Amazon Web Services has become the dominant cloud platform for businesses worldwide, offering over 200 fully featured services that empower organisations to innovate, scale, and operate globally. Despite its advantages, unchecked cloud spending is one of the most common problems organisations face once they are established on AWS. AWS Cost Optimization is the discipline of reducing cloud waste, eliminating unnecessary spend, and ensuring that every rupee spent on AWS delivers proportionate business value. 

Whether you are a startup managing a tight engineering budget, a growing SMB whose AWS bill has begun increasing faster than revenue, or an enterprise running complex multi-account AWS environments, AWS Cost Optimization practices apply at every scale. The strategies in this guide address the three root causes of AWS waste, idle and over-provisioned resources, pricing complexity, and the sheer volume of AWS services available, and provide actionable steps to address each one systematically. 

This 2026 guide covers 10 proven AWS Cost Optimization strategies, from selecting the right region and scheduling unused instance shutdowns to managing Reserved Instances, Savings Plans, and storage cleanup. CloudMinister provides managed AWS services for Indian businesses, including cloud infrastructure management, AWS account optimisation, and cost governance. Explore AWS Cloud Hosting through CloudMinister for managed AWS services in India. 

Root Causes of Wasteful AWS Spending 

Before applying AWS Cost Optimization strategies, understanding why AWS bills grow unexpectedly helps teams prioritise where to focus their efforts. Three categories account for the majority of avoidable AWS spending: 

• Mismanaged cloud resources: idle instances that run continuously without serving traffic, unused EBS volumes and snapshots that persist after instances are terminated, over-provisioned instances sized for peak load but running at low utilisation the majority of the time, and orphaned load balancers with no active backend instances 
• Pricing complexity: AWS pricing varies by region, service, instance type, data transfer direction, and purchasing model. Without a structured AWS Cost Optimization programme, teams default to on-demand pricing for all resources, missing the 40 to 72 percent discounts available through Reserved Instances and Savings Plans 
• Service proliferation: AWS offers over 200 fully featured services. Teams frequently spin up new services for evaluation or short-term projects without establishing policies for cleanup and decommissioning, leaving costs accumulating long after the initial use case has ended 

A key principle of AWS Cost Optimization is that a higher AWS bill is not necessarily bad if it directly corresponds to business growth. The goal is not to minimise the AWS bill at all costs but to minimise the unit cost — the total AWS spend divided by the volume of value-generating actions your application produces, such as user sessions, API calls, transactions processed, or data delivered. When unit cost decreases while output grows, AWS Cost Optimization is working. 

10 AWS Cost Optimization Best Practices for 2026

Strategy 1: Select the Optimal AWS Region for AWS Cost Optimization

Region selection is one of the first and most impactful AWS Cost Optimization decisions because AWS pricing varies significantly between regions. The same EC2 instance type can differ by 10 to 30 percent in cost between regions. Most Indian businesses should evaluate the ap-south-1 (Mumbai) and ap-south-2 (Hyderabad) regions first, as these provide the lowest latency for Indian users and satisfy DPDPA 2023 data residency requirements for personal data of Indian citizens. 

Key factors to evaluate when selecting a region for AWS Cost Optimization:

• Pricing: each AWS region has its own pricing for compute, storage, and data transfer. Use the AWS Pricing Calculator to compare total monthly costs across candidate regions for your specific service mix before committing to infrastructure deployment 
• Latency: regions closer to your primary user base reduce application latency and improve user experience. For Indian applications serving Indian users, ap-south-1 (Mumbai) or ap-south-2 (Hyderabad) provide the lowest latency and should be the default evaluation starting point 
• Service availability: not all AWS services are available in every region. Verify that every AWS service your application requires is available in your target region before making a region selection 
• Data sovereignty and DPDPA 2023: storing and processing personal data of Indian citizens in AWS India regions (ap-south-1 and ap-south-2) satisfies DPDPA 2023 data localisation requirements. For regulated Indian organisations, this constraint may override pure cost considerations 
• Multi-region availability: for applications requiring high availability or disaster recovery, deploying across multiple regions provides resilience but increases cost. Factor cross-region data transfer costs into multi-region architecture decisions 

CloudMinister’s AWS Cloud Hosting services include architecture review and region selection guidance for Indian businesses, ensuring cloud deployments are both cost-optimised and DPDPA 2023 compliant from the initial design stage. 

