Dynatrace and TechCrunch reveal why AI-powered observability and continuous automation are crucial for digital transformation

For many organizations, digital transformation has escalated from an important business strategy to an essential survival strategy. To understand more, Dynatrace recently partnered with TechCrunch to investigate why having the right AI-powered observability platform in place is crucial for companies to not just survive but thrive.

Digital transformation is accelerating. IDC projects that as many apps will be developed and deployed in the next three years as the total built and deployed over the past 40 years[i]. The same IDC report also projects that by 2023, half of enterprise applications will be deployed in containerized hybrid-cloud or multicloud environments. The scope and scale of these environments are beyond human capacity to manage, with millions to billions of microservices coming and going each second in container-based architectures across multiple clouds. To manage the complexity of these environments, teams need AI-assistance. But as Tech Crunch and Dynatrace discovered, not all AI approaches are up to the task.

One approach to AI is correlation-based, like machine learning. This approach relies on pre-built models to determine what is related in a given data set. It’s an educated guess. Correlation approaches work well when people want movie recommendations from Netflix, or to identify statistical patterns. But for managing complex multicloud environments, and more importantly, to gain precise, real-time insights into business-critical use cases, correlation-based approaches lack the real-time context to provide precise answers.

The approach Dynatrace uses is causation-based, also called deterministic AI. This approach, used by our Davis AI-engine, determines the relationships and dependencies among apps, services, and infrastructure based on an automated, interactive real-time map of the environment called Smartscape.  With real-time context, Davis knows what all the entities in an environment do and what parts of the business they serve. It even knows what’s happening at a transaction level, right down to the code. This deterministic approach delivers precise, context-driven answers.

With an always-updated, high-fidelity view of how everything interoperates, Dynatrace facilitates continuous automation—deployment, configuration, updates, upgrades—so instead of wasting time doing manual, repetitive tasks, BizDevOps teams can focus on innovative, high-value tasks that drive better business outcomes.

With the right AI and automation in place, organizations can already declare AIOps victory. But with advanced observability that extends beyond metrics, logs, and traces into the code-level detail of entity relationships, distributed tracing, and user experience and behavior, all in context, BizDevOps teams can derive real-time, precise answers to just about any question, workload, or scenario. Davis can tell you the business impact of an issue or outage, the value of a software update or new feature, or the effectiveness of optimizations made to user experience workflows.

Simply put, Dynatrace, with its deterministic AI engine, Davis, is crucial for enabling organizations to manage their multicloud complexity, develop better software faster, create better digital experiences, and to do more with less at a time when it really matters.

For more insight into what Dynatrace and Tech Crunch confirmed about AI for digital transformation, see Driving digital transformation with continuous automation and AI-assistance on the Tech Crunch website.

[i] IDC FutureScape: Worldwide IT Industry 2020 Predictions, Doc #US45599219, October 2019

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