Estimate your monthly cloud infrastructure costs for AWS, Azure, and GCP. Enter your compute, storage, and bandwidth requirements to get an instant cost comparison across all three providers — with annual savings and optimization tips.
✓Verified: AWS, Azure & GCP published pricing — April 2026
☁️ Your Infrastructure Requirements
Servers, virtual machines, or containers
Enter a valid number of instances (1+).
Closest match to your workload requirements
730 = 24/7 always-on. 160 = business hours only
Enter hours per month (1–730).
GB
Total object/block storage across all instances
Enter a valid storage amount.
GB
Data sent from cloud to internet (egress)
Enter a valid bandwidth amount.
Commitment level affects pricing significantly
Estimated Monthly Cloud Cost
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Provider Comparison (Monthly)
Provider
Compute
Storage
Bandwidth
Total/mo
⚠️ Disclaimer: Estimates are based on publicly published 2026 pricing for US East regions. Actual costs vary by region, usage patterns, support plans, managed services, and negotiated discounts. Always verify with each provider's official pricing calculator before making infrastructure decisions.
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Sources & Methodology
✓Pricing data sourced directly from AWS, Azure, and GCP official pricing pages. Rates reflect US East 1 / East US / us-central1 regions as of April 2026. On-demand rates used as baseline.
Official GCP pricing for us-central1 region, including Compute Engine, Cloud Storage, and network egress. GCP sustained use discounts applied automatically for 100% monthly usage.
Methodology:Monthly Compute Cost = Instances x Hourly Rate x HoursMonthly Storage Cost = Storage (GB) x Rate per GBMonthly Egress Cost = Bandwidth (GB) x Egress RateTotal Monthly Cost = Compute + Storage + Egress
Pricing model discounts applied: On-demand = 1.0x. 1-Year Reserved = 0.65x. 3-Year Reserved = 0.40x. Spot = 0.25x. GCP sustained use discount (28% for always-on) applied to compute only for on-demand pricing. All rates reflect US East / us-central1 baseline. Last verified: April 2026.
Cloud infrastructure cost is one of the largest and fastest-growing line items for modern technology organizations. Yet most teams only discover their true cloud spend after deployment, when it is too late to optimize the architecture. This guide covers every dimension of cloud cost calculation across AWS, Azure, and GCP — including the hidden costs that are consistently overlooked and the optimization strategies that deliver the most impact.
Monthly Cloud Cost = (Instances x Hourly Rate x Hours) + (Storage GB x Rate) + (Egress GB x Rate)
Example — 2 medium instances, 500GB storage, 100GB egress, AWS on-demand:
Compute: 2 x $0.0928/hr x 730 hrs = $135.49
Storage: 500 GB x $0.023/GB = $11.50
Egress: 100 GB x $0.09/GB = $9.00 Total: $155.99/month — $1,871.88/year
AWS vs Azure vs GCP — 2026 Pricing Comparison
At the compute level, AWS, Azure, and GCP are within 5 to 10 percent of each other in 2026 for comparable instance configurations. The real differences emerge in storage pricing, egress fees, managed service costs, and discount structures. Understanding where each provider wins is more valuable than looking at any single price point.
Service
AWS
Azure
GCP
Winner
Standard compute (on-demand)
$0.0928/hr (m5.large)
$0.096/hr (D2s v3)
$0.0950/hr (n2-standard-2)
AWS
Object storage (standard)
$0.023/GB
$0.018/GB
$0.020/GB
Azure
Internet egress (first 10TB)
$0.09/GB
$0.087/GB
$0.12/GB
Azure
1-year reserved discount
~35%
~33%
~37% (CUD)
GCP
3-year reserved discount
~60%
~57%
~55% (CUD)
AWS
Spot/Preemptible discount
Up to 90%
Up to 90%
Up to 91%
Tie
Sustained use discount
Not available
Not available
Auto 20-30%
GCP
Free tier
12 months + always-free
12 months credits
$300 credit (90 days)
AWS
The Hidden Cloud Costs That Double Your Bill
Base instance pricing is just the starting point. Organizations consistently underestimate total cloud spend by 30 to 60 percent because of costs that do not appear in the compute price list. Understanding and accounting for these categories before deployment prevents budget overruns.
Data egress fees: Transferring data out of the cloud to the internet or between regions costs $0.09 to $0.12 per GB on most providers. A data-intensive application moving 10TB per month adds $900 to $1,200 to the bill — before a single compute instance is counted.
