Where are you on the Cloud Spend Optimization Maturity Curve?

Cloud Spend Optimization Maturity Curve

  1. Visibility — visibility of all costs across clouds, accounts, and applications. This is cloud cost management 1.0, the ability to see cost data better through budgeting, chargeback, and showback.
  2. Schedule suspend — turn off idle resources like virtual machines, databases, scale groups, and container services when not being used, such as nights and weekends based on usage data. This is most common for non-production resources but can have a big bang in terms of savings — 65% savings is a good target that many ParkMyCloud customers achieve even during a free trial.
  3. Delete unused resources — this includes identifying orphaned resources and volumes and then deleting them. Even though you may not be using them, your cloud provider is still charging you for them.
  4. Sizing IaaS (non-production) — many enterprises overprovision their non-production resources and are using only 5–10% of the capacity of a given resource, meaning 90% is unused (really!) so by leveraging usage data you can get recommendations to resize those under utilized resources to save 50% or more.
  5. RI / Savings Plan Management — AWS, Azure, and Google provide the ability to pre-buy capacity and get discounts ranging from 20–60% based on your commitments in both spend and terms. While the savings make it worthwhile, this is not a simple process (though it’s improved with AWS’s savings plans) and requires a very good understanding of the services you will need 12–36 months out.
  6. Scaling IaaS (prod) — this requires collecting data and understanding both the infrastructure and application layers and taking sizing actions up or down to improve both performance and cost. Taking these actions on production resources requires strong communication between Operations and LoB.
  7. Optimizing PaaS — virtual machines, databases, and storage are all physical in nature and can be turned off and resized, but these top the maturity curve since many PaaS services have to be optimized in other ways like scaling the service up/down based on usage or rearchitecting parts of your application.



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