Dynatrace Unveils AI-Powered Observability Platform Enhancements at Perform Conference

Dynatrace Perform - CTO Bernd Greifeneder on the new ambitions for the observability company he founded

Dynatrace wants to go beyond observability and offer business and digital leaders an AI-enabled platform that helps their organisations exploit data resources. That's the ambition as articulated by company founder and CTO Bernd Greifeneder. In a keynote address at the start of this week's Perform conference in Las Vegas, Dynatrace CEO Rick McConnell talked about the need for a radically different approach to data management. So in a highly competitive marketplace, what does Greifeneder think makes his company's approach different? He argues that some providers help end users manage data in silos. Others create data lakes that require effort to make the most of the information they hold. Finally, some organizations separate data management by departments, such as security and engineering. He said Dynatrace differs by dealing with these areas simultaneously: It's about the importance of bringing the heterogeneous data together into one place and managing the storage automatically. Getting that together and having it always accessible is one key difference. The other difference is context. He believes Dynatrace Grail, the company's massively parallel processing 'data lakehouse', provides that context. Rather than just being a data store that brings logs, metrics, traces, and other data together, he emphasizes how Grail is also a graph database: You put the data and their dependencies together. So, this is the fundamental difference that no one else is doing and getting there is the hard part. During the event, it was made clear that AI is at the heart of Dynatrace's "radically different approach" to storage. The company announced a series of advancements to its AIOps Capabilities, which it claims will accelerate problem resolution and help customers manage issues proactively. However, the marketplace is competitive. Every tech vendor has its flavour of AI-enabled platform. Worse still, AI brings more complexity in a digital age of disparate systems and services, something Greifeneder recognizes: Businesses are now starting to, for instance, use AI to generate code. Then they throw AI at it to fix the code. Then they want agentic AI, which means one AI speaks to another. That's a lot of additional complexity. So, if you thought moving from multi-tier applications to micro-services and containers to Kubernetes is complex, then the complexity continues to increase dramatically. Greifeneder believes Dynatrace can help digital leaders by drawing on its long history of machine learning developments. Rather than simply adding generative AI capability to an existing service, Dynatrace is aiming to create a nuanced and multi-modal approach to AI that uses Grail, machine learning and the company's AI engine, Davis AI: We analyze billions of dependencies in sub-seconds. This is because we use causal AI, but causal AI only works when you have proper data in the graph. So, our success is not just Davis AI. It is the combination of having Grail with data in context in a graph that powers the causal AI on top that also learns instantaneously. Greifeneder believes the combination of predictive and causal AI provides the root cause of an issue in technical form. Professionals can then use generative AI to help translate these results in easier-to-understand human language: You can use this information to create recommendations about system reconfigurations. But these outputs are just recommendations. We always want a human in control. So, when we do a recommendation and a new configuration, the human says, 'yes' or 'no'. With its increased use of AI, Dynatrace's pitch is that it's building a one-stop shop for observability and data management. In the keynote session, Greifeneder even suggests that the long-term aim is to prevent issues from occurring in the first place. So, is that a realistic aim, and if so, why? He says: The aim is absolutely realistic. Reactive approaches won't go away, but you have an opportunity to cover your issues through predictive means. And also, if you automate harder, even the reactive portion can prevent your step-one issues because you'll be fast enough to stop the problems fanning out. Dynatrace's focus on insight and awareness is an attempt to extend the definition of observability from a niche audience to something all kinds of people - including senior executives - should be interested in. That's an idea that resonates with Greifeneder: This was the key goal we set five years ago that drove Grail and Dynatrace as an open platform on which you can even create apps. I see us as more than just an observability and security company, and more like an analytics company working with that gold mine of data your business has. Such is the level of Greifeneder's confidence that he suggested during the keynote that his team is developing "the best Dynatrace ever", in so far as it brings a consolidated approach to data management that should help digital leaders deal with observability and other concerns, like security and engineering: I would say the number one goal is to give customers the most value out of the data they collect into Dynatrace for the variety of use cases they have. This is our sweet spot because we have the context. The data-aware context is what we provide. Greifeneder also zoomed into the type of IT professionals that Dynatrace is targeting. Rather than just concentrating on monitoring and maintenance, the keynote made heavy mention of people who work with cloud, AI and Kubernetes: "This is where the whole tech stack is going. And that is the audience who wants a converged observability and security offering. They need the business insights and want to leverage decisions, almost intuitively, from these sources. It is exactly this audience that requires an all-in-one converged offering. In conclusion, the one thing Greifeneder wants people to take away from the event is that Dynatrace is changing: We have the most complete offering for cloud and AI natives. We have a combined platform for predictive operations, security, compliance and developers. You can't fault the ambition. Not content with bolting AI on top of its existing observability offering, Dynatrace wants to create a broad platform that helps IT professionals and business leaders exploit their treasure troves of data. One thing is already certain: someone, somewhere has to help digital leaders deal with the deluge of AI and data. Dynatrace hopes that these people will turn to them.

