This is a subsystem of the Cloud-Barista platform that provides workflow management for cloud migration.
- Create and management workflow through Airflow.
- Create workflow based on gusty.
- Tested operating systems (OSs):
- Ubuntu 24.04, Ubuntu 22.04, Ubuntu 18.04
- Language:
- Go: 1.23.0
Build and run the binary with Airflow server
make run
Or, you can run it within Docker by this command.
make run_docker
If you want to stop the binary with Airflow server, run this command.
make stop
- Configuration file name is 'cm-cicada.yaml'
- The configuration file must be placed in one of the following directories.
- .cm-cicada/conf directory under user's home directory
- 'conf' directory where running the binary
- 'conf' directory where placed in the path of 'CMCICADA_ROOT' environment variable
- Configuration options
- task_component
- load_examples : Load task component examples if true.
- examples_directory : Specify directory where task component examples are located. Must be set if 'load_examples' is true.
- workflow_template
- templates_directory : Specify directory where workflow templates are located.
- airflow-server
- address : Specify Airflow server's address ({IP or Domain}:{Port})
- use_tls : Must be true if Airflow server uses HTTPS.
- skip_tls_verify : Skip TLS/SSL certificate verification. Must be set if 'use_tls' is true.
- init_retry : Retry count of initializing Airflow server connection used by cm-cicada.
- timeout : HTTP timeout value as seconds.
- username : Airflow login username.
- password : Airflow login password.
- connections : Pre-define Airflow connections (Set multiple connections)
- id : ID of connection
- type : Type of connection
- description : Description of connection
- host : Host address or URL of connection
- port : Port number for use connection
- schema : Connection schema
- login : Username for use connection
- password : Password for use connection
- dag_directory_host : Specify DAG directory of the host. (Mounted DAG directory used by Airflow container.)
- dag_directory_container : Specify DAG directory of Airflow container. (DAG directory inside the container.)
- task_component
- listen
- port : Listen port of the API.
- Configuration file example
cm-cicada: task_component: load_examples: true examples_directory: "./lib/airflow/example/task_component/" workflow_template: templates_directory: "./lib/airflow/example/workflow_template/" airflow-server: address: 127.0.0.1:8080 use_tls: false # skip_tls_verify: true init_retry: 5 timeout: 10 username: "airflow" password: "airflow_pass" connections: - id: honeybee_api type: http description: HoneyBee API host: 127.0.0.1 port: 8081 schema: http - id: beetle_api type: http description: Beetle API host: 127.0.0.1 port: 8056 schema: http login: default password: default - id: tumblebug_api type: http description: TumbleBug API host: 127.0.0.1 port: 1323 schema: http login: default password: default dag_directory_host: "./_airflow/airflow-home/dags" dag_directory_container: "/usr/local/airflow/dags" # Use dag_directory_host for dag_directory_container, if this value is empty listen: port: 8083
Check workflow template list.
curl -X 'GET' \
'http://127.0.0.1:8083/cicada/workflow_template' \
-H 'accept: application/json'
Get workflow template and copy the content.
curl -X 'GET' \
'http://127.0.0.1:8083/cicada/workflow_template/81bbeb23-2c48-4536-9f01-55796e0fa394' \
-H 'accept: application/json'
Create the workflow by pasting copied workflow template content. Modify all of 'sgId' params. (Create the source group from honeybee.)
Check the ID of the created workflow.
