The underlying network infrastructure is the digital nervous system for the economy. Companies realize that technology is defined in their future strategies and it is not an optional cost any more, it is really at the heart of what every entity is doing around the world.
Demand for networking equipment in India is booming right now. IDC estimates that India’s communications and networking market grew 67 percent during the third quarter of 2018 to USD 430 million. The Ethernet switch market, for instance, shot up 34 percent annually to USD 160 million during the quarter, and the router market showed exemplary annual growth of 140 percent last quarter to USD 215 million. The country’s wireless local-area network (WLAN) market, increased 12 percent annually to a size of USD 54 million.
Looking ahead, there’s a good reason to believe that the networking market in the country will keep growing at an impressive rate. The volume of data, voice and video traffic going across networks continues to escalate exponentially, with no apparent end in sight. Growth in the total number of users is increasing internet bandwidth. Entertainment-related activities, including video, gaming, and multimedia, are forecast to represent 85 percent of all traffic by 2022.
Changing Trends in 2019
The networking field is changing fast. This year, several emerging technologies will fundamentally impact how businesses and their employees connect. The good news is that each technology also represents a solid opportunity to improve some aspect of how a company runs – from network efficiency all the way up to business models.
2.5/5 GbE. The growth of 2.5 and 5 Gigabit Ethernet deserves attention. With the IEEE 802.3bz standard, which defines 2.5/5 GbE, organizations can use the same Cat 5e cabling that is already present in businesses and homes to transmit data at faster rates.
Currently, 1 GbE is typically the rate for data transfer inside of offices and homes, but 2.5/5GbE brings the promise of up to five times the bandwidth. The challenge, however, is that organizations need new hardware, including Network Interface Cards (NICs), to take advantage of the speed boost.
10G. In datacenters, 10 Gigabit Ethernet networking connectivity has been a common connection speed for a decade. Home networks, however, have not had the benefit of 10G and have typically been capped at around 1 Gbps — but that could soon be changing. Lab trials of the 10G for cable technology are currently underway, with field trials set for 2020. With groundbreaking, scalable capacity and speeds, the 10G platform is the wired network of the future that will power the digital experiences and imaginations of consumers for years to come.
Bluetooth Mesh. Inside both homes and business, Bluetooth is widely used to provide basic short range connectivity for devices. Multiple vendors are coming together in support of the emerging Bluetooth Mesh technology. With Bluetooth Mesh, networking devices can be connected together for control, monitoring and automation. For the smart home market to grow, it needs true global wireless mesh networking standards that can meet the reliability, security, and performance needs of the market. The Bluetooth mesh is one of those standards and will enable tremendous growth and innovation in home automation for years to come.
Wi-Fi 6, also called 802.11ax, is an upgrade on the current highest-speed Wi-Fi protocol in wide use, 802.11ac. Wi-Fi 6 brings a dramatic improvement in efficiency across all existing Wi-Fi bands, including older 2.4GHz frequencies. Wi-Fi 6 will also likely get new spectrum in the 6GHz band in 2019 or 2020, further improving its speed.
The biggest improvement that comes with Wi-Fi 6 is that it increases the density of devices that can co-exist in a single space, further increasing the speed of all devices when there is more than one. The new standard also improves performance by supporting deterministic (that is, not random) packet scheduling, which, as well as increasing the efficiency of the use of any given band, also makes for dramatic improvements in power utilization by mobile devices.
5G. Consumers will be itching to get onboard with 5G in 2019, as carriers roll out limited installations that work on a small number of devices. Beyond 2019, 5G will bring improved speed and battery life to smartphones, as well as the growth of fixed wireless for residences, competing with wired broadband for some communities.
In the enterprise, the impact of 5G in 2019 (and beyond) will be more nuanced, but it will be felt.
5G fixed wireless will be a convenient option as a WAN connection for getting branch offices online. It may have the performance (high speed and low latency) to compete with wired connections.
As 5G rolls out (which will take years), it will also open up new possibilities for IoT applications. Thanks to 5G’s time-slicing technology, sensors will able to run on batteries that last for years.
5G’s wireless technology will also make it into corporate local-area networks: An extension of the licensed 5G spectrum into a new, lightly-licensed band, CBRS (Citizens Broadband Radio Service), will allow businesses to set up their own, completely private 5G data networks. For some IoT installations, this could be a compelling solution.
Wi-Fi 6 and 5G will coexist as critical wireless technologies for the enterprise. It will, however, be a challenge at first to find ways to manage networks as users and devices move between them. The two technologies are highly complementary, and will be even more so when network management tools evolve to handle them side-by-side.
Digitized Spaces. New high-resolution geolocation technologies based on wireless radios in mobile devices, plus data mining software, are creating opportunities to understand how people and things move through physical spaces. Companies that adopt these technologies will get access to information about the users of their buildings that will open up new possibilities for business extensions and improvements.
Additionally, digitized spaces will help network managers. They’ll be able to identify areas where wireless service is weak, allowing highly precise deployment of new access points. And in security, it will be easier for analytics engines to notice unusual patterns of movement among wireless devices that could indicate physical beaches.
