Capistrano Version 3 Release Announcement
After what seems like years of work, the Capistrano team (that’s Tom and I) are pleased to announce the first major release of Capistrano in almost 5 years.
The reasons behind the length of time between the last architectural overhaul and this one are numerous, but it can be summarised to say that Capistrano is a widely used tool, and when working around software deployment it’s really a question of downtime. If we had changed something significant in Capistrano we could have taken a lot of sites offline, and made a lot of people very unhappy. Until this point we haven’t felt that the time has been ripe where the benefits of a slightly rocky upgrade path are worth the risks of downtime.
It also hasn’t helped historically that we’ve only just gotten to grips with Ruby 1.9, and that Bundler’s near ubiquity means that now it’s trivial to lock a Gem at a specific version. With other tools in the Ruby ecosystem it’s become easier for us to make significant changes to a tool upon which many hundreds of thousands of people rely.
Design Goals
We had a few goals for this release, in no particular order they were:
- Get away from our own DSL solution. Great DSL alternatives (Rake, Sake, Thor, etc) are already widely used.
- Better modularisation. to enable people outside the Rails community to benefit from Capistrano’s best-practice workflow, and to enable people in the Rails community to pick and choose support for components they use (Database Migrations, Asset Pipeline, etc)
- Easier Debugging. A lot of problems with Capistrano come from weirdness surrounding environmental issues around PTY vs non-TTY environments, login and non-login shells not to mention environment managers such as rvm, rbenv and nvm.
- Speed. We know that in a lot of environments speed of deployment is a huge factor, since Rails introduced the Asset Pipeline it’s not uncommon for a deploy that formerly took 5 seconds now takes 5 minutes. This really is mostly out of our control, but with improved support for parallelism, rolling restarts we feel confident that things will be quicker and easier to keep running quickly now.
- Applicability. We’ve always maintained that Capistrano is a terrible tool for system provisioning, and that more often than not servers are better being setup with Chef, Puppet or similar, whilst we still agree with that, the new features in Capistrano really lend themselves to integrating with these kinds of tools.
What’s missing?
Before we get too carried away it’s worth shortlisting the things that don’t exist in version three, yet.
- SSH Gateway Support SSH Gateway support hasn’t been implemented in version three yet, I hope that this will be done soon. As I have no direct need for it, I haven’t the means to test it with a view to implementing it, yet.
- Mecurial, Subversion, and CVS Support These have been removed as we’ve been able to implement the Git SCM in an incredibly neat way that isn’t compatible with the others. We wanted to break the cycle of always sticking with the lowest common denominator, so we are actively looking for people who are interested in contributing, or sharing expertise on the best-practice way of speedily deploying from your respective choice of source control.
HOSTFILTER
,ROLEFILTER
and friends These have gone away because we always felt they were endemic of a bad design decision about using Environmental Variables. These will be coming back as flags passed tocap
on the CLI, and options that can be set on theCapistrano::Application
Ruby class.- Shell The shell has been removed temporarily pending a neater
implementation, we’ve got something that we are playing with internally, but
it needs better
readline
support, and some more controls around what to do when things go badly on some servers, but not others. - Cold Deploy The
cap deploy:cold
is a really old legacy component, originally from the days of thescript/spinner
where deploying cold (starting workers that weren’t running), and deploying a warm system were different (restarting existing worker pools, which wasn’t fun!) By and large these things have gone away, and it’s timedeploy:cold
went away. It’s safe in every case we could find to call setup, and seed and other Rake tasks without things blowing up, and that should be the approach we take. Tasks on the server should be idempotent, and if something is called twice, let it be.
What’s new?
Each section here really deserves it’s own sub-heading as some of the new features are awesome.
Rake Integration
We have moved away from our own DSL implementation to implement Capistrano as a Rake application.
Rake has always supported being sub-classed, so to speak as a
sub-application; it is however poorly documented. By subclassing
Rake::Application
one can specify what the Rakefile should look like, where
to search for it, and how to load other Rakefiles.
The Rake DSL is widely used, well known and very powerful. As Rake is essentially a dependency resolution system, it offers a lot of nice ways to, for example build a tarball as a dependency of uploading it and deploying it.
This has allowed us to do away with the copy strategy all together, as it can now be implemented from scratch in fewer than ten lines of code.
The guiding principle is dependency resolution, and interoperability with other tools, for example:
The last three lines rely on Rake’s additive task declaration, by redefining the
deploy:default
task by adding another dependency. Rake will automatically
resolve this dependency at Runtime, mailing the recent changelog to your team,
assuming everything is setup correctly.
Built-In Stage Support
In former versions of Capistrano stage support was an after thought,
provided through the capistrano-ext
Gem, and laterally merged into the main
codebase, people insisted in still using the capistrano-ext
version
regardless.
