Taming the Cloud Beast: Effective Strategies to Control AWS Expenses

WhatsApp Group Join Now
Telegram Group Join Now

The agility and scale of AWS can accelerate innovation and business growth. However, the pay-as-you-go model can also result in painful sticker shock if AWS spending grows unchecked.

This guide covers proven strategies to tame the cloud billing beast by optimizing your AWS footprint to reduce costs, including:

  • Enforcing Financial Governance
  • Rightsizing Instances
  • Leveraging Auto Scaling Groups
  • Minimizing Data Transfer Charges
  • Architecting for Cost Efficiency
  • Choosing Savings Plans
  • Building in Reserved Capacity
  • Utilizing Spot Instances
  • Automating Shutdowns
  • Offloading Storage
  • Getting visibility into Spend
  • Eliminating Idle Resources
  • FAQs on Controlling Costs

Equipped with these techniques, you can Continuously optimize AWS usage to achieve economies of scale, rather than penalties of scale. Let’s get started!

Enforcing Financial Governance

The key to long term cost optimization is instituting checks and balances into your cloud financial management early through governance measures like:

  • Tag resources consistently to group usage and allocate charges
  • Configure billing alerts for unexpected spend spikes
  • Enforce approvals for deploying instances or infrastructure
  • Monitor budgets regularly and adjust resources to align with changing needs
  • Democratize visibility into spend and empower teams to optimize their resources

Such governance ensures awareness across the organization and facilitates cost centric decision making when provisioning AWS services.

Rightsizing Instances

A common culprit behind inflated AWS bills is overprovisioned EC2 instances that are underutilized. Right size instances to meet actual demand:

  • Use monitoring tools to determine realistic computing needs
  • Switch to lower cost instance families for adequate performance
  • Scale vertically to use fewer large instances over many small instances
  • Use auto-scaling groups and load testing to right size capacity

Saving even 20% per instance can add up substantially for large deployments.

Leveraging Auto Scaling Groups

While fixed capacity clusters seem simpler to manage, they end up overprovisioned and inefficient cost-wise. Instead, leverage Auto Scaling groups to dynamically scale capacity up or down based on actual demand by:

  • Defining metrics like CPU usage to trigger scaling
  • Adding instances during demand spikes to maintain performance
  • Removing instances when activity decreases to cut costs
  • Paying only for the compute needed minute to minute

This keeps usage aligned to workloads rather than guesstimated projections.

Minimizing Data Transfer Charges

For global deployments, AWS data transfer fees for moving data between regions or in/out of AWS can tack on thousands of dollars in networking costs. Strategies like:

  • Caching common content locally with services like CloudFront
  • Routing traffic strategically closer to users
  • Consolidating data stores to same regions as processing apps
  • Scheduling large data migrations during AWS free tier allowances
  • Using AWS Direct Connect for consistent heavy traffic

Reduces unnecessary data shuffling across geographies.

Architecting for Cost Efficiency

Certain architectures lend themselves better to cost efficiency on AWS:

Serverless Designs

Leverage serverless offerings like Lambda, DynamoDB and S3 where possible to completely eliminate the cost of renting and managing EC2 capacity when workloads are idle or have variable traffic. Only pay for actual compute consumed.


Deconstructing monoliths into independently scalable microservices avoids overprovisioned resources. Individual components can scale up and down to their needs rather than entire bloated apps.

Auto Scaling Groups

Allows horizontal scaling out/in at a granular level based on user load for different application tiers, avoiding stagnant clusters and improving cost elasticity.

Choosing Savings Plans

Savings Plans provide discounted rates in return for a commitment to consistent usage of certain services over a 1 to 3 year term. Ideal when predictable base utilization is expected for offerings like:

  • EC2
  • Fargate
  • Lambda
  • DynamoDB
  • Relational Database Service

Up to 72% discounts are possible in exchange for workload commitment.

