Skip to main content

In Hyperscale Environments Network Visibility Remains Vital

Mike Heumann

Hyperscale infrastructure was once widely considered to be designed for large, web-facing organizations or top-tier colocation and cloud providers. But as the enterprise starts to confront the realities of big data and mobile, dynamic workloads, it seems inevitable that even medium-sized organizations will have to encounter hyperscale environments at some point, either as greenfield deployments or in a hosted/cloud capacity – and we’re seeing this come to fruition. According to an October 2014 Emulex survey of more than 1,600 US and European IT professionals who provided insight into their enterprise data center networking environments, 57 percent of respondents have adopted hyperscale networking environments.

What are the ramifications of this? More than half of these (51 percent) named increasing bandwidth as a major challenge in moving to hyperscale environments, which is driving massive network upgrades. In fact, more than 77 percent of respondents running hyperscale environments say the move to the cloud has already necessitated the upgrade of their networks to at least 40Gb Ethernet. Big data and analytics are driving high volumes of data storage, capture, movement and archiving which all drive an increased need for both higher bandwidth and lower latency on 10Gb and 40Gb Ethernet using RDMA.

We’re seeing hyperscale network environments grow across enterprises because it has a number of benefits: It can be a key piece of smarter, more manageable application ecosystems. On a network level, hyperscale can also aid business continuity and disaster recovery efforts by providing redundant failover architecture and rapid recovery. Hyperscale can also accentuate the benefits that technologies like virtualization and software-defined networking provide, making it a potentially vital configuration in the more scalable data center machinery of the future.

As we know, the loss of application or network services for even a few minutes can mean huge and immediate revenue losses, and can impact long-term customer loyalty. As many enterprises go through these rapid network changes and as hyperscale environments become more common, it is important that IT networking and application staffs prioritize network visibility as a means to identify any network issues that need to be identified quickly. Many organizations are struggling to accurately monitor increasingly complex enterprise networks as they shift to 10Gb Ethernet or even higher speeds.  

For those running hyperscale environments, 97 percent said it has necessitated a move to 10GbE, 40GbE or higher speeds to meet demands of high-performance applications such as big data, analytics and content distribution, compared to only 48 percent of respondents from non-hyperscale organizations. As a result, the underlying communication networks matter, and perhaps not surprisingly, capturing network behavior for incident detection and monitoring network flows for anomalous behavior are just as important. The ability to do both of these is essential in many high-speed networks (such as trading platforms and e-commerce portals) in order to spot cyber threats like DDoS attacks. The migration to larger, faster networks only exacerbates the threat of missing these attacks, and increases the need for clear, deep visibility.

Mike Heumann is VP of Product Marketing and Alliances at Emulex.

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 ...

In Hyperscale Environments Network Visibility Remains Vital

Mike Heumann

Hyperscale infrastructure was once widely considered to be designed for large, web-facing organizations or top-tier colocation and cloud providers. But as the enterprise starts to confront the realities of big data and mobile, dynamic workloads, it seems inevitable that even medium-sized organizations will have to encounter hyperscale environments at some point, either as greenfield deployments or in a hosted/cloud capacity – and we’re seeing this come to fruition. According to an October 2014 Emulex survey of more than 1,600 US and European IT professionals who provided insight into their enterprise data center networking environments, 57 percent of respondents have adopted hyperscale networking environments.

What are the ramifications of this? More than half of these (51 percent) named increasing bandwidth as a major challenge in moving to hyperscale environments, which is driving massive network upgrades. In fact, more than 77 percent of respondents running hyperscale environments say the move to the cloud has already necessitated the upgrade of their networks to at least 40Gb Ethernet. Big data and analytics are driving high volumes of data storage, capture, movement and archiving which all drive an increased need for both higher bandwidth and lower latency on 10Gb and 40Gb Ethernet using RDMA.

We’re seeing hyperscale network environments grow across enterprises because it has a number of benefits: It can be a key piece of smarter, more manageable application ecosystems. On a network level, hyperscale can also aid business continuity and disaster recovery efforts by providing redundant failover architecture and rapid recovery. Hyperscale can also accentuate the benefits that technologies like virtualization and software-defined networking provide, making it a potentially vital configuration in the more scalable data center machinery of the future.

As we know, the loss of application or network services for even a few minutes can mean huge and immediate revenue losses, and can impact long-term customer loyalty. As many enterprises go through these rapid network changes and as hyperscale environments become more common, it is important that IT networking and application staffs prioritize network visibility as a means to identify any network issues that need to be identified quickly. Many organizations are struggling to accurately monitor increasingly complex enterprise networks as they shift to 10Gb Ethernet or even higher speeds.  

For those running hyperscale environments, 97 percent said it has necessitated a move to 10GbE, 40GbE or higher speeds to meet demands of high-performance applications such as big data, analytics and content distribution, compared to only 48 percent of respondents from non-hyperscale organizations. As a result, the underlying communication networks matter, and perhaps not surprisingly, capturing network behavior for incident detection and monitoring network flows for anomalous behavior are just as important. The ability to do both of these is essential in many high-speed networks (such as trading platforms and e-commerce portals) in order to spot cyber threats like DDoS attacks. The migration to larger, faster networks only exacerbates the threat of missing these attacks, and increases the need for clear, deep visibility.

Mike Heumann is VP of Product Marketing and Alliances at Emulex.

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 ...