SWF decider tutorial

Running an SWF decider for a virtual AWS.

We’ll use moto, a tool which mocks out SWF.

Warning

moto v1.3.16 or later is required to correctly mock SWF (however, unlike using AWS for real, task-polling returns instantly).

Set-up

Install Moto, AWS CLI, PyYaml and seddy

pip install moto[server,swf] pyyaml seddy

You are free to use whichever method you like to install AWS CLI, for example installing v1 via pip (pip install awscli) or using the Docker image (docker pull amazon/aws-cli:latest, then alias aws='docker run --rm amazon/aws-cli:latest')

Environment variables

To use moto, we need to point the AWS CLI and seddy to its server (which we’ll start below)

export AWS_DEFAULT_REGION=us-east-1
export AWS_SWF_ENDPOINT_URL=http://localhost:5042/

Example

Create workflow definitions file

workflows.yml

version: 1.0
workflows:
  - spec_type: dag
    name: spam
    version: "1.0"
    description: A workflow with spam, spam, eggs and spam.
    registration:
      active: true
      task_timeout: 5
      execution_timeout: 3600
      task_list: coffee
    tasks:
      - id: foo
        type:
          name: spam-foo
          version: "0.3"
        input:
          type: workflow-input
          path: $.foo
        timeout: 10
        task_list: eggs
        priority: 1
      - id: bar
        type:
          name: spam-foo
          version: "0.4"
        input:
          type: workflow-input
          path: $.bar
        timeout: 10
        task_list: eggs
        dependencies:
          - foo
  - spec_type: dag
    name: spam
    version: "1.1"
    description: A workflow with better spam, spam, eggs and spam.
    registration:
      active: true
      task_timeout: 5
      execution_timeout: 3600
      task_list: coffee
    tasks:
      - id: foo
        type:
          name: spam-foo
          version: "0.4"
        input:
          type: workflow-input
          path: $.foo
        timeout: 5
        task_list: eggs
        priority: 1
      - id: bar
        type:
          name: spam-foo
          version: "0.4"
        input:
          type: workflow-input
          path: $.bar
        timeout: 5
        task_list: eggs
        dependencies:
          - foo

---

Start the mock SWF server (in a separate terminal: don’t forget Environment variables)

moto_server swf -p5042

---

Register domain

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf register-domain \
  --name test-domain --workflow-execution-retention-period-in-days 2

---

Register defined workflows with SWF

seddy -v register workflows.yml test-domain

---

Register referenced activities with SWF

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf register-activity-type \
  --domain test-domain \
  --name spam-foo \
  --activity-version 0.3 \
  --default-task-start-to-close-timeout 20 \
  --default-task-schedule-to-start-timeout 600 \
  --default-task-schedule-to-close-timeout 620 \
  --default-task-heartbeat-timeout 20 \
  --default-task-list name=test-activity-list

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf register-activity-type \
  --domain test-domain \
  --name spam-foo \
  --activity-version 0.4 \
  --default-task-start-to-close-timeout 20 \
  --default-task-schedule-to-start-timeout 600 \
  --default-task-schedule-to-close-timeout 620 \
  --default-task-heartbeat-timeout 20 \
  --default-task-list name=test-activity-list

---

Start the decider (in a separate terminal: don’t forget Environment variables)

seddy -v decider workflows.yml test-domain test-list

---

Start a workflow execution

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf start-workflow-execution \
  --domain test-domain \
  --workflow-id test-wf \
  --workflow-type name=spam,version=1.1 \
  --task-list name=test-list \
  --child-policy ABANDON \
  | python3 -c 'import sys, json; print(json.load(sys.stdin)["runId"])' \
  > /tmp/runid

---

Pretend to be an activity worker

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf poll-for-activity-task \
  --domain test-domain --task-list name=eggs \
  | python3 -c 'import sys, json; print(json.load(sys.stdin)["taskToken"])' \
  > /tmp/tasktoken
aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf respond-activity-task-completed \
  --task-token $(cat /tmp/tasktoken)

aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf poll-for-activity-task \
  --domain test-domain --task-list name=eggs \
  | python3 -c 'import sys, json; print(json.load(sys.stdin)["taskToken"])' \
  > /tmp/tasktoken
aws --endpoint-url $AWS_SWF_ENDPOINT_URL swf respond-activity-task-completed \
  --task-token $(cat /tmp/tasktoken)

---

Check execution status

aws --endpoint-url $AWS_SWF_ENDPOINT_URL describe-workflow-execution \
  --domain test-domain --execution workflowId=test-wf,runId=$(cat /tmp/runid)