Hyperconverged Infrastructure vs. Cloud: What's the Difference?
Hyperconverged Infrastructure vs. Cloud: What's the Difference?
Cloud computing has become an essential component of business operations. Organizations not only use public cloud services for their application and data needs but many are also constructing private clouds in their own data centers or other facilities. However, creating a cloud infrastructure is a major undertaking that must be carefully balanced against the benefits of public cloud services.
A company should also assess if a converged system, such as a hyper-converged infrastructure (HCI), would be more suited to its needs. This evaluation includes considering important aspects like email archiving, which plays a critical role in data management, compliance, and legal discovery processes. Unfortunately, comparing a cloud architecture to HCI isn't always an easy task, partly because manufacturers use the words cloud and hyper-convergence loosely and frequently interchangeably. However, the cloud and HCI are not synonymous. Despite their similarities, they represent different approaches to infrastructure, and businesses should be aware of these differences if they are considering them for their data centers.
Storage
Hyper converged systems primarily perform a function of a storage platform. The storage infrastructure is integrated directly into the platform and aggregated into a shared resource pool, which can contain SSDs, HDDs, or a combination of both. Simultaneously, storage capacity is constrained by the vendor's established node topology, which governs drive kinds and scalability.
Although most providers offer a variety of storage solutions, these pale in comparison to the flexibility provided by cloud architecture. If the cloud software can properly connect with the devices, a company may deploy virtually any form of the storage array in virtually any location. Storage resources, like in HCI, are abstracted and offered as services. The cloud, on the other hand, takes it a step further by allowing customers to employ point-and-click procedures to pick the storage they require for their workloads, selecting from whatever storage alternatives are accessible to that platform.
Performance
It might be difficult to compare the performance between HCI and cloud infrastructure. It depends on whether the cloud is a public platform or an on-premises system, and how the infrastructure is designed if on-premises. An HCI cluster combines all hardware components into a unified infrastructure that keeps applications and data close together, providing fast network speeds and data rates while removing inefficiencies associated with scattered design.
The actual gear that makes up a cloud infrastructure, on the other hand, might span many geographic regions, presenting a wide range of potential bottlenecks. However, if the components are close to each other, as in a private cloud, many of these bottlenecks can be avoided. Furthermore, a cloud infrastructure often gathers precise system telemetry, which may be utilized in conjunction with automation and orchestration capabilities to fine-tune resources on the fly to improve performance.
Scalability
An HCI cluster's nodes act as building blocks for integrating the infrastructure into a cohesive whole. The nodes are preconfigured and pre-integrated and may be added with no effort, eliminating many of the issues associated with growing traditional infrastructure. However, whether it comes to the maximum number of nodes per cluster or the increments in which resources may be expanded, an HCI platform has very strict constraints.
A cloud infrastructure, on the other hand, may sustain thousands of nodes. Its distributed design, broad APIs, and orchestration and automation features allow it to readily adapt infrastructure expansion and contraction as needed. When the challenges of installing and integrating diverse systems are considered, growing a cloud infrastructure is nowhere as simple as it is with HCI.
Reliability
Fault tolerance is embedded into an HCI platform. If a host dies, another host can take up the workload and restart the virtual machines that were previously running on the failed host. Drive failures can also be accommodated by the virtualized storage pool. An HCI platform, on the other hand, may not include all redundant components, such as adapters or controllers, leading to single points of failure. The platform also works in a single location, which may need the use of additional services or systems to maintain the required dependability.
A cloud infrastructure, like HCI, is designed to be reliable. The combination of failover services with virtualization aids in the availability of workloads. Telemetry can be used to notify administrators of problems or to initiate automatic fixes. However, the degree of dependability is dependent on the execution. Given the stakes, public cloud platforms tend to go out of their way to maintain dependability. Organizations constructing their own cloud infrastructures must guarantee that their systems fulfill their own dependability criteria, even if this involves expanding the infrastructure to other geographic locations.
Workloads
Hyper-convergence began as a method to construct virtual desktop infrastructures, but it quickly expanded to encompass other sorts of virtualized workloads. Furthermore, several HCI platforms now enable containerized apps. Indeed, with each successive generation, HCI becomes more versatile, allowing for the deployment of more diversified workloads than ever before.
Nonetheless, HCI is not nearly as adaptable as cloud infrastructure, which may serve a diverse set of virtualized, containerized, and, in some circumstances, bare-metal applications. Because of its flexibility and service-oriented architecture, the infrastructure can quickly reconfigure resources for specific workloads, leveraging orchestration and automation as needed. Its self-service capabilities also enable customers to swiftly deploy the environments required to run their individual workloads, without the need for IT assistance.
Data Security
Data protection must be a primary consideration while constructing IT infrastructure, not just for disaster recovery but also for security and privacy. The data safeguards included in an HCI platform are mostly determined by the vendor or IT team providing the system. However, some disaster recovery is built into HCI via fault-tolerance, which may not defend against catastrophic occurrences like as natural catastrophes or successful cyberattacks.
When it comes to data security, cloud infrastructure is similar to HCI. The precise safeguards depend on how they are implemented. High-profile public cloud platforms go to great lengths to protect data; nevertheless, consumers may have to pay extra for services such as snapshots, backups, and other disaster recovery capabilities. IT teams constructing their own cloud infrastructures may integrate these features into their platforms, tailoring the level of data security to their individual needs.
Management
HCI is the best solution in terms of management, bringing with it a high level of operational efficiency while simplifying data center operations. Hyper-convergence was created to make the procedures of obtaining, installing, maintaining, and growing infrastructure easier. Administrators may control components from a single interface, deploy resources fast and efficiently, and integrate third-party applications via the platform's API without requiring outside knowledge.
It is not straightforward to set up a cloud infrastructure. It can certainly ease provisioning and automate common activities, and it's perfectly suited to DevOps processes like continuous integration and delivery, but installing the environment and keeping it operating is a whole different story. IT must procure, deploy, and integrate hardware, install and configure software, and connect everything via a secure and high-performance network.
Wrapping up!
It is critical to understand that hyper-converged infrastructure and cloud computing are not synonymous. Both of these technologies strive for optimal infrastructure management automation, but they take different approaches. We do hope that you understand the difference now.
