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NetOps: A Key Element for Every Enterprise

Clayton Dukes

You've heard of DevOps and SecOps, but NetOps?

NetOps is a natural progression of legacy Network Operations to foster more efficient and resilient infrastructures through automation and intelligence. NetOps provides enhanced operational awareness and a dramatic reduction in Mean Time To Restore (MTTR) during outages.

When the network is down or degraded, that's when the stress begins for Network Operations teams. NetOps provides the means to detect and remediate network issues as they happen, in real time.

The efficacy of NetOps personnel is reliant upon understanding five key elements of a NetOps Platform and how to best utilize and implement each:

1. Service Assurance

Until recently, it was not possible to keep up with the massive amount of data generated from so many disparate sources of information. This led to Network Management Architectures which contained multiple silos of information making it almost impossible to correlate and enrich data because teams could only see part of the picture and sometimes had no visibility at all into service affecting issues. Bringing your entire infrastructure's telemetry under management in one place provides the ability to quickly identify actionable events.

2. Service Automation

Many of today's network teams are still manually remediating issues because they either 1) don't have the mechanisms to automate it, or 2) they don't realize that it can be automated.

When given the ability to have real-time remediation, the scenarios can be potentially endless, therefore, any problem that can workflow a solution should be automated. This automation allows NetOps to construct a trigger that can automatically execute and resolve problems in real-time before anyone knows there was an issue and removes the need for repetitive tasks which eliminates human error.

3. Event Enrichment

When making informed decisions about what to do during the automation process, event enrichment is used to add a layer of intelligence to information about affected devices. When an event comes into a NetOps system, having the ability to modify the payload, add tags, go to other sources of information and look up details such as device location, SLAs, Change Control policies, contact information or anything else that can be used to further group and identify the affected entity greatly reduces the time needed to investigate and correlate service impacting events.

4. Extensibility and Scale

Being able to scale the platform provides the ability to deal with bursts of event streams when anomalistic behavior occurs. Extensibility allows for extraction and tracking of arbitrary data from incoming events (device types, users, locations, failed login names, IP sources/destination ports, GeoIP tracking, etc.) and provides greater visibility for operational awareness.

5. Agnostic Functions

NetOps are capable of ingesting data from any vendor hardware or software messaging platform which can be used to reap the benefits of automatically identifying actionable events, real-time automatic remediation, and assured availability. Agnostic functionality allows for different areas of the organization to utilize a platform without concern for operational effectiveness. Being able to provide operations insight, coupled with automatic remediation and event enrichment frees up engineering staff to do their job instead of repairing known, repeatable, processes.

If you can link automation of the network to all the interdependent steps of application and service delivery, you have the potential for radical change regarding how IT and networks operate and how users will experience services.

Hot Topics

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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 ...

NetOps: A Key Element for Every Enterprise

Clayton Dukes

You've heard of DevOps and SecOps, but NetOps?

NetOps is a natural progression of legacy Network Operations to foster more efficient and resilient infrastructures through automation and intelligence. NetOps provides enhanced operational awareness and a dramatic reduction in Mean Time To Restore (MTTR) during outages.

When the network is down or degraded, that's when the stress begins for Network Operations teams. NetOps provides the means to detect and remediate network issues as they happen, in real time.

The efficacy of NetOps personnel is reliant upon understanding five key elements of a NetOps Platform and how to best utilize and implement each:

1. Service Assurance

Until recently, it was not possible to keep up with the massive amount of data generated from so many disparate sources of information. This led to Network Management Architectures which contained multiple silos of information making it almost impossible to correlate and enrich data because teams could only see part of the picture and sometimes had no visibility at all into service affecting issues. Bringing your entire infrastructure's telemetry under management in one place provides the ability to quickly identify actionable events.

2. Service Automation

Many of today's network teams are still manually remediating issues because they either 1) don't have the mechanisms to automate it, or 2) they don't realize that it can be automated.

When given the ability to have real-time remediation, the scenarios can be potentially endless, therefore, any problem that can workflow a solution should be automated. This automation allows NetOps to construct a trigger that can automatically execute and resolve problems in real-time before anyone knows there was an issue and removes the need for repetitive tasks which eliminates human error.

3. Event Enrichment

When making informed decisions about what to do during the automation process, event enrichment is used to add a layer of intelligence to information about affected devices. When an event comes into a NetOps system, having the ability to modify the payload, add tags, go to other sources of information and look up details such as device location, SLAs, Change Control policies, contact information or anything else that can be used to further group and identify the affected entity greatly reduces the time needed to investigate and correlate service impacting events.

4. Extensibility and Scale

Being able to scale the platform provides the ability to deal with bursts of event streams when anomalistic behavior occurs. Extensibility allows for extraction and tracking of arbitrary data from incoming events (device types, users, locations, failed login names, IP sources/destination ports, GeoIP tracking, etc.) and provides greater visibility for operational awareness.

5. Agnostic Functions

NetOps are capable of ingesting data from any vendor hardware or software messaging platform which can be used to reap the benefits of automatically identifying actionable events, real-time automatic remediation, and assured availability. Agnostic functionality allows for different areas of the organization to utilize a platform without concern for operational effectiveness. Being able to provide operations insight, coupled with automatic remediation and event enrichment frees up engineering staff to do their job instead of repairing known, repeatable, processes.

If you can link automation of the network to all the interdependent steps of application and service delivery, you have the potential for radical change regarding how IT and networks operate and how users will experience services.

Hot Topics

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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 ...