more internal polish, resilient workers
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work-summary/2026-02-09-phase3-retry-health.md
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work-summary/2026-02-09-phase3-retry-health.md
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# Work Summary: Phase 3 - Intelligent Retry & Worker Health
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**Date:** 2026-02-09
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**Author:** AI Assistant
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**Phase:** Worker Availability Handling - Phase 3
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## Overview
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Implemented Phase 3 of worker availability handling: intelligent retry logic and proactive worker health monitoring. This enables automatic recovery from transient failures and health-aware worker selection for optimal execution scheduling.
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## Motivation
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Phases 1 and 2 provided robust failure detection and handling:
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- **Phase 1:** Timeout monitor catches stuck executions
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- **Phase 2:** Queue TTL and DLQ handle unavailable workers
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Phase 3 completes the reliability story by:
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1. **Automatic Recovery:** Retry transient failures without manual intervention
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2. **Intelligent Classification:** Distinguish retriable vs non-retriable failures
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3. **Optimal Scheduling:** Select healthy workers with low queue depth
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4. **Per-Action Configuration:** Custom timeouts and retry limits per action
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## Changes Made
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### 1. Database Schema Enhancement
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**New Migration:** `migrations/20260209000000_phase3_retry_and_health.sql`
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**Execution Retry Tracking:**
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- `retry_count` - Current retry attempt (0 = original, 1 = first retry, etc.)
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- `max_retries` - Maximum retry attempts (copied from action config)
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- `retry_reason` - Reason for retry (worker_unavailable, queue_timeout, etc.)
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- `original_execution` - ID of original execution (forms retry chain)
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**Action Configuration:**
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- `timeout_seconds` - Per-action timeout override (NULL = use global TTL)
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- `max_retries` - Maximum retry attempts for this action (default: 0)
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**Worker Health Tracking:**
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- Health metrics stored in `capabilities.health` JSONB object
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- Fields: status, last_check, consecutive_failures, queue_depth, etc.
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**Database Objects:**
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- `healthy_workers` view - Active workers with fresh heartbeat and healthy status
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- `get_worker_queue_depth()` function - Extract queue depth from worker metadata
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- `is_execution_retriable()` function - Check if execution can be retried
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- Indexes for retry queries and health-based worker selection
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### 2. Retry Manager Module
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**New File:** `crates/executor/src/retry_manager.rs` (487 lines)
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**Components:**
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- `RetryManager` - Core retry orchestration
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- `RetryConfig` - Retry behavior configuration
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- `RetryReason` - Enumeration of retry reasons
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- `RetryAnalysis` - Result of retry eligibility analysis
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**Key Features:**
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- **Failure Classification:** Detects retriable vs non-retriable failures from error messages
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- **Exponential Backoff:** Configurable base, multiplier, and max backoff (default: 1s, 2x, 300s max)
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- **Jitter:** Random variance (±20%) to prevent thundering herd
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- **Retry Chain Tracking:** Links retries to original execution via metadata
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- **Exhaustion Handling:** Stops retrying when max_retries reached
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**Retriable Failure Patterns:**
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- Worker queue TTL expired
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- Worker unavailable
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- Timeout/timed out
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- Heartbeat stale
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- Transient/temporary errors
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- Connection refused/reset
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**Non-Retriable Failures:**
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- Validation errors
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- Permission denied
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- Action not found
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- Invalid parameters
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- Unknown/unclassified errors (conservative approach)
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### 3. Worker Health Probe Module
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**New File:** `crates/executor/src/worker_health.rs` (464 lines)
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**Components:**
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- `WorkerHealthProbe` - Health monitoring and evaluation
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- `HealthProbeConfig` - Health check configuration
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- `HealthStatus` - Health state enum (Healthy, Degraded, Unhealthy)
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- `HealthMetrics` - Worker health metrics structure
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**Health States:**
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**Healthy:**
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- Heartbeat < 30 seconds old
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- Consecutive failures < 3
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- Queue depth < 50
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- Failure rate < 30%
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**Degraded:**
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- Consecutive failures: 3-9
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- Queue depth: 50-99
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- Failure rate: 30-69%
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- Still receives work but deprioritized
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**Unhealthy:**
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- Heartbeat > 30 seconds stale
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- Consecutive failures ≥ 10
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- Queue depth ≥ 100
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- Failure rate ≥ 70%
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- Does NOT receive new executions
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**Features:**
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- **Proactive Health Checks:** Evaluate worker health before scheduling
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- **Health-Aware Selection:** Sort workers by health status and queue depth
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- **Runtime Filtering:** Select best worker for specific runtime
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- **Metrics Extraction:** Parse health data from worker capabilities JSONB
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### 4. Module Integration
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**Updated Files:**
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- `crates/executor/src/lib.rs` - Export retry and health modules
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- `crates/executor/src/main.rs` - Declare modules
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- `crates/executor/Cargo.toml` - Add `rand` dependency for jitter
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**Public API Exports:**
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```rust
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pub use retry_manager::{RetryAnalysis, RetryConfig, RetryManager, RetryReason};
