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Recommended RU Configuration for CosmosDB Container in Real-Time Event Stream Pipeline

Kbaig109 0 Reputation points
2025-04-23T22:20:22.21+00:00

What is the optimal RU configuration for a CosmosDB container when it is used as a source in a real-time ingestion pipeline? The initial attempt was made with a free tier CosmosDB container, which did not work. After creating another container with unlimited RU, it successfully loaded Cosmos data into the event house. However, the CosmosDB cost dashboard indicates a usage of 9000 RU. What configuration is recommended for the container that retrieves event data and connects to the real-time events pipeline in the data fabric?

Azure Cosmos DB
Azure Cosmos DB
An Azure NoSQL database service for app development.
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  1. Sai Raghunadh M 3,155 Reputation points Microsoft External Staff
    2025-04-23T23:16:15.3366667+00:00

    Hi @ Kbaig109

    Thank you for your question! To recommend an appropriate Request Unit (RU) configuration for your Azure Cosmos DB container, it would be helpful to know more about your workload, such as the expected read/write patterns, data size, query complexity, and whether you prefer manual or autoscale throughput. In the absence of specific details, I can provide general guidance to help you choose an optimal RU/s setting.

    When configuring Request Units (RUs) for a CosmosDB container in a real-time ingestion pipeline, consider the following:

    Use the Azure Cosmos DB Capacity Calculator to estimate RU/s based on your expected operations (reads, writes, queries) and data size.

    Monitor existing workloads using Azure Monitor to analyze the Normalized RU Consumption metric, which shows how much of your provisioned throughput is used.

    https://learn.microsoft.com/en-us/azure/cosmos-db/how-to-choose-offer

    Autoscale Throughput

    Autoscale mode dynamically adjusts RUs based on workload demand, ensuring cost efficiency while handling spikes. You can set a maximum RU limit (e.g., 10,000 RUs) to control costs while maintaining performance.

    Partition Key Optimization

    Ensure your partition key evenly distributes data and workload across partitions. This prevents "hot partitions" that consume disproportionate RUs and can lead to throttling.

    Monitor RU Usage

    Use the CosmosDB Insights feature to monitor RU consumption and identify patterns. This helps in fine-tuning the RU configuration to match your pipeline's requirements.

    Provisioned Throughput

    If your workload is predictable, provisioned throughput might be more cost-effective. For example, setting 9,000 RUs as provisioned throughput ensures consistent performance without over-provisioning.

    Cost Management

    Regularly review the CosmosDB cost dashboard to ensure your RU configuration aligns with budget constraints. Autoscale can help avoid over-provisioning while handling peak loads.

    Follow best practices for scaling provisioned throughput to optimize performance and cost.

    Hope this helps. Do let us know if you any further queries.

    If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

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