In Capistrano 3.0.x there’s stage support built-in, at installation time, two
stages will be created by default, staging and production; it’s easy to
add more, just add a file to config/deploy/______.rb
which follows the
conventions established in the examples we created for you.
To create different stages at installation time, simply set the STAGES
environmental variable to a comma separated list of stages:
Parallelism
In former versions of Capistrano there was a parallel option to run different tasks differently on groups of servers, it looked something like this:
This always felt a little unclean, and indeed it’s a hack that was originally implemented to facilitate rolling deployments at a large German firm by a couple of freelancers who were consulting with them. (Hint, one of those guys went on to found Travis-CI!)
The equivalent code in under Capistrano v3 would look like this:
The second block of code, that representing the new Rake derived DSL and demonstrating how to use the parallel execution mode is a little longer, but I think it’s clearer, more idiomatic Ruby code which relies less on an intimate knowledge of how the Capistrano DSL happens to work. It also hints at the built-in logging subsystem, keep reading to learn more.
Other modes for parallelism include:
The internal tasks, for standard deploy recipes make use of all of these as is appropriate for the normal case, no need to be afraid of scary slow deploys again!
Streaming IO
This IO streaming model means that results from commands, the commands
themselves and any other arbitrary output are sent as objects to a class with
an IO
ish interface, the class knows what to do with these things. There’s a
progress formatter which prints dots for each command that is called, as
well as a pretty formatter which prints the full command, it’s output on
standard out and standard error, as well as the final return status. It would
be trivial to implement HTML formatters, or formatters that reported to your
IRC room, or to email. I look forward to seeing more of these cropping up in
the community.
Host Definition Access
If you didn’t skim over the Parallism section above, you might have noticed we
did something clever that wasn’t possible in Capistrano v2; we accessed the
host
inside the execution block.
For a lot of reasons in Capistrano v2 is wasn’t possible to do this, the block was essentially evaluated once and called verbatim on each host. This lead to disappointing missing features such as not being able to pull the host list out of Capistrano and examine the roles to do something like controlling Chef solo, or similar.
In Capistrano v3 the host
object is the same object that is created when a
server is defined, and is internally used, for example to pass to an ERB
template for rendering a last-deploy message that is dumped onto each server
after a successful deployment. The last deploy log includes everything
Capistrano knew about that server during the deployment.
Users of Capistrano v2 may be familiar with the perenial
cap deploy:cleanup
problem which came to light when servers differed in their old releases list, imagine a scenario with two servers, one has been your bread-and-butter since you launched, it has hundreds of old releases from all your wonderful deploys over the months or years. The second server has been in the cluster for about a month, it didn’t quite slot-in cleanly, so the list of old releases looks a bit weird, you deleted a few by hand, and anyway there might only be ten-or-so releases there.
Now imagine that you call
cap deploy:cleanup
, oldcapture()
implementations silently only ran on the first server that matched the properties defined, so server one returned a list of ~95 old timestamped release directories. Next Capistrano v2 would callrm -rf release1..release95
on both servers, causing server two to error out, and leaving an undefined state on server one, as Capistrano would simply hang up both connections.
This cleanup routine can now be better implemented as follows (which is actually more or less the actual implementation in the the new Gem):
Some handy things to note here are that both server one and server two in our
contrived example will both evaluate that independently, and when both servers
are finished removing old releases the task :cleanup
block will have
finished.
Also in Capistrano v3 most path variables are [Pathname
] objects, so they natively
respond to things like #basename
, #expand_path
, #join
and similar.
Warning: #expand_path
probably won’t do what you expect, it will execute
on your workstation machine, and not on the remote host, so it’s possible
that it will return an error in the case of paths which exist remotely but not
locally.
Host Properties
As the host
object is now available to the task blocks, it made sense to make
it possible to store arbitrarty values against them.
Enter host.properties
. This is a simple
OpenStruct
which can be used to store any additional properties which are important for
your application.
An example of it’s usage might be:
More Expressive Command Language
In Capistrano v2, it wasn’t uncommon to find commands such as:
In Capistrano v3 this looks more like this:
Again, with other examples this format is a little longer, but much more
expressive, and all the nightmare of shell escaping is handled internally for
you, environmental variables are capitalised and applied at the correct point
(i.e between the cd
and rake
calls in this case).
Other options here include as :a_user
and
Better magic Variable Support
In Capistrano v2 there were certain bits of magic where if calling a variable
and NoMethodError
would have been raised (for example the
latest_release_directory
variable). This variable never existed on the
global namespace, as a fall-back the list of set()
variables would be
consulted.
