The v2 API requires a different JSON payload structure than what was being sent.
Both DeleteApp and DeleteAppInstance needed to wrap their parameters properly.
SDK Changes:
- Update DeleteAppInput to use {region, app: {key}} structure
- Update DeleteAppInstanceInput to use {region, appinst: {key}} structure
- Fix DeleteApp method to populate new payload structure
- Fix DeleteAppInstance method to populate new payload structure
CLI Changes:
- Add delete command with -f flag for config file specification
- Support --dry-run to preview deletions
- Support --auto-approve to skip confirmation
- Implement v1 and v2 API support following same pattern as apply
- Add deletion planner to discover resources matching config
- Add resource manager to execute deletions (instances first, then app)
Test Changes:
- Update example_test.go to use EdgeConnectConfig_v1.yaml
- All tests passing including comprehensive delete test coverage
Verified working with manual API testing against live endpoint.
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Co-Authored-By: Claude <noreply@anthropic.com>
Reorganize SDK to support both v1 and v2 APIs following Go conventions:
- sdk/edgeconnect/ now contains v1 SDK (from revision/v1 branch)
- sdk/edgeconnect/v2/ contains v2 SDK with package v2
- Update all CLI and internal imports to use v2 path
- Update SDK examples and documentation for v2 import path
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add edge-connect apply command with -f/--file and --dry-run flags
- Integrate config parser, deployment planner, and resource manager
- Provide comprehensive error handling and progress reporting
- Support deployment confirmation prompts and result summaries
- Move internal packages to public SDK packages for CLI access
- Update all tests to pass with new package structure
- Complete Phase 4 CLI Command Implementation
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Co-Authored-By: Claude <noreply@anthropic.com>
Phase 2 Complete: Deployment Planning
- Add comprehensive deployment plan types with action tracking
- Implement EdgeConnectPlanner with state comparison logic
- Support manifest hash calculation and change detection
- Add parallel infrastructure target planning
- Create deployment summary generation with duration estimates
- Include comprehensive test coverage with mock scenarios
- Handle API errors and edge cases gracefully
Features:
- Smart comparison of current vs desired state
- Minimal API calls through batched queries
- Support for dry-run planning operations
- Detailed deployment summaries with resource counts
- Extensible action types (CREATE, UPDATE, DELETE, NONE)
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Co-Authored-By: Claude <noreply@anthropic.com>
- Add comprehensive YAML configuration types for EdgeConnectConfig
- Implement robust parser with validation and path resolution
- Support both k8sApp and dockerApp configurations
- Add comprehensive test coverage with real example parsing
- Create validation for infrastructure uniqueness and port ranges
- Generate instance names following pattern: appName-appVersion-instance
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Enhanced comprehensive example to wait for AppInstance deployment completion:
## New Polling Features:
- **State Monitoring**: Polls ShowAppInst every 10 seconds until ready
- **Timeout Protection**: 5-minute maximum wait time with context cancellation
- **Smart State Detection**: Handles Creating, Ready, Running, Error states
- **Progress Feedback**: Real-time status updates during deployment
## Implementation Details:
- **waitForInstanceReady()**: Robust polling function with timeout
- **State Logic**: Exits on non-creating states (Ready, Running, Error)
- **Error Handling**: Distinguishes between polling errors and failure states
- **Context Management**: Proper timeout context with cleanup
## User Experience:
```
5️⃣ Waiting for application instance to be ready...
Polling instance state (timeout: 5 minutes)...
📊 Instance state: Creating
📊 Instance state: Creating (power: PowerOn)
📊 Instance state: Ready (power: PowerOn)
✅ Instance reached ready state: Ready
```
This ensures the example demonstrates a complete, realistic deployment
workflow where instance creation is fully completed before proceeding
to subsequent operations.
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Co-Authored-By: Claude <noreply@anthropic.com>
