Azure Cache for Redis is billed at a fixed rate determined entirely by the provisioned tier and cache size — not by actual utilization. A cache instance that consumes only a fraction of its available memory and throughput incurs the same cost as one running at full capacity. This means that when a cache is sized larger than the workload demands, the unused memory and throughput headroom represent pure waste with no corresponding benefit.

Overprovisioning commonly occurs when teams size caches for anticipated peak loads that never materialize, or when workload patterns shift over time — such as after a migration, application refactor, or traffic decline — without a corresponding review of cache sizing. Because there is no option to stop or pause billing on a cache instance, and charges accrue continuously from the moment the cache is created until it is deleted, oversized caches quietly accumulate unnecessary costs around the clock.

An important constraint compounds this issue: scaling down between tiers is not supported. An organization that initially provisions a Premium-tier cache but later determines that a Standard tier would suffice cannot simply downgrade in place — it must create a new cache at the appropriate tier and migrate data. This friction often delays right-sizing efforts and prolongs overspend.