Transition blobs to a cooler storage tier (Hot to Cool, Hot to Archive, Cool to Archive) to optimize for performance and cost. How it will improve performance when there will be latency?

Hello Ankeet Mahto,

Thank you for posting your query here!

Transitioning blobs to different storage tiers in Azure Blob Storage, such as from Hot to Cool, Hot to Archive, or Cool to Archive, primarily optimizes costs rather than improving performance. Each storage tier is designed with a different use case in mind, balancing cost and access frequency:

• Hot Tier: Optimized for data that is accessed frequently. This tier offers the lowest access latency and highest performance, but at a higher cost. Store the latest log files here, as they are frequently accessed for monitoring and debugging.
• Cool Tier: Intended for data that is infrequently accessed and stored for at least 30 days. It has lower storage costs compared to the Hot tier but higher access costs and slightly higher latency. Move log files older than one month to the Cool tier, as they are accessed less frequently but still might be needed occasionally.
• Archive Tier: Meant for data that is rarely accessed and stored for at least 180 days. It offers the lowest storage costs but comes with the highest access costs and significant retrieval latency, as data needs to be rehydrated before it can be accessed. Transition log files older than six months to the Archive tier, as they are rarely accessed but must be retained for compliance.

Cost Savings: By moving infrequently accessed data to the Cool or Archive tiers, you can significantly reduce your storage costs.

Performance Optimization: Keeping frequently accessed data in the Hot tier ensures that performance-sensitive operations run smoothly without latency issues. Transitioning older or less critical data to cooler tiers ensures that your high-performance storage is not cluttered with data that doesn’t need to be accessed quickly.

Do let us know if you have any further queries. I’m happy to assist you further.

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