Skip to main content

Transforming Network Remediation with a Closed-Loop Approach

Sandhya Saravanan
ManageEngine

The modern business world relies heavily on robust and efficient network infrastructures. However, minor network hiccups can quickly become significant financial losses and damage to a company's reputation. Faced with this pressure, organizations often gravitate towards a reactive approach, instinctively increasing staffing levels, which can escalate costs and potentially lead to an inefficient allocation of resources.

The escalating costs of network infrastructure maintenance, including the personnel required to manage them, pose a significant challenge to cost efficiency. While skilled network engineers can be trained and developed, the modern IT landscape, characterized by rapid advancements in applications, cloud technologies, and workloads, demands an unprecedented level of agility and responsiveness. In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance.

This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks.

Closed-Loop Remediation

Closed-loop remediation is an automated, self-correcting process that continuously monitors, detects, and resolves network issues. This approach leverages automation to minimize human intervention while incorporating essential human oversight to ensure the complete and accurate resolution of network problems.

What Makes It a Closed-Loop and How Does It Work?

While resembling traditional network management approaches, closed-loop remediation leverages observability to significantly enhance capabilities. By eliminating blind spots and providing comprehensive network visibility, observability empowers automated systems to independently identify, diagnose, and resolve issues with greater speed and accuracy.

There are similar steps that goes into closed-loop remediation and managing an IT network. The steps include:

Monitoring: Continuous monitoring of the network environment, including devices, applications, and traffic, to collect telemetry data for performance analysis, error detection, and resource utilization assessment.

Detection: The system generates an alert upon the detection of anomalies or the breaching of predefined thresholds, signifying a potential issue.

Analysis: The system effectively pinpoints the root cause of issues by analyzing the collected data.

Remediation: The system autonomously executes corrective actions based on preconfigured rules, workflows, and automated scripts. These actions may include restarting a switch, rerouting traffic, or applying necessary configuration changes.

Verification: The system continues to monitor network performance after implementing remediation steps to ensure that the issue has been resolved and that normal network operation has been restored.

Feedback Loop: The verification step forms a crucial feedback loop in this process. If the issue persists after remediation, the system intelligently adapts by attempting alternative solutions or escalating the issue for human intervention.

True to its name, closed-loop remediation operates as a continuous cycle. By iteratively monitoring, detecting, remediating, and verifying, the system continuously learns and adapts, ensuring that network issues are resolved effectively and efficiently.

What Happens in the Absence of Closed-Loop Remediation?

In the absence of closed-loop remediation, organizations heavily rely on manual intervention to address network issues. IT personnel manually identify problems through monitoring tools or user reports, diagnose the root cause, and then implement manual remediation steps. This approach often lacks a critical verification step, leaving uncertainty as to whether the attempted fix was successful

Benefits of Closed-Loop Remediation

Quick response time: Automated remediation enables near real-time responses to network issues, significantly minimizing downtime and service disruptions. This rapid response mechanism leads to enhanced network reliability and performance.

Improved efficiency: By eliminating the need for manual hand offs between teams and tools, closed-loop automation streamlines the entire remediation workflow, from issue detection to resolution. This fosters improved collaboration and efficiency, enabling faster and more effective resolution of network issues.

Consistent improvement: By analyzing historical data and performance metrics, IT admins can identify patterns and trends in network incidents. This enables proactive identification and remediation of underlying issues before they escalate, fostering a predictive maintenance approach that optimizes network performance over time.

Minimal human error: By adhering to predefined workflows and rulesets, automated remediation minimizes the risk of human error, ensuring consistent and accurate execution of corrective actions. This significantly reduces the likelihood of errors that could further destabilize the network.

Gain full-stack visibility, empower your IT teams, and enhance reliability with OpManager Plus. Embrace the future of IT observability and revolutionize your IT infrastructure. Schedule a demo or explore our free trial today!

