EventMesh Workflow Design Document

Version: v1.0.0 | Updated: 2026-06-29 | DSL: Serverless Workflow 1.0.3 (0.8 compatible)

1. Overview

EventMesh Workflow is the workflow runtime in the Apache EventMesh ecosystem. It parses Serverless Workflow DSL definitions, builds task graphs, schedules execution, and orchestrates microservices on the EventMesh event bus.

1.1 Core Capabilities

Capability	Description
DSL Parsing	Supports Serverless Workflow 1.0.3 and 0.8 dual formats, zero external DSL dependency
Task Graph	Compiles DSL descriptions into a DAG (START -> Task -> Transition -> END)
Runtime Scheduling	Queue-based multi-instance scheduling engine for operation/event/switch/structural tasks
EventMesh Integration	Queries operation definitions via gRPC Catalog, publishes events asynchronously
A2A Bridge	Workflow exposed as A2A Agent; supports calling external A2A Agents
Structural Tasks	9 built-in executors for fork/try/for/do/set and other structural tasks

2. Architecture Overview

┌──────────────────────────────────────────────────────────┐
│                    Controller (HTTP API)                   │
│   POST /workflow   GET /workflow   DELETE /workflow       │
│   POST /workflow/start   GET /workflow/instances          │
└───────────────────────┬──────────────────────────────────┘
                        │ DAL (GORM + MySQL)
                        ▼
┌──────────────────────────────────────────────────────────┐
│              DSL Parser (third_party/swf)                  │
│  ┌──────────────┐  ┌──────────────┐  ┌────────────────┐  │
│  │ V1 Parser    │  │ Legacy Parser│  │ Task Validator  │  │
│  │ (document+do)│  │ (id+states)  │  │ (name/then/graph)│  │
│  └──────────────┘  └──────────────┘  └────────────────┘  │
└───────────────────────┬──────────────────────────────────┘
                        │ Workflow + Tasks + Relations
                        ▼
┌──────────────────────────────────────────────────────────┐
│                   Flow Engine                             │
│  ┌──────────────┐  ┌──────────────┐  ┌────────────────┐  │
│  │ Start()      │  │ Transition() │  │ Queue.Publish()│  │
│  │ (instantiate) │  │ (state trans) │  │ (task enqueue) │  │
│  └──────────────┘  └──────────────┘  └────────────────┘  │
└───────────────────────┬──────────────────────────────────┘
                        │ ObserveQueue
                        ▼
┌──────────────────────────────────────────────────────────┐
│                   Task Executors                          │
│  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌─────────────┐ │
│  │Operation │ │  Event   │ │  Switch  │ │Local Runtime │ │
│  │ Task     │ │  Task    │ │  Task    │ │  Task        │ │
│  └──────────┘ └──────────┘ └──────────┘ └─────────────┘ │
└───────────────────────┬──────────────────────────────────┘
                        │
          ┌─────────────┼─────────────┐
          ▼             ▼             ▼
   ┌──────────┐ ┌──────────┐ ┌──────────────┐
   │ EventMesh│ │   A2A    │ │  Local Ops   │
   │  Queue   │ │  Bridge  │ │ (set/wait/…) │
   └──────────┘ └──────────┘ └──────────────┘

2.1 Component Roles

Component	Path	Responsibility
Controller	`cmd/controller/`	HTTP API service, Gin framework, Swagger docs
Flow Engine	`flow/`	Workflow instance start, task state transitions
DSL Parser	`third_party/swf/`	YAML -> Workflow/Task structs, dual-format parsing
DAL	`internal/dal/`	GORM + MySQL persistence, task graph construction
Task Executors	`internal/task/`	4 executor types: operation/event/switch/local-runtime
Queue	`internal/queue/`	Task queue abstraction: In-Memory / EventMesh
Filter	`internal/filter/`	JQ expression input/output data filtering
A2A Bridge	`internal/bridge/`	A2A protocol client + WorkflowAgent HTTP endpoint
Metrics	`internal/metrics/`	Prometheus metrics collection

3. DSL Parser Design

3.1 Dual-Format Compatibility

The parser entry point swf.Parse() detects the DSL version by checking for a document key at the top level:

func Parse(source string) (*Workflow, error) {
    var raw map[string]interface{}
    yaml.Unmarshal([]byte(source), &raw)
    if _, ok := raw["document"]; ok {
        return parseV1Workflow(raw)    // DSL 1.0.3
    }
    return parseLegacyWorkflow(raw)    // DSL 0.8
}

