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title: Solving the Noisy Neighbor with Sharded Architecture
description: Multi-tenant platforms suffer from the 'noisy neighbor' problem where one tenant's heavy workload degrades performance for all others. The solution is a...
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# Solving the Noisy Neighbor with Sharded Architecture

**[Google Cloud](https://daily.dev/sources/gcp)** · 3 min read · 0 upvotes · 0 comments

## Summary

Multi-tenant platforms suffer from the 'noisy neighbor' problem where one tenant's heavy workload degrades performance for all others. The solution is a sharded hub-and-spoke architecture using Google Cloud Dataflow and Pub/Sub: a lightweight hub pipeline routes data by tenant ID into isolated Pub/Sub buffers, which feed separate spoke pipelines tiered by priority. This isolates blast radius, enables independent scaling per tenant, and stabilizes SLAs. Implementation tips include Dead Letter Queues for failed records, strict connection pooling with low MaximumPoolSize per worker, and asynchronous batched writes using GroupIntoBatches to reduce database connection overhead.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/products/data-analytics/solving-the-noisy-neighbor-with-sharded-architecture>

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---

Tags: [#big-data](https://daily.dev/tags/big-data), [#distributed-systems](https://daily.dev/tags/distributed-systems)

[View this post on daily.dev](https://daily.dev/posts/solving-the-noisy-neighbor-with-sharded-architecture-rxxandjac)

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