This magic led to times when people were not recognising that magic variables
were even being used. The magic variable system of Capistrano v2 did also
include a way to fetch(:some_variable, 'with a default value')
in case the
variable might not be set already, but it wasn’t widely used, and more often
than not people just used things like latest_release_directory
never knowing
that behind the scenes an exception was raised, then rescued, and that
:latest_release_directory
in the variable map was actually a continuation
that was evaluated the first time it was used, and the value then cached until
the end of the script.
The system has now 100% less magic. If you set a variable using set()
, it
can be fetched with fetch()
, if the value you set into the variable responds
to #call
then it will be executed in the current context whenever it is
used, the values will not be cached, unless your continuation does some
explicit caching. Again, we are favoring clarity over micro optimisation.
SSHKit
Many of the new features in Capistrano which relate to logging, formatting, SSH, connection management and pooling, parallelism, batch execution and more are from a library that fell out of the Capistrano v3 development process.
SSHKit is a lower level toolkit, a level higher than Net::SSH still, but lacking the roles, environments, rollbacks and other higher level features from Capistrano.
SSHkit is ideal for use if you need to just connect to a machine and run some arbitrary command, for example:
There is much more than can be done with SSHKit, and we have quite an
extensive list of
examples. For
the most part with Capistrano v3, anything that happens inside of an on()
block is happening in SSHkit, and the documentation from that library is the
place to go to find more information.
Command Mapping
This is another feature from SSHKit, designed to remove a little ambiguity from preceedings, there is a so-called command map for commands.
When executing something like:
The command is passed through to the remote server completely unchanged. This includes the options which might be set, such as user, directory, and environmental variables. This is by design. This feature is designed to allow people to write non-trivial commands in heredocs when the need arises, for example:
Caveat: The SSHKit multiline command sanitizing logic will remove line feeds and add an ;
after each line to separate the commands. So make sure you are not putting a newline between then
and the following command.
The idiomatic way to write that command in Capistrano v3 is to use the separated variadaric method to specify the command:
… or for the larger example
In this way the command map is consulted, the command map maps all unknown
commands (which in this case is git
, the rest of the line are arguments to
git
) are mapped to /usr/bin/env ...
. Meaning that this command would be
expanded to /usr/bin/env git clone ...... ......
which is what happens when
git
is called without a full path, the env
program is consulted (perhaps
indirectly) to determine which git
to run.
Commands such as rake
and rails
are often better prefixed by bundle
exec
, and in this case could be mapped to:
There can also be a lambda
or Proc
applied in place of the mapping like so:
Between these two options there should be quite powerful options to map commands in your environment without having to override internal tasks from Capistrano just because a path is different, or a binary has a different name.
This can also be slightly abused in environments where shim executables
are used, for example rbenv
wrappers:
The above assumes that you have done something like rbenv wrapper default
myproject
which creates wrapper binaries which correctly set up the Ruby
environment without requiring an interactive login shell.
Testing
The old test suite for Capistrano was purely unit tests, and didn’t cover a
wide variety of problem cases, specifically nothing in the deploy.rb
(that is
the actual deployment code) was tested at all; because of having our own DSL
implementation, and other slightly odd design points, it was painful to test
the actual recipes.
Testing has been a focus of Capistrano v3. The integration test suite uses Vagrant to boot a machine, configures certain scenarios using portable shell script, and then executes commands against them, deploying common configurations to typical Linux systems. This is slow to execute, but offers stronger guarantees that nothing is broken that we’ve ever been able to give before.
Capistrano v3 also offers a possibility to swap out backend implementations. This is interesting because for the purpose of testing your own recipes you can use a printer backend, and verify that the output matched what you expected, or use a stubbed backend upon which you can verify that calls were made, or not made as expected.
Arbitrary Logging
Capistrano exposes the methods debug()
, info()
, warn()
, error()
and
fatal()
inside of on()
blocks which can be used to log using the existing
logging infrastructure and streaming IO formatters:
### Upgrading
The best place to go here is the upgrading documentation to get deeper into the specifics.
The simple version is to say that there is no direct upgrade path, versions two and three are incompatible.
This is partly by design, the old DSL was imprecise in places that would have made doing the right thing in most cases tricky, we opted to invest in more features and better reliability than investing in keeping a backwards compatible API.
There are a number of gotchas listed below, but the main points are the new
names of the built-in roles, as well as that by default Capistrano v3 is
platform agnostic, if you need Rails support, for migrations, asset pipeline
and such like, then it’s required to require
the support files.
Gotchas
Rake DSL Is Additive
In Capistrano v2 if you re-define a task then it replaces the original implementation, this has been used by people to replace internal tasks piecemeal with their own implementations