"The path to execution", Styx is a service that schedules batch data processing jobs in Docker containers on Kubernetes.

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We decided to discontinue the Styx oss repo.

Styx

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A batch job scheduler for Kubernetes

Description

Styx is a service that is used to trigger periodic invocations of Docker containers. The information
needed to schedule such invocations, is read from a set of files on disk or an external service
providing such information. The service takes responsibility for triggering and possibly also
re-triggering invocations until a successful exit status has been emitted or some other limit has
been reached. Styx is built using the Apollo framework and uses Kubernetes for container
orchestration.

Styx can optionally provide some dynamic arguments to container executions that indicates which time
period a particular invocation belongs to. For example an hourly job for the first hour of
2016-01-01 might have the dynamic argument 2016-01-01T00 appended to the container invocation.

The envisioned main use case for Styx is to execute data processing job, possibly long running
processes that transform data periodically. Its initial use case is to run workflows of jobs
orchestrated using Luigi, but it does not have any intrinsic ties to Luigi. Styx can just as well
execute a container with some simple bash scripts.

Styx was built to function smoothly on Google Cloud Platform, thus it makes use of Google products
such as Google Cloud Datastore, Google Cloud Bigtable and Google Container Engine. However, the
integrations with these products are all done through clear interfaces and other backends can easily
be added.

Key concepts

The key concept that Styx concerns itself with is Workflows. A Workflow is either enabled or
disabled and has a Schedule. A Schedule specifies how often a Workflow should be triggered, which
Docker image to run and which arguments to pass to it on each execution. Each time a Workflow is
triggered, a Workflow Instance is created. The Workflow instance is tracked as ‘active’ until at
least one execution of the Docker image returns with a 0 exit code. Styx keeps track of Workflow
Instance executions and provides information about them via the API.

Development status

Styx is actively being developed and deployed internally at Spotify where it is being used to run
more than 10000 production workflows. Because of how we build and integrate infrastructure components at
Spotify, this repository does not contain a GUI at the time of writing, while we do have one
internally. The goal is to break out more of these components into open source projects that
complement each other.

More docs

Usage

Setup

A fully functional Service can be found in styx-standalone-service.
This packaging contains both the API and Scheduler service in one artifact. This is how you build
and run it.

The following configuration keys in
styx-standalone.conf have
to be specified for the service to work:

# Google Container Engine (GKE) cluster
styx.gke.default.project-id = ""
styx.gke.default.cluster-zone = ""
styx.gke.default.cluster-id = ""
styx.gke.default.namespace = ""

# Google Cloud Bigtable instance
styx.bigtable.project-id = ""
styx.bigtable.instance-id = ""

# Google Cloud Datastore config
styx.datastore.project-id = ""
styx.datastore.namespace = ""

Build the project:

> mvn package

Run the service:

> java -jar styx-standalone-service/target/styx-standalone-service.jar

Workflow configuration

Refer to API Specification for how to deploy a workflow.

id: my-workflow
docker_image: my-workflow:0.1
docker_args: ['./run.sh', '{}']
schedule: hourly
offset: PT1H
service_account: [email protected]
running_timeout: PT2H
retry_condition: "(#tries < 2 && #triggerType == 'backfill') || (#triggerType != 'backfill')"

id [string]

A unique identifier for the workflow (lower-case-hyphenated). This identifier is used to refer to
the workflow through the API.

docker_image [string]:

The Docker image that should be executed.

docker_args [string]

The list of arguments passed to the Docker container.

This list should only contain strings. Any occurrences of the {} placeholder argument will be
replaced with the current partition date or datehour. Note that it must be quoted in the yaml file
in order not to be interpreted as an object.

Example arguments for the supported schedule values:

- hourly - 2016-04-01T14, 2016-04-01T15, ... (UTC hours)
- daily  - 2016-04-01,    2016-04-02,    ...
- weekly - 2016-04-04,    2016-04-11,    ... (Mondays)

schedule [string]

How often the workflow should be triggered and what the {} placeholder will be replaced with in
docker_args.

Supports cron syntax, along with a set of human readable aliases:

@hourly,   hourly   = 0 * * * *
@daily,    daily    = 0 0 * * *
@weekly,   weekly   = 0 0 * * MON
@monthly,  monthly  = 0 0 1 * *
@yearly,   yearly   = 0 0 1 1 *
@annually, annually = 0 0 1 1 *

offset [string]

An ISO 8601 Duration specification for offsetting the cron schedule.

This is useful for when setting up a schedule that needs to be offset in time relative to the
schedule timestamps. For instance, an hourly schedule that needs to process a bucket of data
for each hour will not be able to run until at the end of that hour. We can then use an offset
value of PT1H. The injected placeholder would reflect a logical time of the schedule
(00, 01, 02, …) one hour earlier than the actual run time (01, 02, 03, …). This is specially
useful for irregular schedules.

In fact, it is so common that we need to use a “last hour” parameter in jobs that we’ve set the
default offset for all the well known (aliased) schedules to +1 period. E.g for an @hourly
schedule, the default offset is PT1H, and for a @daily schedule the offset is P1D

Example: a job needs to run daily at 2 AM but the partition argument needs to be midnight

schedule: '@daily'
offset: P1DT2H

At 2017-06-30T02 the execution for 2017-06-29 will be triggered.

service_account [email address]

The Service Account email address belonging to a project in Google Cloud Platform.

