Orchestra

Что такое Orchestra?

Orchestra is a unified control plane for data and AI orchestration. It helps data teams build, run, and monitor workflows that combine Python, dbt, AI agents, and connected infrastructure. The platform runs code on managed infrastructure and brings pipeline metadata, lineage, observability, data quality checks, and alerts into one interface.

Orchestra supports both visual workflow construction and code-based setup. Its orchestration model is designed for connecting tools across an end-to-end workflow, while its lineage views help teams identify affected assets and investigate failures. AI agent capabilities can be used alongside data workflows, including for maintenance and root-cause analysis.

Что умеет Orchestra?

Data and AI workflow orchestration

Build and run workflows that combine Python code, dbt, AI agents, and other connected tools in a single orchestration layer.

Unified metadata and observability

Collect pipeline metadata in one control plane to monitor runs, send alerts, and investigate failures across connected workflows.

End-to-end asset lineage

Visualize relationships between workflow assets, identify fresh or stale data, and rerun a workflow from a failure point.

Managed execution infrastructure

Run supported workflow code on managed infrastructure, reducing the need to build and maintain orchestration infrastructure separately.

AI-assisted maintenance

Use Orchestra AI agents for tasks such as reviewing account practices, identifying likely failure causes, and supporting automated issue triage.

Infrastructure integrations

Connect cloud, data, communication, monitoring, and developer tools through a library that the website describes as offering more than 100 integrations.

Варианты использования

“Coordinate multi-tool data pipelines”

Connect ingestion, transformation, reverse ETL, alerting, and downstream tasks into observable end-to-end workflows.

“Run dbt and Python workloads”

Use a managed orchestration environment for dbt Core and Python tasks, with completion-based triggers for dependent jobs.

“Investigate pipeline failures”

Use lineage, centralized metadata, alerts, and AI-supported root-cause analysis to locate failures and decide where to rerun.

“Operate lean data teams”

Replace separately maintained orchestration boilerplate with a shared control plane for monitoring and managing recurring data operations.

“Add agents to data operations”

Run AI agents alongside data workflows when teams need agents to access workflow context and take operational actions.

Часто задаваемые вопросы

What is Orchestra?

Orchestra is a declarative control plane for orchestrating and monitoring data and AI workflows, including Python, dbt, AI agents, and connected infrastructure.

Can Orchestra run dbt and Python?

Yes. The website describes managed execution for dbt Core and Python workloads, including workflow triggers that can start downstream jobs after dbt completes.

Does Orchestra provide data lineage?

Yes. Orchestra provides out-of-the-box asset lineage intended to show relationships across jobs, data freshness, and points where workflows can be rerun.

How can teams use AI in Orchestra?

AI agents can run alongside data workflows and support operational tasks such as account reviews, root-cause analysis, and issue triage.

Is there a free Orchestra plan?

The pricing page lists a Lean plan at no monthly charge, alongside paid Scale Up and custom Enterprise plans.

Краткие сведения