Your cloud bill is about to get more expensive. OVH Cloud is forecasting 5-10% price increases taking effect between April and September 2026. That’s not a guess—it’s based on confirmed increases from Dell and Lenovo that are already in effect.
Here’s what makes this interesting: OVH is the only major cloud provider actually telling you what’s coming. AWS, Azure, and GCP? Radio silence on their 2026 pricing plans. But they’re all buying servers from the same manufacturers facing the ongoing DRAM shortage crisis.
Understanding how server hardware costs flow through to cloud pricing helps you prepare your infrastructure budget. This article breaks down the provider comparison, service-level exposure, and timeline so you know exactly what to plan for.
How Much Will Cloud Prices Increase in 2026?
OVH is forecasting 5-10% price increases hitting between April and September 2026. OVH CEO Octave Klaba publicly stated these increases in late 2025, making OVH the only provider being transparent about what’s ahead.
The forecast is based on hard numbers. Dell announced 15-20% server price increases in mid-December 2025. Lenovo followed with increases from January 2026. These aren’t rumours. They’re implemented price changes cloud providers are already paying.
The maths work like this: a 15-25% server cost increase translating to 5-10% cloud service increase represents a 33-40% passthrough rate. That’s the key number. It tells you how much of the hardware cost increase flows through to what you pay.
AWS, Azure, and GCP haven’t announced anything yet. But they’re buying from the same OEMs facing identical cost pressures. So plan for mid-2026 increases in the same 5-10% range regardless of which provider you use.
Server price increases hit in December 2025 and January 2026. Cloud providers typically lag 3-6 months between procurement cost changes and retail pricing adjustments. That puts the implementation window in Q2-Q3 2026, matching OVH’s April-September forecast.
Memory-intensive services face steeper increases than general compute. Databases and caching services have higher DRAM ratios. We’ll get into service-level exposure later in this article. For now, understand that 5-10% is the baseline for general workloads.
This is the first significant cloud price increase cycle driven by supply constraints rather than providers expanding their margins.
Why Are Server Hardware Costs Increasing 15-25%?
The DRAM shortage is causing this cost cascade. Memory manufacturers prioritised HBM (High Bandwidth Memory) production for AI accelerators over conventional server memory. HBM commands higher margins but consumes three times the wafer capacity of standard DRAM.
The numbers are severe. DDR5 prices increased 307% since September 2025. DDR4 increased 158%. NAND flash storage jumped 33-38% quarter-over-quarter.
Memory represents 30-40% of total server bill-of-materials. When memory prices double or triple, server costs can’t stay flat.
The AI infrastructure buildout drives this shortage. Nvidia’s Grace CPU Superchip uses up to 960GB of LPDDR5X memory—dramatically more than the 16GB in premium smartphones. Samsung, SK Hynix, and Micron redirected production capacity to serve that demand because the margins are better.
You’re caught in the crossfire between AI infrastructure expansion and conventional server memory supply. That’s why server costs are climbing 15-25%.
Which Cloud Providers Have Announced Price Increases?
OVH Cloud is the only provider with a public 2026 forecast. AWS, Microsoft Azure, and Google Cloud Platform have made no announcements as of January 2026. Oracle Cloud Infrastructure hasn’t said anything either.
The hyperscaler silence has strategic reasons. Competitive dynamics play a role. They’ve got thousands of enterprise customers with complex contract structures. And they have margin flexibility that might let them delay or phase increases.
But silence doesn’t mean immunity.
AWS is the largest cloud provider by market share. Azure focuses on enterprise customers with complex contract structures. GCP has a heavy AI/ML workload mix, suggesting higher memory-intensive service exposure. Oracle’s database-centric services have inherent high memory dependency.
Should you assume hyperscalers face identical cost pressures? Yes. The only variable is timing and how much they choose to pass through.
Plan for 5-10% increases across all providers in mid-2026 regardless of public announcements. Use OVH’s forecast as the industry bellwether.
How Does the Cloud Cost Passthrough Mechanism Work?
Cost passthrough is the percentage of input cost increases that translate to retail pricing. Understanding this helps you extrapolate when providers don’t publish forecasts.
The OVH example: 15-25% server cost increase translating to 5-10% cloud service increase equals a 33-40% passthrough rate. The formula is simple: (cloud price increase %) ÷ (server cost increase %) = passthrough rate.
Why 33-40% instead of 100%? Cloud providers operate at scale with existing hardware inventory purchased at older pricing. Server hardware is only one input cost alongside power, network, facilities, and staff. Higher-margin services can absorb more cost increase. And competitive pressure dampens how much providers can raise prices.
Service type affects passthrough too. Memory-intensive services have higher passthrough because the DRAM shortage disproportionately affects their cost structure.