SD-WAN. Traditionally, corporate networks have been based around centralized control, routing, and security. Nearly all network traffic in a large business would be back-hauled to a main data center, where the interconnects to other branches and systems were, and where the security applications like firewalls did their work.
That model still exists – businesses don’t change network architectures rapidly – but it is breaking down. Designing networks primarily around branch-to-data-center connections doesn’t make sense when so many business applications are now run out of the cloud, and so many end users rely on the open Internet for connection when they’re not in a company office.
For these and other reasons, businesses are moving to software-defined wide-area networking. SD-WAN allows networks to route traffic based on centrally-managed roles and rules, no matter what the entry and exit points of the traffic is – and with full security. For example, if a user in a branch office is working on Office365, SD-WAN can route their traffic directly to the closest cloud data center for that app, improving network responsiveness for the user and lowering bandwidth costs for the business.
SD-WAN networks can be run by leaner teams of networking engineers, and it is easy for these teams to modify the rules as business needs change. Ultimately, SD-WAN will make it easier for machine intelligence to take a hand in network management, further lowering bandwidth expenses and improving security.
SD-WAN has been a promised technology for years, but in 2019 it will be a major driver in how networks are built and re-built. In the coming year, SD-WAN network traffic will grow by 500 percent, and our research shows that more than half of business customers who do not currently use SD-WAN are expected to make plans for its adoption.
Machine Learning and AI. Managing a modern network requires deep insights into how all its different pieces work in concert – and often rapid reactions to quickly-changing conditions that are unique to every network. In other words, understanding a network’s health takes pattern-recognition skills.
In 2019, companies will start to adopt Artificial Intelligence, in particular Machine Learning, to analyze the telemetry coming off networks to see these patterns, in an attempt to get ahead of issues from performance optimization, to financial efficiency, to security. The pattern-matching capabilities of ML will be used to spot anomalies in network behavior that might otherwise be missed, while also de-prioritizing alerts that otherwise nag network operators but that aren’t critical. Just as we instinctively know which of the little aches we feel in our bodies are new and which are just part of being who we are, networks will get to know themselves and be able to flag the appropriate issues. The first application of AI in network management will be simply reporting on activities that break patterns. In other words, smarter alerts. As technology advances, the tech will grow to be proactive. It will be able to react to more situations autonomously. Workable tools for this should appear later in 2019.
Artificial Intelligence is throwing a curve ball at traditional network architectures, given its penchant for crunching massive volumes of data to influence the behavior of networks, applications and management software. For instance, Cisco’s AppDynamics subsidiary has put the rising field of AIOps in its sights with the new Central Nervous System monitoring platform that helps third-party systems ingest, correlate and analyze data across multiple domains as a means to troubleshoot problems and optimize performance. The system is based on three key components: a serverless agent for Amazon’s Lambda ecosystem, an application monitoring tool for the Cisco ACI platform, and a machine learning engine to glean operational insights into application environments.
Enterprises should also be aware that AI itself will also require changes to fundamental network infrastructure. Most networks were built to support typical application workloads, mostly structured data, to on-site processing resources. AI workloads, on the other hand, support not only the parallel processing requirements of Big Data solutions like Hadoop, but must accommodate a world in which remote compute capacity is readily available on-demand and at scale. This means high-speed, always-available networking has become a critical element for organizations undergoing the transition to a digital services business model.
IoT. The Internet of Things presents another challenge, both for the enterprise and for regional network providers. Long-standing solutions like the Spanning Tree Protocol (STP) are in dire need of updating in order to produce adequate stability and reliability on Ethernet LANs. Meanwhile, alternate solutions like Multi System Link Aggregation (MLAG) and Shortest Path Bridging (SPB) are gaining support, leaving organizations with a dilemma as to whether they prefer higher link redundancy or loop-free multipathing and consolidation.
Hybrid Cloud. In a data center, hybrid cloud may be the preferred data architecture at most enterprises these days, but it is still very much a work in progress. And as development continues, it is becoming clear that its success or failure will depend very much on the network.
To support dreams of seamless application migration and workload balancing across local and distributed infrastructure, the network will not only have to be in tip-top shape but will require a level of functionality that is only just starting to emerge in software-defined environments.
Development continues because, we will not have an effective hybrid cloud without it.
Most enterprises take the unfortunate step of building a hybrid cloud first and then worrying about networking later. This is not necessarily a fatal step, although it will take some work to retrofit networks around hybrid architectures without diminishing resource efficiency or creating bandwidth constraints. For one thing, it helps to determine ahead of time what applications can be migrated to certain resources and where key data sets are to be housed. Also, it helps to employ the latest encryption tools, such as elliptic curve cryptography (ECC), to ease bottlenecks at the load balancer.
Hybrid networking also suffers from the dreaded last mile problem. In any given data center, all traffic is funneled through the link to the Internet, so if the bandwidth is lacking here, it affects performance across the entire cloud infrastructure. Many enterprises address this through multiple ISPs, which not only increases throughput but provides protection against outages – at least when disruptions are not occurring on a regional basis.