Strategy 2: Schedule Shutdowns for Unused Instances 

One of the simplest and most immediately effective AWS Cost Optimization measures is automatically shutting down instances that are not in use. Development, staging, and testing environments that run continuously through nights, weekends, and holidays generate costs without delivering value. A development environment running 24/7 at full on-demand price can be reduced to 40 to 50 percent of its current cost by implementing scheduled shutdowns during off-hours. 

AWS Cost Optimization approaches for instance scheduling: 

• AWS Instance Scheduler: an Amazon-provided solution that automatically starts and stops EC2 and RDS instances based on a defined schedule. Configure instances to stop at the close of the business day and restart at the start of the next working day, eliminating overnight and weekend costs for non-production environments 
• Usage pattern analysis: use AWS CloudWatch metrics to analyse actual instance utilisation patterns before defining schedules. This identifies the genuine usage windows and prevents schedules that inadvertently stop instances during actual working hours 
• Non-production environment policies: establish an organisational policy that all development, staging, QA, and testing instances must have shutdown schedules applied. Treat always-on non-production instances as a policy exception that requires explicit justification and approval 
• EBS volume cost awareness: verify whether EBS volumes associated with scheduled instances incur charges when the instance is stopped. EBS storage charges continue whether the instance is running or stopped, so AWS Cost Optimization requires reviewing storage alongside compute costs 

Strategy 3: Identify and Right-Size Underutilised EC2 Instances 

Over-provisioning EC2 instances is one of the most common AWS Cost Optimization opportunities. Teams frequently select instance types based on peak load requirements or default to large instances to avoid performance issues, resulting in instances running at 10 to 20 percent CPU utilisation for the majority of their lifetime. Identifying and right-sizing these instances is a direct path to AWS Cost Optimization without any impact on application performance. 

AWS tools for identifying right-sizing opportunities: 

• AWS Cost Explorer Resource Optimization report: identifies idle or underutilised EC2 instances and provides specific recommendations for stopping or downsizing each instance based on historical utilisation data 
• AWS Compute Optimizer: analyses EC2 instance usage patterns and recommends the optimal instance type for each workload, including recommendations to downsize over-provisioned instances, upsize instances with performance bottlenecks, and change instance families for better price-performance ratios 
• AWS Operations Conductor: automatically resizes EC2 instances based on recommendations from Cost Explorer, enabling automated right-sizing without manual intervention for qualifying instances 
• AWS Trusted Advisor: flags EC2 instances with low utilisation as part of its cost optimisation checks, providing a high-level view of right-sizing opportunities across the account 

When implementing right-sizing as part of AWS Cost Optimization, review CPU, memory, network, and disk I/O utilisation together rather than CPU alone. An instance with low average CPU utilisation may still be correctly sized if it experiences regular memory pressure or disk I/O bursts that a smaller instance type would not handle adequately. 

Related reading: Unlocking the Power of AWS: Simplifying Cloud Servers with Managed Hosting 

Strategy 4: Use Amazon EC2 Spot Instances for Appropriate Workloads 

EC2 Spot Instances represent the single largest percentage discount available in AWS Cost Optimization — up to 90 percent compared to on-demand prices. Spot Instances use spare AWS EC2 capacity that Amazon makes available at a significantly discounted price. The trade-off is that Amazon can reclaim Spot Instances with a two-minute warning when the capacity is needed for on-demand or Reserved Instance customers. 

Workload types suitable for AWS Cost Optimization with Spot Instances: 

• Batch processing jobs and data analytics workloads that can checkpoint progress and resume after interruption 
• CI/CD pipeline build jobs that can be retried without data loss if an instance is reclaimed 
• Machine learning training jobs that use checkpoint-based training frameworks 
• Video transcoding, image processing, and rendering workloads that are stateless between units of work 
• Development and testing environments where occasional interruption is acceptable 

AWS Cost Optimization approaches for Spot Instance reliability: 

• Auto Scaling Group with mixed instance types: run Spot Instances within an Auto Scaling Group alongside a baseline of on-demand instances. When Spot Instances are reclaimed, the ASG maintains minimum capacity through on-demand instances, preventing complete service interruption 
• Spot Instance diversification: request multiple instance types and Availability Zones in a Spot fleet to reduce the likelihood of simultaneous reclamation across all instances 
• EC2 Spot placement score: use the Spot placement score feature to identify instance type and Availability Zone combinations with the highest availability of Spot capacity and lowest interruption frequency before deploying Spot workloads 

Strategy 5: Optimise EC2 Auto Scaling Group Configuration 

Auto Scaling Groups are an important component of AWS Cost Optimization because they allow EC2 capacity to match actual application demand rather than running at fixed capacity provisioned for peak load. An incorrectly configured ASG can either over-provision capacity during low-demand periods or under-provision during peaks, both of which are failures of AWS Cost Optimization. 