Building in Reserved Capacity

If consistent EC2 usage is guaranteed for a target instance type, Reserved Instance (RI) capacity delivers steep discounts up to 75% for 1 to 3 year terms compared to on-demand costs. Strategic provisioning of RIs for steady state usage paired with auto-scaling groups and augmented by Spot capacity allows optimizing blended EC2 expenses.

Utilizing Spot Instances

For batch jobs, Dev/Test environments or workloads with flexible start/stop timing, Spot instances offer extreme discounts up to 90% off of on-demand costs. By defining maximum hourly price thresholds for compute capacity, unused EC2 capacity can be accessed at a fraction of typical costs. Savings can be substantial for price insensitive fault tolerant workloads.

Automating Shutdowns

With developers spins up resources for tasks but then forgetting to terminate, unused resources left running overnight or weekends racks up unnecessary charges. Automation ensures prompt shut down:

  • Schedule Lambda functions to stop/terminate resources on timing
  • Configure auto-scaling groups to fully scale in during non-peak times, shutting down unused capacity
  • Leverage third party tools like CloudCustodian to enforce shutdown policies across accounts

Offloading Storage

Persisting rapidly growing data in lower cost S3 tiers instead of relying solely on provisioned EBS volumes leads to substantial savings, while data lifecycle management automates transition across access tiers:

  • Archive cold data to cheaper Infrequent Access or Glacier tiers
  • Delete stale logs and artifacts with lifecycle expiration policies
  • Leverage EBS snapshots for backup/recovery over retaining volumes

This reduces the accumulating footprint of high IOPS storage capacity.

Getting Visibility into Spend

You can’t control what you don’t measure. Granular visibility into expenditure and adoption enables targeted optimization:

  • Break down monthly costs by service, user, tags
  • Configure fine grained budgets with alerts and alarms
  • Analyze usage and forecast trends with Cost Explorer
  • Normalize reports for department or project chargebacks

This illuminates cost drivers prompting action like reserved capacity purchases or elimination of unused resources.

Eliminating Idle Resources

Finding and ruthlessly culling unused and stale resources eliminates paying for wasted capacity:

  • Enforce auto shutdown of inactive development environments overnight
  • Monitor CloudTrail logs to detect ghost accounts or unattached resources
  • Right size to actual minimum capacity needed rather than simple defaults
  • Set policies to deny non-approved instance types or resource configurations
  • Subscribe to Trusted Advisor notifications for optimization tips

Scaling back forgetten resources saves thousands.

FAQs About Controlling AWS Costs

Here are some frequent questions about optimizing cloud spends:

How do you avoid sticker shock from AWS?

Use granular tags, budgets, alarms and cost allocation to get visibility for accountability. Analyze monthly charges at a detailed level instead of just total amounts to find problem areas prompting action.

When are Reserved Instances (RIs) worth it?

For steady usage of resource types like RDS databases, Elasticache nodes or consistent EC2 instance families, 1-3 year RIs makes sense over paying hourly on-demand rates. Discounts up to 75% are possible with upfront payment on RIs.

How do Savings Plans compare to RIs?

While RIs lock you into specific instance types, Savings Plans offer similar discounts more flexibly across a scope of resources like Lambda and Fargate, not just EC2. This provides greater agility.

Can third party tools help control AWS costs?

Yes. Cloud financial management tools like Cloudability, CloudHealth, ParkMyCloud etc. can automate policy enforcement, provide granular visibility into usage and forecasts and optimize deployments through recommendations.


Taming unwieldy AWS expenses boils down to governance, granular visibility, architectural strategies like auto-scaling and serverless, plus automation of shutdowns, autoscaling and resource sizing.

Additional best practices like consolidating accounts, using tags judiciously and maximizing free tier benefits also facilitate cost centric cloud management. With growing cloud bills giving finance teams heartburn, proactively implementing these measures will help keep your cloud footprint lean.

The economies of scale made possible by the cloud are only capped by the creativity of builders. Stay ahead of the curve through continuous optimization.

Share This

Hello, I have been doing Blogging for more than 3 years. Currently I am sharing this experience with you on this website.

Leave a Comment