Infrequently Accessed Data Stored in Azure Cosmos DB

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Chibueze Eke

Service Category

Database

Cloud Provider

Azure

Service Name

Azure Cosmos DB

Inefficiency Type

Inefficient Storage Tiering

Explanation

Azure Cosmos DB is optimized for low-latency, globally distributed workloads—not long-term storage of infrequently accessed data. Yet in many environments, cold data such as logs, telemetry, or historical records is retained in Cosmos DB due to a lack of lifecycle management.

Relevant Billing Model

Cosmos DB charges include:

Data storage billed per GB per month, across all regions where data is replicated
Provisioned throughput (RU/s) or autoscale, billed regardless of actual usage
Backup storage billed separately (if configured)
Serverless mode available, but subject to limitations on scaling and total RU consumption

Storing cold data incurs persistent storage charges and may inflate RU requirements unnecessarily.

Detection

Identify Cosmos DB resources (e.g., containers, collections, or tables) with high storage usage but low request volume
Use Azure Monitor, diagnostic logs, or Workload Insights to assess read/write activity over time
Evaluate whether the data is actively queried or needed for operational workloads
Check whether data retention or lifecycle policies are defined for the resource

Remediation

Export infrequently accessed data to lower-cost storage services:
Use Blob Storage Cool for rarely accessed but readily retrievable data
Use Blob Storage Archive for long-term retention with delayed retrieval
Use Azure Table Storage for simple key/value access when global distribution is unnecessary
Delete cold data from Cosmos DB after successful archival
Implement data lifecycle automation to routinely transition stale data out of Cosmos DB

Relevant Documentation

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