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5 Critical Network Management Capabilities for Modern Enterprises

Jay Botelho

Gone are the days when enterprises viewed the network as an assortment of technology infrastructure and assets. It has become a critical component of modern corporate strategy in the digital age, one capable of supporting and driving business operations and growth. The consequences of any kind of IT disruption are severe.

In fact, an hour of downtime can cost businesses anywhere from $300,000 to $540,000 in total, according to Gartner. That's an average of $5,600 per minute (at the low end!). As such, today's IT teams must proactively boost network performance and reliability. Doing so, however, is easier said than done.


Network management teams routinely perform several activities to plan, deploy, upgrade, troubleshoot, maintain, and monitor the network. These processes are all tremendously data-driven and dependent on your team's visibility into and understanding of the data coming from applications, network devices and the traffic traversing the network.

There are many challenges when it comes to collecting, organizing and analyzing this data. The volume, speed and variety of network data can make it difficult and time-consuming to analyze. Today's enterprise networks are vast and intricate, and can obfuscate the data and its context. And the sheer variety of network domains and architectures today makes data analysis much more challenging, especially with specialized tools or siloed data collection.

So what can you do in the face of all this complexity to ensure network experiences and performance levels that satisfy the needs of the business?

The truth is, there's not much you can do if you lack the fundamental capabilities today's digital enterprises require.

Here are five key questions to ask that will serve as a starting point for ensuring your team is up to the task:

1. Can you monitor the entire network?

Today's enterprise IT environments span a wide range of domains, including LAN, WAN, data centers, SD-WAN, cloud, Wi-Fi, applications and distributed campuses. Do you have the visibility you need to monitor and manage the entire hybrid network from end to end, at scale?

Siloed visibility can be terminal in the long run. If you're experiencing performance issues with a specific application or site, the effects can extend across any number of other domains. With so many moving parts to monitor, and blind spots can prevent you from tracking down the root cause and preserving business-critical digital experiences.

Your team must be able to collect and correlate performance data throughout the entire hybrid network. Measuring metrics such as top network users, availability, common traffic patterns, application jitter, latency, and loss, and more will help you establish baseline and trending metrics. This will ensure you can proactively identify abnormalities that might cause downtime or performance issues that impact the business.

2. Do you measure and correlate granular network traffic analytics?

Whether users access key applications hosted in the cloud or on-premises, it's critical to correlate real-time application performance data with end-user experience analytics. This way, your team can avoid analyzing every issue (and false-positive or alarm overloads) that might come up, and focus their valuable time on solving problems that genuinely impact users.

The best way to establish this correlation is with deep, real-time processing and packet-by-packet analysis that present network transactions with performance insights, even for complex, multi-tiered applications. With this level of visibility and network domain awareness, your team should quickly isolate and resolve network performance issues.

3. Are there any application visibility gaps?

There's no way to support a seamless, high-performance digital experience without granular application visibility. Can your team effectively monitor and analyze application paths?

Are you able to discern when network devices cause application performance issues?

These are critical capabilities that require application detailed performance baselines and usage insights and packet-by-packet analysis. Any application monitoring deficiencies can dramatically extend the time it takes you to identify and resolve performance problems that degrade user experiences.

4. Can your team handle tens of thousands of devices?

Large-scale performance management across numerous devices and distributed environments is a business requirement for most enterprises today. Can your team maintain performance at this scale securely and without latency?

If not, this should be a top priority. You must also ensure you're capable of maintaining performance as device and infrastructure monitoring requirements expand due to new computing environments such as SD-WAN deployments, multi-vendor WANs and new public or private cloud implementations.

You need to be able to monitor all current environments and devices, as well as have the network visibility you'll need to support capacity planning to avoid both over- and under-provisioning resources as the business and its IT needs grow.

5. Is AIOps a priority today?

Scale-related performance is critical. If your team hasn't incorporated AIOps to detect, correlate and visualize anomalies, you're stuck in a reactive stance. How can you effectively manage the increasingly complex IT domains you're monitoring without capitalizing on machine learning (ML) to understand and leverage big data trends?

ML algorithms can support critical performance corrections, including determining which voice traffic to prioritize, when to throttle bandwidth, and whether to block a user's access. AIOps can alleviate many of the time-consuming manual components involved in network performance management by detecting any departures from baseline metrics at a level of speed and accuracy human engineers simply can't.

Questions Worth Asking

Networks have never been more complex, and the need for reliable network performance has never been greater. Demands and challenges for enterprise networks and the IT teams that support them will continue to change over time, but your desire to continually re-examine and evolve your approach should remain constant.

To better position your team and business for success in 2021, take a step back and explore the above network performance management considerations. Identify any gaps and assemble a strategy for building any key capabilities that might be absent. Doing so will help ensure you're able to effectively monitor and manage your entire network, proactively remediate performance issues and incidents, improve user experiences and support your business as it grows.

