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How It Works
A hybrid cloud strategy divides workloads across two environments: private infrastructure (on-premises data centers or a hosted private cloud) and public cloud providers such as AWS, Azure, or GCP. Steady, predictable workloads often run on private infrastructure where unit costs are fixed and well understood. Variable or bursty workloads move to the public cloud, where capacity scales on demand. Networking, identity, and data pipelines connect the two environments so they operate as a single logical system. The goal is to place each workload in the environment that minimizes total cost while meeting performance and compliance requirements.
Why It Matters for Cloud Cost
Without a deliberate hybrid strategy, finance and engineering teams often default to running everything in the public cloud, which generates significant on-demand spend that could have been avoided. Private infrastructure carries fixed costs that go to waste if underused, while public cloud costs spike when bursty workloads are not optimized with commitment-based discounts. A hybrid strategy forces teams to classify workloads by usage pattern before deciding where to run them. That classification is also the prerequisite for purchasing Savings Plans, Reserved Instances, or Committed Use Discounts on the public cloud side, since commitment-based discounts only produce savings when the underlying workload is stable enough to justify a term commitment.
Usage AI’s Autopilot mode automatically purchases and adjusts Savings Plans and Reserved Instances daily across AWS, GCP, and Azure, making it well-suited for organizations optimizing the public cloud portion of their infrastructure spend. ClearCost provides the showback reporting layer to track where costs are landing across cloud accounts.