TABLE OF CONTENTS:
- Shifting from data collection to answers
- Modern cloud environments need an expanded approach to observability
- Automation, context, and AI required for Advanced Observability
- Automation for scalability and completeness
- Real-time topology mapping provides context across the full stack
- Causation-based code-level AI delivers precise answers
- Looking ahead: OpenTelemetry for better coverage
Observability, when combined with continuous automation and AI-assistance, holds the promise to deliver the actionable answers needed to ensure cloud-native applications work perfectly and cross-collaborative teams can deliver the best user experiences and business outcomes possible.
We recognized that while observability is important, it’s not enough to just “observe” data– it’s imperative to be able to use that data to deliver answers that ultimately drive better business outcomes.
As microservice environments become increasingly dynamic and scale to hundreds of thousands of hosts, the real challenge becomes making sense of data, within the context of the entire technology stack in real-time, to quickly understand the impact to users and prevent business-impacting issues from proliferating. This can be a daunting task that quickly surpasses the capacity of even the most skilled and experienced human operators. That’s why Dynatrace developed a radically different Software Intelligence Platform, expanding on traditional observability with automated, AI-assisted answers that can scale to the largest and most complex environments.
*In software, observability refers to the extent that the internal status and performance of a system can be inferred from its externally available data.
Automation, context, and AI required for Advanced Observability
Advanced observability addresses the challenges of cloud-native applications by proposing a better way of collecting data from all system components to gain complete and effortless visibility. Most legacy tools focus on collecting and aggregating three principal data types—metrics, traces, and logs—the so-called three pillars of observability.
Dynatrace has pioneered and expanded the collection of observability data in highly dynamic cloud environments with the OneAgent. In addition to metrics, logs and traces, we also collect user experience data for full-stack, end-to-end code-level observability.
Most importantly, Dynatrace delivers answers, not just more data, through three distinct and completely differentiated capabilities:
Continuous and automatic discovery and instrumentation
to ensure scalability, complete, and always-on coverage in highly dynamic environments with zero manual configuration.
for understanding the billions of interdependencies and context between entities across the full-stack and the data being observed.
Causation-based AI engine
to provide actionable answers to problems through real-time, code-level, precise root-cause analysis.
Automation for scalability and completeness
Most observability approaches require developers to manually instrument their code. In environments with thousands of hosts and microservices that dynamically scale across global, multi-cloud infrastructure, this becomes a futile effort and forces you to shift your team’s primary focus to non-value-add work.
The Dynatrace platform continuously automates data collection and analysis for enterprise-grade scalability and end-to-end advanced observability.
Upon installation, the Dynatrace OneAgent automatically detects all applications, containers, services, processes, and infrastructure at start-up in real-time.
System components are instrumented automatically with zero configuration or code change. Collection of high-fidelity data such as metrics, logs, traces, and user experience, in addition to topology data, begin as soon as a system component becomes available.
Dynatrace’s smart baselining automatically learns “normal” performance behaviors and adapts dynamically as the environment changes.
To minimize ongoing maintenance, the Dynatrace OneAgent continuously, automatically and securely updates throughout the entire environment.
But what makes Davis so different to what other platforms offer?
- Built at the core: Davis™ is built at the core of the Dynatrace platform, and processes all advanced observability data from across the full technology stack and third-party data, independent of origin.
- Precise code-level root-cause analysis: Davis pinpoints malfunctioning components with code-level visibility by probing billions of dependencies in milliseconds.
- Identification of bad deployments: Davis removes the guesswork and knows exactly which deployment or configuration change has caused each particular anomaly.
- Discovery of unknown unknowns: Davis doesn’t rely on predefined anomaly thresholds but automatically detects any unusual “change points” in the data.
- Automatic hypothesis testing: Davis quickly and systematically works through the complete fault tree before making real-time decisions.
- No repetitive model learning or guessing: Unlike machine learning approaches, that can’t discover unknown unknowns, Davis’ causation-based AI relies on a topology map, which is updated continuously in real-time.
Looking ahead: OpenTelemetry for better coverage
The OpenTelemetry open-source project is spearheaded by the Cloud Native Computing Foundation (CNCF), with the aim of making software more observable and to establish telemetry as a built-in feature of cloud- native software. OpenTelemetry focuses on improving the collection of observability data, specifically metrics and distributed traces for some of the emerging and increasingly adopted cloud frameworks.
This initiative is broadly supported by the open source community, as well as leading contributors including Dynatrace, Google, and Microsoft. Dynatrace is actively contributing and sharing its expertise with auto- instrumentation, interoperability, and enterprise grade solutions. Once OpenTelemetry is more widely adopted as a standard, it will serve as an additional data source that further extends the already impressive breadth of Dynatrace’s technology coverage.
The Dynatrace platform will help enterprises leverage OpenTelemetry by providing the highest possible scalability through automation, full-stack topology mapping, and most importantly, causation-based AI analysis through Davis to deliver answers, not simply exponentially increasing amounts data to observe.
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