Dynatrace announced a significant expansion of its AI engine, Davis® AI, that can move enterprises beyond reactive AIOps to true preventive operations.
These enhanced capabilities enable organizations to predict and prevent potential incidents before they occur through AI-driven automation, while accelerating problem investigation and enhancing automated remediation when issues do arise.
The latest enhancements to the predictive, causal, and generative capabilities of Davis AI include:
- Dynatrace unlocks the AI-powered generation of artifacts to enhance automated remediation workflows. For example, Dynatrace enables the generation of Kubernetes deployment resources to adjust limits based on actual usage to prevent over- or under-provisioning.
- Davis AI strengthens its automatic root cause analysis with natural language explanations and contextual recommendations. It provides clear problem summaries, specific remediation steps, and surfaces relevant best practices based on its analysis of past incidents. This accelerates Mean Time To Resolution (MTTR) while building an intelligent knowledge base, enabling teams to learn from previous experiences and mitigate the risk of knowledge loss.
- The above capabilities, combined with existing predictive AI capabilities from Davis AI that forecast future behavior, enable true preventive operations. Teams can now access instant predictions based on observability data, AI-created artifacts, and Dynatrace automation all in one place to help prevent issues before they occur. This extends Dynatrace AIOps beyond IT operations and into security use cases like proactive firewall configuration.
"The shift from reactive to preventive operations represents the next evolution in AIOps," said Bernd Greifeneder, CTO at Dynatrace. "With further additions to our advanced AI capabilities, we believe Dynatrace is cementing its leadership as an intelligent, problem-solving partner for our global enterprise customers. By combining precise contextual data with advanced AI capabilities, we're enabling organizations to become truly proactive. This is not just about earlier detection of problems or faster resolution—it's about preventing problems from occurring in the first place."
Expanded Davis AI capabilities are expected to be available from Dynatrace within the next 90 days.
The Latest
Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...
IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...
Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...
In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ...
In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...
In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...
In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...
In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...
From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...
Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...