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IT Can't Afford to be Static - It's Time to Automate Visibility

Ananda Rajagopal

As any network administrator can tell you, network traffic doesn't stand still. It is constantly changing and increasing in complexity. Networks have fundamentally changed, and the demands put on them by new technology, customers, mobility, and other factors are forcing IT to develop networks that are more agile and dynamic than ever before. While it seems like IT departments are bombarded with new challenges, there are three major trends that are making it difficult to gain visibility into networks: the increased adoption of virtualized infrastructure, enterprise mobility and the rise in encrypted traffic.

Virtualization and associated software-defined networking (SDN) approaches have created tremendous change in the data center, while mobility and encryption have created blind spots in infrastructure that traditional monitoring tools do not recognize. Compounding this problem is the fact that network administrators have been compelled to meet the needs of an organization's cybersecurity initiatives – which requires that they have full visibility into their infrastructure – and it's clear how difficult the problem they are facing is. Simply put, network administrators need to be able to see every packet to guarantee the performance and security of their networks, but the accelerated rate of change, and the complexities that has wrought, have made it nearly impossible.

Since networks and infrastructure are constantly changing, the methods that are used to gain visibility into them cannot afford to be static. When done well, visibility shines light on blind spots, enables detection of anomalous behavior and gives administrators the power to fix network and application issues proactively before they become problems for end users. But, giving administrators the power to be proactive is not enough in today's complex environment. It is no longer enough to simply point to a network bottleneck or send an alert for a spike in bandwidth demand – visibility must be automated so that the information is shared instantly. Manual intervention is a point of failure for network operations and security operations teams, and can be eliminated if the tools we use for visibility are designed to take action.

To automate visibility, we must architect visibility as a critical layer of infrastructure. Once designed in this fashion, an administrator is empowered with the ability to intelligently deliver any portion of network traffic to as many appliances and tools that need to monitor and analyze it. The administrator can use policies to select specific traffic that needs to be delivered to each of these tools. Such an architectural approach to visibility has the additional benefit of abstracting the operational tools needed to secure and manage a network from the specifics of the underlying network. Once such a layer is created, all security and operational tools can get access to critical network traffic from anywhere in the infrastructure. Further, when the intelligence derived from visibility is united with the rest of the network and security infrastructure, it is possible to automate policy management so that the tools can programmatically control the information they receive from the Visibility Fabric. Such automation improves responsiveness and effectiveness, simplifies tasks and establishes a framework for continuous monitoring and analytics of the infrastructure.

Technology will continue to be transformative – in the data center and beyond. No one can afford to sit still in this environment, least of all IT departments. Automating visibility is a critical step in getting control of the dramatic changes affecting infrastructure, and one that should be taken sooner rather than later – the next big challenge is likely right around the corner.

Ananda Rajagopal is VP of Product Management at Gigamon.

Hot Topics

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...

IT Can't Afford to be Static - It's Time to Automate Visibility

Ananda Rajagopal

As any network administrator can tell you, network traffic doesn't stand still. It is constantly changing and increasing in complexity. Networks have fundamentally changed, and the demands put on them by new technology, customers, mobility, and other factors are forcing IT to develop networks that are more agile and dynamic than ever before. While it seems like IT departments are bombarded with new challenges, there are three major trends that are making it difficult to gain visibility into networks: the increased adoption of virtualized infrastructure, enterprise mobility and the rise in encrypted traffic.

Virtualization and associated software-defined networking (SDN) approaches have created tremendous change in the data center, while mobility and encryption have created blind spots in infrastructure that traditional monitoring tools do not recognize. Compounding this problem is the fact that network administrators have been compelled to meet the needs of an organization's cybersecurity initiatives – which requires that they have full visibility into their infrastructure – and it's clear how difficult the problem they are facing is. Simply put, network administrators need to be able to see every packet to guarantee the performance and security of their networks, but the accelerated rate of change, and the complexities that has wrought, have made it nearly impossible.

Since networks and infrastructure are constantly changing, the methods that are used to gain visibility into them cannot afford to be static. When done well, visibility shines light on blind spots, enables detection of anomalous behavior and gives administrators the power to fix network and application issues proactively before they become problems for end users. But, giving administrators the power to be proactive is not enough in today's complex environment. It is no longer enough to simply point to a network bottleneck or send an alert for a spike in bandwidth demand – visibility must be automated so that the information is shared instantly. Manual intervention is a point of failure for network operations and security operations teams, and can be eliminated if the tools we use for visibility are designed to take action.

To automate visibility, we must architect visibility as a critical layer of infrastructure. Once designed in this fashion, an administrator is empowered with the ability to intelligently deliver any portion of network traffic to as many appliances and tools that need to monitor and analyze it. The administrator can use policies to select specific traffic that needs to be delivered to each of these tools. Such an architectural approach to visibility has the additional benefit of abstracting the operational tools needed to secure and manage a network from the specifics of the underlying network. Once such a layer is created, all security and operational tools can get access to critical network traffic from anywhere in the infrastructure. Further, when the intelligence derived from visibility is united with the rest of the network and security infrastructure, it is possible to automate policy management so that the tools can programmatically control the information they receive from the Visibility Fabric. Such automation improves responsiveness and effectiveness, simplifies tasks and establishes a framework for continuous monitoring and analytics of the infrastructure.

Technology will continue to be transformative – in the data center and beyond. No one can afford to sit still in this environment, least of all IT departments. Automating visibility is a critical step in getting control of the dramatic changes affecting infrastructure, and one that should be taken sooner rather than later – the next big challenge is likely right around the corner.

Ananda Rajagopal is VP of Product Management at Gigamon.

Hot Topics

The Latest

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...