Compuware Corporation announced enhancements to the Abend-AID fault management solution.
The latest improvements make Abend-AID even easier to use, especially for staff unfamiliar with mainframe legacy systems.
In addition, Abend-AID Fault Analytics further shortens the time it takes to analyze and resolve application failures -- absolutely vital given today’s prolific deployment of complex and customer facing applications.
Since its introduction 35 years ago, Compuware has consistently updated Abend-AID to keep it current and relevant for customers, including ensuring “day one” support of IBM hardware and software introductions and updates. Today, the solution is more important to IT organizations than ever for resolving mainframe application failures. That’s because mainframe applications increasingly support critical activities such as Web and mobile banking and e-commerce, and even a short-term outage could have dire consequences.
According to a recent survey conducted by Compuware, a tech performance failure can cost an organization, on average, approximately $10M in short-term costs business wide, from operations and sales and marketing, to finance and distribution/supply chain. This figure is before longer-term consequences including loss of market share, erosion of brand equity and reputational damage, are accounted for. Importantly, Abend-AID would be able to prevent a mainframe application outage by leading developers directly to the precise information they need to resolve application faults before they result in downtime.
“IT organizations are continually pressed by line of business executives to produce highly complex applications to meet the needs of their end users,” said Kris Manery, Sr. VP and GM, Compuware Mainframe Solutions. “Given the rapid rate at which these applications are put into production, faulty code is bound to rear its ugly head. At the same time, mainframe developers who are comfortable with diagnosing and fixing faults are preparing to retire. A trusted solution like Abend-AID is a must in today’s mainframe environment where the standard is complexity. It provides everything developers, regardless of their skill level, need to diagnose and resolve a fault that could potentially cost an organization millions if an application outage were to occur.”
Abend-AID’s tighter integration of fault identification with advanced Fault Analytics benefits multiple roles in the mainframe environment. Managers will see the value of Abend-AID’s increased visibility into faults, including trend analysis, enabling them to prioritize work assignments based on the frequency and severity of the issues. Developers can leverage Abend-AID’s new usability improvements that significantly shorten root cause analysis time, reducing application downtime and accelerating time to market for new functionality.
The product has also added information to assist programmers to better understand the code in question, and customization capabilities to allow programmers to tailor the product to best suit their needs.
Importantly, Abend-AID also provides the ability to keep long-term historical information on abend activity, allowing managers to determine at a glance if quality is degrading, and programmers to see if common problems are causing recurring abends. The Fault Analytics is zAAP-eligible to keep the CPU footprint of Abend-AID to a minimum.
Related Links:
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 ...