Serena Software launched Serena Service Manager to help organizations close the gap between application development and IT operations.
Serena Service Manager is a brand new solution that provides the industry an easily configurable and flexible process-based approach to delivering IT services, along with a unified service portal and integrated service dashboards.
Built on the experience of 300 worldwide customers already using Serena products to orchestrate IT services, Serena Service Manager syncs people, processes and services to improve overall visibility into incidents, problems and changes, increase customer satisfaction and drive down service desk costs.
Serena Service Manager leverages a process-based approach. Linking people with process in orchestrated service management, Serena tackles the current challenges around flexibility, visibility and usability inherent in legacy ITSM solutions. With Serena Service Manager – which can be deployed from the cloud or on-premises – IT organizations can lower Total Cost of Ownership (TCO) for their service desk solutions and speed up issue resolution with full visibility across the service lifecycle. This improves user satisfaction and reduces “backdoor” requests to IT for support by providing a unified, easy-to-navigate end user service request portal.
The new Serena Service Manager solution offers:
A Flexible, Process-Based Approach: Serena Service Manager provides customers with service management processes that encapsulate ITIL best practices. Customers can graphically change these processes to match their unique way of addressing constantly changing business demands – without having to rely on an army of vendor consultants. Intuitive, easily configurable forms and screens result in a lower learning curve and improved agent productivity.
Integrated Visibility: The new ITSM solution provides an integrated Configuration Management Database (CMDB), which provides greater control over infrastructure changes by delivering contextual information that speeds incident and problem investigation. Timely, contextual reports about the process, audit trails, and ITIL-based service desk metrics also ensure IT organizations get visibility across the service delivery lifecycle.
A Single, Friendly End User View: Serena Service Manager gives business users a single view of all the services available to them through a unified service request portal and service catalog. They can easily order services, track the status of their requests and have knowledge base articles proactively suggested to them as they submit tickets, thereby reducing service desk call volumes and the number of times users bypass Level 1 agents.
The Latest
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.
The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...