Eliminate Downtime With Effective Application Performance Management

Anand Akela

As public, private and hybrid cloud are becoming mainstream and applications are transitioning to these complex environments, IT has to effectively manage applications running on mobile devices to legacy mainframes and traditional multi-tier application servers and everywhere in the middle. Operational complexity due to running applications in the diverse and distributed environment makes it difficult for IT to have complete control over the environment.

At the same time, tolerance for application downtime is decreasing, the cost of service slowdowns and interruptions is increasing, and the resources dedicated to manage the entire, complex, heterogeneous environment are flat at best if not shrinking. You don’t need a crystal ball to see that this is a recipe for disaster.

In a recent survey by UBM Tech of 230 business technology professionals, 66% of the respondents said that the loss of employee productivity due to application downtime is a top challenge for their business. Loss of employee productivity and revenue can result from an inability to monitor end-to-end transaction performance and analyze application-related data from across your organization.

What IT managers need is a solution that provides clear visibility and advance warning of IT application performance issues and failures, allowing them to proactively address them before the system goes down. Application Performance Management (APM) addresses these challenges and helps IT managers ensure quality of service and experience for critical business applications so that revenue, end-user productivity and customer satisfaction are protected.

The UBM Tech Survey also identified top decision criterion for an APM solution. Scaling to complex applications, automatic diagnostics, and complete view of business transaction were on the top of the list per the survey result.

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Eliminate Downtime With Effective Application Performance Management

Anand Akela

As public, private and hybrid cloud are becoming mainstream and applications are transitioning to these complex environments, IT has to effectively manage applications running on mobile devices to legacy mainframes and traditional multi-tier application servers and everywhere in the middle. Operational complexity due to running applications in the diverse and distributed environment makes it difficult for IT to have complete control over the environment.

At the same time, tolerance for application downtime is decreasing, the cost of service slowdowns and interruptions is increasing, and the resources dedicated to manage the entire, complex, heterogeneous environment are flat at best if not shrinking. You don’t need a crystal ball to see that this is a recipe for disaster.

In a recent survey by UBM Tech of 230 business technology professionals, 66% of the respondents said that the loss of employee productivity due to application downtime is a top challenge for their business. Loss of employee productivity and revenue can result from an inability to monitor end-to-end transaction performance and analyze application-related data from across your organization.

What IT managers need is a solution that provides clear visibility and advance warning of IT application performance issues and failures, allowing them to proactively address them before the system goes down. Application Performance Management (APM) addresses these challenges and helps IT managers ensure quality of service and experience for critical business applications so that revenue, end-user productivity and customer satisfaction are protected.

The UBM Tech Survey also identified top decision criterion for an APM solution. Scaling to complex applications, automatic diagnostics, and complete view of business transaction were on the top of the list per the survey result.

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Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

The Network Data Problem Slowing Down Enterprise AIOps

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

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Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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