Over the last 15 years, cloud computing has allowed businesses unparalleled flexibility, enabling companies to scale resources up or down according to demand.
This scalability meant businesses could adapt quickly to changing markets without being tied to expensive, inflexible infrastructure. Beyond that, the cloud eliminated the need for costly data centres and constant hardware upgrades, reducing capital expenditure and shifting IT budgets towards operational efficiency.
But while cloud services have transformed how organisations operate, revolutionizing workflows and enabling innovation, they often come with hidden costs. Many companies find themselves overspending on underused resources due to poor planning or inefficient designs. This is where edge computing solutions can make a difference, complementing cloud strategies to drive cost savings and enhance performance.
How edge computing reduces cloud costs
Minimize cloud data transfer and bandwidth costs
One of the most immediate ways edge computing helps cut cloud spending is by reducing the amount of data that needs to be sent to the cloud.
When data is processed locally, only the most relevant summaries, results, or exceptions need to be transmitted. This minimizes bandwidth usage and lowers the fees associated with moving data into and out of cloud environments.
Example: A logistics hub uses Simply NUC edge systems to process real-time tracking and environmental sensor data for shipments. The edge devices handle local analytics, flagging delays or temperature deviations on-site and sending only exception reports to the cloud. This approach slashes data transfer volumes while keeping cloud costs in check.
Reduce reliance on cloud compute resources
Edge AI allows businesses to run inference and analytics at the data source. Instead of sending raw data to the cloud for processing, which can mean high compute charges for real-time analytics, local devices handle that workload. This frees up cloud compute instances and reduces ongoing charges.
Example: A retailer deploys edge AI in stores to monitor customer foot traffic and shopping patterns. The AI models run on local edge hardware, delivering insights in real time without incurring the costs of spinning up cloud compute resources for every analytic task. The result? Faster decisions and lower bills.
Lower cloud storage costs with local data retention
Cloud storage can get expensive, especially when vast amounts of raw data are sent for archiving or compliance purposes. Edge computing offers an alternative: keeping time-sensitive or operational data locally and uploading only what’s necessary for long-term storage or regulatory requirements.
Example: A healthcare provider uses edge devices to monitor patient vitals in real time. Critical information is processed and acted upon locally, while only required records are uploaded to the cloud for archiving, significantly cutting down on cloud storage expenses.
Enable hybrid and distributed architectures for cost efficiency
Edge computing doesn’t replace the cloud, it complements it. By balancing local processing with selective cloud use, businesses can optimize both performance and spending. A well-designed hybrid architecture lets edge devices handle immediate, high-volume tasks while reserving the cloud for activities like historical data analysis, cross-site aggregation, or backup.
Example: A logistics firm uses compact Simply NUC edge hardware in its delivery vehicles and warehouses to track packages in real time. This local processing keeps cloud use minimal, with the cloud reserved for consolidating historical data, running large-scale analytics, and generating long-term reports. The company reduces bandwidth costs and limits the need for constant high-level cloud compute power.
Read more about cloud vs Edge in our free ebook.
Additional strategies to reduce cloud costs
Rightsize cloud resources
A common source of wasted spend is over-provisioned cloud resources. Businesses often allocate more compute, storage, or database capacity than they truly need, just to be safe. But that “just in case” mentality can result in significant unnecessary expense over time.
How to approach it:
- Regularly analyze usage data to identify underutilized instances or oversized services.
- Adjust instance types, storage sizes, or service tiers to better align with actual workloads.
Example: If a virtual machine regularly runs at 20–30% CPU utilization, consider downsizing to a smaller, more cost-efficient type or consolidating workloads.
Tip: Use native tools like AWS Cost Explorer, Azure Advisor, or GCP Recommender to spot rightsizing opportunities.
Leverage auto-scaling and spot instances
Auto-scaling ensures you only pay for what you use. It dynamically adjusts your cloud resources based on demand, scaling up during busy periods and scaling down when demand drops. Combining this with edge computing allows your local systems to handle baseline workloads, reserving cloud resources for true peak needs.
Spot instances (or preemptible instances) offer another route to savings. These allow you to use unused cloud capacity at a steep discount, ideal for flexible or non-critical workloads.
Example: A media company uses auto-scaling to handle spikes in web traffic during big events, while its edge devices manage local caching and initial content processing. Spot instances handle video encoding tasks at a fraction of normal cost.
Monitor and audit regularly
Visibility is key to controlling cloud costs. Without regular monitoring, it’s easy for waste to creep in unnoticed, whether through idle resources, oversized instances, or forgotten services.
How to stay on top of it:
- Set up cost alerts at key thresholds (e.g., 80% of monthly budget).
- Combine edge device monitoring (e.g., via Simply NUC BMC) with cloud cost dashboards for full visibility across your hybrid environment.
- Review reports monthly to identify unusual patterns or growth.
Example: A SaaS provider sets up automated reports in Azure Cost Management and uses the insights to reduce overprovisioning by 25% over three months.
Identify and eliminate unused resources
Orphaned cloud services, like unattached storage volumes, idle load balancers, or forgotten test environments, are silent budget drainers.
Best practices:
- Schedule regular cleanups or use scripts/tools to find and terminate unused resources.
- Set policies for automatic cleanup of temporary assets like snapshots or staging environments.
Example: A development team automates snapshot lifecycle policies so that test environment backups older than 30 days are automatically deleted, saving thousands per year.
Edge computing offers a practical, powerful way to reduce cloud costs by processing and storing data closer to where it’s generated. When combined with smart cloud strategies like rightsizing, auto-scaling, and regular audits, businesses can cut unnecessary spend while maintaining performance and flexibility.
By blending edge and cloud thoughtfully, you gain the best of both worlds, reduced operating costs, faster local processing, and scalable cloud power when needed. Simply NUC’s modular, scalable edge platforms provide an ideal starting point for this balanced approach, helping businesses get the most from their hybrid architecture without breaking the budget.
Speak to us to see how edge can help you reduce cloud costs.
