Idera announced the acquisition of Precise Software, a provider of end-to-end application performance management software.
The acquisition expands the company’s application performance management offerings.
Precise Software products monitor and evaluate end-to-end performance information across physical and virtual environments for major packaged and custom application architectures.
“We are excited about the acquisition of Precise. They pioneered application performance management solutions and built a portfolio of intellectual property that includes patents, developed technology and best practices for the industry,” said Randy Jacops, CEO of Idera. “With Precise and Idera, IT professionals can deploy a complete solution that covers monitoring, detection, resolution, prevention and administration.”
Precise Software serves more than 800 customers. Like Idera, Precise provides solutions to problems that IT professionals face daily, by managing and securing applications in the enterprise and the cloud.
John Vitalie, CEO of Precise Software said, “Our highly dedicated team at Precise has delivered market leading innovations to global customers for over 20 years. I’m very confident that combining our experience and leveraging our strengths will ensure customers achieve greater value via actionable intelligence about true application performance across the enterprise. This is a very exciting new era and significant achievements will follow.”
Precise Software products will continue to be marketed, sold and supported by Precise Software employees, the existing company website, and select channel partners, and the Precise brand will continue as a distinct offering with minimal disruption to current customers.
Idera expects a renewed focus on customer success, with product roadmaps focused on the highest value features and performance metrics.
Josh Stephens, VP of Product Strategy for Idera, said, “With the Precise acquisition we have the unique opportunity to engage a new customer base with our product emphasis on quality, usability, and customer value. We are also able to provide innovations and new products to Idera’s 12,000 existing customers. Application performance drives significant cost and efficiency improvements, a result coveted by every C-level executive. We are determined to build a world-class portfolio of technology assets to lead the application management space as well as drive the software value discussion.”
The Latest
In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...
Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...
Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...
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 ...