AWS Cost Optimization configuration guidance for Auto Scaling Groups: 

• Scale conservatively when adding capacity: configure scale-out policies to add instances incrementally rather than in large steps. Adding too many instances too quickly during a traffic spike creates cost waste once the spike subsides 
• Scale aggressively when removing capacity: configure scale-in policies to reduce instance count to the minimum needed to sustain current load as quickly as the application allows. Slow scale-in policies leave excess capacity running unnecessarily 
• Use predictive scaling for known traffic patterns: AWS Auto Scaling predictive scaling analyses historical CloudWatch metrics to anticipate demand and add capacity proactively before expected spikes, reducing the latency of reactive scale-out events 
• Define accurate minimum and maximum capacities: set minimum capacity to the level required to handle baseline load without any scale-out. Set maximum capacity to a value that prevents runaway scaling events from generating unexpected cost spikes 
• Monitor scaling activity: review the ASG activity history regularly using the Auto Scaling Console or the describe-scaling-activities CLI command to identify instances of unnecessary scaling and refine policies 

For AWS Cost Optimization in Auto Scaling Groups, combine on-demand instances for baseline capacity with Spot Instances for burst capacity. This mixed purchasing model captures the 90 percent Spot discount for variable capacity while maintaining guaranteed baseline availability through on-demand instances. 

Strategy 6: Maximise Reserved Instance Utilisation 

Reserved Instances are one of the most powerful tools in AWS Cost Optimization for workloads with consistent, predictable usage. By committing to use an EC2 instance for one or three years, organisations receive discounts of up to 72 percent compared to on-demand pricing. For any workload that runs continuously or near-continuously, Reserved Instances deliver significant and immediate AWS Cost Optimization benefit. 

Reserved Instance types and their AWS Cost Optimization trade-offs: 

• Standard Reserved Instances: provide the highest discount (up to 72 percent) but cannot be changed to a different instance family. Standard RIs can be sold on the AWS Reserved Instance Marketplace if the commitment period ends before the requirement does 
• Convertible Reserved Instances: provide a lower discount (up to 66 percent) but allow the instance type, operating system, and tenancy to be changed during the commitment period. Cannot be sold on the Marketplace. Best for workloads where the required instance type may change as the application evolves 
• Regional vs Zonal Reserved Instances: Regional RIs apply discount to any instance in the same family across all Availability Zones in the region and allow instance size flexibility within the family. Zonal RIs apply to a specific Availability Zone and guarantee capacity but do not allow flexibility 
• Payment options: paying all upfront provides the largest discount. Partial upfront provides a moderate discount. No upfront provides the smallest discount but preserves cash flow. The optimal payment option depends on the organisation’s cost of capital compared to the AWS Cost Optimization benefit of larger upfront discounts 

The most common AWS Cost Optimization mistake with Reserved Instances is committing to capacity that the organisation does not actually sustain. Before purchasing Reserved Instances, analyse at least 90 days of historical usage data in AWS Cost Explorer to confirm that the workload runs consistently at the level for which Reserved Instances are being purchased. 

Strategy 7: Implement AWS Compute Savings Plans 

AWS Compute Savings Plans provide flexible discounts of up to 66 percent compared to on-demand pricing in exchange for a commitment to a consistent level of compute usage, measured in USD per hour, for one or three years. Unlike Reserved Instances, Savings Plans automatically apply discounts across EC2, Lambda, and Fargate regardless of instance type, family, operating system, or region. 

