The Kubernetes-native platform (v2).
The Package manager for Kubernetes.
The Kubernetes-native Service Broker.
Workflow is comprised of a number of small, independent services that combine to create a distributed PaaS. All Workflow components are deployed as services (and associated controllers) in your Kubernetes cluster. If you are interested we have a more detailed exploration of the Workflow architecture.
All of the componentry for Workflow is built with composability in mind. If you need to customize one of the components for your specific deployment or need the functionality in your own project we invite you to give it a shot!
Project Location: drycc/controller
The controller component is an HTTP API server which serves as the endpoint for
drycc CLI. The controller provides all of the platform functionality as
well as interfacing with your Kubernetes cluster. The controller persists all
of its data to the database component.
Project Location: drycc/postgres
The database component is a managed instance of PostgreSQL which holds a majority of the platforms state. Backups and WAL files are pushed to object storage via WAL-E. When the database is restarted, backups are fetched and replayed from object storage so no data is lost.
Project Location: drycc/builder
git pushrequests over SSH
Builder currently supports both buildpack and Dockerfile based builds.
Project Location: drycc/slugbuilder
For Buildpack-based deploys, the builder component will launch a one-shot Pod
drycc namespace. This pod runs
slugbuilder component which handles
default and custom buildpacks (specified by
BUILDPACK_URL). The "compiled"
application results in a slug, consisting of your application code and all of
its dependencies as determined by the buildpack. The slug is pushed to the
cluster-configured object storage for later execution. For more information
about buildpacks see using buildpacks.
Project Location: drycc/dockerbuilder
For Applications which contain a
Dockerfile in the root of the repository,
builder will instead launch the
dockerbuilder to package your application.
Instead of generating a slug,
dockerbuilder generates a Docker image (using
the underlying Docker engine). The completed image is pushed to the managed
Docker registry on cluster. For more information see using Dockerfiles.
Project Location: drycc/slugrunner
Slugrunner is the component responsible for executing buildpack-based Applications. Slugrunner receives slug information from the controller and downloads the application slug just before launching your application processes.
Project Location: drycc/minio
All of the Workflow components that need to persist data will ship them to the object storage that was configured for the cluster.For example, database ships its WAL files, registry stores Docker images, and slugbuilder stores slugs.
Workflow supports either on or off-cluster storage. For production deployments we highly recommend that you configure off-cluster object storage.
To facilitate experimentation, development and test environments, the default charts for Workflow include on-cluster object storage via minio.
If you also feel comfortable using Kubernetes persistent volumes you may configure minio to use persistent storage available in your environment.
Project Location: drycc/registry
The registry component is a managed docker registry which holds application images generated from the builder component. Registry persists the Docker image images to either local storage (in development mode) or to object storage configured for the cluster.
Project Location: drycc/router
The router component is based on Nginx and is responsible for routing
inbound HTTP(S) traffic to your applications. The default workflow charts
provision a Kubernetes service in the
drycc namespace with a service type of
LoadBalancer. Depending on your Kubernetes configuration, this may provision
a cloud-based loadbalancer automatically.
The router component uses Kubernetes annotations for both Application discovery as well as router configuration. For more detailed documentation and possible configuration view the router project documentation.
The logging subsystem consists of two components. Fluentd handles log shipping and logger maintains a ring-buffer of application logs.
Project Location: drycc/fluentd
Fluentd is deployed to your Kubernetes cluster via Daemon Sets. Fluentd
subscribes to all container logs, decorates the output with Kubernetes metadata
and can be configured to drain logs to multiple destinations. By default,
fluentd ships logs to the logger component, which powers
Project Location: drycc/logger
logger component receives log streams from
fluentd, collating by
Application name. Logger does not persist logs to disk, instead maintaining an
in-memory ring buffer. For more information on logger see the project
Project Location: drycc/monitor
The monitoring subsystem consists of three components: Telegraf, InfluxDB and Grafana.
Telegraf is the is the metrics collection agent that runs using the daemon set API. It runs on every worker node in the cluster, fetches information about the pods currently running and ships it to InfluxDB.
InfluxDB is a database that stores the metrics collected by Telegraf. Out of the box, it does not persist to disk, but you can set it up to back it with a persisitent volume or swap this out with a more robust InfluxDB setup in a production setting.
Grafana is a standalone graphing application. It natively supports InfluxDB as a datasource and provides a robust engine for creating dashboards on top of timeseries data. Workflow provides a few dashboards out of the box for monitoring Drycc Workflow and Kubernetes. The dashboards can be used as a starting point for creating more custom dashboards to suit a user's needs.
Project Location: drycc/workflow-manager
Workflow Manager will regularly check your cluster against the latest stable
components. If components are missing due to failure or are simply out of date,
Workflow operators will know at a glance. By default, this submits component
and version information to Drycc' version service. If you prefer, you may
disable the function by setting
WORKFLOW_MANAGER_CHECKVERSIONS to false in
Workflow Manager's Deployment.