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- Remove intermediary types `Component`, `Script`, `Op`, `mount`: just use `cc.Value` directly - Remove `Executable` interface. - Execute llb code with a simple concrete type `Pipeline` - Analyze llb code with a simple utility `Analyze` Signed-off-by: Solomon Hykes <sh.github.6811@hykes.org>
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The Dagger architecture
This document provides details on the internals of Dagger, key design decisions and the rationale behind them.
What is a DAG?
A DAG is the basic unit of programming in dagger. It is a special kind of program which runs as a aipeline of inter-connected computing nodes running in parallel, instead of a sequence of operations to be run by a single node.
DAGs are a powerful way to automate various parts of an application delivery workflow: build, test, deploy, generate configuration, enforce policies, publish artifacts, etc.
The DAG architecture has many benefits:
- Because DAGs are made of nodes executing in parallel, they are easy to scale.
- Because all inputs and outputs are snapshotted and content-addressed, DAGs can easily be made repeatable, can be cached aggressively, and can be replayed at will.
- Because nodes are executed by the same container engine as docker-build, DAGs can be developed using any language or technology capable of running in a docker. Dockerfiles and docker images are natively supported for maximum compatibility.
- Because DAGs are programmed declaratively with a powerful configuration language, they are much easier to test, debug and refactor than traditional programming languages.
To execute a DAG, the dagger runtime JIT-compiles it to a low-level format called llb, and executes it with buildkit. Think of buildkit as a specialized VM for running compute graphs; and dagger as a complete programming environment for that VM.
The tradeoff for all those wonderful features is that a DAG architecture cannot be used for all software: only software than can be run as a pipeline.