Dynatrace's fully-automated, AI-powered, full stack performance monitoring capabilities are available to customers of VMware Cloud on AWS.
Launched with initial availability in AWS US West region, VMware Cloud on AWS brings together VMware’s enterprise-class Software-Defined Data Center (SDDC) software and elastic, bare-metal infrastructure from Amazon Web Services (AWS) to give organizations consistent operating model and application mobility for private and public cloud. Dynatrace enables VMware Cloud on AWS customers to gain a deep understanding of their hyper-dynamic public, private and hybrid cloud environments.
Dynatrace’s AI-powered, full stack monitoring solution enables full transaction visibility. Its AI capabilities can continuously auto-detect dependencies, learn application behavior, detect anomalies and proactively pinpoint the root cause of performance problems. Preconfigured and automatically adjusted dashboards allow organizations to maintain visibility into their hyper-dynamic application environments during vMotion events with ease.
The automated capabilities of Dynatrace also allow users to baseline application performance and instantly identify any negative impact on resource consumption or user-experience during the migration of running virtual machines in hyper-dynamic hybrid environments. This enables them to migrate virtual machines between their private VMware vSphere-based data center and the AWS cloud with confidence, monitoring the whole vMotion event through a single pane of glass.
“Dynatrace’s longstanding collaboration with AWS provides a tried-and-tested monitoring solution for customers of VMware Cloud on AWS,” said Franz Karlsberger, Director, Strategic Partners at Dynatrace. “The AI capabilities in Dynatrace provide a way for organizations to automate the management and monitoring of these hyper-complex, hyper-dynamic environments. Its ability to auto-discover application dependencies and baseline performance, and to instantly pinpoint the root cause of performance problems before they impact the end-user will be invaluable in helping organizations maximize the benefits of VMware Cloud on AWS.”
VMware Cloud on AWS technology partners enable customers to deploy the same proven solutions seamlessly in both the public and private cloud. VMware simplifies the deployment and eliminates the need for partners to refactor solutions for VMware Cloud on AWS. If a partner solution works on-premises in a VMware vSphere environment, it will easily support VMware Cloud on AWS. VMware technology partners complement and enhance native VMware Cloud on AWS service and enable customers to realize new capabilities.
“VMware Cloud on AWS provides customers a seamlessly integrated hybrid cloud offering that gives customers the SDDC experience from the leader in private cloud, running on the leading public cloud provider, AWS,” said Mark Lohmeyer, VP Products, Cloud Platforms Business Unit, VMware. “Solutions such as Dynatrace enable IT teams to reduce cost, increase efficiency, and create operational consistency across cloud environments. We’re excited to work with partners such as Dynatrace to enhance native VMware Cloud on AWS capabilities and empower customers with flexibility and choice in solutions that can drive business value.”
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 ...