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This tutorial introduces Qdrant deployment options before walking through a managed cloud setup. The speaker describes Docker as the usual starting point for local deployment and testing: download the image, then start a container with exposed ports. Docker Compose provides a reusable configuration for a single node. For Kubernetes, the tutorial outlines adding Qdrant's Helm repository and installing its chart. These are the open source, self-hosted routes covered in the overview.
The Qdrant Cloud walkthrough covers account creation, cluster naming, and provider and region selection. The presenter chooses a free configuration for learning and testing. Connecting to the resulting cluster requires both its endpoint and an API key.
The web UI handles collections and requests. Its interactive tutorials cover loading sample data, filtering and hybrid search. The new instance has no collections yet; the speaker explains that collections hold vectors, points and payloads. The cloud dashboard handles cluster administration, including API key creation, metrics, logs and supported configuration settings. The presenter advises copying newly created keys before closing the window.
The final section introduces Cloud Inference for converting text or images into vectors with embedding models. It points to supported models but leaves the embeddings and inference walkthrough for another tutorial.