Network connectivity is the lynchpin for all data operations, but in the hybrid cloud it takes on new meaning because it must be both fast and flexible. That means the enterprise will have to address it on the physical layer with wider pipes and bigger switches, and on the management side with increased programmability and dynamic services deployment.
Hybrid clouds, after all, do not build their own abstract networks.
Customizing network hardware solutions. In a data center, one of the more ironic aspects of modern network infrastructure is that while high levels of customization are taking root on virtual architectures, the physical layer is becoming increasingly generic.
But even that may be about to change now that the ability to program, and thus customize, network hardware, and even basic silicon, is starting to creep into the latest solutions.
By itself, today’s hyper-converged infrastructure (HCI), which is usually built on white-box, modular hardware, presents a number of inefficiencies, particularly in areas like scalability. This is why manufacturers are already turning to Composable-Disaggregated Infrastructure (CDI), which provides more flexibility when deploying varying amounts of compute, storage and networking. But even this is not enough without a virtual layer that can pool these resources so they can be tailored to the consumption needs of individual workloads. A programmable fabric is crucial to this effort because it provides the necessary connectivity to selected resources within and between clusters, and it can do so at the speed of a modern, automated data environment.
Still, without complete control over both the software and hardware stacks, the enterprise is limited in its ability to craft a fully customized data ecosystem. Even in fully open environments that incorporate programmable APIs, a network operator must still write code to a controller to implement basic functions like forwarding and routing.
But even this is not the end-all and be-all of network customization. For that, the enterprise will need to either design and commission its own hardware from ODMs in Asia, the way hyperscalers like Google and Facebook do, or employ programmable silicon like the Field Programmable Gate Array across its data footprint. Custom chips are likely to replace generic software in the coming year as functions like virtualization, graphics and HPC start to push performance and efficiency requirements. In fact, FPGAs are already showing up on key networking devices.
All of this customization and programmability will put an end to the many strictures that have inhibited data performance thus far, ushering in an entirely new era of data productivity.
Intent-Based Networking. IBN is the catch-all term for the gradual shift from today’s manual network operations to a more hands-off automated ecosystem. Using AI, sensor-driven data flows, virtual abstraction and a host of other technologies, the idea is simply to define what you hope to achieve, then let the data environment itself configure the network in the most optimal way to suit those needs. But it is not that simple.
The fact is, IBN is only truly effective when deployed universally. Without full end-to-end abstraction and automation, operators will only be able to define their intent within a relatively limited scope, resulting in a situation in which the automated portion of the network is functioning at hyper-speed and efficiency, while the rest tries to play catch-up. But implementing IBN as a fork-lift upgrade is equally problematic, and will likely lead to widespread disruption of applications and services.
Still, IBN is expected to grow at a rapid clip. According to Market Research Future, the sector is expected to surge from USD 634.5 million in 2017 to more than USD 4.9 billion by 2023, a compound annual growth rate of 42 percent. Much of this activity will take place in the data center, the cloud, and remote offices, all of which are rapidly converting from traditional IT infrastructure to modularized, hyperconverged footprints. In this way, IBN can avoid the hassles of integrating into legacy environments by becoming a core attribute of this new environment, which is likely to support next-generation apps and services catering to the IoT, DevOps and other advanced data initiatives.
“Clearly, this is a huge opportunity for today’s leading networking companies, but it represents a threat as well. Cisco, for example, has made no secret of its support for IBN, and has been acquiring a wealth of technologies to make it happen. Some of these are obvious, such as AI and SDN; some are not, like the recent acquisition of Luxtera, a semiconductor firm that specializes in silicon photonics (SP). Juniper is on board with IBN, although they are taking a slightly different track. Last October, the company unveiled the EngNet, a series of automation tools that network operators can mix and match to produce their own optimized management environments. In this way, rather than simply impose a top-down IBN platform, the company can foster a development community for users to share experiences, develop new products and in general chart the best way toward IBN and away from the traditional Command Line Interface.
Meanwhile, however, several smaller companies are looking at IBN as a way to break the stranglehold that markets leaders like Cisco and Juniper have had on networking for the past two decades or more. Data Center Knowledge notes that a start-up called Apstra has released an IBN operating system that works on any hardware, while another called VeriFlow acts as the eyes and ears of abstract network architectures to enable predictive management models and other automated functions,” says Arthur Cole, senior consultant and expert.
IBN is more than just a new management regime, of course. It represents an entirely new relationship between data, infrastructure, and the people who work with them. As the network becomes more adept at analyzing, provisioning and repairing itself, the challenge shifts from figuring out how to make it work to figuring out what you want it to do in the first place.
In the end, expect IBN to make networking both easier and more complex, even as it opens up a whole new world of digital possibilities.
Emerging technologies require highly specialized environments of their own, and some of which require substantial changes to core infrastructure. For the enterprise, perhaps the most difficult aspect of these changes is that they are being driven by application and user demands rather than advancements in technology. In the past, new networking capabilities were deployed, then, the user community set to work exploiting them to the greatest extent (and then immediately calling for newer, better technology). This time, the use cases are being defined first, and the networking team is expected to fulfill them or watch users gravitate to another network. And time is in increasingly short supply as the digital economy moves forward.