Cloud vs. On-Premise: The Data Debate Goes “Back To The Future”

Ocient’s SVP Cloud Operations George Kondiles offers commentary on cloud vs. on-premise and the data debate goes back to the future. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

Enterprise data infrastructure is undergoing a notable shift. While the past decade saw a rapid transition from on-prem deployments toward cloud-first strategies, a new reality is setting in. Organizations are reexamining the benefits of on-premise infrastructures — not as an antiquated or regressive move, but as a highly strategic choice, particularly for AI, analytics, and mission-critical workloads.

Real Talk – Why Are Enterprises Headed Back On Prem?

So, why are so many companies going back on prem? The answer isn’t a wholesale rejection of the cloud, but rather a nuanced reevaluation of workload placement. Optimizing for where workloads are deployed has a direct impact on data processing speed, latency, and overall system efficiency – all of which are essential for enterprises dealing with growing data and AI workloads to get right.

Plus, there are some compelling drivers shaping this new reality.

• The ‘surprise cloud costs’ conundrum – Public cloud pricing models, though attractive at first, have lost the predictability promise for running compute-intensive, always-on workloads. With unexpectedly high operational costs, enterprises are reconsidering the total cost of ownership (TCO) of their cloud deployments.
• AI and operational performance – Put simply, some workloads that require low latency and high throughput (e.g., edge computing or intensive AI) achieve better performance and results when run on dedicated, local infrastructure.

Cloud vs. On Prem Trade-Offs: Performance, Cost, and Sustainability 

It’s important to weigh the business-critical trade-offs when evaluating (or reevaluating) cloud vs. on prem infrastructures.

Performance 

Cloud environments offer unmatched flexibility and scalability, making them a natural choice for sporadic or unpredictable workloads. However, always-on workloads that demand consistent, high-performance computing may suffer from latency and network bottlenecks in the cloud, even with cloud services optimized for speed.

On-prem infrastructures, on the other hand, offer direct control over hardware, enabling IT teams to tailor configurations for maximized throughput and minimal response times.

Cost 

Cloud services entered the game as a cost-effective option for organizations with fluctuating data needs, with pay-as-you-go pricing models that initially promised scalability and cost savings. However, costs scale dramatically as workloads increase in complexity, leaving enterprises paying premiums for compute cycles, large data transfers, and increased storage needs.

Conversely, on-prem solutions may require a higher upfront investment but also deliver long-term savings due to fixed costs and reduced reliance on third-party services, particularly for high-volume workloads.

Sustainability

The trade-offs surrounding sustainability can be even more nuanced.

For instance, cloud providers invest heavily in renewable energy and energy-efficient data centers. However, running compute-intensive tasks over distributed infrastructures can consume significant resources, which we know is an industry-wide problem that needs urgent addressing.

On-prem solutions, on the other hand, can offer better control over energy consumption based on efficiencies delivered at the hardware and software layer, with some able to deliver critical data performance in a significantly smaller data center footprint.

The Takeaway 

Considering performance requirements, budget constraints, and sustainability commitments within the greater evaluation of workload optimization is essential when constructing a resilient and adaptable infrastructure.

Example: Cloud vs On Prem in AdTech

Consider an AdTech company managing real-time bidding (RTB) operations.

RTB demands ultra-low latency because ad placements must be processed in milliseconds to ensure optimal campaign performance. TL;DR: Operational performance is a critical driver of success for the company.

With a cloud-first infrastructure approach, network variability that can stem from multi-tenant architectures could mean unpredictable latency spikes and result in the company missing critical bidding opportunities. In addition, the high-volume, real-time operations typical for AdTech and other organizations may push the company’s cloud costs outside of acceptable thresholds.

Running the same workloads on-prem, the company can minimize network latency and achieve faster data processing speeds, allowing for seamless bidding and reduced ad server response times. This control also means consistent and predictable performance, which is critical for real-time bidding, as well as less varied OpEx costs.

A Peek At the Future 

Change and innovation with technology happens rapidly. Though we don’t have a crystal ball, there are trends taking hold of enterprise IT that may shape the future of data infrastructure in five to 10 years. Consider the below as food for thought:

• Increasing Needs At The Edge: Real-time data and IoT operations at the edge are influencing rapid computing infrastructure innovation. The need to process data closer to its source will continue pushing the industry at large for decentralized processing capabilities.
• Hyper-Personalized AI Systems: Future AI-driven systems will not only determine infrastructure needs in real time, they will deploy those resources autonomously (or at least semi-autonomously) — which creates the potential for enterprises to optimize their infrastructure for performance, cost, etc.
• Built-In Efficiency Layers: Hardware-software codesign is creating operational and energy efficiencies that are unlocking new levels of performance and minimizing resource consumption. As these innovations shape a new era of intelligent hardware and software integration, enterprise leaders will have an increased ability to reconfigure and balance business needs and sustainability goals.

The debate surrounding cloud vs. on-premise infrastructures is dynamic and evolving. Just like the need for agility carved out a path for innovative cloud applications, the future of enterprise IT will be shaped by intelligent, workload-specific optimizations made by enterprises creating the infrastructure for data-driven innovation.