Digitate announced the general availability of its latest release, Dragon, which adds enhanced product functionalities across the entire ignio product line as well as new out-of-the box solutions that help enterprises kickstart and accelerate their digital transformation at scale.
Dragon introduces SaaS-based, pre-packaged solutions across IT and business operations that combine automation, AI, and machine learning, allowing enterprises at any stage of their digital journey to get started faster and maximize the return on their technology investments. These out-of-the-box solutions – IT Event Management, Business Health Monitoring, Business Service Level Agreement (SLA) Prediction, and IDoc Management for SAP – are designed to support common use cases for maximizing uptime and guaranteeing smooth operations.
With the vision to help enterprise operations migrate to the cloud, the Dragon version of the ignio flagship AIOps suite adds multi-cloud support with leading providers including Microsoft Azure and AWS. The release also expands the reach of ignio with a new, state-of-the-art observability module. ignio Observe offers a single, integrated monitoring platform that not only replaces disparate views across the IT landscape but also predicts system issues and resolves them autonomously. Additionally, the release improves the overall user experience with easy-to-use integrations, new, intuitive interfaces, and enhanced mobile app access.
Together, the new releases give Digitate customers a comprehensive, unified, and easy-to-use software suite to increase business velocity and achieve greater resilience and agility, while propelling their cloud migrations forward.
“This new release significantly expands and enhances product capabilities and delivers pre-packaged solutions on an integrated SaaS platform. Digitate is advancing the autonomous enterprise by equipping organizations with the industry’s first single-stack solution across IT operations, assurance, and business operations,” said Akhilesh Tripathi, CEO of Digitate. “As organizations navigate increasingly complex multi-cloud and hybrid environments in their cloud journeys, we are empowering our customers to innovate, migrate and manage workloads, and boost business outcomes by increasing productivity, lowering risk, and providing greater coverage, choice and control.”
ignio AIOps for Multi-Cloud Support, a new module of the AIOps suite, brings together visibility and intelligence across hybrid environments, providing a distinctive closed-loop solution that autonomously detects, analyzes, and remediates infrastructure, applications, and cloud resources. ignio AIOps for Multi-Cloud Support also identifies cloud waste and resource sprawl based on configuration, usage, and cost, and provides actionable recommendations to eliminate unnecessary costs and security risks. With cloud adoption on the rise, organizations are facing more operational and implementation complexities. ignio AIOps for Multi-Cloud Support makes it easier for organizations to manage IT landscapes efficiently as they migrate to the cloud.
Powered by AI and advanced machine learning capabilities, Digitate’s IT Event Management solution reduces event noise by proactively suppressing, filtering, and aggregating redundant alerts, as well as predicting and preventing issues. With increased visibility and actionable insights across the IT infrastructure, the solution reduces the risk of missing genuine alerts, speeds up resolution, eases operator overload, and boosts availability for a better customer experience. Enterprises globally are leveraging the new IT Event Management solution to speed up incident resolution, reducing alert noise and service impacts.
All organizations must respond to IT incidents, which is why solutions to manage them efficiently – screening out unnecessary alerts without overlooking important ones – are key, according to Valerie O’Connell, Research Director from Enterprise Management Associates. “One way or another, all organizations do incident management. If they didn’t, they’d be out of business. It’s a question of how well they do it,” O’Connell says. “AI and ML can be game changers, making it possible to identify potential incidents so they can be addressed before any impact to users or the business. It’s not unusual for event management initiatives to detect and remediate 40% -- or more -- of incidents prior to impact. When looking for an event management system, scalability, flexibility, and time to value share top billing with cost. Equally important is the ability to scale the use of both AI and automation to meet organizations where they are today – and to keep pace with maturing demands for increasingly advanced capabilities over time.”
ignio Observe is a comprehensive monitoring module that covers metrics, alerts, and logs, providing a single, unified view across all components of the organization’s infrastructure. It draws on industry-leading machine learning algorithms to swiftly mine and analyze millions of log lines and highlight behavior patterns that may be problematic.
ignio Observe proactively identifies and even predicts system issues, then offers solutions. As a result, Digitate customers gain end-to-end visibility to monitor, troubleshoot, and prevent business-critical incidents early and reduce ticket volumes, thereby reducing the time and efforts required by the IT team.
The Latest
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...
AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.