|By Umesh Mahajan||
|April 11, 2015 01:45 PM EDT||
Black Friday? Cyber Monday? Bring It on with Analytics and SDx-Based Application Delivery
It's terminology specific to the retail industry though just about anyone who shops for consumer goods is familiar with the phrase "Black Friday" or, more recently, its online instantiation "Cyber Monday." Both terms refer to the anticipated rush of commercial traffic in advance of the holiday season. For the retailers themselves, it's an odd blend of the Apocalypse and Christmas magic, something to dread and anticipate simultaneously. For e-tailers specifically, this season requires that their web portals are capable of navigating huge spikes in online traffic without compromising the user experience. The threshold is extreme. Industry research has revealed that most consumers expect websites to load in under two seconds and that nearly half of them will abandon the site if loading exceeds a mere three seconds.
In the heyday of legacy TCP/IP networking, IT's response (or preparation) for this scenario would have been simple: overprovision the heck out of network capacity. For the web infrastructure, IT would have likely purchased and provisioned a large number of load balancers, a pair at a time to enable high availability. More than likely, the excess capacity would have been overkill, but hey, better safe than sorry, right? The reason for this overprovisioning was also simple - there was no accurate way for IT to dynamically provision network capacity on-demand. In essence, IT was flying blind, which benefited networking vendors who commanded insane market capitalization values due to the excess purchasing in the "good old days".
This very scenario, played out countless times, was one of the drivers for the advent of cloud computing, data center virtualization, and then software-defined networking as enterprises and service providers sought ways to maximize efficiencies in their network infrastructure. Another driver was the need to reduce network management complexity, made possible by the abstraction of key network services such as security, load balancing, application delivery, etc., through the SDN model. The migration toward these new constructs were based on three realities about networking in the modern era:
One, as upper-layer network services occupy the strategic high ground in the data center infrastructure between IT and the end-users themselves, these technologies play a major role in determining the all-important end-user experience. This may be the difference between a making a sale and losing a customer. However, as apps migrated to the cloud, the control and visibility that traditional application delivery controllers (ADC) could provide diminished, which threatened established service level agreements and, ultimately, user experience.
Two, the architecture of how applications are developed today has evolved from purpose-built, monolithic ("shrink wrapped") code and products to a tightly federated collection of microservices that are both modular are reusable. It's as if app developers moved to using a common set of Lego blocks to build any number of web-based apps only limited by their imagination. For networking teams, however, the move to microservice-app development meant that the existing assumptions around traffic patterns, load-balancing scale, and service requirements went out the window, requiring far greater levels of network-wide intelligence.
Three, the wide adoption of connected mobile devices has made anticipating where and when people were accessing applications a completely unpredictable exercise.
These megatrends pose disruptive impact for legacy ADC vendors because they tend to undermine the core value proposition of hardware, appliance-based products. That is, the hallmark of the vendors who led in this space was their ability to build high-performance gear and their intimate familiarity of monolithic apps - think SAP, Oracle, Microsoft, etc. But mobile computing and microservice-based apps requires load balancing capable of providing holistic network intelligence and the ability to co-locate these critical services directly with the microservices themselves (aka "application affinity") - whether they reside in the cloud or on-prem. For these requirements, we believe that the most logical form factor is software-based delivered as VMs or even containers.
Facebook, a company who helped drive these technology transformations, argued for these very principles the introduction of its homegrown Autoscale load balancer, which it positioned as a more efficient and intelligent way to deliver these network services. To achieve this engineering milestone, Facebook dedicated dozens of engineers, a luxury most enterprises cannot afford. But for Facebook, building a custom load balancer/ADC for its limited and specific set of applications was the only way it could guarantee end-user experience as well as optimize its compute resources at the levels its hyperscale environment required.
The opportunity now exists to build a next-generation ADC for mainstream enterprises who typically manage hundreds of different applications compared to one or two that a Web 2.0 company might. We believe this requires fundamentally rearchitecting what an ADC is and how it's delivered. Specifically, we believe the next-gen architecture requires:
- A true separation of the control and data plane. We believe that SDN has been hindered in some way by "SDN-light" or "SDN-like" approaches by vendors that have simply taken the software running on their hardware appliances and squeezed them into VMs that never separated the data plane from the control plane. To support a true multi-cloud environment, the architecture requires an elastically scalable, load-balancer with a distributed data plane that casn span, serve and scale with apps across various on-premise and cloud locations. The distributed data plane enables customers to achieve application affinity at the application microservice levels thereby dramatically improving application performance. In addition, the clean separation of planes also enables the creation of a unified, centralized control plane, which significantly alleviates the operational complexity associated with integrating, operating and managing each ADC appliance across locations individually.
- Holistic, in-line big data analytics that deliver real-time user, application and network performance not possible with the mishmash of offline/out-of-band monitoring tools currently available in the marketplace. I've already argued that the load balancer or ADC occupies the enviable, strategic location between the infrastructure and the end-user. Why not take advantage of this by delivering powerful performance insights and other KPI important to network operators, application admins, and DevOps teams? Further, real-time, in-line information can make the network smarter over time and enable it to automate, influence certain feature activation and resource scaling without human intervention, or what I refer to as "insight-to-action"
Now imagine that same Black Friday or Cyber Monday scenario but this time with a next-generation analytics and SDN-enabled ADC. Online traffic spikes from users all over the world using a myriad of connected devices. The network infrastructure is now intelligent enough to spin up new resources in a moment's notice to boost capacity and performance dynamically wherever required, as well as arbitrating the load efficiently throughout the data center. Further, with Big Data analytics, the network will eventually be able to make predictive decisions based on historical traffic, usage patterns unique to that environment such as online retailers and the holiday shopping season. This is not only possible today, we believe it's the mandate for where networking and, specifically, what ADCs must deliver.
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