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Top Transformative Technology Trends in Networking for 2016

Pete Goldin
APMdigest

The Year 2015 has seen organizations disrupting their markets with the digital transformation of their businesses as they embrace 3rd Platform computing and New IP networking strategies that have helped them become leaders in new markets. According to Brocade, moving into 2016, more businesses are expected to leverage smart machines and transformative technologies to give them a clear competitive advantage.

Brocade outlines the top transformative technology trends in networking to watch for in 2016 and beyond:

1. The cloud will gain even greater traction

According to IDC, more than half of all IT spending is going to be on the 3rd Platform, otherwise known as cloud-based technologies, and that figure will surpass 60 percent of all IT spending by 2020. The migration of old, legacy IP network architectures to New IP networks will accelerate, reaching near-mainstream adoption as enterprises and service providers transform their networks into an open, software-driven platform for innovation and a competitive edge.

2. Software-based networks are clearly the future

Over the past year, software has transformed the data center and networks in general, with service providers and enterprises turning to Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) to create new services quickly, scale them easily, and deliver them in user-centric ways. 2016 will bring about the expanded adoption of innovative, open, and automated software networking platforms as enterprises and service providers migrate to New IP networks. The increasing deployment of x86 server architecture will accelerate this transformation, replacing specialized networking hardware in multiple network roles, such as Application Delivery Controllers (ADCs). ADCs have already begun transforming to a virtual (vADC) model to help enterprises and services providers scale capacity on demand to handle peak workloads. Software is increasingly permeating every aspect of this virtualization transformation.

3. The importance of security will skyrocket

Organizations operating in today's New IP networking environment face increasing demands for cloud-based applications and need to support social, mobile, and Big Data initiatives. However, security-related attacks and breaches continue to impede the delivery of services and create additional challenges to network and service reliability. New IP networking solutions allow organizations to deploy more advanced security that is designed into the network from the start, not bolted on at edge to existing infrastructure. The network itself can be pervasively vigilant and track behavior on and not just access to the network, to quickly identify and prevent unwanted activity. Security services can be virtualized, enabling organizations to distribute security wherever it is needed and customize security at various levels -- by geography or location, function, group or individual, or application.

4. DevOps will play a much larger role

DevOps, or any agile software development methodology that closely matches services with business demands, will gain widespread influence and uptake among both enterprises and service providers as a way to ensure they remain competitive. According to IDC, enterprises pursuing digital transformation strategies will more than double their software development capabilities by 2018. Companies that build and use field-focused development teams that operate without the constraints of rigid traditional product development processes will have a significant advantage in customer-focused innovation. This advantage extends to both the speed of development and to customer intimacy and retention.

5. Big Data and analytics will get even bigger

Organizations that are able to take advantage of the explosion of data will seize the day, and many of these disrupters will be startups that use Big Data to make strategic decisions based on analytics. As data gets increasingly colossal, so do the opportunities, skillsets, and demand for analytic and cognitive services across industries. The ability to derive intelligence from Big Data in real time will create a distinct competitive edge for any business.

6. Machine learning takes off

The advent of machine learning is the computing breakthrough made possible by Big Data. The emergence of algorithms that can learn from and even make predictions based on the enormous amounts of data and meta-data that are generated, transmitted, and stored via networks will change the world of data centers and networks beginning in 2016. This process is already underway, as facial and speech recognition are changing the worlds of consumer electronics and the cloud services that use them, and anomaly detection is quickly becoming a crucial part of network security.

7. The rise of the telco with virtual architecture

Mobile Network Operators (MNOs) that have been struggling to keep up with fast-changing customer needs and market opportunities will be compelled to embrace SDN and NFV in 2016. The risk of falling behind is set to intensify with each passing day as carriers and service providers that embrace change will become the winners in the Internet of Things (IoT) ecosystem and 5G race by 2020.

8. The technical talent crunch gets serious

Vendors, service providers, and user organizations are all competing for a limited pool of next-generation talent with the required coding and technical skills. The talent crunch issue will become increasingly acute, and organizations will have to rethink their human resource strategies and policies in order to attract, develop, and retain strong talent. Technical qualifications that were only recently seen as de facto passports to important positions in networking will change in the face of self-provisioning and self-programming networks. Increasingly, critical networking positions will begin to require advanced analytical and coding skills that are in very short supply today.

Pete Goldin is Editor and Publisher of APMdigest

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 ...