Managed database costs: Running a managed database (RDS, Azure SQL, Cloud SQL) typically costs 2 to 3 times more than a self-managed instance because you pay for the management overhead plus the underlying compute and storage separately.
Load balancer fees: AWS ALB charges $0.0225 per hour plus LCU fees. Azure and GCP have similar metered pricing. A highly trafficked load balancer can add $50 to $200 per month independently of compute costs.
Support plan costs: AWS Business support starts at 10 percent of monthly bill (minimum $100). At $5,000/month cloud spend, that is $500/month or $6,000/year just for support access. Azure and GCP have equivalent tiered support pricing.
NAT gateway and inter-AZ traffic: Traffic between availability zones within the same region is charged on AWS ($0.01/GB). NAT gateway adds further per-GB and per-hour fees. These can silently compound in microservice architectures with high internal communication.
Idle and orphaned resources: Unused Elastic IPs, unattached EBS volumes, forgotten development environments, and snapshot storage accumulate silently. Most organizations have 20 to 35 percent idle cloud resources at any given time.
Reserved Instances vs Spot vs On-Demand — When to Use Each
The pricing model you choose has a far bigger impact on your cloud bill than choosing between providers. A 3-year reserved commitment on AWS saves up to 60 percent compared to on-demand for the same workload. The decision framework is straightforward: match the pricing model to the predictability of the workload.
Use on-demand for development environments, unpredictable workloads, and new services where usage patterns are unknown. The flexibility premium is worth it until you have stable usage data. Use 1-year reserved for any service that has been running consistently for 3+ months and shows stable baseline usage. The 30 to 40 percent savings almost always justify the commitment. Use 3-year reserved only for mission-critical, stable infrastructure that is extremely unlikely to change — database servers, authentication services, and core APIs. Use Spot or Preemptible for batch jobs, video rendering, CI/CD pipelines, data processing, and any workload that can tolerate interruption. The 60 to 90 percent discount makes these pricing tiers the highest-ROI optimization available for appropriate workloads.
💡 GCP Sustained Use Discounts (unique advantage): Google Cloud automatically applies sustained use discounts of up to 30 percent when you run a Compute Engine instance for more than 25 percent of the month — no reservation or commitment required. This means an always-on GCP instance is effectively 20 to 28 percent cheaper than the published on-demand rate without any action required. AWS and Azure offer no equivalent automatic discount.
Cloud Cost Optimization — The Highest-Impact Actions
Cloud cost optimization is not a one-time project. It is a continuous practice that requires visibility, regular review, and engineering discipline. These are the actions that consistently deliver the greatest cost reduction across organizations of all sizes:
Rightsizing is the single highest-impact action. Most cloud instances are oversized at deployment. CloudWatch (AWS), Azure Monitor, and Cloud Monitoring (GCP) all provide utilization data. If average CPU utilization is below 40 percent over 2 weeks, the instance is likely oversized. Moving from an XLarge to a Large instance cuts compute cost by 50 percent. Moving from Large to Medium cuts it by another 50 percent. Start here before any other optimization. Tagging and cost attribution is the foundation of all cloud cost management. Without tagging every resource by team, environment, and application, you cannot identify which workloads are driving costs. Implement a mandatory tagging policy before resources are created, not after. Auto-scaling eliminates paying for compute during low-traffic periods. A web application that gets 80 percent of its traffic between 8am and 10pm can reduce compute costs by 25 to 40 percent using scheduled or metric-based auto-scaling without any user impact.
Cloud Cost by Region — Why Location Matters
Cloud pricing is not uniform across regions. US East 1 (AWS), East US (Azure), and us-central1 (GCP) are the baseline cheapest regions for their respective providers. European regions typically cost 5 to 15 percent more. Asia-Pacific regions cost 15 to 30 percent more than US East. South American and African regions carry the highest premiums, often 30 to 50 percent above US East pricing. For global applications, co-locating the majority of workloads in US East while serving traffic through CDN edge nodes provides the best balance of cost and performance. This calculator uses US East pricing as the baseline for all estimates.
Frequently Asked Questions
To estimate your monthly cloud cost, multiply your compute instance hourly rate by the number of hours in a month (730 for always-on), add your storage cost (GB multiplied by price per GB), add your data egress cost (outbound GB multiplied by egress rate), and add any managed service fees. Our calculator does all of this automatically for AWS, Azure, and GCP using 2026 published rates, giving you a side-by-side comparison instantly.
