Concepts
This page is a quick reference for the core building blocks you will encounter throughout Yeedu. Each section links to the area of the docs where you can configure that concept in detail.
Workspaces
Workspaces are isolated, top-level environments that group users, projects, resources, and policies for a team or business unit. A workspace centralizes configuration — networking, storage, integrations — and membership controls so you can keep development, staging, and production cleanly separated.
See [Workspaces](../Workspaces/Create Workspaces.md) to create and manage them.
Clusters
Clusters supply the compute (CPU, RAM, autoscaling) for interactive analysis and batch jobs. Use ephemeral clusters for ad-hoc work and persistent clusters for production. You manage cluster lifecycle, sizing, and autoscaling to balance performance, cost, and workload isolation.
See [Clusters](../Clusters/Create Cluster.md) for sizing and lifecycle options.
Catalogs (metastores)
Catalogs hold table and schema metadata — locations, partitions, formats — so compute engines can discover datasets reliably across object stores. Use a centralized, Hive-compatible metastore or an external catalog (Glue, Unity) to share schemas and enable governance.
See [Catalogs](../Catalogs/Create Catalogs/Hive Metastore.md) for the supported types.
Access control
Access control (RBAC and ACLs) determines who can view or modify workspaces, clusters, catalogs, jobs, and notebooks. It integrates with SSO and your identity provider for centralized identity. Apply least-privilege roles, group-based policies, and resource-level ACLs, and use audit logs to satisfy security and compliance requirements.
See [Access management](../Access Control/access_management.md) and [Roles](../Access Control/Roles.md).
Jobs
Jobs are reproducible, scheduled or event-driven pipelines that run code with parameters on a specified cluster profile. They support retries, alerts, and artifact tracking. Use jobs to operationalize ETL, ML training, and production workflows, then monitor each run through logs and metrics.
See [Jobs](../Jobs/Create Job.md) and the [Jobs dashboard](../Jobs/Jobs dashboard.md).
Notebooks
Notebooks combine code, visualizations, and narrative for exploratory data analysis and prototyping. Attach a notebook to a cluster for interactive execution. For reproducibility, pin environment specs and convert stable analyzes into parameterised jobs for production scheduling.
See [Create a notebook](../Notebook/Create notebook.md) and the [Editor pane](../Notebook/Editor Pane.md).
Secrets
Secrets store the credentials your clusters and jobs need to reach external systems — object stores, databases, third-party APIs — without committing values into code. Yeedu organizes secrets into tenant, workspace, and user scopes so you can control who can read each value.
See Secrets overview.
Mounts
Mounts attach external storage (S3, Azure Blob Storage, GCS, NFS, SMB) to your clusters so workloads can read and write data without hard-coding credentials.
See Mounts overview.
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