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Empowering Human Ingenuity in APM with Collaborative-Driven Automation

There are many challenges facing application teams today, as they are tasked with trying to reduce administrative, support, and help desk costs through active application management; improve end-user quality of service with efficient application and upgrade delivery; and lower operational costs through automatic application self-healing.

Some companies have turned to automation to lower costs and increase efficiency, but the increasing number of distributed, virtual and cloud-based applications pose a unique challenge for Application Performance Management (APM) as processes quickly become outdated and insufficient. And to make matters worse, the complexity of application delivery environments is outstripping the ability of APM products to monitor and manage performance.

Recent headlines, such as “Person Drives 100 Miles in Wrong Direction, Following GPS,” have shown us that automating complex processes without any human touch has a high propensity to go awry. Relying 100 percent on automation without any human intervention can leave processes stale and keep businesses stuck in a holding pattern, waiting for the next major process update that could take months to years to complete.

That's why innovative companies are leveraging next-generation technologies that integrate social and collaborative capabilities at the platform layer of automation tools to create a human-centric approach to complex process automation.

More traditional APM automation tools enable users to leverage reporting and analytics to detect issues and then use static run books to remediate those issues. But rather than getting a real-time glimpse into service issues, these static procedures are only providing a snapshot in time. What if the users had access to more than analytics and static run books? What if the users were empowered with the knowledge of an organization’s subject matter experts in real-time?

Traditional runbooks typically contain static decision trees that capture a process at one given point in time. Collaborative-driven automation tools feature dynamic decision trees, which allow users to drill down to resolutions faster within the knowledge management database, based on a series of intuitive questions assessing the symptom or the reported application issue.

The effectiveness of these decision trees is enhanced when the organization's most skilled experts are updating or adding to resolutions in real time to address newly emerging and/or more prominent topics. The result is a method of dynamic knowledge capture that keeps the bank of procedures current, so that users are able to rely upon information that reflects the resolutions that work best at any given point in time.  

With this immediate access to real-time updated knowledge, innovative companies are empowering human ingenuity in their organizations and achieving the below results with the latest APM automation tools:

- End-to-End Process Automation with unified orchestration and collaboration, combining multiple automation solutions into one process with integrated workflow capabilities and end-to-end reporting across multiple and parallel workflows. 

- First level staff are enabled to perform automated diagnostics and remediation in response to both inbound tickets and analytic trends and notifications picked up by performance reporting tools.

- Associate skillsets are being normalized with automations that don’t require advanced or specialized skills to create. Relevant knowledge documents are “pushed out” based on incident/issue type, and decision tree technology guides IT/First-Level technicians to relevant information and automations based on the symptoms presented.

- Improved application availability for end-users is created by reducing downtime cycles from hours to minutes and reducing the number of emergency bridge calls required to resolve issues.

- Compliance and auditing (CoBIT/SOX) are improved with analytics for audit trails and SLA compliance.

- Reduced average Mean Time to Resolution (MTTR) can be seen through enabled engineers.

- Application teams can run tests outside of their application and assign fault to those groups without a bridge call.  

- Problem solving steps are automatically executed in parallel instead of serial manual execution. Issues are no longer fixed by the engineer logging into tool #one, executing a series of commands, interpreting results, then logging into tool #two, executing commands, interpret results, etc. Instead, the engineer runs a series of commands simultaneously at the push of a button, and gets back results in a simple to understand format.

Application Performance Management entails complex processes that can and should be automated. But rather than eliminate human touch, automation tools should empower associates to execute the best possible automations with the collective, real-time knowledge of the organization.

When organizations implement automation technologies that leave human collaboration out of the process, it isn’t difficult for the “less-than-best” process to be followed, requiring multiple teams to be thrown into fire-fighting mode. Improved collaboration on processes allows more time to be spent on strategic initiatives and proactive management of applications. Not only will the entire organization benefit, so will the customers. And making and keeping customers happy should be the top goal for every organization.

ABOUT Payal Kindiger

As Executive Vice President of Marketing and Managed Services for gen-E, Payal Kindiger leads the company’s branding and marketing efforts, inside sales operations, organizational strategy, customer care, and managed services offerings. Prior to joining gen-E in 2003, she was a member of the management team at Deloitte and Touche. She has worked with several Fortune 500 companies and has managed client-service projects in IT business process re-engineering and organizational development across a number of industries. 