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pub use worker_health::{HealthMetrics, HealthProbeConfig, HealthStatus, WorkerHealthProbe};
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```
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### 5. Documentation
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**Quick Reference Guide:** `docs/QUICKREF-phase3-retry-health.md` (460 lines)
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- Retry behavior and configuration
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- Worker health states and metrics
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- Database schema reference
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- Practical SQL examples
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- Monitoring queries
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- Troubleshooting guides
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- Integration with Phases 1 & 2
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## Technical Details
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### Retry Flow
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```
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Execution fails → Retry Manager analyzes failure
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↓
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Is failure retriable?
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↓ Yes
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Check retry count < max_retries?
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↓ Yes
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Calculate exponential backoff with jitter
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↓
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Create retry execution with metadata:
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- retry_count++
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- original_execution
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- retry_reason
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- retry_at timestamp
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↓
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Schedule retry after backoff delay
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↓
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Success or exhaust retries
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```
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### Worker Selection Flow
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```
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Get runtime requirement → Health Probe queries all workers
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↓
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Filter by:
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1. Active status
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2. Fresh heartbeat
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3. Runtime support
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↓
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Sort by:
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1. Health status (healthy > degraded > unhealthy)
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2. Queue depth (ascending)
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↓
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Return best worker or None
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```
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### Backoff Calculation
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```
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backoff = base_secs * (multiplier ^ retry_count)
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backoff = min(backoff, max_backoff_secs)
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jitter = random(1 - jitter_factor, 1 + jitter_factor)
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final_backoff = backoff * jitter
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```
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**Example:**
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- Attempt 0: ~1s (0.8-1.2s with 20% jitter)
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- Attempt 1: ~2s (1.6-2.4s)
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- Attempt 2: ~4s (3.2-4.8s)
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- Attempt 3: ~8s (6.4-9.6s)
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- Attempt N: min(base * 2^N, 300s) with jitter
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## Configuration
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### Retry Manager
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```rust
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RetryConfig {
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enabled: true, // Enable automatic retries
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base_backoff_secs: 1, // Initial backoff
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max_backoff_secs: 300, // 5 minutes maximum
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backoff_multiplier: 2.0, // Exponential growth
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jitter_factor: 0.2, // 20% randomization
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}
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```
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### Health Probe
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```rust
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HealthProbeConfig {
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enabled: true,
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heartbeat_max_age_secs: 30,
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degraded_threshold: 3, // Consecutive failures
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unhealthy_threshold: 10,
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queue_depth_degraded: 50,
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queue_depth_unhealthy: 100,
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failure_rate_degraded: 0.3, // 30%
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failure_rate_unhealthy: 0.7, // 70%
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}
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```
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### Per-Action Configuration
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```yaml
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# packs/mypack/actions/api-call.yaml
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name: external_api_call
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runtime: python
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entrypoint: actions/api.py
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timeout_seconds: 120 # 2 minutes (overrides global 5 min TTL)
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max_retries: 3 # Retry up to 3 times on failure
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```
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## Testing
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### Compilation
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- ✅ All crates compile cleanly with zero warnings
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- ✅ Added `rand` dependency for jitter calculation
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- ✅ All public API methods properly documented
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### Database Migration
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- ✅ SQLx compatible migration file
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- ✅ Adds all necessary columns, indexes, views, functions
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- ✅ Includes comprehensive comments
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- ✅ Backward compatible (nullable fields)
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### Unit Tests
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- ✅ Retry reason detection from error messages
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- ✅ Retriable error pattern matching
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- ✅ Backoff calculation (exponential with jitter)
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- ✅ Health status extraction from worker capabilities
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- ✅ Configuration defaults
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## Integration Status
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### Complete
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- ✅ Database schema
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- ✅ Retry manager module with full logic
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- ✅ Worker health probe module
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- ✅ Module exports and integration
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- ✅ Comprehensive documentation
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### Pending (Future Integration)
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- ⏳ Wire retry manager into completion listener
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- ⏳ Wire health probe into scheduler
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- ⏳ Add retry API endpoints
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- ⏳ Update worker to report health metrics
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- ⏳ Add retry/health UI components
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**Note:** Phase 3 provides the foundation and API. Full integration will occur in subsequent work as the system is tested and refined.
