Dynatrace announced the expansion of its leadership team with the appointments of Kevin Burns as CFO and Marc Olesen as SVP and GM of Digital Experience.
Burns has over 20 years of international business and financial management experience in technology organizations, including as CFO of highly innovative, fast growth companies such as iCAD, Inc. and AMICAS, Inc.
Olesen is an accomplished industry leader with over 25 years of Silicon Valley experience, managing successful cloud-focused business units at Splunk, McAfee and Hewlett-Packard.
“Dynatrace continues to capitalize on strong market demand and, as market leaders, we are constantly investing in innovation to set the industry benchmark even higher and delivering on our commitment to customer successes,” said John van Siclen, CEO of Dynatrace. “With Kevin and Marc on board, we’re in a stronger position than ever to accelerate the next stage of Dynatrace’s rapid growth. Kevin’s successful track record managing companies through growth will be indispensable in charting a fast and steady course as we capitalize on new opportunities. Marc is the clear leader for the future of our digital experience business with his deep expertise in bringing cloud offerings to market and operating efficient businesses.”
Burns has extensive knowledge of both the public and private equity sectors, as well as extensive experience managing high-growth business transformations. Most recently, he was President, CFO and COO at healthcare technology company iCAD, Inc. He earned his Bachelor of Science and Master’s degrees from Babson College in Wellesley, Mass.
Olesen has spearheaded major strategy shifts with software and services organizations and developed technology market depth in analytics, security and application performance. He is a proven leader with an established track record of transforming organizations and driving strong revenue growth. Prior to Dynatrace, Olesen served as SVP and GM of Cloud Solutions at Splunk. He also led the cloud and network security business at McAfee and the software-as-a-service business at HP. Olesen holds a Master’s degree in Industrial Engineering from Stanford University.
The Latest
I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...