If the workflow intends to use keys of a Service Account,
Styx will create both JSON and p12 keys for the specified service_account, rotate keys on daily basis,
and garbage collect unused keys older than 48h.

Styx stores the created keys in Kubernetes Secrets and mounts them under /etc/styx-wf-sa-keys/
in the container.

Styx injects an environment variable to the container named as GOOGLE_APPLICATION_CREDENTIALS pointing
to the JSON key file.

In order for Styx to be able to create/delete keys for the service_account of a workflow,
the Service Account that Styx itself runs as should be granted Service Account Key Admin
role for the service_account of the workflow.

If authorization is enabled for the service, the service_account will be used to authorize
deployments and actions (create/modify/delete, trigger a new instance, retry/halt an
existing instance and create backfill) on the workflow. To authorize an account, grant it the
configured role) for the Service Account of the workflow.

For information on how to grant an account a role in a Service Account, follow this
guide: Granting Roles to Service Accounts.

env [dictionary]

Custom environment variables to be injected into running container.

running_timeout [string]

An ISO 8601 Duration specification for timing out container execution. The default is configurable in styx conf file through styx.stale-state-ttls.running.
If not set it defaults to styx.stale-state-ttls.default.
The upper boundary of the running_timeout is configurable through styx.max-running-timeout.
If not set it defaults to styx.stale-state-ttls.running, which defaults to styx.stale-state-ttls.default as stated above.

retry_condition [string]

A SpEL boolean expression.
If the expression evaluates to false, Styx will stop retrying and halt the workflow instance immediately. This
configuration has no impact on possible max number of tries, meaning it can only be used to halt workflow instance
earlier.

The following variables will be injected by Styx so that they can be used in the expression:

  • #exitCode: the exit code from the last execution
  • #tries: total number of tries, which equals to 1 when the first time a workflow instance gets executed and 2 when
    the first retry is issued
  • #consecutiveFailures: total number of consecutive failures that is not missing dependency
  • #triggerType: natural, backfill or ad-hoc

Triggering and executions

Each time a Workflow Schedule is triggered, Styx will treat that trigger as a first class entity.
Each Trigger will have at least one Execution which can potentially take a long time to execute. If
another Trigger happens during this time, both triggers will be active, each with one running
container. Because Styx treats each Trigger individually, it can ensure that each one of them
complete successfully.

Styx does not assume anything about what is executed in the container, it only cares about the exit
code. Any execution returning a non-zero exit code will either cause a re-try to be scheduled, or be
interpreted as a permanent failure of the workflow instance. For detailed description of exit codes,
please refer to Workflow state graph section in Styx design.

Injected environment variables

For each execution, Styx will inject a set of environment variables into the Docker container.

Variable Name Description
STYX_COMPONENT_ID The component id of the workflow. This will be the filename of the file which defines the workflow schedule.
STYX_WORKFLOW_ID The workflow id of the workflow. This is the id field specified in the workflow schedule.
STYX_PARAMETER The parameter argument. See section about docker_args above.
STYX_SERVICE_ACCOUNT The service account.
STYX_COMMIT_SHA The commit-sha of the workflow.
STYX_DOCKER_ARGS The arguments passed to the container.
STYX_DOCKER_IMAGE The docker image.
STYX_TRIGGER_ID The ID of the trigger.
STYX_TRIGGER_TYPE The type of the trigger. Possible values are: natural, adhoc, backfill and unknown
STYX_EXECUTION_ID A unique identifier for the execution. This is the execution id used to identify execution attempts of a trigger.
STYX_LOGGING Container logging format, text or structured.
STYX_ENVIRONMENT Styx environment, staging, production, testing, etc. Should be defined in styx-standalone.conf.
STYX_EXECUTION_COUNTER to be implemented - A counter indicating which execution this is. Goes from 0…N per trigger.

High availability

Since version 2.0, Styx supports full HA (High Availability) where both styx-api-service and styx-scheduler-service can be set up
to have multiple instances.

Authorization

Enabling authorization means that any workflow with a configured service_account will only allow authorized
users to deploy and manage it.

You can enable authorization in your configuration, either for all workflows or a subset of workflows.
You will also need to provide the name of the role to use for determining if an account is an authorized
user of the service_account or not. Read more about how to authorize accounts for a service account here.

Development

Backwards Compatibility & API Stability

Most core features and Styx APIs are considered to be stable and changes to them should be backwards compatible. Styx users should normally not be affected by minor/patch releases.

Stable features and APIs:

  • Styx CLI
  • Styx REST API
  • Styx Client API
  • Styx Workflows

All other APIs are considered unstable and can change at any time. E.g. the StyxScheduler class offers some plugin APIs for customizing functionality but they might change at any time. This should only affect engineers that link against and customize the Styx services.

Code Coverage

An aggregate code coverage report for the entire project is created by the styx-report submodule.

> mvn clean verify
> open styx-report/target/site/jacoco-aggregate/index.html

CircleCI builds submit code coverage reports to codecov.io. In addition, the aggregate
JaCoCo report can be viewed under the Artifacts tab in the CircleCI build view.


This project adheres to the Open Code of Conduct. By participating, you are
expected to honor this code.