Savings Plans advantages for AWS Cost Optimization: 

• Flexibility: Savings Plans apply to any EC2 instance type, size, operating system, or region, and to Lambda and Fargate usage. This flexibility makes Savings Plans suitable for organisations whose workloads change over time without requiring the organisation to sell and repurchase Reserved Instances 
• Automatic application: AWS automatically applies Savings Plans discounts to eligible compute usage as it occurs, reducing the complexity of managing which specific instances should be covered by which commitment 
• Right-sizing compatibility: because Savings Plans apply at the USD per hour commitment level rather than to specific instance types, right-sizing exercises do not invalidate existing Savings Plan commitments 
• AWS Cost Explorer integration: AWS Cost Explorer provides Savings Plans purchase recommendations based on actual recent usage patterns, making it straightforward to identify the commitment level that maximises AWS Cost Optimization benefit without over-committing 

Third-party AWS Cost Optimization platforms such as CloudHealth, Spot.io, and Apptio Cloudability provide continuous analysis of Savings Plan utilisation and recommendations for adjusting commitments as usage patterns change, which is particularly valuable for organisations with large or dynamic compute footprints. 

Strategy 8: Manage Storage Costs Through EBS and S3 Optimisation 

Storage costs are a frequently overlooked area of AWS Cost Optimization. EBS volumes, S3 objects, and EBS snapshots accumulate over time and can represent a significant portion of the AWS bill without ongoing governance. AWS Cost Optimization for storage requires both reducing waste and implementing intelligent tiering policies. 

AWS Cost Optimization for EBS storage: 

• Delete unattached EBS volumes: when an EC2 instance is terminated, EBS volumes may persist and continue incurring storage charges. Use AWS Trusted Advisor or AWS Config rules to identify EBS volumes in Available state and establish a review and deletion process. The Delete on Termination flag should be enabled for EBS volumes that do not need to survive instance termination 
• Downsize over-provisioned volumes: EBS volumes are frequently provisioned larger than needed. Use AWS CloudWatch disk utilisation metrics to identify volumes where actual usage is significantly below provisioned capacity and resize to reduce costs 
• Choose the right EBS volume type: gp3 volumes provide higher performance than gp2 at a lower price for most workloads and should be the default EBS volume type for AWS Cost Optimization. io2 and io1 volumes should only be used for workloads with documented IOPS requirements that gp3 cannot meet 

AWS Cost Optimization for S3 storage: 

• Implement S3 lifecycle policies: automatically transition objects to lower-cost storage classes based on access frequency. S3 Standard-Infrequent Access costs approximately 40 percent less than S3 Standard. S3 Glacier Instant Retrieval costs approximately 68 percent less. S3 Glacier Deep Archive provides the lowest cost for archival data with retrieval times measured in hours 
• Enable S3 Intelligent-Tiering: S3 Intelligent-Tiering automatically moves objects between access tiers based on actual access patterns without retrieval fees. It is the recommended AWS Cost Optimization approach for datasets with unknown or variable access patterns 
• Use S3 Analytics: enable S3 Analytics on buckets with large data volumes to analyse access patterns over 30 or more days before implementing lifecycle policies, ensuring policies reflect actual usage rather than assumptions 

Strategy 9: Delete Orphaned Snapshots and Manage Backup Retention 

EBS snapshots are one of the most overlooked categories of AWS Cost Optimization. Snapshots are stored in S3 and incur monthly storage charges for the lifetime of the snapshot. When EC2 instances are terminated and EBS volumes are deleted, the snapshots created from those volumes often remain, accumulating ongoing costs without any corresponding infrastructure. 

AWS Cost Optimization for snapshot management: 

• Audit existing snapshots: use the AWS Console, AWS CLI, or a third-party tool to generate an inventory of all snapshots across all accounts and regions, identifying snapshots associated with terminated instances or deleted volumes 
• Delete unnecessary snapshots starting with the initial snapshot: most EBS snapshots are incremental and depend on the initial full snapshot of the EBS volume. Deleting the initial snapshot typically produces more significant storage savings than deleting a large number of incremental snapshots 
• Implement Amazon Data Lifecycle Manager: Amazon DLM automates the creation, retention, and deletion of EBS snapshots based on lifecycle policies. Define maximum retention periods appropriate to your recovery time objectives, and DLM will automatically delete snapshots that exceed the retention period, preventing indefinite accumulation 
• Review cross-account snapshot copies: snapshots shared or copied to other AWS accounts for disaster recovery or data sharing purposes incur charges in the destination account. Audit cross-account snapshot policies as part of AWS Cost Optimization to confirm all copies are necessary and appropriately aged 

Related reading: Why AWS Stands Out: 5 Features to Look Out For Small Businesses 

Strategy 10: Delete Idle Load Balancers and Manage Data Transfer Costs 

Elastic Load Balancers and data transfer costs are two frequently overlooked areas of AWS Cost Optimization. Load balancers incur hourly charges regardless of whether they are serving traffic. Data transfer between AWS services, Availability Zones, and to the public internet generates costs that accumulate quickly for high-traffic applications. 

