Blog/Article
Cutting costs without cutting corners: a practical approach to workload placement in 2025
Over the past decade, the cloud has been the go-to solution for performance, reliability, and, initially, even cost efficiency. However, it is no secret that a bare metal as a cloud solution can often be more useful and predictable.
In 2025, IT leaders must take a more strategic approach. Blanket migrations no longer cut it. Instead, success comes from placing workloads where they perform best without overspending. The quickest option is to sign up on Latitude.sh right now.
The Shifting Landscape of Infrastructure Options
While the public cloud still dominates headlines, it’s not a one-size-fits-all solution. As more organizations revisit their architectures, repatriation is gaining traction.
Especially now—with Equinix Metal announcing end-of-life by June 2026—many are reassessing their bare metal strategies, aiming for more nuanced approaches.
This isn’t just about replacing a platform—it's your chance to optimize your entire infrastructure strategy.
If you're currently running workloads on Equinix Metal, our recent article, "5 signs you need to start your migration now," provides guidance on planning your transition.
This transition period allows you to reevaluate your entire infrastructure strategy rather than simply migrating like-for-like.
The True Cost of Cloud: Beyond the Monthly Bill
In 2021, the viral article “The Cost of Cloud, a Trillion Dollar Paradox,” published by Andreessen Horowitz, highlighted how cloud spending could quickly spiral out of control.
When evaluating infrastructure costs, many organizations focus exclusively on the monthly bill from their cloud provider. However, the actual cost equation is far more complex than that:
Performance inefficiencies: Applications running on virtualized infrastructure often require more resources to achieve the same performance level as bare metal, resulting in hidden costs
Egress charges: Data transfer costs can quickly spiral, especially for data-intensive applications
Over-provisioning: "Just to be safe" resource allocation leads to significant waste
Specialized instance premiums: GPU, high-memory, and other specialized instances command premium pricing
Licensing costs: Software licensing models often don't align well with cloud deployment patterns
Understanding these hidden costs is crucial for making informed decisions about where to place your workloads in 2025 and beyond.
A Framework for Workload Placement Decisions in 2025
Rather than defaulting to a single infrastructure approach, consider this decision framework for optimal workload placement:
Classify Your Workloads
Begin by categorizing your workloads based on the following:
Performance sensitivity (latency, throughput, consistency)
Predictability (steady-state vs. variable load)
Data gravity (where does your data live, and how expensive is it to move?)
Compliance requirements
Criticality to business operations
Benchmark Real-World Performance
Synthetic benchmarks rarely tell the whole story. Instead:
Test with production-like workloads
Measure end-to-end performance, not just isolated components
Include data transfer in your testing
Run tests over extended periods to capture variability
Calculate Total Cost of Ownership
Go beyond the sticker price to calculate:
Infrastructure costs (compute, storage, networking)
Operations overhead (management, monitoring, security)
The opportunity cost of performance limitations
Risk-adjusted costs (reliability, security incidents, vendor lock-in)
The Rise of Hybrid Infrastructure Models
The most sophisticated organizations are moving beyond the outdated "cloud vs. on-premises" debate. Instead, they embrace hybrid models that strategically place each workload in its optimal environment based on its unique requirements.
Core applications that demand consistent performance and have steady resource needs are often best hosted on bare metal servers.
These environments offer the reliability and control necessary for mission-critical systems.
On the other hand, variable workloads that require the ability to scale horizontally—such as web applications experiencing fluctuating traffic—are well-suited for the public cloud, which provides elasticity and cost efficiency.
Latency-sensitive applications, particularly those requiring real-time responsiveness, benefit from edge computing. These workloads reduce delay and improve user experience by processing data closer to the user.
Meanwhile, highly specialized workloads, such as those involving artificial intelligence, machine learning, or high-performance computing (HPC), are deployed on purpose-built infrastructure designed to handle their demanding computational needs.
This nuanced approach allows organizations to optimize performance, cost, and scalability across their entire IT landscape.
Workload Placement Guide: Matching Environments to Application Needs
Understanding which workloads belong where is the first step to optimizing your infrastructure strategy. Here's a practical guide to help you make these critical decisions:
Bare Metal Cloud: Performance Without Compromise
Ideal for:
Database Systems: Particularly OLTP databases with high transaction volumes and strict latency requirements
AI/ML Training Workloads: When GPU utilization needs to be maximized without virtualization overhead
Real-time Trading Platforms: Where microseconds of latency translate directly to dollars
Game Servers: Especially for competitive, real-time multiplayer games requiring consistent performance
High-Performance Computing (HPC): Scientific simulations, financial modeling, and other compute-intensive workloads
Media Encoding/Transcoding: For streaming services that need predictable, high-throughput processing
Why it fits: These workloads benefit from direct hardware access, consistent performance, and the elimination of the "noisy neighbor" problem. With Equinix Metal's approaching end-of-life in June 2026, exploring alternative bare metal providers should be a priority for organizations running these workloads.
