Expert Guide: How to Slash Cloud Cost in 2025
In this guide, we will zero in on high-impact tips for cloud cost optimization. Cost is still a hurdle as many companies onboard to cloud computing.
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Join For FreeCloud computing has revolutionized the way companies scale and innovate, but cost control is one hurdle. According to Precedence Research, the cloud computing market size is going to increase to $2.3 trillion by 2032, which necessitates prioritizing cost optimizations as many organizations move to Cloud computing.
In this guide, we will zero in on high-impact, actionable tips toward cloud cost optimization using real-world case studies. We will reference AWS Cloud in this guide; however, please follow the table below to apply the same tips to other major cloud providers. The steps are easy to follow as a developer, architect, or cloud practitioner and help cut down the cost.
1. Optimize S3 Storage Costs
Why It Matters
AWS S3 is amazingly flexible, but storage of all data under a default class of storage contributes vastly to expenses. The right optimization of storage classes with access frequency is key to cost savings.
Action Plan
- Turn ON S3 Intelligent-Tiering for objects to which access patterns are unpredictable.
- Configure S3 Lifecycle Policies to automatically transfer data to Glacier for long-term storage after 30-60 days.
- Analyze bucket usage with S3 Storage Lens to quickly identify opportunities to reduce costs.
Code Example
{
"Rules": [
{
"ID": "MoveToGlacier",
"Prefix": "",
"Status": "Enabled",
"Transitions": [
{
"Days": 30,
"StorageClass": "GLACIER"
}
]
}
]
}Case Study
Airbnb optimized AWS S3 usage by transferring its less frequently accessed data to S3 Glacier and reduced its storage costs by 27%. Read more about it here.
2. Leverage Spot Instances for Flexible Workloads
Why It Matters
You will be able to take advantage of spare computing power available in AWS and save up to 90% off the On-Demand Instance prices using Spot Instances. It is ideal for flexible, stateless, fault-tolerant workloads, such as batch processing, continuous integration, continuous deployment, and big data.
Action Plan
- Identify interrupt-tolerable workloads, such as ETL processes, video rendering, and test beds.
- Leverage EC2 Auto Scaling with a mixed instances policy for seamless balancing of Spot and On-Demand Instances for reliability.
- Monitor Spot prices using the AWS Spot Instance Advisor and set the max price threshold.
Code Example
{
"LaunchTemplate": {
"LaunchTemplateId": "lt-0abcd1234efgh5678",
"Version": "1"
},
"InstanceCount": 5,
"Type": "request",
"InstanceInterruptionBehavior": "terminate"
}Case Study
National Australia Bank (NAB) shaved 20% off its cloud bill in 2022 by utilizing Spot Instances for analytics workloads and moving to affordable computing on AWS Graviton processors. Read more about it here.
3. Automate Resource Scheduling
Why It Matters
Resources such as dev environments and staging environments run 24x7 even when nobody is accessing the resource. If there is automation of those resources to turn them off during non-business hours, that saves them a ton.
Action Plan
- Build schedules automation to start and stop your resources in pre-configured time windows with AWS Instance Scheduler.
- Create a solution for Lambda — update the schedule dynamically based on workload or holiday calendar.
Code Example
{
"InstanceId": "i-0abcd1234efgh5678",
"Schedule": "office-hours"
}Case Study
Logistics firm Archway saved 40% in non-production and 15% in production environment by automatically shutting off resources using AWS Instance Scheduler. Read more about it here.
4. Right-Size EC2 Instances
Why It Matters
Overprovisioning of the instances in EC2 is one of the most common reasons for inefficiency in cloud costs. A large number of organizations have a tendency to overestimate their resource utilization, thus getting stuck with unused compute and heavy bills.
Action Plan
- Analyze CPU, memory, and disk usage across instances using AWS Compute Optimizer; it provides recommendations for resizing to optimal instance types.
- Switch to burstable instances like T3 for workloads that witness periodical spikes in demand.
- Automate right-sizing by integrating Compute Optimizer recommendations into your CI/CD pipeline.
Code Example
aws ec2 modify-instance-attribute --instance-id i-0abcd1234efgh5678 --instance-type "{\"Value\": \"t3.medium\"}"Case Study
Innovaccer, a healthcare technology company, right-sized its EC2 instances based on Compute Optimizer insights and reduced cloud spending by 33%. They also have been able to deploy T3 instances for workloads with sudden peaks and bring down their idle compute cost accordingly. Read more about it here.
5. Adopt Serverless Architectures
Why It Matters
With serverless platforms like AWS Lambda, you only pay as you go, meaning you pay for the computing time you use, which helps eliminate the costs associated with idle use.
Action Plan
- Refactor monolithic applications to event-driven AWS Lambda functions.
- Perform Memory Size and Execution Time Optimizations with AWS Lambda Power Tuning.
