E-book „22 steps to reduce your AWS bill”


Data ostatniej aktualizacji: 13.08.2021 03:37

A brief introduction to AWS cloud cost optimization

According to IDG’s 2020 Cloud Computing Survey, 59% of companies plan to be “mostly” (43%) or “all” (16%) in the cloud within the next 18 months. Flexera 2020 State of the Cloud Report also reports that companies expect to increase their cloud spend by almost 50%. Additionally, more than 50% of companies expect higher cloud usage than initially planned due to the COVID-19 effects:

  • the extra capacity needed for current cloud-based applications,
  • accelerated migration from data centers to cloud,
  • business continuity requirements.

Surprisingly only 20% of organizations would save money by moving to the cloud, whereas 80% would see an increase in their annual costs (research by Dr. Jonathan Koomey, Stanford University). The average extra cost can reach up to 36% more for cloud services than it is needed. This fear is reflected by 25% of CIOs mentioning “high or unforeseen costs” as their top challenge (McKinsey cloud survey and interview article, Oct 1, 2020). The Flexera respondents estimate that their cloud spend is over budget by an average of 23% and their organizations waste 30% of it. Therefore, it is not surprising that cloud cost optimization (“controlling cloud costs” and “cost savings”) remains at the top of companies’ 2020 priority list for the fourth year in a row becoming the no. 1:

  • cloud computing challenge chosen by 40% of the IDG respondents,
  • top initiative for a year ahead chosen by 70% of the Flexera respondents.


What you will find in our e-book

Cloud cost optimization can be defined as a process of reducing the total cloud spend by identifying mismanaged resources, eliminating waste, right sizing services, and choosing the most suitable pricing model. Successful cloud cost optimization relies on three pillars:

  • waste – tidying up how resources are used,
  • capacity – matching optimal resources configuration to workload requirements,
  • procurement – intelligent use of savings plans and reservations.

In practice, cloud cost optimization represents an ongoing process of monitoring resources performance and cost interrupted by periodic reassessment looking for opportunities to reduce cost across each of three pillars.

Through years of supporting AWS, we have faced a lot of completely different solution architectures built on top of it. No matter how simple or complicated that architecture was the first and most effective cloud cost optimization steps always came down to 22 points. Of course, the significance of these points to cost optimization could have been different for each environment but regardless of this, checking each one resulted in greater control over the use of resources and a reduction of the overall AWS cost.

In this publication, we aim to show how extensive is the topic of cost optimization and how many elements may be important for the total cost of your AWS services. If you have not yet carried out the AWS cloud cost optimization project, a safer, quicker, and more effective approach would be to get the support of an AWS expert like Altkom Software & Consulting with experience in this area. After you finish the first optimization round and set up the process then each following reassessment will be easier, more reliable, and less time-consuming for you.

We have divided the cloud cost optimization into 4 areas of interest:

  • compute – servers and databases,
  • storage – files, volumes, and buckets,
  • networking – localization and data transfer,
  • procurement – pricing and licensing.

Each area can be analyzed across three cloud cost optimization pillars.


22 cloud cost optimization areas

The AWS cloud cost optimization is a very broad topic with many different components which are cost drivers adding-up to your total bill. The optimization process is not limited to the list presented below but these are the most common and most obvious sources.


  • Terminate “Zombie assets”
  • Consolidate idle resources
  • Monitor utilization patterns
  • Match EC2 instance with workload needs
    • Scale horizontally
    • Scale vertically
  • Upgrade to the latest generation
  • Match Amazon RDS DB engine with workload needs
    • Select DB engine
    • Scale horizontally and vertically
  • Cache DB storage in-memory
  • Configure instance scheduling


  • Tidy up EBS volumes
  • Delete obsolete snapshots
  • Choose the right storage class
  • Manage files lifecycle
  • Compress files before storage
  • Remove incomplete multipart uploads
  • Optimize AWS S3 API calls


  • Control data transfer
    • Static assets
    • Cross-region transfer
  • Optimize resources location
  • Release Elastic IP addresses
  • Reorganize load balancers
    • Decommission inactive load balancers
    • Switch to application load balancers


  • Choose the right pricing model
    • Savings Plans
      • Compute Savings Plans
      • EC2 Instance Savings Plans
    • Reserved instances
      • Standard
      • Convertible
    • Spot instances
  • Consolidate billing
  • Bring Your Own License (BYOL)

Author: Dariusz Korzun
Cloud and Big Data Solutions Manager