Optimizing Storage Costs for Historical Data in Elasticsearch on Azure: Seeking Community Advice

I have an Elasticsearch cluster deployed on Azure. I need to retain historical data in Elasticsearch and currently use snapshot policies to store snapshots in Azure Blob storage. However, over time, I noticed that the storage costs for Azure Blob are becoming significant. I'm considering using Azure Blob's lifecycle management policy to move blobs older than 1 year to the Archive tier. This way, I can save costs while still being able to unfreeze and restore the archived data if needed. Is this a reasonable approach?

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