Code Example
import boto3
lambda_client = boto3.client('lambda')
response = lambda_client.update_function_configuration(
FunctionName='MyFunction',
MemorySize=128
)Case Study
Coca-Cola reduced 65% of operational overhead by migrating vending machine telemetry services to AWS Lambda in 2022. Read more about it here.
6. Leverage Reserved Instances and Savings Plans
Why It Matters
For predictable workloads, Reserved Instances (RIs) and Savings Plans offer up to 72% savings over On-Demand pricing.
Action Plan
- Analyze steady-state workloads and commit to 1-year or 3-year Reserved Instances.
- Position Compute Savings Plans when instance family and region flexibility is required.
- Track usage through AWS Cost Explorer to realize your full commitment ROI.
Case Study
Hiya, a telecommunications firm, automated Savings Plans and increased its Effective Savings Rate by 22% in 2022, which reduced incremental costs by $110,000 per year. Read more about it here.
7. Optimize Data Transfer Costs
Why It Matters
Data transfer is an aggressively growing cost for any workload, mainly if your workload requires cross-region traffic or content delivery.
Action Plan
- Leverage AWS CloudFront to serve frequently accessed data closer to your customers to decrease egress costs.
- Collocate resources within the same region to minimize inter-region transfer fees.
- Take advantage of usage monitoring through AWS Cost Explorer and AWS Billing Dashboard.
Case Study
Canva optimized its cloud infrastructure to yield a 46% reduction in both compute and data transfer cost, thanks to the use of CloudFront and efficient networking strategies. Read more about it here.
8. Monitoring and Cost Governance With AWS Budgets
Why It Matters
If someone does not have visibility into AWS resources spent, it is easy to overshoot. AWS Budgets and Cost Anomaly Detection provide actionable insights with alerts.
Action Plan
- Set up budgets for particular services or teams and configure notifications via email or SNS.
- Use AWS Cost Anomaly Detection to automatically flag unusual spending patterns.
Code Example
{
"Budget": {
"BudgetLimit": {
"Amount": 1000,
"Unit": "USD"
},
"Notification": {
"ComparisonOperator": "GREATER_THAN",
"Threshold": 80,
"Subscribers": [
{
"SubscriptionType": "EMAIL",
"Address": "[email protected]"
}
]
}
}
}Case Study
Zynga, a gaming company, saves millions annually by using AWS Budgets to monitor its spending to control spending on unused resources. Read more about it here.
Achieving Cost Savings in Other Major Cloud Providers
Although this guide focuses primarily on AWS, these cost savings tips also apply to other major cloud providers like Microsoft Azure, Google Cloud Platform (GCP), and. Most cloud providers offer compute, storage, networking, and monitoring services. Below is a reference table that maps AWS services to similar offerings from GCP and Azure, which makes it easier to apply the tips and suggestions discussed earlier to GCP and Azure.
| Feature/Service | AWS | Azure | Google Cloud (GCP) |
|---|---|---|---|
|
Storage Optimization |
S3 Lifecycle Policies, Intelligent-Tiering |
Azure Blob Storage Lifecycle Management |
Cloud Storage Lifecycle Policies |
|
Archival Storage |
S3 Glacier |
Azure Blob Archive Tier |
Cloud Storage Archive |
|
Compute Optimization |
EC2 Instances, Spot Instances |
Azure Virtual Machines, Spot VMs |
Compute Engine, Preemptible VMs |
|
Right-Sizing Tools |
AWS Compute Optimizer |
Azure Advisor |
GCP Recommender |
|
Serverless Computing |
AWS Lambda |
Azure Functions |
Cloud Functions |
|
Auto-Scaling |
Auto Scaling Groups |
Virtual Machine Scale Sets |
Autoscaler |
|
Monitoring & Alerts |
CloudWatch, Cost Explorer |
Azure Monitor, Azure Cost Management |
Cloud Monitoring, Billing Alerts |
|
Reserved Pricing |
Reserved Instances, Savings Plans |
Reserved Virtual Machines |
Committed Use Discounts |
|
Data Transfer Optimization |
CloudFront |
Azure Front Door |
Cloud CDN |
|
Spot Pricing Management |
Spot Instance Advisor |
Azure Spot Advisor |
Preemptible VM Recommender |
|
Budget Management |
AWS Budgets, Anomaly Detection |
Azure Budgets |
Budgets and Cost Alerts |
Conclusion
It's all about establishing an environment of effectiveness and responsibility-not just cutting a pretty penny. Take a look at how the implementation of these high-impact strategies will enable you to slash Cloud Computing costs without slashing performance. Start with the basics: right-size your compute instances or automate resource scheduling and scale your effort all the way to advanced techniques using Spot Instances, Serverless Computing, and Savings Plans. If you have a particular workload or challenge in mind, let's go a little deeper into some tailored solutions to tame your cloud bill.
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