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Showing content from https://sourcegraph.com/docs/admin/deploy/kubernetes/scale below:

Scaling Sourcegraph on Kubernetes - Sourcegraph docs

Sourcegraph can scale to accommodate large codebases and many users.

Increase resources according to the Scaling Overview per Service if you notice slower search or navigation.

For production environments, we recommend allocate resources based on your instance size. See our resource estimator for estimates.

Here is a simplified list of the key parameters to tune when scaling Sourcegraph to many repositories:

• sourcegraph-frontend CPU/memory resource allocations
• searcher replica count and CPU/memory resource allocations
• indexedSearch replica count and CPU/memory resource allocations
• gitserver replica count
• gitMaxConcurrentClones, because git clone and git fetch operations are IO and CPU-intensive
• repoListUpdateInterval (in minutes), because each interval triggers git fetch operations for all repositories

Notes:

• If your change requires restarting gitserver pods and they are rescheduled to other nodes, they may go offline briefly (showing a Multi-Attach error). This is due to volume detach/reattach. Contact us for mitigation steps depending on your cloud provider.
• See the docs to understand each service's role:
  • Sourcegraph Architecture Overview
  • Scaling Overview per Service

Here is a simplified list of key parameters to tune when scaling Sourcegraph to large monorepos:

• sourcegraph-frontend CPU/memory resource allocations
• searcher CPU/memory resource allocations (allocate enough memory to hold all non-binary files in your repositories)
• indexedSearch CPU/memory resource allocations (for the zoekt-indexserver pod, allocate enough memory to hold all non-binary files in your largest repository; for the zoekt-webserver pod, allocate enough memory to hold ~2.7x the size of all non-binary files in your repositories)
• gitserver CPU/memory resource allocations (allocate enough memory to hold your Git packed bare repositories)

Many parts of Sourcegraph's infrastructure benefit from using SSDs for caches. This is especially important for search performance. By default, disk caches will use the Kubernetes hostPath and will be the same IO speed as the underlying node's disk. Even if the node's default disk is a SSD, however, it is likely network-mounted rather than local.

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