Cloud cost optimisation has traditionally focused on right-sizing virtual machines, shutting down idle resources, and selecting appropriate storage tiers. While these remain important, they often overlook one of the fastest-growing contributors to cloud spend: data egress.
Cloud cost optimisation has traditionally focused on right-sizing virtual machines, shutting down idle resources, and selecting appropriate storage tiers. While these remain important, they often overlook one of the fastest-growing contributors to cloud spend: data egress.
Whenever data leaves a cloud provider, whether to another cloud, an on-premises environment, or the public internet, it can incur additional charges. Unlike fixed infrastructure costs, egress charges are usage-based, making them difficult to forecast and even harder to control.
For businesses running analytics platforms, AI/ML workloads, backups, disaster recovery, and hybrid cloud environments, these charges can quickly rival or even exceed compute costs.
Where Cloud Costs Usually Escalate
Cloud overspending is rarely caused by a single issue. Instead, it's typically the result of several inefficiencies accumulating over time. The most common cost drivers include idle or oversized compute resources, storage that remains in premium tiers longer than necessary, cross-region and cross-cloud data transfers, data egress charges, and limited visibility into cloud usage across teams and business units.
While organisations often monitor compute utilisation closely, data movement is frequently overlooked. As cloud adoption grows, data transfer increases alongside it, creating unpredictable monthly costs that are difficult to budget for.
Cloud Migration: The Best Time to Optimise
A cloud migration isn't simply an infrastructure project; it's one of the best opportunities to improve long-term cost efficiency. Rather than migrating existing workloads as-is, organisations should evaluate how applications communicate, where data resides, and how frequently information moves between services.
A successful migration strategy should include mapping application and data flows, not just workloads; identifying cross-cloud and cross-region dependencies; comparing total usage-based costs instead of headline compute pricing; and implementing tagging, budgets, and cost monitoring from day one.
Many organisations optimise performance during migration but postpone cost governance. Unfortunately, expensive architectural decisions become much harder to reverse once workloads are in production.
Why No-Egress Self-Provisioning Platforms Are Gaining Attention
As cloud spending continues to rise, organisations are increasingly looking beyond traditional hyperscaler pricing models. One solution gaining momentum is the adoption of self-provisioning platforms with minimal or zero egress fees. These platforms typically provide transparent usage-based billing, zero or flat-rate data egress, self-service infrastructure provisioning, and standards-based APIs for easier migration and interoperability. The biggest advantage isn't simply reducing costs — it's improving cost predictability.
Where This Approach Delivers the Greatest Value
While no-egress platforms aren't intended to replace every cloud workload, they can be particularly effective for data-intensive environments such as object storage, backup and archival systems, disaster recovery environments, AI and machine learning datasets, analytics platforms, and multi-cloud and hybrid cloud architectures.
For organisations already invested in hyperscaler-native services, a hybrid strategy often delivers the best balance of performance and cost efficiency — keeping compute where it performs best while optimising storage and data-heavy workloads using more predictable pricing models.
A Practical Starting Point
Reducing cloud costs doesn't require a complete platform migration. Review your cloud spend across compute, storage, networking, and data transfer; identify workloads generating the highest egress costs; pilot a zero-egress storage platform for backup or archival workloads; compare actual invoices over multiple billing cycles; and expand adoption based on measurable savings. Evaluate cloud costs using real operational usage patterns rather than relying solely on published pricing calculators.
The Bottom Line
Cloud cost optimisation is no longer just about running fewer virtual machines or purchasing discounted compute capacity. It's about designing architectures that move data efficiently and minimise unnecessary operational costs. Evaluating platforms with transparent pricing and minimal or zero egress fees can help organisations improve cost control, simplify budgeting, and build cloud environments that are both scalable and financially sustainable.
At CoreGenix, we help organisations design secure, scalable, and cost-efficient cloud environments, from cloud migration and infrastructure modernisation to cloud governance and optimisation. Understanding the true cost of data movement is an essential step towards long-term cloud success.