Sandhya Saravanan is a Product Marketer at ManageEngine

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

Transforming Network Remediation with a Closed-Loop Approach

Sandhya Saravanan
ManageEngine

The modern business world relies heavily on robust and efficient network infrastructures. However, minor network hiccups can quickly become significant financial losses and damage to a company's reputation. Faced with this pressure, organizations often gravitate towards a reactive approach, instinctively increasing staffing levels, which can escalate costs and potentially lead to an inefficient allocation of resources.

The escalating costs of network infrastructure maintenance, including the personnel required to manage them, pose a significant challenge to cost efficiency. While skilled network engineers can be trained and developed, the modern IT landscape, characterized by rapid advancements in applications, cloud technologies, and workloads, demands an unprecedented level of agility and responsiveness. In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance.

This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks.

Closed-Loop Remediation

Closed-loop remediation is an automated, self-correcting process that continuously monitors, detects, and resolves network issues. This approach leverages automation to minimize human intervention while incorporating essential human oversight to ensure the complete and accurate resolution of network problems.

What Makes It a Closed-Loop and How Does It Work?

While resembling traditional network management approaches, closed-loop remediation leverages observability to significantly enhance capabilities. By eliminating blind spots and providing comprehensive network visibility, observability empowers automated systems to independently identify, diagnose, and resolve issues with greater speed and accuracy.

There are similar steps that goes into closed-loop remediation and managing an IT network. The steps include:

Monitoring: Continuous monitoring of the network environment, including devices, applications, and traffic, to collect telemetry data for performance analysis, error detection, and resource utilization assessment.

Detection: The system generates an alert upon the detection of anomalies or the breaching of predefined thresholds, signifying a potential issue.

Analysis: The system effectively pinpoints the root cause of issues by analyzing the collected data.

Remediation: The system autonomously executes corrective actions based on preconfigured rules, workflows, and automated scripts. These actions may include restarting a switch, rerouting traffic, or applying necessary configuration changes.

Verification: The system continues to monitor network performance after implementing remediation steps to ensure that the issue has been resolved and that normal network operation has been restored.

Feedback Loop: The verification step forms a crucial feedback loop in this process. If the issue persists after remediation, the system intelligently adapts by attempting alternative solutions or escalating the issue for human intervention.

True to its name, closed-loop remediation operates as a continuous cycle. By iteratively monitoring, detecting, remediating, and verifying, the system continuously learns and adapts, ensuring that network issues are resolved effectively and efficiently.

What Happens in the Absence of Closed-Loop Remediation?

In the absence of closed-loop remediation, organizations heavily rely on manual intervention to address network issues. IT personnel manually identify problems through monitoring tools or user reports, diagnose the root cause, and then implement manual remediation steps. This approach often lacks a critical verification step, leaving uncertainty as to whether the attempted fix was successful

Benefits of Closed-Loop Remediation

Quick response time: Automated remediation enables near real-time responses to network issues, significantly minimizing downtime and service disruptions. This rapid response mechanism leads to enhanced network reliability and performance.

Improved efficiency: By eliminating the need for manual hand offs between teams and tools, closed-loop automation streamlines the entire remediation workflow, from issue detection to resolution. This fosters improved collaboration and efficiency, enabling faster and more effective resolution of network issues.

Consistent improvement: By analyzing historical data and performance metrics, IT admins can identify patterns and trends in network incidents. This enables proactive identification and remediation of underlying issues before they escalate, fostering a predictive maintenance approach that optimizes network performance over time.

Minimal human error: By adhering to predefined workflows and rulesets, automated remediation minimizes the risk of human error, ensuring consistent and accurate execution of corrective actions. This significantly reduces the likelihood of errors that could further destabilize the network.

Gain full-stack visibility, empower your IT teams, and enhance reliability with OpManager Plus. Embrace the future of IT observability and revolutionize your IT infrastructure. Schedule a demo or explore our free trial today!

Sandhya Saravanan is a Product Marketer at ManageEngine

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...