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Qdrant Vector Database

Master Qdrant — the open-source vector database. Deploy with Docker, Kubernetes, configure for performance, and manage production clusters.

What you'll learn

Deploy Qdrant with Docker, Docker Compose, and Kubernetes Helm charts
Configure storage options: in-memory, on-disk, and hybrid modes
Tune performance parameters for low-latency vector search
Implement vector quantization to reduce memory usage
Set up distributed Qdrant clusters with sharding and replication
Configure Prometheus monitoring and Grafana dashboards
Enable TLS encryption and API key authentication
Perform backup and restore operations with snapshots

Course content

6 sections · 19 articles · 8h total

Course OverviewArticle
15m
Course RoadmapArticle
15m
Docker DeploymentArticle
Code25m
Docker Compose SetupArticle
Code25m
Kubernetes with HelmArticle
Code40m
Configuration FileArticle
25m
Storage & MemoryArticle
20m
Performance TuningArticle
15m
Collections & PointsArticle
25m
Vector Types & QuantizationArticle
20m
Payload & FilteringArticle
15m
Clustering ConceptsArticle
25m
Sharding StrategyArticle
25m
Replication & HAArticle
20m
Scaling OperationsArticle
20m
Backup & RestoreArticle
25m
Monitoring & MetricsArticle
25m
Security & TLSArticle
20m
TroubleshootingArticle
20m

Prerequisites

  • Basic Linux command line knowledge
  • Docker and Docker Compose fundamentals
  • Understanding of JSON and REST APIs
Docker Engine or Docker DesktopInstall or Podman

Container runtime required for all labs in this course.

Docker ComposeInstall or Podman Compose

Multi-container orchestration used in every hands-on exercise.