For standard compute instances in 2026, AWS, Azure, and GCP are within 5 to 10 percent of each other. GCP tends to be cheaper for compute-heavy workloads due to automatic sustained use discounts. Azure wins on storage pricing and egress fees. AWS offers the widest range of instance types and the longest track record of price reductions. The cheapest provider for your workload depends on the specific service mix, region, and commitment level.
Cloud TCO (Total Cost of Ownership) is the true total cost of running your workloads in the cloud, including compute, storage, egress, managed services, support plans, networking, operational overhead, and tooling. Most organizations underestimate cloud costs by 30 to 60 percent by only calculating base instance prices. TCO analysis includes the often-overlooked categories like egress, NAT gateway fees, load balancer costs, idle resources, and support plan pricing.
Standard object storage in 2026 costs approximately $0.023 per GB per month on AWS S3, $0.018 per GB on Azure Blob Storage, and $0.020 per GB on Google Cloud Storage. Cold or archive tiers are 60 to 90 percent cheaper, starting from $0.001 per GB per month. Block storage (attached disks) costs more: approximately $0.10 per GB per month for SSD. The actual cost depends on storage tier, access frequency, retrieval patterns, and geographic region.
Reserved instances (AWS), Reserved VM instances (Azure), and Committed Use Discounts (GCP) provide discounts of 30 to 70 percent off on-demand pricing in exchange for 1 or 3 year commitments. A 1-year commitment typically saves 30 to 40 percent. A 3-year commitment saves 50 to 70 percent. These are ideal for predictable, always-on workloads like production databases, core APIs, and authentication services. For variable workloads, Spot instances offer even higher discounts but with the risk of interruption.
Egress cost is what cloud providers charge when data leaves their network to the internet or between regions. AWS charges $0.09 per GB for the first 10TB of internet egress. Azure and GCP have similar tiered pricing starting at $0.087 and $0.12 per GB respectively. Egress is one of the most overlooked cloud costs and can easily add 20 to 40 percent to your monthly bill for data-intensive applications. Using a CDN, keeping data within a single region, and optimizing API response sizes are the most effective ways to reduce egress costs.
The highest-impact cloud cost reduction strategies are: rightsizing instances to match actual CPU and RAM utilization, using reserved or committed use pricing for predictable workloads, implementing auto-scaling to eliminate paying for idle capacity, using Spot or Preemptible instances for fault-tolerant batch jobs, applying storage lifecycle policies to move infrequently accessed data to cold tiers, tagging all resources to identify cost ownership, and setting budget alerts to catch unexpected spend early before it compounds.
On-demand pricing charges the full published hourly rate with no commitment and is the most flexible but most expensive option. Reserved pricing requires a 1 or 3 year commitment in exchange for 30 to 70 percent discounts and is best for stable, predictable workloads. Spot or Preemptible pricing offers 60 to 90 percent discounts but the instance can be terminated by the provider with short notice (2 minutes on AWS, 30 seconds on GCP). Spot is ideal for batch processing, rendering, data analysis, and any workload that can tolerate interruption and checkpoint state.
Cloud pricing varies significantly by region. US East regions are the baseline and cheapest for most services on AWS, Azure, and GCP. European regions cost 5 to 15 percent more. Asia-Pacific regions cost 15 to 30 percent more. South American and African regions are typically 30 to 50 percent above US East pricing. Choosing the region nearest to your users reduces latency, but for pure cost optimization, US East is the most economical starting point and is used as the baseline for all estimates in this calculator.
The cloud costs most commonly overlooked include data egress fees, API call charges for object storage, NAT gateway and inter-AZ traffic fees, load balancer hourly and LCU charges, managed database fees above and beyond storage, support plan costs (AWS Business starts at 10 percent of monthly bill), and idle or orphaned resources like unattached disks, unused elastic IPs, and forgotten development environments. Setting budget alerts and using native cloud cost management tools (AWS Cost Explorer, Azure Cost Management, GCP Billing Reports) is essential for avoiding surprise bills.
FinOps (Financial Operations) is the practice of bringing financial accountability to the variable spend model of cloud computing. It involves engineering, finance, and operations teams collaborating to track, analyze, and optimize cloud costs without sacrificing performance or reliability. Key FinOps practices include mandatory resource tagging for cost attribution, setting team-level budget alerts, conducting monthly rightsizing reviews, and using committed use discounts strategically for stable workloads. Organizations that adopt FinOps practices typically reduce cloud spend by 20 to 30 percent without impacting service delivery.