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## Benefits
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### Automatic Recovery
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- **Transient Failures:** Retry worker unavailability, timeouts, network issues
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- **No Manual Intervention:** System self-heals from temporary problems
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- **Exponential Backoff:** Avoids overwhelming struggling resources
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- **Jitter:** Prevents thundering herd problem
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### Intelligent Scheduling
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- **Health-Aware:** Avoid unhealthy workers proactively
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- **Load Balancing:** Prefer workers with lower queue depth
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- **Runtime Matching:** Only select workers supporting required runtime
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- **Graceful Degradation:** Degraded workers still used if necessary
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### Operational Visibility
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- **Retry Metrics:** Track retry rates, reasons, success rates
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- **Health Metrics:** Monitor worker health distribution
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- **Failure Classification:** Understand why executions fail
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- **Retry Chains:** Trace execution attempts through retries
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### Flexibility
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- **Per-Action Config:** Custom timeouts and retry limits per action
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- **Global Config:** Override retry/health settings for entire system
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- **Tunable Thresholds:** Adjust health and retry parameters
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- **Extensible:** Easy to add new retry reasons or health factors
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## Relationship to Previous Phases
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### Defense in Depth
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**Phase 1 (Timeout Monitor):**
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- Monitors database for stuck SCHEDULED executions
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- Fails executions after timeout (default: 5 minutes)
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- Acts as backstop for all phases
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**Phase 2 (Queue TTL + DLQ):**
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- Expires messages in worker queues (default: 5 minutes)
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- Routes expired messages to DLQ
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- DLQ handler marks executions as FAILED
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**Phase 3 (Intelligent Retry + Health):**
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- Analyzes failures and retries if retriable
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- Exponential backoff prevents immediate re-failure
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- Health-aware selection avoids problematic workers
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### Failure Flow Integration
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```
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Execution scheduled → Sent to worker queue (Phase 2 TTL active)
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↓
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Worker unavailable → Message expires (5 min)
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↓
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DLQ handler fails execution (Phase 2)
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↓
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Retry manager detects retriable failure (Phase 3)
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↓
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Create retry with backoff (Phase 3)
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↓
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Health probe selects healthy worker (Phase 3)
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↓
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Retry succeeds or exhausts attempts
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↓
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If stuck, Phase 1 timeout monitor catches it (safety net)
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```
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### Complementary Mechanisms
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- **Phase 1:** Polling-based safety net (catches anything missed)
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- **Phase 2:** Message-level expiration (precise timing)
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- **Phase 3:** Active recovery (automatic retry) + Prevention (health checks)
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Together: Complete reliability from failure detection → automatic recovery
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## Known Limitations
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1. **Not Fully Integrated:** Modules are standalone, not yet wired into executor/worker
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2. **No Worker Health Reporting:** Workers don't yet update health metrics
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3. **No Retry API:** Manual retry requires direct execution creation
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4. **No UI Components:** Web UI doesn't display retry chains or health
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5. **No per-action TTL:** Worker queue TTL still global (schema supports it)
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## Files Modified/Created
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### New Files (4)
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- `migrations/20260209000000_phase3_retry_and_health.sql` (127 lines)
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- `crates/executor/src/retry_manager.rs` (487 lines)
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- `crates/executor/src/worker_health.rs` (464 lines)
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- `docs/QUICKREF-phase3-retry-health.md` (460 lines)
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### Modified Files (4)
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- `crates/executor/src/lib.rs` (+4 lines)
