Tutorials & Examples on Qdrant - Vector Database

Cloud Inference Hybrid Search

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Hybrid Search Using Qdrant Cloud Inference

Time: 30 min	Level: Intermediate

In this tutorial, we’ll walkthrough building a hybrid semantic search engine using Qdrant Cloud’s built-in inference capabilities. You’ll learn how to:

Automatically embed your data using cloud Inference without needing to run local models,
Combine dense semantic embeddings with sparse BM25 keywords, and
Perform hybrid search using Reciprocal Rank Fusion (RRF) to retrieve the most relevant results.

Initialize the Client

Initialize the Qdrant client after creating a Qdrant Cloud account and a dedicated paid cluster. Set cloud_inference to True to enable cloud inference.

Managed Cloud Prometheus Monitoring

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Monitoring Managed Cloud with Prometheus and Grafana

This tutorial will guide you through the process of setting up Prometheus and Grafana to monitor Qdrant databases running in Qdrant Managed Cloud.

Prerequisites

This tutorial assumes that you already have a Kubernetes cluster running where you want to deploy your monitoring stack, and a Qdrant database created in Qdrant Managed Cloud. You should also have kubectl and helm configured to interact with your cluster.

Self-Hosted Prometheus Monitoring

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Monitoring Hybrid/Private Cloud with Prometheus and Grafana

Time: 30 min	Level: Intermediate

This tutorial will guide you through the process of setting up Prometheus and Grafana to monitor Qdrant databases running in a Kubernetes cluster used for Hybrid or Private Cloud.

Prerequisites

This tutorial assumes that you already have a Kubernetes cluster running and a Qdrant database deployed in it, using either a Hybrid Cloud or Private Cloud deployment. You should also have kubectl and helm configured to interact with your cluster.