AWS Cost Optimization for load balancers: 

• Identify idle load balancers: use AWS Trusted Advisor to identify load balancers with fewer than 100 requests in the last seven days, which indicates the load balancer is idle or misconfigured. Delete confirmed idle load balancers to eliminate their hourly charges 
• Consolidate underutilised load balancers: Application Load Balancers support multiple target groups and path-based routing, allowing multiple applications to share a single ALB rather than each application requiring a dedicated load balancer 

AWS Cost Optimization for data transfer: 

• Use Amazon CloudFront for egress reduction: CloudFront caches content at edge locations globally, reducing the volume of requests that reach EC2 origin instances and lowering data transfer costs from EC2 to the public internet. For applications with large content delivery volumes, CloudFront can reduce egress costs by 40 to 70 percent 
• Keep traffic within the same Availability Zone: data transfer between EC2 instances in different Availability Zones within the same region incurs charges. Architecture that minimises cross-AZ data transfer reduces these costs, which can be significant for applications with high internal API call volumes 
• Use VPC endpoints for AWS service access: accessing AWS services such as S3, DynamoDB, and SQS through public internet routes incurs data transfer costs. VPC endpoints provide private connectivity to these services without traffic leaving the AWS network, eliminating these data transfer charges 

AWS Cost Optimization Tools and Governance in 2026 

AWS provides a native suite of cost management tools that should be configured as part of any AWS Cost Optimization programme. Understanding and actively using these tools is the foundation of ongoing cost governance: 

• AWS Cost Explorer: the primary AWS Cost Optimization analysis tool. Provides visualisations of historical spending by service, account, tag, and region, and includes built-in recommendations for Reserved Instances, Savings Plans, and right-sizing 
• AWS Budgets: creates spending thresholds with automated alerts when actual or forecasted costs exceed defined limits. AWS Budgets should be configured for every AWS account as a baseline AWS Cost Optimization control, alerting teams before overspend occurs rather than after 
• AWS Cost and Usage Report (CUR): the most granular AWS billing data available, delivered to an S3 bucket for analysis in Athena, QuickSight, or third-party BI tools. CUR provides line-item detail on every AWS charge and is essential for detailed AWS Cost Optimization analysis in large accounts 
• AWS Trusted Advisor: provides automated checks across cost, performance, security, fault tolerance, and service limits. The cost optimisation checks identify idle resources, underutilised instances, unattached EBS volumes, and Reserved Instance coverage gaps 
• Resource tagging: a prerequisite for effective AWS Cost Optimization governance. Apply consistent tags for environment, team, project, and cost centre to all AWS resources, enabling cost allocation reports that show which teams and projects are driving spending 

AWS Cost Optimization Support from CloudMinister 

CloudMinister provides managed AWS services for Indian businesses, including cloud infrastructure management, cost governance, and AWS account optimisation. For organisations that want expert assistance with AWS Cost Optimization, CloudMinister offers: 

• AWS architecture review: evaluate existing infrastructure against AWS Cost Optimization best practices and identify the highest-impact savings opportunities across compute, storage, data transfer, and purchasing models 
• Reserved Instance and Savings Plans management: analyse usage patterns and recommend the appropriate RI and Savings Plan commitments to maximise discount capture without over-committing 
• Resource governance: implement tagging policies, idle resource detection, and automated cleanup for orphaned snapshots, unattached EBS volumes, and idle load balancers 
• Cost monitoring and alerting: configure AWS Budgets, Cost Explorer alerts, and account-level spending dashboards to ensure AWS Cost Optimization is visible and actionable for engineering and finance teams 
• DPDPA 2023 compliant architecture: design AWS architectures using India-region resources (ap-south-1 and ap-south-2) that satisfy DPDPA 2023 data localisation requirements for Indian organisations processing personal data 

Conclusion

AWS Cost Optimization is not a one-time project but a continuous practice that must evolve alongside your infrastructure and business requirements. AWS releases new services, instance types, pricing models, and cost management tools on a regular basis, creating ongoing opportunities to improve cost efficiency. Teams that treat AWS Cost Optimization as a regular operational discipline, reviewing utilisation monthly, acting on right-sizing recommendations, managing Reserved Instance portfolios quarterly, and enforcing resource tagging and cleanup policies — consistently achieve lower unit costs and more predictable AWS bills than teams that only review costs when a billing spike occurs. 

