A pure Ruby library for defining and running Cadence workflows and activities.
To find more about Cadence please visit https://cadenceworkflow.io/.
NOTE: Make sure you have both Cadence and TChannel Proxy up and running. Head over to this section for installation instructions.
Clone this repository:
> git clone [email protected]:coinbase/cadence-ruby.git
Include this gem to your Gemfile
:
gem 'cadence-ruby', path: 'path/to/a/cloned/cadence-ruby/'
Define an activity:
class HelloActivity < Cadence::Activity
def execute(name)
puts "Hello #{name}!"
return
end
end
Define a workflow:
require 'path/to/hello_activity'
class HelloWorldWorkflow < Cadence::Workflow
def execute
HelloActivity.execute!('World')
return
end
end
Configure your Cadence connection:
Cadence.configure do |config|
config.host = 'localhost'
config.port = 6666 # this should point to the tchannel proxy
config.domain = 'ruby-samples'
config.task_list = 'hello-world'
end
Register domain with the Cadence service:
Cadence.register_domain('ruby-samples', 'A safe space for playing with Cadence Ruby')
Configure and start your worker process:
require 'cadence/worker'
worker = Cadence::Worker.new
worker.register_workflow(HelloWorldWorkflow)
worker.register_activity(HelloActivity)
worker.start
And finally start your workflow:
require 'path/to/hello_world_workflow'
Cadence.start_workflow(HelloWorldWorkflow)
Congratulation you've just created and executed a distributed workflow!
To view more details about your execution, point your browser to http://localhost:8088/domain/ruby-samples/workflows?range=last-3-hours&status=CLOSED.
There are plenty of runnable examples demonstrating various features of this library available, make sure to check them out.
In order to run your Ruby workers you need to have the Cadence service and the TChannel Proxy running. Below are the instructions on setting these up:
Cadence service handles all the persistence, fault tolerance and coordination of your workflows and activities. To set it up locally, download and boot the Docker Compose file from the official repo:
> curl -O https://raw.githubusercontent.com/uber/cadence/master/docker/docker-compose.yml
> docker-compose up
Right now the Cadence service only communicates with the workers using Thrift over TChannel. Unfortunately there isn't a working TChannel protocol implementation for Ruby, so in order to connect to the Cadence service a simple proxy was created. You can run it using:
> cd proxy
> bin/proxy
The code and detailed instructions can be found here.
A workflow is defined using pure Ruby code, however it should contain only a high-level deterministic outline of the steps (their composition) that need to be executed to complete a workflow. The actual work should be defined in your activities.
NOTE: Keep in mind that your workflow code can get run multiple times (replayed) during the same execution, which is why it must NOT contain any non-deterministic code (network requests, DB queries, etc) as it can break your workflows.
Here's an example workflow:
class RenewSubscriptionWorkflow < Cadence::Workflow
def execute(user_id)
subscription = FetchUserSubscriptionActivity.execute!(user_id)
subscription ||= CreateUserSubscriptionActivity.execute!(user_id)
return if subscription[:active]
ChargeCreditCardActivity.execute!(subscription[:price], subscription[:card_token])
RenewedSubscriptionActivity.execute!(subscription[:id])
SendSubscriptionRenewalEmailActivity.execute!(user_id, subscription[:id])
rescue CreditCardNotChargedError => e
CancelSubscriptionActivity.execute!(subscription[:id])
SendSubscriptionCancellationEmailActivity.execute!(user_id, subscription[:id])
end
end
In this simple workflow we are checking if a user has an active subscription and then attempt to charge their credit card to renew an expired subscription, notifying the user of the outcome. All the work is encapsulated in activities, while the workflow itself is responsible for calling the activities in the right order, passing values between them and handling failures.
There is a couple of ways to execute an activity from your workflow:
# Calls the activity by its class and blocks the execution until activity is
# finished. The return value of your activity will get assigned to the result
result = MyActivity.execute!(arg1, arg2)
# Here's a non-blocking version of the execute, returning back the future that
# will get fulfilled when activity completes. This approach allows modelling
# asynchronous workflows with activities executed in parallel
future = MyActivity.execute(arg1, arg2)
result = future.get
# Full versions of the calls from above, but has more flexibility (shown below)
result = workflow.execute_activity!(MyActivity, arg1, arg2)
future = workflow.execute_activity(MyActivity, arg1, arg2)
# In case your workflow code does not have access to activity classes (separate
# process, activities implemented in a different language, etc), you can
# simply reference them by their names
workflow.execute_activity('MyActivity', arg1, arg2, options: { domain: 'my-domain', task_list: 'my-task-list' })
Besides calling activities workflows can:
- Use timers
- Receive signals
- Execute other (child) workflows
- Respond to queries [not yet implemented]
An activity is a basic unit of work that performs the desired action (potentially causing side-effects). It can return a result or raise an error. It is defined like so:
class CloseUserAccountActivity < Cadence::Activity
class UserNotFound < Cadence::ActivityException; end
def execute(user_id)
user = User.find_by(id: user_id)
raise UserNotFound, 'User with specified ID does not exist' unless user
user.close_account
user.save
AccountClosureEmail.deliver(user)
return
end
end
It is important to make your activities idempotent, because they can get retried by Cadence (in case a timeout is reached or your activity has thrown an error). You normally want to avoid generating additional side effects during subsequent activity execution.
To achieve this there are two methods (returning a UUID token) available from your activity class:
activity.run_idem
— unique within for the current workflow execution (scoped to run_id)activity.workflow_idem
— unique across all execution of the workflow (scoped to workflow_id)
Both tokens will remain the same across multiple retry attempts of the activity.