Related Links:

www.gen-e.com

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Empowering Human Ingenuity in APM with Collaborative-Driven Automation

There are many challenges facing application teams today, as they are tasked with trying to reduce administrative, support, and help desk costs through active application management; improve end-user quality of service with efficient application and upgrade delivery; and lower operational costs through automatic application self-healing.

Some companies have turned to automation to lower costs and increase efficiency, but the increasing number of distributed, virtual and cloud-based applications pose a unique challenge for Application Performance Management (APM) as processes quickly become outdated and insufficient. And to make matters worse, the complexity of application delivery environments is outstripping the ability of APM products to monitor and manage performance.

Recent headlines, such as “Person Drives 100 Miles in Wrong Direction, Following GPS,” have shown us that automating complex processes without any human touch has a high propensity to go awry. Relying 100 percent on automation without any human intervention can leave processes stale and keep businesses stuck in a holding pattern, waiting for the next major process update that could take months to years to complete.

That's why innovative companies are leveraging next-generation technologies that integrate social and collaborative capabilities at the platform layer of automation tools to create a human-centric approach to complex process automation.

More traditional APM automation tools enable users to leverage reporting and analytics to detect issues and then use static run books to remediate those issues. But rather than getting a real-time glimpse into service issues, these static procedures are only providing a snapshot in time. What if the users had access to more than analytics and static run books? What if the users were empowered with the knowledge of an organization’s subject matter experts in real-time?

Traditional runbooks typically contain static decision trees that capture a process at one given point in time. Collaborative-driven automation tools feature dynamic decision trees, which allow users to drill down to resolutions faster within the knowledge management database, based on a series of intuitive questions assessing the symptom or the reported application issue.

The effectiveness of these decision trees is enhanced when the organization's most skilled experts are updating or adding to resolutions in real time to address newly emerging and/or more prominent topics. The result is a method of dynamic knowledge capture that keeps the bank of procedures current, so that users are able to rely upon information that reflects the resolutions that work best at any given point in time.  

With this immediate access to real-time updated knowledge, innovative companies are empowering human ingenuity in their organizations and achieving the below results with the latest APM automation tools:

- End-to-End Process Automation with unified orchestration and collaboration, combining multiple automation solutions into one process with integrated workflow capabilities and end-to-end reporting across multiple and parallel workflows. 

- First level staff are enabled to perform automated diagnostics and remediation in response to both inbound tickets and analytic trends and notifications picked up by performance reporting tools.

- Associate skillsets are being normalized with automations that don’t require advanced or specialized skills to create. Relevant knowledge documents are “pushed out” based on incident/issue type, and decision tree technology guides IT/First-Level technicians to relevant information and automations based on the symptoms presented.

- Improved application availability for end-users is created by reducing downtime cycles from hours to minutes and reducing the number of emergency bridge calls required to resolve issues.

- Compliance and auditing (CoBIT/SOX) are improved with analytics for audit trails and SLA compliance.

- Reduced average Mean Time to Resolution (MTTR) can be seen through enabled engineers.

- Application teams can run tests outside of their application and assign fault to those groups without a bridge call.  

- Problem solving steps are automatically executed in parallel instead of serial manual execution. Issues are no longer fixed by the engineer logging into tool #one, executing a series of commands, interpreting results, then logging into tool #two, executing commands, interpret results, etc. Instead, the engineer runs a series of commands simultaneously at the push of a button, and gets back results in a simple to understand format.

Application Performance Management entails complex processes that can and should be automated. But rather than eliminate human touch, automation tools should empower associates to execute the best possible automations with the collective, real-time knowledge of the organization.

When organizations implement automation technologies that leave human collaboration out of the process, it isn’t difficult for the “less-than-best” process to be followed, requiring multiple teams to be thrown into fire-fighting mode. Improved collaboration on processes allows more time to be spent on strategic initiatives and proactive management of applications. Not only will the entire organization benefit, so will the customers. And making and keeping customers happy should be the top goal for every organization.

ABOUT Payal Kindiger

As Executive Vice President of Marketing and Managed Services for gen-E, Payal Kindiger leads the company’s branding and marketing efforts, inside sales operations, organizational strategy, customer care, and managed services offerings. Prior to joining gen-E in 2003, she was a member of the management team at Deloitte and Touche. She has worked with several Fortune 500 companies and has managed client-service projects in IT business process re-engineering and organizational development across a number of industries. 

Related Links:

www.gen-e.com

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 ...