3.2 DSL 1.0.3 Parsing Flow

YAML Source
    │
    ▼
parseV1Workflow(raw)
    │
    ├─ document.name / version / dsl → Workflow metadata
    ├─ raw["do"] → parseV1TaskList → []*Task
    ├─ raw["use"].functions → map[string]*Function
    ├─ raw["schedule"] → Schedule (cron/start/after)
    ├─ raw["input"] → data input filter
    ├─ raw["output"].as → output filter
    │
    ▼
wf.Validate()
    ├─ FlattenTasks()  → flatten nested tasks
    ├─ Check task name uniqueness
    ├─ Validate then/switch.when targets
    │
    ▼
*Workflow (normalized result)

3.3 Task Type Detection

func detectV1TaskType(def map[string]interface{}) string {
    if _, ok := def["call"]; ok  → TaskTypeOperation
    // Detect standard DSL keys:
    // switch / set / do / fork / for / try
    // wait / raise / run / emit / listen
    return TaskTypeOperation  // default fallback
}

3.4 Data Model

Workflow
  ├─ ID, Name, Version, DSL, Namespace
  ├─ Start: entry task name
  ├─ Tasks: []*Task
  │   ├─ Name, Type, InputFilter, OutputFilter
  │   ├─ InlineData, Then, ExplicitThen
  │   ├─ Actions: []*Action {OperationName, OperationType}
  │   ├─ Cases: []*SwitchCase {Name, Condition, Then, IsDefault}
  │   └─ Children: []*Task (nested sub-tasks)
  ├─ Functions: map[string]*Function {Name, Operation, Type}
  └─ Schedule: {Start, Cron, After}

4. Task Graph Construction

4.1 DAL.create() Flow

func (w *workflowDALImpl) create(ctx context.Context, tx *gorm.DB, record *model.Workflow) error {
    wf, _ := swf.Parse(record.Definition)
    
    // 1. Build WorkflowTask (flatten all nested tasks)
    tasks := w.buildTask(wf)          // FlattenTasks → model.WorkflowTask
    
    // 2. Build WorkflowTaskRelation (inter-task edges)
    relations := w.buildTaskRelation(wf, tasks)
    
    // 3. Concurrent write to MySQL
}

4.2 Task Relation Construction Rules

START → first task (workflow.Start)

For each task:
  ┌─ Switch type → buildSwitchTaskRelation
  │                 each case.Then → target TaskID (or END)
  ├─ Fork type   → buildForkTaskRelation
  │                 each child → independent branch edge
  ├─ Explicit then → resolveNextTaskID(Then)
  │                 "end"/"exit"/"continue" → END
  │                 named target → taskIDs[name]
  └─ Default      → Children[0].Name (nested structure) or END

4.3 Fork Task Graph Example

      ┌─────────┐
      │  FORK   │
      └────┬────┘
     ┌─────┴─────┐
     ▼           ▼
  branch_a    branch_b
     │           │
     ▼           ▼
    END         END

During fork construction, all child branches are published in parallel via publishNextTasks().

5. Task Executors

5.1 Task Dispatch Factory

func New(instance *model.WorkflowTaskInstance) Task {
    if isLocalRuntimeTask(taskType) → NewLocalRuntimeTask
    switch taskType:
        operation → NewOperationTask
        event     → NewEventTask
        switch    → NewSwitchTask
        default   → NewOperationTask  // fallback
}

5.2 Executor Types

Executor	Handles	Run() Behavior
OperationTask	call / listen / run	Executes catalog operations, publishes EventMesh events / A2A calls
EventTask	event / listen	Delegates to OperationTask
SwitchTask	switch	JQ condition matching → branch selection → publishOrComplete
LocalRuntimeTask	set / do / fork / for / try / wait / raise / emit	Built-in executors, see §5.3

