Qdrant Tenant Scaling
Guides Qdrant multi-tenant scaling. Use when someone asks 'how to scale tenants', 'one collection per tenant?', 'tenant isolation', 'dedicated shards', or reports tenant performance issues. Also use when multi-tenant workloads outgrow shared infrastructure.
MCP get_skill({ skillId: "what-to-do-when-scaling-multi-tenant-qdrant-06828541" })Use this skill with your agent
Create a free account and connect via MCP
# What to Do When Scaling Multi-Tenant Qdrant Do not create one collection per tenant. Does not scale past a few hundred and wastes resources. One company hit the 1000 collection limit after a year of collection-per-repo and had to migrate to payload partitioning. Use a shared collection with a tenant key. - Understand multitenancy patterns [Multitenancy](https://skills.qdrant.tech/md/documentation/manage-data/multitenancy/) Here is a short summary of the patterns: ## Number of Tenants is around 10k Use the default multitenancy strategy via payload filtering. Read about [Partition by payload](https://skills.qdrant.tech/md/documentation/manage-data/multitenancy/?s=partition-by-payload) and [Calibrate performance](https://skills.qdrant.tech/md/documentation/manage-data/multitenancy/?s=calibrate-performance) for best practices on indexing and query performance. ## Number of Tenants is around 100k and more At this scale, the cluster may consist of several peers. To localize tenant data and improve performance, use [custom sharding](https://skills.qdrant.tech/md/documentation/distributed_deployment/?s=user-defined-sharding) to assign tenants to specific shards based on tenant ID hash. This will localize tenant requests to specific nodes instead of broadcasting them to all nodes, improving performance and reducing load on each node. ## If tenants are unevenly sized If some tenants are much larger than others, use [tiered multitenancy](https://skills.qdrant.tech/md/documentation/manage-data/multitenancy/?s=tiered-multitenancy) to promote large tenants to dedicated shards while keeping small tenants on shared shards. This optimizes resource allocation and performance for tenants of varying sizes. ## Need Strict Tenant Isolation Use when: legal/compliance requirements demand per-tenant encryption or strict isolation beyond what payload filtering provides. - Multiple collections may be necessary for per-tenant encryption keys - Limit collection count and use payload filtering within each collection - This is the exception, not the default. Only use when compliance requires it. ## What NOT to Do - Do not create one collection per tenant without compliance justification (does not scale past hundreds) - Do not skip `is_tenant=true` on the tenant index (kills sequential read performance) - Do not build global HNSW for multi-tenant collections (wasteful, use `payload_m` instead)
Related Skills
More skills in DevOps & Cloud
1password Skill
1password Skill linked from Juliano Barbosa Claude Code Skills, with the upstream skill instructions available on GitHub.
Actions Manager
GitHub Actions command center -- view workflow runs, read logs, re-run failed jobs, manage workflows, and debug CI failures entirely from the editor. Bypasses the deeply nested, visually-dependent Actions UI that is largely inaccessible to screen readers.
Airunway Aks Setup
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".
Alz Accelerator
Deploy Azure Landing Zones using the ALZ Accelerator with AVM (Azure Verified Modules). Use this skill whenever the user mentions Azure Landing Zones, ALZ, Azure landing zone accelerator, AVM modules for landing zones, deploying management groups, hub-and-spoke networking, Virtual WAN, platform landing zones, or asks about Bicep vs Terraform for Azure infrastructure. Also trigger when the user wants to bootstrap CI/CD for Azure platform deployment, set up management groups hierarchy, or deploy connectivity/identity/management platform subscriptions.
Alz Accelerator Skill
Alz Accelerator Skill linked from Juliano Barbosa Claude Code Skills, with the upstream skill instructions available on GitHub.
Ansible Conventions and Best Practices
Ansible conventions and best practices
Explore Other Categories
Skills from other categories with shared topics
Chroma
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
Pinecone
Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or semantic search at scale. Best for serverless, managed infrastructure.
Qdrant Hybrid Search
Explains hybrid search in Qdrant. Use when someone asks 'how do I setup hybrid search?', 'how to combine keyword and semantic search?', 'sparse plus dense vectors?', 'missing keyword matches', 'how to combine results from multiple searches?' and 'combining multiple representations'