Dagger

Dagger is a workflow orchestration platform for building, testing, and deploying codebases with modular functions and containers. Dagger Cloud adds traces, logs, metrics, and operational insights.

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Overview

Dagger is a platform for building, testing, and deploying codebases through modular components and simple functions. The product is positioned for repeatable software delivery workflows, including complex orchestration and AI-agent-driven operations.

Its core runtime runs workflows in containers and supports local execution, CI, and cloud environments. Dagger Cloud extends that platform with pipeline visualization and operational insights so teams can debug traces, inspect logs and metrics, and understand how workflows behave across development and CI.

Features

Programmable workflow platform

Dagger provides a runtime, system API, SDKs for 8 languages, and an interactive REPL for building and orchestrating delivery workflows as programmable functions.

Containerized, typed execution model

Workflows run in containers, with orchestration logic executed in sandboxed functions and host dependencies kept explicit and strictly typed.

Local and remote execution

The platform is designed to run locally, in CI servers, in AI sandboxes, or on dedicated cloud infrastructure, with the only stated dependency being a recent Linux kernel.

Observability for workflows

Dagger Cloud adds workflow visualization, traces, logs, metrics, and operational insights for debugging and understanding delivery workflows.

Default caching with visibility

Caching is built in by default, with fine-grained cache control and workflow cache visibility available in Dagger Cloud.

Module sharing and reuse

The Daggerverse lets teams publish and reuse prebuilt modules, and Dagger Cloud surfaces module insights and module catalog features on the Team plan.

Use Cases

Build repeatable delivery pipelines
Use Dagger to define test and delivery workflows as code, then run them repeatably across local machines, CI pipelines, or cloud infrastructure.
Debug workflow failures
Use Dagger Cloud traces, logs, and metrics to inspect failures, identify where a workflow broke, and understand step-by-step execution.
Cross-team operational visibility
Give platform teams one place to see pre-push and post-push workflow activity across the organization, then standardize or streamline shared delivery processes.
Module reuse across teams
Publish and reuse prebuilt modules through the Daggerverse so teams can share workflow logic and reduce duplicate implementation work.
Local-to-CI workflow validation
Run the same orchestration model in local development and CI to validate workflows before they are pushed and compare behavior across environments.

Pros and Cons

Pros

Runs locally, in CI, or in cloud infrastructure with the same workflow model.
Uses containers, sandboxed functions, and explicit typed dependencies to support repeatable execution.
Includes built-in tracing, logs, and metrics for workflow debugging and operational insight.
Supports module reuse through the Daggerverse and module sharing on paid plans.
Offers a free individual plan for Dagger Cloud.

Cons

The source does not list detailed setup requirements beyond a recent Linux kernel for supported systems.
Some capabilities are still marked as coming soon, including centralized telemetry service.

FAQ

What is Dagger Cloud?

Dagger Cloud is the observability layer for Dagger workflows. It provides pipeline visualization, traces, logs, metrics, and operational insights so you can understand what happened in a workflow and where it failed.

Is there a free plan?

Yes. The pricing page says Dagger Cloud is free for individual users, with a Team plan for up to 10 users and an Enterprise plan available by contacting sales.

Does Dagger Cloud host the Dagger Engine?

No. Dagger Cloud is described as a bring-your-own-compute service rather than a hosting service for Dagger Engines.

Which CI systems does it work with?

The pricing page says Dagger Engine can integrate with practically any CI, and examples listed include GitLab, CircleCI, GitHub Actions, Jenkins, and Tekton.

Can it be used for both local and CI workflows?

The source says Dagger Cloud is useful for debugging workflows running locally and in CI, and it supports pre-push and post-push visibility across an organization.