The core capabilities of hyperconverged products have evolved rapidly in the past five years to the point that they are becoming standardized. To build further differentiation, vendors are starting to introduce new functionalities, such as network automation and artificial intelligence (AI) for operational simplicity. They are also targeting new use cases, such as hybrid cloud deployments and edge computing.
According to Arun Chandrasekaran, research vice president at Gartner, four key factors will shape the future of hyperconvergence. Infrastructure and operations (I&O) leaders should embed these factors in their vendor selection processes to extend the potential use cases of hyperconverged infrastructure (HCI) and protect their investments in the future.
Factor No. 1: Prioritize HCI vendors with strong hybrid cloud capabilities
Workloads are increasingly hybrid, as organizations exploit the benefits of cloud infrastructure as a service (IaaS) and platform as a service (PaaS) for better elasticity, agility and total cost of ownership (TCO). Most organizations would like to evolve their virtualized infrastructures to functional hybrid clouds and integrate them with public cloud IaaS for workload portability and redundancy reasons.
Although the cloud management capabilities HCI vendors have added can appear basic when compared to cloud management platforms, vendors have formed closer partnerships with public cloud providers to deliver more integrated services in the cloud. “This could potentially ease customer challenges around deploying legacy and cloud-native applications in a hybrid environment,” says Chandrasekaran. “I&O leaders should prioritize HCI vendors with strong hybrid cloud capabilities across a broad set of parameters, including a wide choice of cloud provider support, on-demand consumption-based pricing and depth of application programming interface (API) support.”
Factor No. 2: Opt for lean and rugged platforms for edge use cases
HCI has the potential to address both traditional and emerging needs of edge computing because of its operational simplicity and form factor. Gartner expects that in the next two years hardware vendors will support HCI on ruggedized server platforms to address edge use cases, particularly in retail, mining and manufacturing. I&O leaders should favor HCI vendors that can deliver lower TCO through support of lean hardware that can scale down effectively and support newer computing abstractions (such as containers).
Advanced analytics applications can be deployed at the edge using HCI fully virtualized with a reasonable level of resiliency to address digital business needs.
Chandrasekaran says that in the mining industry, for example, sensor data can be aggregated using gateways, and analyzed on a HCI hosted in a micro-data center at the mining site. “This process can address issues including predictive maintenance of mining equipment, mining process control and seismic analysis of mines for personnel safety and emergency response,” he explains. “As more endpoints are added at the edge location, the HCI itself can scale out by adding more nodes. In comparison to a traditional three-tier architecture, HCI has a smaller form factor and occupies less ‘rack space,’ consumes less power and has lower cooling requirements — all critical design decisions when architecting an edge computing infrastructure.”
The ability of the infrastructure to adapt to workload needs and self-healing infrastructure will become critical
Factor No. 3: Insist that network automation is a priority
As HCIs are used to support applications that demand more and better performance and availability — and as those clusters grow beyond a handful of nodes — networking must be an integral part of the cluster design. Without system-level integration, the delivery of service-level agreements (SLAs) is difficult to achieve, and troubleshooting and problem resolution become very complex.
“Until recently HCI vendors have largely treated networking as a ‘dumb’ interconnect, an approach that has inhibited problem resolution and adherence to SLAs,” says Chandrasekaran. “However, they are increasingly realizing that network integration can no longer be ignored and, if properly done, can even be a competitive asset.”
Factor No. 4: Ensure vendors apply AIOps to guarantee application SLAs
As the complexity of mixed workloads increases and mission-critical applications are added, optimal workload placement, the ability of the infrastructure to adapt to workload needs and self-healing infrastructure will become critical. More I&O leaders will evaluate HCI as an on-premises and multicloud architecture, opening up a wide variety of choices for the placement of applications where artificial intelligence for IT operations (AIOps) will help optimize the resources holistically.
However, because integration and connections are ballooning, the amount of raw data, analysis, resolution and remediation is exceeding most IT organizations’ capacity and intelligence to deal with the problems.
“The solution lies in AI that can supply high-quality, real-time data; run algorithms and models on detecting anomalies; examine correlations of incidents that may have existed elsewhere; and handle root-cause analysis with recommendations for remediation,” explains Chandrasekaran. “The best cases will have HCI administrators working with AI-enabled analysis and recommendations as part of a proactive decision tree that protects SLAs.”