You can use the 33-40% passthrough rate as a framework. If server costs increased 20%, expect cloud pricing to eventually reflect 6-8% increases. This works when providers stay silent but hardware cost signals are public. For foundational context on memory market dynamics, understanding how supply constraints create these cost pressures helps you model future passthrough scenarios.
Which Cloud Services Face the Steepest Price Increases?
Memory-intensive services take the biggest hit. The DRAM shortage drives this cost cascade, so services that consume more memory see steeper increases.
Managed databases like RDS, Azure SQL Database, and Cloud SQL have high memory-to-compute ratios. Expect above-average increases in the 7-12% range compared to the 5-10% baseline.
Caching services are even more exposed. Redis, Memcached, ElastiCache, and Azure Cache for Redis store everything in memory by design. These services will see the top end of cost increases.
General compute services like EC2, Virtual Machines, and Compute Engine have lower memory ratios. They’re closer to the baseline 5-10% forecast. Compute-optimised instance types might see smaller increases in the 3-7% range.
Storage services face different pressure. S3, Blob Storage, and Cloud Storage are affected by the NAND shortage, but NAND price increases are less severe than DRAM.
Serverless functions like Lambda, Functions, and Cloud Run price by compute duration and memory allocation. The memory-based pricing components will likely increase proportionally, but serverless shared infrastructure might dampen individual function cost changes.
Look at your service mix. If 40% of your spend is RDS and ElastiCache (high memory intensity) and 60% is EC2 (baseline compute), your blended increase lands around 7%.
When Will Price Increases Take Effect in 2026?
OVH targets April-September 2026 implementation. Server hardware increases are already in effect: Dell’s mid-December 2025, Lenovo’s January 2026.
The lag between server cost increases and cloud pricing adjustments is typically 3-6 months. Cloud providers have existing hardware inventory purchased at older pricing. They need to evaluate competitive positioning and navigate enterprise contract terms.
Q1 2026 is when server cost increases fully embed in cloud provider procurement. Q2-Q3 2026 is when you should expect cloud service price increase announcements.
Contract-specific timing varies. Enterprise contracts with annual renewal might see increases at your renewal date. Existing reserved instances are locked at current pricing until term expiration—1-3 years of price protection.
On-demand pricing adjusts fastest. List pricing will likely shift mid-2026 to reflect new costs.
Update budgets and contracts now. Waiting until official announcements gives you less runway to negotiate or lock in current pricing. For tactical approaches to cloud contract negotiation during this supply constraint period, you need strategies that work when providers hold unprecedented leverage.
How Should You Calculate Your Expected Cost Increase?
Start by identifying your service mix. What percentage of your cloud spend goes to memory-intensive services versus general compute?
High memory intensity: managed databases, caching services, in-memory analytics. Apply 7-12% increase estimates.
Baseline compute: EC2, Virtual Machines, Compute Engine, container services. Apply 5-10% increase estimates.
Lower exposure: compute-optimised instances, storage-only services, serverless with minimal memory allocation. Apply 3-7% estimates.
Weight by current spend allocation. Example: 40% of spend on RDS/ElastiCache at 10% increase + 60% on EC2 at 5% increase = 7% blended increase.
Account for contract protection. Reserved instances lock current pricing for 1-3 years. If 50% of your compute is reserved, the effective increase halves for that portion during the reservation term.
Apply timeline factors. Annual contracts renewing in Q2 2026 face the full increase immediately. Q4 renewals give you more time to optimise or negotiate.
Multi-cloud adds complexity. Different providers might implement at different times and rates, spreading the budget impact across quarters.
Run the calculation conservatively. Use the higher end of estimate ranges to build budget headroom. Once you’ve calculated your expected increases, translating cost increases into budget planning becomes the critical next step for 2026 financial planning.
Is Cloud Repatriation Cheaper Than Accepting Price Increases?
No. On-premises infrastructure faces identical 15-25% server cost increases. There’s no escape from the DRAM shortage whether you’re running in AWS or your own datacentre.
The economics actually favour staying in the cloud. Cloud providers have OEM relationships and scale to secure scarce hardware better than individual enterprises.
The TCO comparison shows why repatriation doesn’t solve cost pressure. You’re comparing 5-10% cloud increases versus 15-25% direct server procurement plus operational overhead. Hardware accounts for only 18-25% of total server ownership cost while support, downtime, power, and upgrades make up the rest.
Migration costs make it worse. The costs of returning to on-premises include upfront capital investment, specialised employees and infrastructure, plus operational expenditure.
AI workloads face particular challenges. On-premises struggles to secure AI accelerators with HBM while cloud access remains more reliable despite cost increases.
For a comprehensive evaluation of cloud repatriation as a cost alternative, understanding the technical and financial barriers specific to AI workloads prevents expensive strategic mistakes. Repatriation is rarely justified by price increases alone. Evaluate based on control requirements, compliance needs, or specific workload economics where dedicated hardware provides measurable advantage.
What Mitigation Strategies Can You Apply Immediately?