5.3 LocalRuntimeTask Built-in Executors

Task	execute() Method	Logic
set	executeSet()	JQ Object() applies set expressions to input JSON
do	executeDo()	Sequentially executes sub-tasks in do list (set / raise)
fork	(no local exec)	DAL builds multi-branch relations; run() then publishNextTasks
for	executeFor()	Parses JSON array → iterates each element through do body set tasks
try	executeTry()	Sequentially attempts try list tasks; skips on failure
wait	executeWait()	time.ParseDuration → time.Sleep
raise	executeRaise()	Constructs structured error and returns it
run	executeRun()	Publishes to EventMesh (delegates publishEvent)
emit	executeEmit()	Publishes to EventMesh (delegates publishEvent)

5.4 Data Flow

Input ──→ [InputFilter] ──→ Task.Execute() ──→ output ──→ [OutputFilter] ──→ Next Task
                                    │
                          publishNextOrComplete()
                          (publish next task to Queue)

InputFilter: Applied during task enqueue via FilterWorkflowTaskInputData()
OutputFilter: Applied before LocalRuntimeTask.Run() returns via FilterWorkflowTaskOutputData()
Filters use JQ expression syntax: ${ .field }

6. Queue & Scheduling

6.1 Queue Abstraction

type ObserveQueue interface {
    Publish(instances []*model.WorkflowTaskInstance) error
    Subscribe(handler func(*model.WorkflowTaskInstance))
    UnSubscribe() error
}

Two implementations:

InMemoryQueue: Dev/test environment, memory channel
EventMeshQueue: Production, published via EventMesh SDK

6.2 Scheduling Flow

Engine.Start(param)
  → SelectStartTask → find the first task linked to START
  → InsertInstance → create workflow instance record
  → Queue.Publish(taskInstance) → enqueue

Consumer processing:
  → task.New(instance) → create corresponding executor
  → task.Run()
    → OperationTask: publish EventMesh event (async) + enqueue next task (sleep)
    → EventTask: delegate to OperationTask
    → SwitchTask: match condition → publish next task
    → LocalRuntimeTask: synchronous execution → publish next task

Engine.Transition(param)  ← EventMesh callback
  → SelectTransitionTask (sleep → wait)
  → Queue.Publish → re-enqueue for consumption

7. A2A Bridge

7.1 Architecture

┌────────────────────┐       A2A Protocol        ┌──────────────────┐
│ EventMesh Workflow │ ──── call a2a: ──────→    │  External A2A    │
│  (A2A Client)      │ ←─── task result ────     │  Agent           │
└────────────────────┘                            └──────────────────┘

┌────────────────────┐       A2A Protocol        ┌──────────────────┐
│  External A2A      │ ──── POST /a2a/tasks ──→  │ EventMesh Workflow│
│  Client            │ ←─── task status ─────    │  (WorkflowAgent)  │
└────────────────────┘                            └──────────────────┘

7.2 A2A Client

A2AExecutor implements polling-based task execution:

SendTask(input, metadata) → pollUntilComplete(taskID)
  // Poll /a2a/tasks/{id} every 2 seconds, max 30 attempts

Task detection via isA2ATask(): OperationType == "a2a" or OperationName starts with "a2a".

7.3 WorkflowAgent (Server)

Exposes workflows as A2A Agents:

GET  /.well-known/agent-card.json → Agent Card
POST /a2a/tasks                   → Start workflow instance
GET  /a2a/tasks/{id}              → Query workflow instance status
GET  /a2a/health                  → Health check

7.4 A2A Message Format (v1.0 Compatible)

TaskRequest {
    id, message: { role, parts: [{ type: "text", text }] },
    metadata: { source, timestamp, ... }
}

TaskResponse {
    id, status: "working"|"completed"|"failed",
    message, artifacts: [{ name, parts }], error: { message }
}

8. Database Model

8.1 ER Diagram

t_workflow ──1:N── t_workflow_task ──1:N── t_workflow_task_action
     │                    │
     │                    └──1:N── t_workflow_task_relation
     │
     └──1:N── t_workflow_instance ──1:N── t_workflow_task_instance

8.2 Core Tables

Table	Purpose	Key Fields
t_workflow	Workflow definition	workflow_id, definition(DSL YAML), version
t_workflow_task	Flattened task nodes	task_id, task_name, task_type, task_input_filter, task_output_filter
t_workflow_task_action	Task operation definitions	operation_name, operation_type
t_workflow_task_relation	Inter-task edges	from_task_id, to_task_id, condition
t_workflow_instance	Workflow instances	workflow_instance_id, workflow_status
t_workflow_task_instance	Task instances	task_instance_id, status, input

