When organizations begin experimenting with AI and machine learning, they typically use public cloud services to avoid the cost and complexity of implementing AI-capable systems. As they transition into full-scale adoption of AI, however, they begin to see the drawbacks of the public cloud.
While the public cloud provides a pay-as-you-go model, the costs of resource-intensive AI workloads can quickly add up. Hidden fees, complex pricing structures and growing AI use often contribute to unexpected costs. At the same time, the shared nature of the public cloud can lead to latency and performance bottlenecks.
Of course, security and privacy are critical concerns when running AI workloads in the public cloud. Public cloud resources can be vulnerable to unauthorized access and data breaches that expose sensitive data that’s used to train AI models. Data residency issues can also create regulatory compliance challenges.
In light of these issues, many organizations are rethinking their AI strategies. A hybrid mix of public and private clouds is often the best long-term solution for AI workloads. However, implementing a private cloud can be a costly and complex process. Organizations can overcome that challenge with hosted private cloud solutions.
Why Private Cloud for AI
A private cloud offers all the flexibility and scalability of the public cloud in a single-tenant platform with dedicated sources. Because private cloud resources aren’t shared with other tenants, the organization gets the predictable performance that’s critical for AI workloads.
The organization also controls where data is stored, and can customize the private cloud to meet its specific security and compliance requirements. Only individuals within the organization who have the necessary permissions can access private cloud resources. As a result, a private cloud offers greater security and privacy and aids in regulatory compliance.
A private cloud is an essential element of a hybrid cloud strategy, which blends multiple public and private cloud resources. In a true hybrid cloud environment, workloads can move seamlessly between public and private clouds. Organizations can choose the platform that’s best for each application, and keep their most sensitive data in the private cloud.
Other Benefits of Private Cloud
Of course, a private cloud isn’t just for AI. It can help organizations modernize their legacy applications and ease the transition to a “cloud first” strategy. Because the organization can deploy and configure hardware to meet the needs of its applications, moving workloads to the cloud is smoother and more secure.
A private cloud also facilitates edge computing, which brings compute and storage resources closer to the “edge” of the network where data is generated. By deploying a private cloud at the edge, organizations can use smart sensors and other IoT devices to monitor their infrastructure and operations and generate alerts when metrics deviate from acceptable levels. Users and applications can access this data in real time for faster decision-making.
Edge computing can also work in concert with AI to support applications such as autonomous vehicles, smart cities and remote patient monitoring. AI-powered tools get the data they need with minimal latency to enable predictive maintenance, smarter inventory management, fraud detection and more.
The Hosted Private Cloud Alternative
Despite its benefits, a private cloud can be difficult to design, implement and maintain. It can also be expensive. Although a private cloud eliminates the monthly fees of a public cloud service, the upfront costs deter many organizations.
A hosted private cloud can be a good alternative for organizations that lack the budget or skill sets to implement a private cloud. The private cloud is hosted in a service provider’s data center, but it’s isolated from other customers and workloads. Organizations gain the benefits of a private cloud without having to buy, implement and maintain equipment onsite.
Verteks takes this concept a step further with a fully managed virtual private cloud. In addition to providing the hosting, we handle the ongoing maintenance and management, with 24x7 monitoring to ensure the highest levels of performance, availability and security. Let us help you utilize a private cloud for your AI workloads without the cost and headaches.
