Skip to main content

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.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

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.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...