The 10 strategies in this guide cover the most impactful AWS Cost Optimization opportunities for the majority of organisations. Implementing even the first three, right-sizing, scheduled shutdowns, and Reserved Instances or Savings Plans for steady-state workloads, typically delivers 20 to 40 percent reduction in AWS spend for organisations that have not previously applied structured AWS Cost Optimization practices. Adding storage cleanup, snapshot lifecycle management, and load balancer audits compounds these savings further. 

Frequently Asked Questions

What is AWS Cost Optimization and why does it matter? 

AWS Cost Optimization is the practice of reducing cloud waste and ensuring that every dollar of AWS spending delivers proportionate business value. It matters because cloud costs are variable and can grow rapidly as infrastructure scales, but without structured optimisation, a significant portion of that spending typically covers idle, over-provisioned, or unnecessary resources. Effective AWS Cost Optimization reduces unit cost (total AWS spend divided by business output), improves the financial predictability of cloud spending, and ensures that engineering investment in cloud infrastructure generates measurable return. 

How much can AWS Cost Optimization typically save? 

AWS Cost Optimization savings vary by organisation and starting point, but commonly documented outcomes include: 30 to 75 percent reduction in EC2 costs through a combination of right-sizing, Reserved Instances or Savings Plans, and Spot Instance adoption; 40 to 70 percent reduction in S3 costs through lifecycle policies and Intelligent Tiering; and 20 to 50 percent reduction in total AWS bill for organisations implementing a comprehensive AWS Cost Optimization programme for the first time. The largest savings typically come from Reserved Instances and Savings Plans for steady-state compute workloads. 

What is the difference between Reserved Instances and Savings Plans for AWS Cost Optimization? 

Both Reserved Instances and Savings Plans provide discounts in exchange for usage commitments but differ in flexibility. Reserved Instances commit to a specific instance type, family, region, and operating system and provide discounts of up to 72 percent. They are most appropriate when the required instance configuration is known and stable. Savings Plans commit to a level of compute spend in USD per hour across EC2, Lambda, and Fargate, and automatically apply discounts regardless of instance type or region. Savings Plans provide up to 66 percent discount and are more appropriate for organisations with evolving infrastructure or frequent right-sizing activities. Most AWS Cost Optimization programmes use a combination of both. 

What AWS tools should I use for AWS Cost Optimization? 

The core AWS Cost Optimization tool set includes: AWS Cost Explorer for analysis, right-sizing recommendations, and Reserved Instance and Savings Plans purchase recommendations; AWS Budgets for spending thresholds and alerts; AWS Trusted Advisor for automated cost optimisation checks across idle resources, underutilisation, and RI coverage; AWS Compute Optimizer for EC2 right-sizing recommendations; AWS Cost and Usage Report for granular line-item billing data; and Amazon Data Lifecycle Manager for automated snapshot retention management. Consistent resource tagging is also a prerequisite for effective AWS Cost Optimization governance, enabling cost allocation by team, project, and environment. 

How does DPDPA 2023 affect AWS Cost Optimization decisions for Indian businesses? 

DPDPA 2023 data localisation requirements mean that Indian businesses processing personal data of Indian citizens should prefer AWS India regions (ap-south-1 Mumbai and ap-south-2 Hyderabad) for workloads involving personal data. While global regions may occasionally offer lower pricing for specific services, the compliance risk of processing Indian personal data in non-Indian regions can outweigh the cost difference. AWS Cost Optimization for Indian businesses should treat DPDPA 2023 compliance as a constraint that limits region flexibility for regulated workloads, and focus cost optimisation efforts on purchasing model optimisation, right-sizing, and storage efficiency within the India regions. 

Can CloudMinister help with AWS Cost Optimization for Indian businesses? 

Yes. CloudMinister provides managed AWS services for Indian businesses including AWS architecture review, Reserved Instance and Savings Plans management, resource governance, cost monitoring and alerting configuration, and DPDPA 2023 compliant architecture design. Our India-based team in Jaipur and Noida provides 24/7 support in IST and has experience optimising AWS environments for Indian businesses across e-commerce, SaaS, fintech, healthcare, and manufacturing sectors. Contact us at cloudminister.com/contact/ to discuss an AWS Cost Optimization engagement.