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5 challenges to achieving observability at scale

Complex multicloud environments. Siloed teams. A huge volume, velocity, and variety of data that overwhelms human teams. The challenges organizations face in accelerating digital transformation are obvious, but meaningful answers are hard to come by.

Download our free eBook to learn how to overcome those challenges, innovate faster, and transform the way you work with AI and automation.

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What is Observability and why does it matter?

Observability is the extent to which the internal states of a system can be inferred from externally available data. An observable software system provides the ability to understand any issue that arises. Conventionally, the three pillars of observability data are metrics, logs and traces. Dynatrace extends this with UX, security and topology information. However, turning data into answers requires more than just an observable system.

Harness intelligent observability

Dynatrace advances observability with contextual information, artificial intelligence, and automation. Remove blind spots, resolve problems rapidly and deliver superior customer experience.

Intelligent observability turns data into answers.

  • Contextual information

    Extend the three pillars of observability with UX, security and topology data. Understand the full context of the observed data from user impact through entity interdependencies.

  • Causation-based AI

    Provide actionable answers to performance problems through a precise root-cause analysis.

  • Automatic discovery and instrumentation

    Ensure scalability and complete coverage in highly dynamic environments without manual configuration.

Real-time topology mapping provides context across the full stack

Dynatrace captures and unifies the dependencies between all observability data in order to intelligently combine metrics, logs, traces, user experience and security data. This real-time entity topology map is for intelligent observability.

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Causation-based AI delivers precise answers

Davis®, Dynatrace’s AI, automates anomaly root-cause analysis, even in highly dynamic microservice environments. Traditional monitoring tools offer little beyond dashboard visualizations, forcing manual root-cause analysis. Dynatrace is the only platform that takes the burden off human operators, by providing precise answers.

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OpenTelemetry for better coverage

Dynatrace is teaming up with Google and Microsoft and others on the OpenTelemetry project to shape the future of observability. OpenTelemetry will serve as an additional data source that extends the breadth of cloud observability, expanding the broad reach of what Dynatrace already automatically collects and ingests into Davis, its explainable AI engine.

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A Leader in the 2023 Gartner® Magic Quadrant™ and Ranked #1 in the Critical Capabilities for APM and Observability Reports

See why Gartner positioned us furthest for Completeness of Vision and highest for Ability to Execute in the Magic Quadrant, and ranked us #1 in all Use Cases in the Critical Capabilities Report.

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Dynatrace is a G2 Leader in observability

Dynatrace has been named a Leader among products in observability. These user ratings reflect the advantage of Dynatrace’s all-in-one-platform, which was made for IT, DevOps, and digital experience use cases, and built on a unified data model to enable increased automation and intelligence.
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Real-world impacts of observability, intelligence, and automation

How does observability work in real life? Help Davis solve problems and discover how automatic and intelligent observability works for systems we all rely on daily.

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Dynatrace scales effortlessly in a dynamic microservice environment. Before, we had blind spots. With Dynatrace we see everything.
Reinhard Weber Senior Product Manager at SAP CX