Public Cloud: Flexibility and Scalability
Ideal for:
Web Applications: Particularly those with variable traffic patterns
Dev/Test Environments: Where rapid provisioning and tear-down are valuable
Batch Processing Jobs: That run occasionally but require significant resources when active
Content Delivery: Leveraging global edge locations for user proximity
Serverless Applications: Where you want to pay only for execution time
Analytics Platforms: Especially when they need to scale up for periodic reporting
Why it fits: These workloads typically have variable resource needs, benefit from rapid scaling, and don't usually suffer from the performance variability of virtualized environments.
Colocation/On-Premises: Control and Compliance
Ideal for:
Legacy Applications: Particularly those not designed for cloud environments
Highly Regulated Workloads: Where data sovereignty and compliance are paramount
Network Equipment: Routers, firewalls, and specialized hardware
Large, Stable Databases: Where data gravity makes movement costly
Specialized Hardware Requirements: Applications requiring uncommon configurations
Long-term, Stable Workloads: Where upfront investment provides better economics over 3+ years
Why it fits: These workloads benefit from physical control and customized hardware configurations, and they typically have long deployment lifecycles that make capital expenditures justifiable.
Edge Computing: The Hybrid Approach
Everybody has their own definition of the edge. For us, edge computing means meeting users where they are, functioning as a hybrid solution that combines elements of bare metal, public cloud, and on-premises deployments.
Rather than being a separate category, Edge represents a deployment strategy that can leverage any or all of these environments.
How Edge Computing Hybridizes Infrastructure:
Distributed Bare Metal: Edge often utilizes bare metal servers in distributed locations to achieve the performance benefits of dedicated hardware without centralization constraints
Cloud-Connected: Most edge deployments maintain connections to centralized public clouds for orchestration, management, and data aggregation
On-Premises Extension: For many organizations, edge represents the modern evolution of their on-premises strategy, pushing computing resources closer to data sources and users
Multi-Environment Orchestration: Edge architectures typically require orchestration tools that can manage workloads across heterogeneous environments
Ideal Edge Workloads:
IoT Data Processing: First-level filtering and aggregation at the edge, with deeper analytics in the cloud
Content Delivery: Dynamic caching and personalization at edge nodes, with origin servers in centralized locations
Real-time Applications: Processing time-sensitive data locally while synchronizing with central systems
Distributed Databases: Edge nodes for low-latency reads/writes with eventual consistency to central data stores
Compliance-Bound Processing: Performing regulated computing within specific geographic boundaries while maintaining global service delivery
Why the Hybrid Approach Works: This distributed strategy combines edge deployment's low latency and locality benefits with the management and scalability advantages of centralized infrastructure. The result is an architecture that places computing resources precisely where they deliver optimal value.
The Path Forward: Beyond Cloud-First to Infrastructure-Appropriate
The next evolution in infrastructure strategy isn't about abandoning the cloud or committing entirely to on-premises deployments.
Instead, it's about adopting a nuanced, workload-aware approach that leverages the right environment for each specific need.
This means matching applications and components to the infrastructure that best supports their performance, scalability, and cost-efficiency requirements.
By being intentional about where each workload runs, organizations can achieve what often seems impossible: lowering costs while improving performance.
Those who strike this balance effectively gain a meaningful competitive edge—not just through technical agility but also through smarter financial operations.
Still, it’s important to remember that the ultimate goal isn’t simply to shrink your cloud bill; it’s to maximize the value your infrastructure delivers to your business.
That requires shifting the focus away from speeds, feeds, and line-item costs and toward outcomes. When you prioritize total value and strategic alignment, your infrastructure becomes more than a cost center—it becomes a driver of innovation and growth.
Now, it’s time to review your organization's workload placement strategies and evaluate what has worked and what hasn’t. For those currently running on Equinix Metal, check out our comprehensive guide, "5 signs you need to start your migration now," which offers a practical framework for planning your transition.
If you are ready to maximize the benefits of bare metal, get started on Latitude.sh today. And if you need support with your Equinix Metal migration, contact our team for a customized solution for your specific workload needs.