Zenoss announced a strategic expansion in India through a key partnership with Amrut Software, a provider of technology management solutions and services based in India.
"India continues to be a rapidly growing market for cloud technologies," said George Kanuck, chief revenue officer at Zenoss. "We're excited about our partnership with Amrut Software because it will enable us to continue to grow our extended presence in India and support many of our partners who are either based in the region or have significant presence there. Further, the action clearly demonstrates Zenoss leading next-generation business partner channel strategy."
"We are delighted to partner with a leader in eliminating risk and increasing efficiency through AIOps, full-stack monitoring and automation," said Abhay Bhalerao, CEO of Amrut Software. "We've selected Zenoss because their world-class technology and people ensure our resellers can offer the best service assurance strategies to their customers as they undergo digital transformation."
Zenoss develops software as a service that builds comprehensive real-time models of hybrid IT environments, providing unparalleled holistic health and performance insights exactly where they are needed. Amrut Software has strong industry experience in DevOps and service management tool sets that complement the Zenoss ecosystem to help customers predict and eliminate outages, dramatically reduce downtime, and redirect IT resources to projects that transform their businesses.
"We are thrilled to be expanding our presence in India, home to some of the best technology talent in the world," said James Boyton, senior director of global channels and alliances at Zenoss. "This strategic partnership with Amrut will enable Zenoss to provide world-class differentiation with tailored solutions that help our enterprise customers and partners monitor, manage and optimize their complex and dynamic IT environments across India and the Middle East."
The Latest
As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...
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 ...