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- `crates/executor/src/main.rs` (+2 lines)
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- `crates/executor/Cargo.toml` (+1 line)
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- `work-summary/2026-02-09-phase3-retry-health.md` (this document)
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### Total Changes
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- **New Files:** 4
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- **Modified Files:** 4
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- **Lines Added:** ~1,550
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- **Lines Removed:** ~0
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## Deployment Notes
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1. **Database Migration Required:** Run `sqlx migrate run` before deploying
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2. **No Breaking Changes:** All new fields are nullable or have defaults
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3. **Backward Compatible:** Existing executions work without retry metadata
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4. **No Configuration Required:** Sensible defaults for all settings
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5. **Incremental Adoption:** Retry/health features can be enabled per-action
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## Next Steps
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### Immediate (Complete Phase 3 Integration)
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1. **Wire Retry Manager:** Integrate into completion listener to create retries
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2. **Wire Health Probe:** Integrate into scheduler for worker selection
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3. **Worker Health Reporting:** Update workers to report health metrics
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4. **Add API Endpoints:** `/api/v1/executions/{id}/retry` endpoint
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5. **Testing:** End-to-end tests with retry scenarios
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### Short Term (Enhance Phase 3)
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6. **Retry UI:** Display retry chains and status in web UI
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7. **Health Dashboard:** Visualize worker health distribution
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8. **Per-Action TTL:** Use action.timeout_seconds for custom queue TTL
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9. **Retry Policies:** Allow pack-level retry configuration
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10. **Health Probes:** Active HTTP health checks to workers
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### Long Term (Advanced Features)
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11. **Circuit Breakers:** Automatically disable failing actions
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12. **Retry Quotas:** Limit total retries per time window
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13. **Smart Routing:** Affinity-based worker selection
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14. **Predictive Health:** ML-based health prediction
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15. **Auto-scaling:** Scale workers based on queue depth and health
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## Monitoring Recommendations
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### Key Metrics to Track
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- **Retry Rate:** % of executions that retry
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- **Retry Success Rate:** % of retries that eventually succeed
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- **Retry Reason Distribution:** Which failures are most common
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- **Worker Health Distribution:** Healthy/degraded/unhealthy counts
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- **Average Queue Depth:** Per-worker queue occupancy
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- **Health-Driven Routing:** % of executions using health-aware selection
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### Alert Thresholds
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- **Warning:** Retry rate > 20%, unhealthy workers > 30%
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- **Critical:** Retry rate > 50%, unhealthy workers > 70%
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### SQL Monitoring Queries
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See `docs/QUICKREF-phase3-retry-health.md` for comprehensive monitoring queries including:
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- Retry rate over time
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- Retry success rate by reason
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- Worker health distribution
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- Queue depth analysis
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- Retry chain tracing
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## References
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- **Phase 1 Summary:** `work-summary/2026-02-09-worker-availability-phase1.md`
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- **Phase 2 Summary:** `work-summary/2026-02-09-worker-queue-ttl-phase2.md`
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- **Quick Reference:** `docs/QUICKREF-phase3-retry-health.md`
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- **Architecture:** `docs/architecture/worker-availability-handling.md`
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## Conclusion
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Phase 3 provides the foundation for intelligent retry logic and health-aware worker selection. The modules are fully implemented with comprehensive error handling, configuration options, and documentation. While not yet fully integrated into the executor/worker services, the groundwork is complete and ready for incremental integration and testing.
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Together with Phases 1 and 2, the Attune platform now has a complete three-layer reliability system:
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1. **Detection** (Phase 1): Timeout monitor catches stuck executions
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2. **Handling** (Phase 2): Queue TTL and DLQ fail unavailable workers
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3. **Recovery** (Phase 3): Intelligent retry and health-aware scheduling
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This defense-in-depth approach ensures executions are resilient to transient failures while maintaining system stability and performance. 🚀
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