Best practices for using blob access tiers
This article provides best practice guidelines that help you use access tiers to optimize performance and reduce costs. To learn more about access tiers, see Hot, cool, and archive access tiers for blob data.
Choose the most cost-efficient access tiers
You can reduce costs by placing blob data into the most cost-efficient access tiers. Choose from three tiers that are designed to optimize your costs around data use. For example, the hot tier has a higher storage cost but lower read cost. Therefore, if you plan to access data frequently, the hot tier might be the most cost-efficient choice. If you plan to read data less frequently, the cool or archive tier might make the most sense because it raises the cost of reading data while reducing the cost of storing data.
To identify the most optimal access tier, try to estimate what percentage of the data will be read on a monthly basis. The following chart shows the impact on monthly spending given various read percentages.
To model and analyze the cost of using cool versus archive storage, see Archive versus cool. You can apply similar modeling techniques to compare the cost of hot to cool or archive.
Migrate data directly to the most cost-efficient access tiers
Choosing the most optimal tier up front can reduce costs. If you change the tier of a block blob that you've already uploaded, then you'll pay the cost of writing to the initial tier when you first upload the blob, and then pay the cost of writing to the desired tier. If you change tiers by using a lifecycle management policy, then that policy will require a day to take effect and a day to complete execution. You'll also incur the capacity cost of storing data in the initial tier prior to the tier change.
For guidance about how to upload to a specific access tier, see Set a blob's access tier.
For offline data movement to the desired tier, see Azure Data Box.
Move data into the most cost-efficient access tiers
After data is uploaded, you should periodically analyze your containers and blobs to understand how they are stored, organized, and used in production. Then, use lifecycle management policies to move data to the most cost-efficient tiers. For example, data that has not been accessed for more than 30 days might be more cost efficient if placed into the cool tier. Consider archiving data that has not been accessed for over 180 days.
To gather telemetry, enable blob inventory reports and enable last access time tracking. Analyze use patterns based on the last access time by using tools such as Azure Synapse or Azure Databricks. To learn about ways to analyze your data, see any of these articles:
Calculate blob count and total size per container using Azure Storage inventory
How to calculate Container Level Statistics in Azure Blob Storage with Azure Databricks
Tier append and page blobs
Your analysis might reveal append or page blobs that are not actively used. For example, you might have log files (append blobs) that are no longer being read or written to, but you'd like to store them for compliance reasons. Similarly, you might want to back up disks or disk snapshots (page blobs). You can move these blobs into cooler tiers as well. However, you must first convert them to block blobs.
For information about how to convert append and page blobs to block blobs, see Convert append blobs and page blobs to block blobs.
Pack small files before moving data to cooler tiers
Each read or write operation incurs a cost. To reduce the cost of reading and writing data, consider packing small files into larger ones by using file formats such as TAR or ZIP. Fewer files reduce the number of operations required to transfer data.
The following chart shows the relative impact of packing files for the cool tier. The read cost assumes a monthly read percentage of 30%.
The following chart shows the relative impact of packing files for the archive tier. The read cost assumes a monthly read percentage of 30%.
To model and analyze the cost saving of packing files, see Packing Saving tab in this workbook.
To facilitate search and read scenarios, consider creating an index that maps packed file paths with original file paths, and then storing these indexes as block blobs in the hot tier.
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