Reserved capacity expansion is the highest-leverage tactic. Purchase reserved instances now at current pricing to lock multi-year protection. Reserved instances offer 30-70% savings compared to on-demand pricing even before considering price increase protection.
Contract negotiation comes next. Lock in current pricing through early renewals or multi-year commits before mid-2026 increases. Enterprise customers with significant spend may have negotiation leverage. But understand that hardware cost increases are supply-driven, limiting how much providers can flex. Focus negotiation on timing delays, reserved capacity incentives, or service credits.
Memory optimisation delivers medium-term savings. Architectural changes to reduce DRAM dependency include caching efficiency improvements, query optimisation, and data compression. If you can reduce memory footprint by 10% across database instances, that partially offsets price increases. For detailed guidance on memory-efficient architecture patterns, technical teams can implement specific design changes that reduce DRAM dependency by 30-50%.
Budget forecasting needs updating now. Revise 2026 budgets with a 5-10% cloud cost assumption and contingency for higher memory-intensive exposure.
FinOps practices offset increases with efficiency gains. Implement cost monitoring, rightsizing, and waste elimination. Organisations typically waste approximately 21% of cloud spending on underutilised resources. Capturing that waste funds price increase absorption.
Engineering ROI calculation determines whether optimisation work costs less than accepting increases. If you’d spend six months of engineering time to reduce memory usage by 8% versus accepting a 10% price increase, the calculation might favour accepting the increase and directing engineering to revenue-generating features.
Start now while you have runway before Q2 2026 implementation.
FAQ Section
Here are answers to common questions about the 2026 cloud cost increases:
Do on-demand and reserved instance pricing both increase?
On-demand pricing will adjust to new rates when increases take effect in mid-2026. Existing reserved instances are locked at current pricing for their term duration (1-3 years). New reserved instance purchases after price increases will reflect higher baseline pricing. This creates a strategic opportunity to expand reserved capacity now at current rates.
Which geographic regions face the highest cloud cost increases?
The DRAM shortage is global, affecting all regions identically. OVH announced first, suggesting European pricing may adjust earlier than North America or APAC. Server OEM increases are worldwide, so regional variation will be timing-based (Q2 vs Q3) not magnitude-based.
Can I negotiate lower increases with my cloud provider account team?
Enterprise customers with significant spend may have negotiation leverage, especially on multi-year contracts. However, hardware cost increases are supply-driven, limiting provider flexibility. Focus negotiation on timing delays, reserved capacity incentives, or service credits. If you’re spending less than $500K annually, negotiation leverage is minimal.
How do serverless pricing models (Lambda, Functions) change with memory cost increases?
Serverless functions price by compute duration and memory allocation. Memory-based pricing components will likely increase proportionally (5-10% for baseline allocations). However, serverless shared infrastructure may dampen individual function cost changes compared to dedicated database instances.
Should I switch cloud providers to avoid price increases?
All providers face identical server hardware cost pressures from the DRAM shortage. Switching providers incurs migration costs that likely exceed 5-10% cost increases. Evaluate multi-cloud for strategic reasons like vendor diversification, not price avoidance.
Will cloud price increases reverse when the DRAM shortage resolves?
Cloud providers historically do not reduce pricing after cost-driven increases, even when input costs decline. The 5-10% increase will likely become the new baseline. Budget for a permanent baseline shift rather than a temporary surge.
How do database-as-a-service costs compare to self-managed on EC2 during price increases?
Managed databases like RDS have higher memory ratios than general compute, suggesting steeper increases (7-12% vs 5% for EC2). However, total cost of ownership includes DBA time for self-managed operations, which may offset pricing differential. Managed services typically remain more cost-effective.
Are spot instance prices also affected by hardware cost increases?
Spot pricing reflects supply-demand dynamics and unused capacity, not direct cost passthrough. However, if providers reduce capacity investment due to high server costs, spot availability may decrease and average prices may increase indirectly. Expect spot price volatility rather than consistent baseline increase.
When should I update my 2026 infrastructure budget forecast?
Immediately. OVH’s forecast and server OEM announcements provide sufficient confidence for budget planning. Use a 5-10% cloud cost increase assumption with higher estimates (7-12%) for memory-intensive workloads. Waiting for official announcements leaves insufficient time for mitigation.
Can I lock in current pricing by purchasing reserved instances now?
Yes, this is one of the highest-leverage mitigation tactics. Reserved instances purchased before mid-2026 price increases lock in current rates for 1-3 year terms. Evaluate workload stability and capacity needs carefully. Over-committing to reserved capacity creates waste if usage patterns change.
How do multi-cloud strategies affect cost increase exposure?
Multi-cloud spreads risk across providers with potentially different implementation timelines (Q2 vs Q3 2026). However, all providers face the same hardware cost pressures, so multi-cloud doesn’t avoid increases—it diversifies timing and negotiation opportunities.
