Operations

Everything you need to deploy, configure, and run Qdrant in production. These pages cover installation, capacity planning, distributed setups, security, monitoring, performance optimization, and troubleshooting.

Capacity Planning

Capacity Planning helps you estimate memory and storage requirements based on your vector dimensions, quantization settings, and dataset size.

Installation

Installation covers how to run Qdrant using Docker, from packages, or from source, including basic configuration options.

Snapshots

Snapshots describe how to back up and restore collections at a point in time, for individual nodes or the full cluster.

Usage Statistics

Usage Statistics explains the anonymized telemetry Qdrant collects and how to opt out.

Monitoring & Telemetry

Monitoring covers Qdrant’s metrics endpoint, Prometheus integration, and health-check APIs for observability.

Security

Security explains how to enable API key authentication and TLS to secure your Qdrant instance.

Troubleshooting

Troubleshooting lists common errors and their solutions to help diagnose issues quickly.

Configuration

Configuration documents all available Qdrant configuration file settings and environment variable overrides.

Administration

Administration covers runtime administration tools, including recovery mode and collection locking.

Distributed Deployment

Distributed Deployment explains how to run Qdrant as a multi-node cluster, including sharding, replication, and consensus.

Running with GPU

Running with GPU describes how to enable GPU-accelerated indexing using dedicated Qdrant Docker images for NVIDIA and AMD GPUs.

Optimize Performance

Optimize Performance walks through three main strategies for tuning Qdrant for high speed, low memory, or high precision workloads.

Optimizer

Optimizer describes the background optimizer process that rebuilds segments to improve search performance over time.