curl -X 'POST' \
'http://127.0.0.1:8083/cicada/workflow' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"name": "migrate_infra_workflow",
"data": {
"description": "Migrate Server",
"task_groups": [
{
"name": "migrate_infra",
"description": "Migrate Server",
"tasks": [
{
"name": "infra_import",
"task_component": "honeybee_task_import_infra",
"request_body": "",
"path_params": {
"sgId": "ba695bbb-d673-4092-9821-c9cb05676228"
},
"dependencies": []
},
{
"name": "infra_get",
"task_component": "honeybee_task_get_infra_refined",
"request_body": "",
"path_params": {
"sgId": "ba695bbb-d673-4092-9821-c9cb05676228"
},
"dependencies": [
"infra_import"
]
},
{
"name": "infra_recommend",
"task_component": "beetle_task_recommend_infra",
"request_body": "infra_get",
"path_params": null,
"dependencies": [
"infra_get"
]
},
{
"name": "infra_migration",
"task_component": "beetle_task_infra_migration",
"request_body": "infra_recommend",
"path_params": null,
"dependencies": [
"infra_recommend"
]
},
{
"name": "register_target_to_source_group",
"task_component": "honeybee_register_target_info_to_source_group",
"request_body": "infra_migration",
"path_params": {
"sgId": "ba695bbb-d673-4092-9821-c9cb05676228"
},
"dependencies": [
"infra_migration"
]
}
]
}
]
}
}'
curl -X 'POST' \
'http://127.0.0.1:8083/cicada/workflow/4420da6c-c50f-4d8b-bc2e-f02d8b557fad/run' \
-H 'accept: application/json' \
-d ''
Each task in the workflow references a Task Component.
The Task Component part frequently leads to mistakes, and when the Request Body structure is complex or changes, it becomes difficult to keep up. Therefore, we have implemented a feature that automatically generates Task Components by reading JSON files.
As shown below, using JSONs containing name, description, api_connection_id, swagger_yaml_endpoint, and endpoint, the cicada reads the Swagger YAML and finds the endpoint to automatically construct task components.
The api_connection_id corresponds to one of the connection ids defined in https://github.com/cloud-barista/cm-cicada/blob/main/conf/cm-cicada.yaml
{
"name": "tumblebug_mci_dynamic",
"description": "Create MCI Dynamically from common spec and image.",
"api_connection_id": "tumblebug_api",
"swagger_yaml_endpoint": "/tumblebug/api/doc.yaml",
"endpoint": "/ns/{nsId}/mciDynamic"
}
Examples of these JSONs can be found at: https://github.com/cloud-barista/cm-cicada/tree/main/lib/airflow/example/task_component
The Task Component automatically generated from the above JSON is as follows:
Expand
{
"id": "796645fc-c594-4263-a9ff-243051d1f3a5",
"name": "tumblebug_mci_dynamic",
"description": "Create MCI Dynamically from common spec and image.",
"data": {
"options": {
"api_connection_id": "tumblebug_api",
"endpoint": "/tumblebug/ns/{nsId}/mciDynamic",
"method": "POST",
"request_body": "{\n \"description\": \"Made in CB-TB\",\n \"installMonAgent\": \"no\",\n \"label\": {},\n \"name\": \"mci01\",\n \"systemLabel\": \"\",\n \"vm\": [\n {\n \"commonImage\": \"ubuntu18.04\",\n \"commonSpec\": \"aws+ap-northeast-2+t2.small\",\n \"connectionName\": \"string\",\n \"description\": \"Description\",\n \"label\": {},\n \"name\": \"g1-1\",\n \"rootDiskSize\": \"default, 30, 42, ...\",\n \"rootDiskType\": \"default, TYPE1, ...\",\n \"subGroupSize\": \"3\",\n \"vmUserPassword\": \"string\"\n }\n ]\n}"
},
"body_params": {
"required": [
"name",
"vm"
],
"properties": {
"description": {
"type": "string",
"example": "Made in CB-TB"
},
"installMonAgent": {
"type": "string",
"description": "InstallMonAgent Option for CB-Dragonfly agent installation ([yes/no] default:no)",
"default": "no",
"enum": [
"yes",
"no"
],
"example": "no"
},
"label": {
"type": "object",
"description": "Label is for describing the object by keywords"
},
"name": {
"type": "string",
"example": "mci01"
},
"systemLabel": {
"type": "string",
"description": "SystemLabel is for describing the mci in a keyword (any string can be used) for special System purpose",
"example": ""
},
"vm": {
"type": "array",
"items": {
"type": "object",
"properties": {
"commonImage": {
"type": "string",
"description": "CommonImage is field for id of a image in common namespace",
"example": "ubuntu18.04"
},
"commonSpec": {
"type": "string",
"description": "CommonSpec is field for id of a spec in common namespace",
"example": "aws+ap-northeast-2+t2.small"
},
"connectionName": {
"type": "string",
"description": "if ConnectionName is given, the VM tries to use associtated credential.\nif not, it will use predefined ConnectionName in Spec objects"
},
"description": {
"type": "string",
"example": "Description"
},
"label": {
"type": "object",
"description": "Label is for describing the object by keywords"
},
"name": {
"type": "string",
"description": "VM name or subGroup name if is (not empty) && (> 0). If it is a group, actual VM name will be generated with -N postfix.",
"example": "g1-1"
},
"rootDiskSize": {
"type": "string",
"description": "\"default\", Integer (GB): [\"50\", ..., \"1000\"]",
"default": "default",
"example": "default, 30, 42, ..."
