An Azure storage review checks four things in order: blob access tiers against real usage, lifecycle rules that move data automatically, redundancy settings against the actual durability requirement, and orphaned snapshots and disks that nobody owns. Most of the savings come from two moves, tiering cold data down from Hot and removing geo redundancy that no policy ever required. None of it changes how an application reads or writes, which is why storage is one of the safest lines on the Azure bill to optimize.
This is an Azure data and PaaS discipline. Run it once to recover the backlog, then automate it so it does not creep back. Here is the playbook.
Tier blob storage to access patterns
Azure Blob Storage has four access tiers: Hot for frequently accessed data, Cool for infrequent, Cold for rarely touched, and Archive for long term retention. Each step down lowers the per gigabyte storage rate but raises the cost to read the data, so the right tier follows the access pattern, not a guess.
The default failure is data written to Hot that becomes cold within weeks and stays in Hot for years. Logs, backups, raw ingest, and finished project data are usual suspects. Identify them by last access time and tier them down. The detail on each tier is in blob tiers and lifecycle management.
Automate with lifecycle rules
A one time tiering pass recovers the backlog; lifecycle management rules keep it from rebuilding. Set rules that move blobs to Cool after a defined idle period, to Cold or Archive after longer, and that delete data past its retention. Once the rules run, tiering is automatic and the review only has to confirm they still match how the data is used. Automation is what turns a one time cleanup into a permanently lower bill.
Right size redundancy and clear the orphans
Redundancy is the quiet multiplier. Geo redundant storage costs more than locally redundant storage because it replicates across regions, and it is often set higher than the workload's real durability need. Review each account against the actual requirement: not every log archive needs cross region replication. Match redundancy to the requirement and the saving is immediate.
Then clear the orphans: unattached managed disks, snapshots no restore policy will ever use, and storage accounts left behind by retired projects. These accrue with zero benefit and delete cleanly. Pair the cleanup with ownership so it does not return, covered in storage tagging and ownership on Azure.
A Fortune 500 retailer found years of telemetry and backup data sitting in the Hot tier on geo redundant accounts. A single review tiered the cold data down with lifecycle rules, dropped redundancy to locally redundant where the durability requirement allowed, and removed a stack of orphaned disks and snapshots. The storage line fell sharply with no change to any application. Figures are verified against billing data and anonymised.
Watch egress and PaaS data services
Storage cost is not only what sits at rest. Egress and cross region reads add up, and the PaaS data services around storage have their own discipline. Decommission what you no longer need before tiering it, covered in decommissioning Azure data you no longer need. The full Azure picture, including reservations and compute, is in the Azure cost optimization guide.
Frequently asked questions
What does an Azure storage review cover?
What are the Azure blob storage tiers?
How often should you review Azure storage?
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