.png)
How It Works
In a write-once workload, data flows in one direction: it is written to storage and then locked. Common examples include audit logs, compliance archives, financial records, backup snapshots, and media assets. Because the data never changes after it lands, you do not need the high-throughput, low-latency storage tier that active application data requires. Cloud providers offer cheaper storage classes specifically designed for this pattern. On AWS, S3 Glacier and S3 Intelligent-Tiering can automatically move infrequently accessed objects to lower-cost tiers. On Azure, Blob Storage offers Cool and Archive access tiers for the same purpose. On GCP, Cloud Storage provides Nearline, Coldline, and Archive storage classes suited to data that is rarely read after being written.
Why It Matters for Cloud Cost
Teams that store write-once data in high-performance, frequently accessed storage tiers consistently overpay. A log file written once and read only during an incident investigation costs the same per GB as a database serving live traffic if both sit in standard storage. Identifying write-once workloads and routing them to the appropriate lower-cost tier is one of the highest-return, lowest-effort actions in cloud cost optimization. The cost delta between standard and archive-class storage can exceed 80% for the same data volume. Without a lifecycle policy to automate the transition, most write-once data stays in expensive tiers indefinitely because no one manually reviews it.