One-stop ZFS backup & replication solution
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GitHub license Language: Go User Docs Donate via PayPal Donate via Liberapay Twitter

zrepl

zrepl is a one-stop ZFS backup & replication solution.

User Documentation

User Documentation can be found at zrepl.github.io.

Bug Reports

  1. If the issue is reproducible, enable debug logging, reproduce and capture the log.
  2. Open an issue on GitHub, with logs pasted as GitHub gists / inline.

Feature Requests

  1. Does you feature request require default values / some kind of configuration? If so, think of an expressive configuration example.
  2. Think of at least one use case that generalizes from your concrete application.
  3. Open an issue on GitHub with example conf & use case attached.

The above does not apply if you already implemented everything. Check out the Coding Workflow section below for details.

Package Maintainer Information

  • Follow the steps in docs/installation.rst -> Compiling from Source and read the Makefile / shell scripts used in this process.
  • Make sure your distro is compatible with the paths in docs/installation.rst.
  • Ship a default config that adheres to your distro's hier and logging system.
  • Ship a service manager file and please try to upstream it to this repository.
    • dist/systemd contains a Systemd unit template.
  • Ship other material provided in ./dist, e.g. in /usr/share/zrepl/.
  • Use make release ZREPL_VERSION='mydistro-1.2.3_1'
    • Your distro's name and any versioning supplemental to zrepl's (e.g. package revision) should be in this string
  • Use make platformtest on a test system to validate that zrepl's abstractions on top of ZFS work with the system ZFS.
  • Make sure you are informed about new zrepl versions, e.g. by subscribing to GitHub's release RSS feed.

Developer Documentation

zrepl is written in Go and uses Go modules to manage dependencies. The documentation is written in ReStructured Text using the Sphinx framework.

To get started, run ./lazy.sh devsetup to easily install build dependencies and read docs/installation.rst -> Compiling from Source.

Overall Architecture

The application architecture is documented as part of the user docs in the Implementation section (docs/content/impl). Make sure to develop an understanding how zrepl is typically used by studying the user docs first.

Project Structure

├── artifacts               # build artifcats generate by make
├── cli                     # wrapper around CLI package cobra
├── client                  # all subcommands that are not `daemon`
├── config                  # config data types (=> package yaml-config)
│   └── samples
├── daemon                  # the implementation of `zrepl daemon` subcommand
│   ├── filters
│   ├── job                 # job implementations
│   ├── logging             # logging outlets + formatters
│   ├── nethelpers
│   ├── prometheus
│   ├── pruner              # pruner implementation
│   ├── snapper             # snapshotter implementation
├── docs                    # sphinx-based documentation
├── dist                    # supplemental material for users & package maintainers
│   ├── **/*.rst            # documentation in reStructuredText
│   ├── sphinxconf
│   │   └── conf.py         # sphinx config (see commit 445a280 why its not in docs/)
│   ├── requirements.txt    # pip3 requirements to build documentation
│   ├── publish.sh          # shell script for automated rendering & deploy to zrepl.github.io repo
│   └── public_git          # checkout of zrepl.github.io managed by above shell script
├── endpoint                # implementation of replication endpoints (=> package replication)
├── logger                  # our own logger package
├── pruning                 # pruning rules (the logic, not the actual execution)
│   └── retentiongrid
├── replication
│   ├── driver              # the driver of the replication logic (status reporting, error handling)
│   ├── logic               # planning & executing replication steps via rpc
|   |   └── pdu             # the generated gRPC & protobuf code used in replication (and endpoints)
│   └── report              # the JSON-serializable report datastructures exposed to the client
├── rpc                     # the hybrid gRPC + ./dataconn RPC client: connects to a remote replication.Endpoint
│   ├── dataconn            # Bulk data-transfer RPC protocol
│   ├── grpcclientidentity  # adaptor to inject package transport's 'client identity' concept into gRPC contexts
│   ├── netadaptor          # adaptor to convert a package transport's Connecter and Listener into net.* primitives
│   ├── transportmux        # TCP connecter and listener used to split control & data traffic
│   └── versionhandshake    # replication protocol version handshake perfomed on newly established connections
├── tlsconf                 # abstraction for Go TLS server + client config
├── transport               # transports implementation
│   ├── fromconfig
│   ├── local
│   ├── ssh
│   ├── tcp
│   └── tls
├── util
├── vendor                  # managed by dep
├── version                 # abstraction for versions (filled during build by Makefile)
└── zfs                     # zfs(8) wrappers

Coding Workflow

  • Open an issue when starting to hack on a new feature
  • Commits should reference the issue they are related to
  • Docs improvements not documenting new features do not require an issue.

Breaking Changes

Backward-incompatible changes must be documented in the git commit message and are listed in docs/changelog.rst.

  • Config-breaking changes must contain a line BREAK CONFIG in the commit message
  • Other breaking changes must contain a line BREAK in the commit message

Glossary & Naming Inconsistencies

In ZFS, dataset refers to the objects filesystem, ZVOL and snapshot.
However, we need a word for filesystem & ZVOL but not a snapshot, bookmark, etc.

Toward the user, the following terminology is used:

  • filesystem: a ZFS filesystem or a ZVOL
  • filesystem version: a ZFS snapshot or a bookmark

Sadly, the zrepl implementation is inconsistent in its use of these words: variables and types are often named dataset when they in fact refer to a filesystem.

There will not be a big refactoring (an attempt was made, but it's destroying too much history without much gain).

However, new contributions & patches should fix naming without further notice in the commit message.