Tenant-specific Optimization in Tectonic

In the previous lesson, we discussed how we used multitenancy to fairly and efficiently share IOPS and storage capacity. Earlier tenants were using different strategies to store data reliably. Some were using full data replication for speedy writes and reads, while others were using the Reed-Solomon encoding to reduce storage needs, but at the cost of added latency (that will be needed to encode data while writing and decoding data while reading).

We allowed multiple tenants with various workload characteristics and performance requirements to work on the same shared storage. We’ll enable tenants to request their required storage mechanism via the Client Library that we discussed earlier in our design.


Now, we consider two tenants, data warehousing and blob store, as our examples to explain the specific storage consumption or latency-related optimizations. The following are the two ways to perform tenant-specific optimization for low latency and storage efficiency.

  1. Optimizing writes on data warehouse: We need to optimize how large-scale data can be stored using full-block operations. Since the data is large, we can’t use partial block operations because, in such use cases, partial blocks will increase the latency and decrease storage efficiency.

  2. Optimizing blob storage: We need to optimally store the small-scale data (blobs) as well, where blob storage comes in. Since the data is not at a large scale, we’ll perform partial-block operations on both hot and warm blobs.

The following illustration shows the summary of the optimizations for both tenants.

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