},
"rootDiskType": {
"type": "string",
"description": "\"\", \"default\", \"TYPE1\", AWS: [\"standard\", \"gp2\", \"gp3\"], Azure: [\"PremiumSSD\", \"StandardSSD\", \"StandardHDD\"], GCP: [\"pd-standard\", \"pd-balanced\", \"pd-ssd\", \"pd-extreme\"], ALIBABA: [\"cloud_efficiency\", \"cloud\", \"cloud_essd\"], TENCENT: [\"CLOUD_PREMIUM\", \"CLOUD_SSD\"]",
"default": "default",
"example": "default, TYPE1, ..."
},
"subGroupSize": {
"type": "string",
"description": "if subGroupSize is (not empty) && (> 0), subGroup will be generated. VMs will be created accordingly.",
"default": "1",
"example": "3"
},
"vmUserPassword": {
"type": "string"
}
}
}
}
}
},
"path_params": {
"required": [
"nsId"
],
"properties": {
"nsId": {
"type": "string",
"description": "Namespace ID",
"default": "default"
}
}
},
"query_params": {
"properties": {
"option": {
"type": "string",
"description": "Option for MCI creation",
"enum": [
"hold"
]
}
}
}
},
"created_at": "2024-11-01T14:16:21.541043563+09:00",
"updated_at": "2024-11-01T17:03:37.326385637+09:00",
"is_example": true
}
file path : /_airflow/docker-compose.yml
modify docker-compose.yml file and enter your smtp info.
gmail example : https://support.google.com/a/answer/176600?hl=en
...
airflow-server:
environment:
AIRFLOW__SMTP__SMTP_HOST: 'smtp.gmail.com'
AIRFLOW__SMTP__SMTP_USER: 'yourEmail@gmail.com'
AIRFLOW__SMTP__SMTP_PASSWORD: 'wtknvaprkkwyaurd'
AIRFLOW__SMTP__SMTP_PORT: 587
AIRFLOW__SMTP__SMTP_MAIL_FROM: 'yourEmail@gmail.com'
...
file path : /_airflow/airflow-home/dags/mail.py
Modify the recipient's email address in the email_task.
...
email_task = EmailOperator(
task_id='send_email',
to='Your Email@example.com',
subject='DAG 상태 보고서',
...
)
...
Add trigger_email task component at the bottom of the workflow to receive email alarms.
...
{
"name": "trigger_email",
"task_component": "trigger_email",
"request_body": "",
"path_params": {},
"dependencies": [
"{$Pre_taskName}"
]
}
...
[GET] /workflow/{wfId}/workflowRun/{wfRunId}/taskInstances
[GET] /workflow/{wfId}/workflowRun/{wfRunId}/task/{taskId}/taskTryNum/{taskTyNum}/logs
Check if CM-Cicada is running
curl http://127.0.0.1:8083/cicada/readyz
# Output if it's running successfully
# {"message":"CM-Cicada API server is ready"}