strategy is dependent on its ability to anticipate change, operate under continuous stress, and adapt confidently amid uncertainty ...
Datadog announced a strategic partnership with Sakana AI, a next-generation AI research lab building advanced foundation models, to collaborate on research, product innovation, and go-to-market initiatives focused on enterprise AI adoption.
Datadog launched Feature Flags, which unifies feature management with observability to help engineering teams release new functionality fast without compromising reliability.
Datadog announced a new strategic collaboration agreement (SCA) with Amazon Web Services (AWS) and showcased multiple product launches across AI, observability and security to help organizations running on AWS monitor, optimize and secure their cloud environments.
Datadog launched Bits AI SRE, an AI agent aware of telemetry, architecture, and organizational context that investigates alerts and surfaces actionable root cause in minutes, giving engineers the information they need to confidently resolve incidents faster, save engineering hours, and reduce end-user and business impact.
Datadog announced new integrations for customers using Datadog on Oracle Cloud Marketplace and deployable on Oracle Cloud Infrastructure (OCI).
Datadog announced that it is now ‘In Process’ for GovRAMP High Authorization.
Datadog launched its full range of products and services on the Amazon Web Services’ (AWS) Asia-Pacific (Sydney) Region.
Datadog announced its inclusion on the S&P 500 Index, effective prior to the opening of trading today.
Datadog announced new capabilities in its log management suite, which are designed to help organizations optimize logging costs at scale and meet the stringent data retention, auditability and data residency requirements of regulated industries.
Datadog announced new agentic AI monitoring and experimentation capabilities to give organizations end-to-end visibility, rigorous testing capabilities, and centralized governance of both in-house and third-party AI agents.
Datadog introduced three new AI agents that perform interactive investigations and asynchronous code fixes for development, security and operations teams.
Datadog is advancing toward Federal Risk and Authorization Management Program (FedRAMP) High authorization, which will ultimately enable federal agencies to more effectively monitor, secure and optimize their critical applications and infrastructure while adhering to stringent compliance frameworks.
Datadog unveiled the first two launches from Datadog AI Research, which is tackling research challenges that are firmly rooted in real-world problems within cloud observability and security.
Datadog has acquired Eppo, a feature flagging and experimentation platform, which will tightly integrate with Datadog's existing Product Analytics suite.
Datadog has acquired Metaplane, an end-to-end data observability platform that provides advanced machine learning-powered monitoring and column-level lineage to prevent, detect and resolve data quality issues across a company’s entire data stack.