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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.

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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

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...