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https://github.com/rtyler/otto

Otto is your friendly continuous delivery companion.
https://github.com/rtyler/otto

ci ci-cd continuous-delivery rust

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Otto is your friendly continuous delivery companion.

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README 

        
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= Otto



**link:https://webchat.freenode.net/?channels=#otto[Chat on IRC]**



Meet Otto, your friendly continuous delivery companion.



Otto is a robust distributed system for scalable continuous integration and

delivery. To accomplish this Otto is multi-process oriented and distributed by

default; all system interactions must occur over process boundaries even if

executing in the same logical host. This document outlines the high level

architecture but omits specific inter-process communication formats, protocols,

and dependencies.



Otto does not aim to be the center of the entire continuous delivery process,

but rather seeks to interoperate seamlessly with all the various components

which make CD work for you.



toc::[]



= Status



**Otto is currently not usable.**



There are link:rfc[design documents] in the `rfc/` directory which can help

describe the state of development for Otto.



The components are in different states of development. Please consult

the README document in the subfolders for their current purpose and status.



= Development



Much of Otto is built in link:https://www.rust-lang.org/[Rust]. The project is

a "cargo workspace" which means that there are multiple binaries and libraries

defined in the source tree, which can all be built together via the root

`Cargo.toml`. Much can be accomplished with `cargo build` and `cargo test`,

which is easily scoped to a single project via the `-p` flag, for example

`cargo test -p otto-parser`. There is also a `Makefile` which drives some

higher-level build system behavior.



Otto is composed of many different services, which communicate via JSON over HTTP.



== Make targets



Running `make` in the root directory will list some brief help output, but some useful make targets to be aware of are documented below:



=== `release`



Build and strip release binaries to prepare for packaging. Most developers

won't need to execute this target.



=== `run`



Launch the services defined in the `Procfile`. This requires a `cargo build`

ahead of time, and is really only useful for manual integration testing.



=== `steps`



This target will build and package all the steps defined in `stdlib/`



=== `test`



Runs all the acceptance tests, typically implemented with

link:https://github.com/kward/shunit2/[shunit2]. This target will *not* run

`cargo build` or `cargo test`. From a fresh clone, running the acceptance tests

will require an initial build, for example `cargo build && make test`.



== Subdirectories



Each subdirectory should have its own README with a little more information,

but at a glance:



=== `cli/`



This directory contains all the command-line interfaces for Otto.



=== `crates/`



This directory contains the various pieces of shared code



=== `rfcs/`



RFCs (Request for Comment) are design documents for different patterns or

subcomponents within Otto.



=== `services/`



Projects in this directory are Otto's mesh of services, which speak HTTP to

provide different aspects of functionality for the Otto project.



=== `stdlib/`



The Otto step "Standard Library." In essence, these are all the step libraries

that are assumed to be installed by default with Otto.



== Problems to Solve



Below is an incomplete listing of the problems Otto aims to solve for:



* **Existing tools do not model the entire continuous delivery process.** Using

  an external tool such as Puppet, or relying on an external provider such as

  AWS ECS, there can be a "black hole" in the deployment. A point where control

  is delegated to an external system, and the orchestration tool (Otto), loses

  sight of what is happening.

* **Expecting "one single instance" to be the hub is unrealistic.** Many

  deployment processes have "development" operated components, and "ops"

  operated components, with little to no automated hand-off of control between

  the two.

* **Mixing of management and execution contexts causes a myriad of issues.**

  Many tools allow the management/orchestrator process to run user-defined

  workloads. This allows breaches of isolation between user-defined workloads

  and administrator configuration and data.

* **Non-deterministic runtime behavior adds instability.** Without being able to

  "explain" a set of operations which should occur before runtime, it is

  impossible to determine whether or not a given delivery pipeline is correctly

  constructed.

* **Blending runtime data and logic with process definition confuses users.** Related to the

  problem above, Providing runtime data about the process in a manner which is

  only accessible in the delivery process itself, overly complicates the parsing

  and execution of a defined continuous delivery process.

* **Modeling of the delivery process is blurred with build tooling.** Without a

  clear separation of concerns between the responsibility of build tools like

  GNU/Make, Maven, Gradle, etc and the continuous delivery process definition,

  logic invariably bleeds between the two.

* **Opinionated platform requirements prevent easy usage across different

  environments.** Forcing a reliance on containers, or a runtime like the Java

  Virtual Machine results in burdensome system configuration before starting to

  do the real work of defining a continuous delivery process. Without gracefully

  degrading in functionality depending on the system requirements which are

  present, users are forced to hack around the platform requirements, or spent

  significant worrying about and maintaining pre-requisites.

* **Many tools are difficult to configure  by default.** For most application

  stacks, there are common conventions which can be easily prescribed for the

  80% use-case.  Ruby on Rails applications will almost all look identical, and

  should require zero additional configuration.

* **Secrets and credentials can be inadvertently leaked.** Many tools provide

  some ability to configure secrets for the continuous delivery process, but

  expose them to the process itself in insecure ways, which allow for leakage.

* **Extensibility must not come at the expense of system integrity.** Systems

  which allow for administrator, or user-injected code at runtime cannot avoid

  system reliability and security problems. Extensibility is an important

  characteristic to support, but secondary to system integrity.

* **Usage cannot grow across an organization without user-defined extension**.

  The operators of the system will not be able to provide for every eventual

  requirement from users. Some mechanism for extending or consolidating aspects

  of a continuous delivery process must exist.



== Modeling Continuous Delivery



Some characteristics of a continuous delivery process model which Otto must ensure:



* **Deterministic ahead-of-time**. Without executing the full process, it must

  be possible to "explain" what will happen.

* **External interactions must be model-able.** Deferring control to an

  external system must be accounted for in a user-defined model. For example,

  submitting a deployment request, and then waiting for some external condition

  to be made to indicate that the deployment has completed and the service is now

  online. This should support both an evented model, wherein the external service

  "calls back" and a polling model, where the process waits until some external

  condition can be verified.

* **Branching logic**, a user must be able to easily define branching logic.

  For example, a web application's delivery may be different depending on

  whether this is a production or a staging deployment.

* **Describe, though not fully, environments.** All applications have at least

  some concept of environments, whether it is a web application's concept of

  staging/production, or a compiled asset's concept of debug/release builds.

* **Safe credentials access**, credentials should not be exposed to in a way

  which might allow the user-defined code to inadvertently leak the credential.

* **Caching data between runs** must be describable in some form or fashion.

  Taking Maven projects as an example, where successive runs of `mvn` on a

  cold-cache will result in significant downloads of data, whereas caching

  `~/.m2` will result in more acceptable performance.

* **Refactor/extensibility support in-repo or externally.** Depending on

  whether the source repository is a monorepo, or something more modular.

  Common aspects of the process must be able to be templatized/parameterized in

  some form, and shared within the repository or via an external repository.

* **Scale down to near zero-configuration.** the simplest model possible should

  simply define what platform's conventions to use. With Rails applications,

  many applications are functionally in the same with their use of Bundler,

  Rake, and RSpec.