8.3 State Machine

Task instance: SLEEP(1) → WAIT(2) → PROCESS(3) → SUCCESS(4) / FAIL(5)

Workflow instance: PROCESS(1) → SUCCESS(2)

SLEEP: OperationTask enqueues the next task immediately after publishing an event, with SLEEP status; waits for EventMesh callback Transition
WAIT: Ready, awaiting consumption
PROCESS: Being consumed (actual execution)
SUCCESS / FAIL: Terminal state

9. Data Filtering

JQ (itchyny/gojq) based JSON data filtering:

FilterWorkflowTaskInputData(task)
  → filterJsonData(task.TaskInputFilter, task.Input)
    → jqer.Object(jsonObj, "${ filterExp }")

FilterWorkflowTaskOutputData(input, outputFilter)
  → filterJsonData(outputFilter, input)
    → jqer.Object(jsonObj, "${ filterExp }")

Expression normalization: bare expressions are auto-wrapped as ${ expr }.

10. Module Dependencies

cmd/controller ──→ internal/dal
cmd/engine ──→ flow ──→ internal/dal
                     ──→ internal/queue

internal/dal ──→ third_party/swf
             ──→ internal/dal/model
             ──→ internal/util

internal/task ──→ internal/dal
             ──→ internal/dal/model
             ──→ internal/queue
             ──→ internal/bridge
             ──→ internal/filter
             ──→ third_party/jqer
             ──→ third_party/swf (type constants)

Zero external SWF SDK dependency. third_party/swf/ is a fully self-contained DSL parser.

11. Design Decisions

Decision	Rationale
Zero external DSL dependency	sdk-go/v2 only supports 0.8 and cannot upgrade; fully controllable custom parser
Dual-format compatibility	Gradual migration; existing 0.8 workflows unaffected
Flattened task graph	Unified task graph model simplifies runtime scheduling
LocalRuntimeTask	Built-in executors avoid external EventMesh call overhead for structural tasks
A2A polling mode	Simple and reliable; suitable for non-streaming Agent call scenarios
GORM + MySQL	Consistent with EventMesh ecosystem; transaction support
JQ expression filtering	Lightweight JSON transformation, zero new dependencies (reuses gojq)

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EventMesh Workflow Design Document

1. Overview

1.1 Core Capabilities

2. Architecture Overview

2.1 Component Roles

3. DSL Parser Design

3.1 Dual-Format Compatibility

3.2 DSL 1.0.3 Parsing Flow

3.3 Task Type Detection

3.4 Data Model

4. Task Graph Construction

4.1 DAL.create() Flow

4.2 Task Relation Construction Rules

4.3 Fork Task Graph Example

5. Task Executors

5.1 Task Dispatch Factory

5.2 Executor Types

5.3 LocalRuntimeTask Built-in Executors

5.4 Data Flow

6. Queue & Scheduling

6.1 Queue Abstraction

6.2 Scheduling Flow

7. A2A Bridge

7.1 Architecture

7.2 A2A Client

7.3 WorkflowAgent (Server)

7.4 A2A Message Format (v1.0 Compatible)

8. Database Model

8.1 ER Diagram

8.2 Core Tables

8.3 State Machine

9. Data Filtering

10. Module Dependencies

11. Design Decisions

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EventMesh Workflow Design Document

1. Overview

1.1 Core Capabilities

2. Architecture Overview

2.1 Component Roles

3. DSL Parser Design

3.1 Dual-Format Compatibility

3.2 DSL 1.0.3 Parsing Flow

3.3 Task Type Detection

3.4 Data Model

4. Task Graph Construction

4.1 DAL.create() Flow

4.2 Task Relation Construction Rules

4.3 Fork Task Graph Example

5. Task Executors

5.1 Task Dispatch Factory

5.2 Executor Types

5.3 LocalRuntimeTask Built-in Executors

5.4 Data Flow

6. Queue & Scheduling

6.1 Queue Abstraction

6.2 Scheduling Flow

7. A2A Bridge

7.1 Architecture

7.2 A2A Client

7.3 WorkflowAgent (Server)

7.4 A2A Message Format (v1.0 Compatible)

8. Database Model

8.1 ER Diagram

8.2 Core Tables

8.3 State Machine

9. Data Filtering

10. Module Dependencies

11. Design Decisions