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Merge pull request #12 from jianxiaoguo/dev
chore(docs): add rabbitmq docs
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‎src/_includes/install-workflow.md‎

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NAME READY STATUS RESTARTS AGE
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drycc-builder-hy3xv 1/1 Running 5 5m
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drycc-controller-g3cu8 1/1 Running 5 5m
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drycc-controller-celery-cmxxn 3/3 Running 0 5m
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drycc-database-rad1o 1/1 Running 0 5m
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drycc-logger-fluentd-1v8uk 1/1 Running 0 5m
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drycc-logger-fluentd-esm60 1/1 Running 0 5m
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drycc-logger-sm8b3 1/1 Running 0 5m
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drycc-minio-4ww3t 1/1 Running 0 5m
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drycc-registry-asozo 1/1 Running 1 5m
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drycc-rabbitmq-0 1/1 Running 0 5m
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```
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Once all of the pods are in the `READY` state, Drycc Workflow is up and running!

‎src/installing-workflow/index.md‎

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drycc/workflow
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```
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By default, registry uses docker hub, at present, we support three registries. They are:
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By default, registry uses docker hub, at present, we support three registries. They are:
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* redhat quay `quay.io`
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* docker hub `docker.io`
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--set fluentd.image_registry=quay.io \
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--set redis.image_registry=quay.io \
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--set influxdb.image_registry=quay.io \
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--set rabbitmq.image_registry=quay.io \
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--set logger.image_registry=quay.io \
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--set minio.image_registry=quay.io \
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--set monitor.image_registry=quay.io \
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NAME READY STATUS RESTARTS AGE
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drycc-builder-574483744-l15zj 1/1 Running 0 4m
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drycc-controller-3953262871-pncgq 1/1 Running 2 4m
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drycc-controller-celery-cmxxn 3/3 Running 0 4m
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drycc-database-83844344-47ld6 1/1 Running 0 4m
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drycc-influxdb-2729788615-m9b5n 1/1 Running 0 4m
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drycc-logger-176328999-wjckx 1/1 Running 4 4m
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drycc-nsqd-3597503299-6mn2x 1/1 Running 0 4m
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drycc-registry-756475849-lwc6b 1/1 Running 1 4m
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drycc-registry-proxy-96c4p 1/1 Running 0 4m
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drycc-rabbitmq-0 1/1 Running 0 4m
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```
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Once all of the pods are in the `READY` state, Drycc Workflow is up and running!

‎src/installing-workflow/ingress.md‎

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--set global.platform_domain=drycc.cc \
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--set builder.service.type=NodePort \
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--set builder.service.nodePort=32222
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```
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```
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If you want to use Load Balancer on a bare machine, you can look at [metallb](https://github.com/danderson/metallb)
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Where `global.platform_domain` is a **required** parameter that is traditionally not required for Workflow that is explained in the next section. In this example we are using `drycc.cc` for `$hostname`.
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Helm will install a variety of Kubernetes resources in the `drycc` namespace.
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Wait for the pods that Helm launched to be ready. Monitor their status by running:
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NAME READY STATUS RESTARTS AGE
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drycc-builder-hy3xv 1/1 Running 5 5m
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drycc-controller-g3cu8 1/1 Running 5 5m
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drycc-controller-celery-cmxxn 3/3 Running 0 5m
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drycc-database-rad1o 1/1 Running 0 5m
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drycc-logger-fluentd-1v8uk 1/1 Running 0 5m
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drycc-logger-fluentd-esm60 1/1 Running 0 5m
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drycc-logger-sm8b3 1/1 Running 0 5m
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drycc-minio-4ww3t 1/1 Running 0 5m
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drycc-registry-asozo 1/1 Running 1 5m
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drycc-rabbitmq-0 1/1 Running 0 5m
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```
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## Install a Kubernetes Ingress Controller

‎src/managing-workflow/upgrading-workflow.md‎

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NAME READY STATUS RESTARTS AGE
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drycc-builder-2448122224-3cibz 1/1 Running 0 5m
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drycc-controller-1410285775-ipc34 1/1 Running 3 5m
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drycc-controller-celery-694f75749b-cmxxn 3/3 Running 0 5m
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drycc-database-e7c5z 1/1 Running 0 5m
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drycc-influxdb-ah8io 1/1 Running 0 5m
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drycc-logger-cgjup 1/1 Running 3 5m
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drycc-registry-proxy-no3r1 1/1 Running 0 5m
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drycc-registry-proxy-ou8is 1/1 Running 0 5m
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drycc-registry-proxy-zyajl 1/1 Running 0 5m
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drycc-rabbitmq-0 1/1 Running 0 5m
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```
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### Step 3: Upgrade the Drycc Client

‎src/quickstart/provider/azure-acs/install-azure-acs.md‎

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NAME READY STATUS RESTARTS AGE
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drycc-builder-hy3xv 1/1 Running 5 5m
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drycc-controller-g3cu8 1/1 Running 5 5m
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drycc-controller-celery-cmxxn 3/3 Running 0 5m
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drycc-database-rad1o 1/1 Running 0 5m
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drycc-logger-fluentd-1v8uk 1/1 Running 0 5m
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drycc-logger-fluentd-esm60 1/1 Running 0 5m
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drycc-logger-sm8b3 1/1 Running 0 5m
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drycc-minio-4ww3t 1/1 Running 0 5m
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drycc-registry-asozo 1/1 Running 1 5m
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drycc-rabbitmq-0 1/1 Running 0 5m
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```
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Once all of the pods are in the `READY` state, Drycc Workflow is up and running!