When dealing with asynchronous business logic in your activities, you might need to wait for an
external event to complete your activity (e.g. a callback or a webhook). This can be achieved by
manually completing your activity using a provided async_token
from activity's context:
class AsyncActivity < Cadence::Activity
def execute(user_id)
user = User.find_by(id: user_id)
# Pass the async_token to complete your activity later
ExternalSystem.verify_user(user, activity.async_token)
activity.async # prevents activity from completing immediately
end
end
Later when a confirmation is received you'll need to complete your activity manually using the token provided:
Cadence.complete_activity(async_token, result)
Similarly you can fail the activity by calling:
Cadence.fail_activity(async_token, MyError.new('Something went wrong'))
This doesn't change the behaviour from the workflow's perspective — as any other activity the result will be returned or an error raised.
NOTE: Make sure to configure your timeouts accordingly and not to set heartbeat timeout (off by default) since you won't be able to emit heartbeats and your async activities will keep timing out.
Similar behaviour can also be achieved in other ways (one which might be more preferable in your specific use-case), e.g.:
- by polling for a result within your activity (long-running activities with heartbeat)
- using retry policy to keep retrying activity until a result is available
- completing your activity after the initial call is made, but then waiting on a completion signal from your workflow
Worker is a process that communicates with the Cadence server and manages Workflow and Activity execution. To start a worker:
require 'cadence/worker'
worker = Cadence::Worker.new
worker.register_workflow(HelloWorldWorkflow)
worker.register_activity(SomeActivity)
worker.register_activity(SomeOtherActivity)
worker.start
A call to worker.start
will take over the current process and will keep it unning until a TERM
or INT
signal is received. By only registering a subset of your workflows/activities with a given
worker you can split processing across as many workers as you need.
All communication is handled via Cadence service, so in order to start a workflow you need to send a message to Cadence:
Cadence.start_workflow(HelloWorldWorkflow)
Optionally you can pass input and other options to the workflow:
Cadence.start_workflow(RenewSubscriptionWorkflow, user_id, options: { workflow_id: user_id })
Passing in a workflow_id
allows you to prevent concurrent execution of a workflow — a subsequent
call with the same workflow_id
will always get rejected while it is still running, raising
CadenceThrift::WorkflowExecutionAlreadyStartedError
. You can adjust the behaviour for finished
workflows by supplying the workflow_id_reuse_policy:
argument with one of these options:
:allow_failed
will allow re-running workflows that have failed (terminated, cancelled, timed out or failed):allow
will allow re-running any finished workflows both failed and completed:reject
will reject any subsequent attempt to run a workflow
There are lots of ways in which you can configure your Workflows and Activities. The common ones (domain, task_list, timeouts and retry policy) can be defined in one of these places (in the order of precedence):
- Inline when starting or registering a workflow/activity (use
options:
argument) - In your workflow/activity class definitions by calling a class method (e.g.
domain 'my-domain'
) - Globally, when configuring your Cadence library via
Cadence.configure
Since the workflow execution has to be deterministic, breaking changes can not be simply added and deployed — this will undermine the consistency of running workflows and might lead to unexpected behaviour. However, breaking changes are often needed and these include:
- Adding new activities, timers, child workflows, etc.
- Remove existing activities, timers, child workflows, etc.
- Rearranging existing activities, timers, child workflows, etc.
- Adding/removing signal handlers
In order to add a breaking change you can use workflow.has_release?(release_name)
method in your
workflows, which is guaranteed to return a consistent result whether or not it was called prior to
shipping the new release. It is also consistent for all the subsequent calls with the same
release_name
— all of them will return the original result. Consider the following example:
class MyWorkflow < Cadence::Workflow
def execute
ActivityOld1.execute!
workflow.sleep(10)
ActivityOld2.execute!
return
end
end
which got updated to:
class MyWorkflow < Cadence::Workflow
def execute
Activity1.execute!
if workflow.has_release?(:fix_1)
ActivityNew1.execute!
end
workflow.sleep(10)
if workflow.has_release?(:fix_1)
ActivityNew2.execute!
else
ActivityOld.execute!
end
if workflow.has_release?(:fix_2)
ActivityNew3.execute!
end
return
end
end
If the release got deployed while the original workflow was waiting on a timer, ActivityNew1
and
ActivityNew2
won't get executed, because they are part of the same change (same release_name),
however ActivityNew3
will get executed, since the release wasn't yet checked at the time. And for
every new execution of the workflow — all new activities will get executed, while ActivityOld
will
not.
Later on you can clean it up and drop all the checks if you don't have any older workflows running or expect them to ever be executed (e.g. reset).
NOTE: Releases with different names do not depend on each other in any way.
It is crucial to properly test your workflows and activities before running them in production. The provided testing framework is still limited in functionality, but will allow you to test basic use-cases.
The testing framework is not required automatically when you require cadence-ruby
, so you have to
do this yourself (it is strongly recommended to only include this in your test environment,
spec_helper.rb
or similar):
require 'cadence/testing'
This will allow you to execute workflows locally by running HelloWorldWorkflow.execute_locally
.
Any arguments provided will forwarded to your #execute
method.
In case of a higher level end-to-end integration specs, where you need to execute a Cadence workflow as part of your code, you can enable local testing:
Cadence::Testing.local!
This will treat every Cadence.start_workflow
call as local and perform your workflows inline. It
also works with a block, restoring the original mode back after the execution:
Cadence::Testing.local! do
Cadence.start_workflow(HelloWorldWorkflow)
end
Make sure to check out example integration specs for more details.
There's plenty of work to be done, but most importanly we need:
- Write specs for everything
- Implement support for missing features
Copyright 2020 Coinbase, Inc.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.