Top Transformative Technology Trends in Networking for 2016

Pete Goldin
APMdigest

The Year 2015 has seen organizations disrupting their markets with the digital transformation of their businesses as they embrace 3rd Platform computing and New IP networking strategies that have helped them become leaders in new markets. According to Brocade, moving into 2016, more businesses are expected to leverage smart machines and transformative technologies to give them a clear competitive advantage.

Brocade outlines the top transformative technology trends in networking to watch for in 2016 and beyond:

1. The cloud will gain even greater traction

According to IDC, more than half of all IT spending is going to be on the 3rd Platform, otherwise known as cloud-based technologies, and that figure will surpass 60 percent of all IT spending by 2020. The migration of old, legacy IP network architectures to New IP networks will accelerate, reaching near-mainstream adoption as enterprises and service providers transform their networks into an open, software-driven platform for innovation and a competitive edge.

2. Software-based networks are clearly the future

Over the past year, software has transformed the data center and networks in general, with service providers and enterprises turning to Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) to create new services quickly, scale them easily, and deliver them in user-centric ways. 2016 will bring about the expanded adoption of innovative, open, and automated software networking platforms as enterprises and service providers migrate to New IP networks. The increasing deployment of x86 server architecture will accelerate this transformation, replacing specialized networking hardware in multiple network roles, such as Application Delivery Controllers (ADCs). ADCs have already begun transforming to a virtual (vADC) model to help enterprises and services providers scale capacity on demand to handle peak workloads. Software is increasingly permeating every aspect of this virtualization transformation.

3. The importance of security will skyrocket

Organizations operating in today's New IP networking environment face increasing demands for cloud-based applications and need to support social, mobile, and Big Data initiatives. However, security-related attacks and breaches continue to impede the delivery of services and create additional challenges to network and service reliability. New IP networking solutions allow organizations to deploy more advanced security that is designed into the network from the start, not bolted on at edge to existing infrastructure. The network itself can be pervasively vigilant and track behavior on and not just access to the network, to quickly identify and prevent unwanted activity. Security services can be virtualized, enabling organizations to distribute security wherever it is needed and customize security at various levels -- by geography or location, function, group or individual, or application.

4. DevOps will play a much larger role

DevOps, or any agile software development methodology that closely matches services with business demands, will gain widespread influence and uptake among both enterprises and service providers as a way to ensure they remain competitive. According to IDC, enterprises pursuing digital transformation strategies will more than double their software development capabilities by 2018. Companies that build and use field-focused development teams that operate without the constraints of rigid traditional product development processes will have a significant advantage in customer-focused innovation. This advantage extends to both the speed of development and to customer intimacy and retention.

5. Big Data and analytics will get even bigger

Organizations that are able to take advantage of the explosion of data will seize the day, and many of these disrupters will be startups that use Big Data to make strategic decisions based on analytics. As data gets increasingly colossal, so do the opportunities, skillsets, and demand for analytic and cognitive services across industries. The ability to derive intelligence from Big Data in real time will create a distinct competitive edge for any business.

6. Machine learning takes off

The advent of machine learning is the computing breakthrough made possible by Big Data. The emergence of algorithms that can learn from and even make predictions based on the enormous amounts of data and meta-data that are generated, transmitted, and stored via networks will change the world of data centers and networks beginning in 2016. This process is already underway, as facial and speech recognition are changing the worlds of consumer electronics and the cloud services that use them, and anomaly detection is quickly becoming a crucial part of network security.

7. The rise of the telco with virtual architecture

Mobile Network Operators (MNOs) that have been struggling to keep up with fast-changing customer needs and market opportunities will be compelled to embrace SDN and NFV in 2016. The risk of falling behind is set to intensify with each passing day as carriers and service providers that embrace change will become the winners in the Internet of Things (IoT) ecosystem and 5G race by 2020.

8. The technical talent crunch gets serious

Vendors, service providers, and user organizations are all competing for a limited pool of next-generation talent with the required coding and technical skills. The talent crunch issue will become increasingly acute, and organizations will have to rethink their human resource strategies and policies in order to attract, develop, and retain strong talent. Technical qualifications that were only recently seen as de facto passports to important positions in networking will change in the face of self-provisioning and self-programming networks. Increasingly, critical networking positions will begin to require advanced analytical and coding skills that are in very short supply today.

Pete Goldin is Editor and Publisher of APMdigest

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 ...