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

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...