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5 Critical Network Management Capabilities for Modern Enterprises

Jay Botelho

Gone are the days when enterprises viewed the network as an assortment of technology infrastructure and assets. It has become a critical component of modern corporate strategy in the digital age, one capable of supporting and driving business operations and growth. The consequences of any kind of IT disruption are severe.

In fact, an hour of downtime can cost businesses anywhere from $300,000 to $540,000 in total, according to Gartner. That's an average of $5,600 per minute (at the low end!). As such, today's IT teams must proactively boost network performance and reliability. Doing so, however, is easier said than done.


Network management teams routinely perform several activities to plan, deploy, upgrade, troubleshoot, maintain, and monitor the network. These processes are all tremendously data-driven and dependent on your team's visibility into and understanding of the data coming from applications, network devices and the traffic traversing the network.

There are many challenges when it comes to collecting, organizing and analyzing this data. The volume, speed and variety of network data can make it difficult and time-consuming to analyze. Today's enterprise networks are vast and intricate, and can obfuscate the data and its context. And the sheer variety of network domains and architectures today makes data analysis much more challenging, especially with specialized tools or siloed data collection.

So what can you do in the face of all this complexity to ensure network experiences and performance levels that satisfy the needs of the business?

The truth is, there's not much you can do if you lack the fundamental capabilities today's digital enterprises require.

Here are five key questions to ask that will serve as a starting point for ensuring your team is up to the task:

1. Can you monitor the entire network?

Today's enterprise IT environments span a wide range of domains, including LAN, WAN, data centers, SD-WAN, cloud, Wi-Fi, applications and distributed campuses. Do you have the visibility you need to monitor and manage the entire hybrid network from end to end, at scale?

Siloed visibility can be terminal in the long run. If you're experiencing performance issues with a specific application or site, the effects can extend across any number of other domains. With so many moving parts to monitor, and blind spots can prevent you from tracking down the root cause and preserving business-critical digital experiences.

Your team must be able to collect and correlate performance data throughout the entire hybrid network. Measuring metrics such as top network users, availability, common traffic patterns, application jitter, latency, and loss, and more will help you establish baseline and trending metrics. This will ensure you can proactively identify abnormalities that might cause downtime or performance issues that impact the business.

2. Do you measure and correlate granular network traffic analytics?

Whether users access key applications hosted in the cloud or on-premises, it's critical to correlate real-time application performance data with end-user experience analytics. This way, your team can avoid analyzing every issue (and false-positive or alarm overloads) that might come up, and focus their valuable time on solving problems that genuinely impact users.

The best way to establish this correlation is with deep, real-time processing and packet-by-packet analysis that present network transactions with performance insights, even for complex, multi-tiered applications. With this level of visibility and network domain awareness, your team should quickly isolate and resolve network performance issues.

3. Are there any application visibility gaps?

There's no way to support a seamless, high-performance digital experience without granular application visibility. Can your team effectively monitor and analyze application paths?

Are you able to discern when network devices cause application performance issues?

These are critical capabilities that require application detailed performance baselines and usage insights and packet-by-packet analysis. Any application monitoring deficiencies can dramatically extend the time it takes you to identify and resolve performance problems that degrade user experiences.

4. Can your team handle tens of thousands of devices?

Large-scale performance management across numerous devices and distributed environments is a business requirement for most enterprises today. Can your team maintain performance at this scale securely and without latency?

If not, this should be a top priority. You must also ensure you're capable of maintaining performance as device and infrastructure monitoring requirements expand due to new computing environments such as SD-WAN deployments, multi-vendor WANs and new public or private cloud implementations.

You need to be able to monitor all current environments and devices, as well as have the network visibility you'll need to support capacity planning to avoid both over- and under-provisioning resources as the business and its IT needs grow.

5. Is AIOps a priority today?

Scale-related performance is critical. If your team hasn't incorporated AIOps to detect, correlate and visualize anomalies, you're stuck in a reactive stance. How can you effectively manage the increasingly complex IT domains you're monitoring without capitalizing on machine learning (ML) to understand and leverage big data trends?

ML algorithms can support critical performance corrections, including determining which voice traffic to prioritize, when to throttle bandwidth, and whether to block a user's access. AIOps can alleviate many of the time-consuming manual components involved in network performance management by detecting any departures from baseline metrics at a level of speed and accuracy human engineers simply can't.

Questions Worth Asking

Networks have never been more complex, and the need for reliable network performance has never been greater. Demands and challenges for enterprise networks and the IT teams that support them will continue to change over time, but your desire to continually re-examine and evolve your approach should remain constant.

To better position your team and business for success in 2021, take a step back and explore the above network performance management considerations. Identify any gaps and assemble a strategy for building any key capabilities that might be absent. Doing so will help ensure you're able to effectively monitor and manage your entire network, proactively remediate performance issues and incidents, improve user experiences and support your business as it grows.

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

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 ...