Dynatrace Perform - why businesses must take a radically different approach to data management

Dynatrace wants to create a centralized and AI-enabled observability approach that helps businesses manage IT issues proactively and automatically. In a keynote speech to kick off Dynatrace Perform in Las Vegas, CEO Rick McConnell explained to attendees how the upsurge in data from AI means an observability platform that can help organizations manage their applications and issues pro-actively is crucial: The world is evolving at an incredible pace. It's about amazing increases in complexity, but also amazing increases in innovation. It's also about business acceleration. We want to help you improve business results. We want to help you get closer to your customers. And we want to enable you and your businesses to generate incredible competitive advantages. Multiple drivers - an explosion in cloud, tools and AI - means everything in enterprise IT is becoming more complicated, according to McConnell, who posited that these drivers have led to huge increases in information, with about 149 zettabytes of new data created during the past 15 years. During the keynote, he pitched that the foundational platform for this new era of observability is Grail, Dynatrace's massively parallel processing 'data lakehouse', arguing that the company is building AI layers on top of Grail that exploit causal, predictive and generative AI to power the next era of observability: It's evolved from dashboards to insights, or, as we say at Dynatrace, 'answers' and intelligent automation, so you can provide real value from that data. The next step is auto-remediation, where we're actioning those insights to address issues before they become problems. Dynatrace founder and CTO Bernd Greifeneder summarized how the company will meet those goals by building "the best Dynatrace ever". He explained how the company is building a consolidated observability platform with new features that address customer concerns in three key areas - AIOps, security and development, which are explored in more detail below: You can predict issues and prevent them before they impact your production. You have the automation to be continuously compliant, the context to automate security, and you can help your developers be more productive. The company announced a series of proclaimed advancements to its AIOps Capabilities to accelerate problem resolution and help customers manage issues pro-actively. Last week's quarterly numbers release from Dynatrace stressed the importance of AIOps, where McConnell highlighted the company's long-standing commitment to using AI to manage and monitor operations. During the keynote, Greifeneder said advancements to AIOps Capabilities make it possible for digital leaders to ensure reliable applications and operational resilience: This capability means the mean time to appear and the remediation goes faster with automation, probably so fast that it doesn't even hit your customers. And what we ultimately want to do is prevent issues from happening at all. Generative AI, in the form of Davis AI, is at the heart of this product evolution, helping to boost Grails with natural language explanations and contextual recommendations. The AI provides summaries, remediation steps and best practices based on past incidents. Greifeneder explained how Davis AI uses its knowledge to forecast future behaviours and prevent issues before they occur: The enhanced data is compiled so that it learns from past incidents. We take collective intelligence from your various teams and, when a new incident comes up, Davis gives you the guidance from the learnings of previous incidents. The result, said Greifeneder, is an AI-powered observability platform that is deeply integrated into enterprise IT systems and provides useful suggestions for managing resources: We have embedded AI in a copilot that provides automatic recommendations for configuration changes. This effort is all to make you more productive in preventing issues from happening. Dynatrace also announced new Cloud Security Posture Management (CSPM) capabilities for businesses managing complex hybrid environments. Greifeneder said these new CSPM capabilities enhance security through continuous monitoring and centralised visibility: So, that's automating, in a continuous way, the configuration of your hyperscale posture. It's taking the end-to-end context of all your data together to help make your enterprise secure. Such a consolidated approach to security can reduce operational complexity and help organisations comply with regulatory technical standards, such as PCI and GDPR, Greifeneder said, with early customers already reporting that the technology saves them between 75% and 90% of the time dedicated to identifying issues and remediating them: The new compliance assistant automates 80% of the tasks for these compliance requirements. You can continuously report on your compliance status at any point in time in an automatic way. Finally, Dynatrace announced new capabilities to extend observability insights to the development community. Greifeneder explained how Observability for Developers gives development teams runtime insights, advanced analytics, and a new Live Debugger to streamline troubleshooting and performance monitoring: The technology allows you to focus on break points. The developers can step through the code line by line to review what's going on without having to interrupt any production process that's going on. Preview customers are said to be reporting a 40% acceleration in the mean time to repair. The company hopes these new capabilities will help accelerate the shift left, moving testing and quality assurance activities to an earlier stage in the development lifecycle. Once again, the focus is on speed and efficiency. Greifeneder said Dynatrace expects IT professionals to use the capabilities to turn insights into action faster and more effectively: I believe the best approach is 'extending the lift'. You provide self-service mechanisms to the other teams, for instance to developers. You prepare the next-stage integration mapping to allow developers to plate up the service they want. Dynatrace spots a gap - a consolidated and AI-enabled observability platform that helps businesses innovate faster and securely. The company has big aims and wants to stamp out issues before they appear. At Perform, Dynatrace rolled out a series of tools to help businesses automate observability. Over the next few days, I'll check in with customers to see how they believe the company's tools help their organisations manage data effectively. I've also got time scheduled to get up close with Grefeneder. Watch this space.