‎src/quickstart/provider/minikube/install-minikube.md‎

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NAME READY STATUS RESTARTS AGE
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drycc-builder-hy3xv 1/1 Running 5 5m
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drycc-controller-g3cu8 1/1 Running 5 5m
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drycc-controller-celery-cmxxn 3/3 Running 0 5m
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drycc-database-rad1o 1/1 Running 0 5m
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drycc-logger-fluentd-1v8uk 1/1 Running 0 5m
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drycc-logger-fluentd-esm60 1/1 Running 0 5m
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drycc-logger-sm8b3 1/1 Running 0 5m
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drycc-minio-4ww3t 1/1 Running 0 5m
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drycc-registry-asozo 1/1 Running 1 5m
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drycc-rabbitmq-0 1/1 Running 0 5m
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```
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Once all of the pods are in the `READY` state, Drycc Workflow is up and running!

‎src/troubleshooting/kubectl.md‎

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drycc-builder-gqum7 0/1 ContainerCreating 0 4s
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drycc-controller-h6lk6 0/1 ContainerCreating 0 4s
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drycc-controller-celery-cmxxn 0/3 ContainerCreating 0 4s
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drycc-database-56v39 0/1 ContainerCreating 0 4s
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drycc-influxdb-f9ftm 0/1 Pending 0 3s
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drycc-influxdb-f9ftm 0/1 Pending 0 3s
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drycc-logger-fluentd-xihr1 0/1 Pending 0 2s
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drycc-logger-grupg 0/1 ContainerCreating 0 3s
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drycc-minio-c2exb 0/1 Pending 0 3s
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drycc-monitor-grafana-9ccur 0/1 Pending 0 3s
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drycc-monitor-stdout-novxs 0/1 Pending 0 3s
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drycc-monitor-telegraf-dc3y3 0/1 Pending 0 2s
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drycc-registry-5bor6 0/1 Pending 0 3s
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drycc-rabbitmq-0 0/1 ContainerCreating 0 3s
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!!! tip
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To save precious keystrokes, alias `kubectl --namespace=drycc` to `kd` so it is easier to type

‎src/understanding-workflow/components.md‎

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images to either local storage (in development mode) or to object storage
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## Router
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**Project Location:** [drycc/router](https://github.com/drycc/router)
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The router component is based on [Nginx][] and is responsible for routing
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inbound HTTP(S) traffic to your applications. The default workflow charts
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provision a Kubernetes service in the `drycc` namespace with a service type of
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`LoadBalancer`. Depending on your Kubernetes configuration, this may provision
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a cloud-based loadbalancer automatically.
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The router component uses Kubernetes annotations for both Application discovery
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as well as router configuration. For more detailed documentation and possible
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configuration view the router [project documentation][router-documentation].
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## Logger: fluentd, logger
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**Project Location:** [drycc/monitor](https://github.com/drycc/monitor)
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The monitoring subsystem consists of three components: Telegraf, InfluxDB and Grafana.
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The monitoring subsystem consists of two components: Telegraf and Grafana.
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Telegraf is the is the metrics collection agent that runs using the daemon set API. It runs on
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every worker node in the cluster, fetches information about the pods currently running and ships it
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InfluxDB is a database that stores the metrics collected by Telegraf. Out of the box, it does not
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persist to disk, but you can set it up to back it with a persisitent volume or swap this out with
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a more robust InfluxDB setup in a production setting.
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Grafana is a standalone graphing application. It natively supports InfluxDB as a datasource and
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provides a robust engine for creating dashboards on top of timeseries data. Workflow provides a few
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dashboards out of the box for monitoring Drycc Workflow and Kubernetes. The dashboards can be used
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as a starting point for creating more custom dashboards to suit a user's needs.
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## InfluxDB
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**Project Location:** [drycc/influxdb](https://github.com/drycc/influxdb)
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InfluxDB is a database that stores the metrics collected by Telegraf. Out of the box, it does not
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persist to disk, but you can set it up to back it with a persisitent volume or swap this out with
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a more robust InfluxDB setup in a production setting.
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## Rabbitmq
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**Project Location:** [drycc/rabbitmq](https://github.com/drycc/rabbitmq)
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RabbitMQ is the most widely deployed open source message broker.
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Controller use celery with rabbitMQ to execute the asynchronous task.
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## See Also
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[configure-objectstorage]: ../installing-workflow/configuring-object-storage.md
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[logger-documentation]: https://github.com/drycc/logger
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[release]: ../reference-guide/terms.md#release
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[router-documentation]: https://github.com/drycc/router
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[router]: #router
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[using-buildpacks]: ../applications/using-buildpacks.md
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[using-dockerfiles]: ../applications/using-dockerfiles.md

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