Dynatrace debuts new AI, security features for its observability platform - SiliconANGLE

Dynatrace debuts new AI, security features for its observability platform Dynatrace Inc. is rolling out new features that will make it easier for enterprises to troubleshoot their software and fix cybersecurity issues. The company debuted the enhancements today at its annual Perform product event in Las Vegas. The additions are rolling out to Dynatrace's namesake observability platform, which helps enterprises detect performance issues, outages and hacker activity in their infrastructure. The software ships with an artificial intelligence assistant called Davis that eases tasks such as identifying the cause of server malfunctions. The first set of new features that the company debuted today is rolling out for Davis. Dynatrace is enhancing the AI assistant's ability to explain the technical issues it finds. According to the company, Davis can now provide natural language problem summaries and suggests "specific remediation steps." The underlying AI models generate recommendations by analyzing similar incidents that occurred in the past. In addition to troubleshooting technical issues, Davis lends itself to a number of other tasks. Administrators can, for example, ask the assistant to predict when they should add more storage capacity to a cloud environment. Davis also generates alerts when it detects malfunctions. Today's update equips the assistant with the ability to generate artifacts, or software-related files such as an application's configuration scripts. The assistant can generate, among other things, scripts for configuring Kubernetes clusters. An administrator could ask Davis to increase the amount of processing power available to a Kubernetes cluster when it's receiving more network traffic than usual. "The shift from reactive to preventive operations represents the next evolution in AIOps," said Chief Technology Officer Bernd Greifeneder. "This is not just about earlier detection of problems or faster resolution -- it's about preventing problems from occurring in the first place." The upgrades to Davis are rolling out alongside a new suite of features called Observability for Developers. It's headlined by Live Debugger, a tool that promises to ease the task of troubleshooting software issues. When a faulty piece of code interrupts an application, developers usually have to reproduce the outage to identify what happened and how it can be fixed. The task can take a significant amount of time. Dynatrace says that Live Debugger enables developers to collect the technical data they need to fix an application malfunction without having to reproduce the incident. Observability for Developers also includes dashboarding features for monitoring workload health. Additionally, developers can use the offering to track how customers interact with their software and identify ways to improve the user experience. The new service is rolling alongside another new feature bundle called Dynatrace CSPM. According to the company, it enables customers to centrally monitor their cloud environments' cybersecurity posture. The offering is positioned as an alternative to platform-specific tools that only collect data from a single public cloud. Companies such as banks can use Dynatrace CSPM to ensure their cloud environments adhere to industry-specific cybersecurity standards. Privacy teams, in turn, can monitor systems' compliance with data protection laws such as GDPR. Dynatrace says the information collected by the feature suite is also useful for breach investigations. "With our unified solution, organizations achieve a single-platform approach that delivers continuous security insights, AI-ranked risk analysis and automated remediation," said Chief Product Officer Steve Tack. "Dynatrace continues to push the boundaries of observability and AIOps with its latest advancements, including Live Debugger and expanded security capabilities," said Rob Strechay, managing director of SiliconANGLE's sister market research firm theCUBE Research. "By integrating gen AI with its established Davis AI in an agentic manner, Dynatrace enhances preventive operations, reduces developer toil and accelerates MTTR. Its commitment to self-service observability and OpenTelemetry support underscores its role in enabling platform engineering at scale." Strechay also sees the expansion from Kubernetes Security Posture Management to Cloud Security Posture Management as a logical progression, leveraging its deep telemetry expertise to provide broader security insights. "With a strong application-centric approach, Dynatrace extends security posture management across cloud environments, reinforcing its position as a partner-focused innovator in modern enterprise IT," he said.