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Orchestrata Ultimate / Specs / 100-logging-exception-handling

100-logging-exception-handling: Global Logging and Exception Handling

This specification defines project-wide standards for structured logging, exception handling, and observability across the orchestrata-ultimate system. It establishes consistent patterns for error management, logging contexts, metrics collection, and distributed tracing.

At a glance

Item Value
Spec directory specs/100-logging-exception-handling/
Status line in the spec Draft
Requirement IDs defined 104
With a @traces citation in src/ 0 (0.0%)
With a @traces citation in tests/ 0 (0.0%)
Tracked files 6
RTM page 100-logging-exception-handling

Reading this spec

This spec sets project-wide standards for structured logging, exception handling and observability across orchestrata-ultimate. It aims at one consistent way to manage errors, carry logging context, collect metrics and trace requests across components and agents, so that logs are machine-readable, production problems are debuggable, performance can be monitored and alerted on, and an audit trail exists. It also separates operational concerns from business logic.

The approach has four parts: structlog with JSON output for structured logging, a hierarchical exception class tree, context propagation through thread-local and async context variables, and observability integration. The functional requirements run from FR-001 to FR-010: the structured logging framework, the exception hierarchy, distributed tracing, metrics collection, error handling patterns, log context propagation, configuration management, performance requirements, security and compliance, and integration requirements. Data models define the log entry schema, the error response schema and the exception hierarchy.

The 104 requirement IDs (REQ-100-NNN) state the rules. Every log entry conforms to a LogEntry JSON Schema whose required fields are timestamp, level, logger, event and component. Log levels are configurable through an environment variable, and the metrics port through METRICS_PORT. Trace context propagates across component boundaries, counters cover request counts and error rates, and a circuit breaker has configurable failure thresholds and reset timeouts. Request-scoped context appears automatically in log entries. Every error belongs to a category (AUTH, AUTHZ, VAL and others) and carries a code from that category's numeric range, and specific conditions such as resource conflict and failed trace propagation have their own codes. Unexpected exceptions log at ERROR and expected ones at WARNING. Audit logging covers security-sensitive operations with user context in immutable, tamper-evident logs, and observability data is available on dashboards within 30 seconds.

The spec's status line reads Draft, and no code module cites it. The requirements traceability matrix lists every ID. It tracks 6 files. No src/ symbol cites any of the 104 requirements, so measured trace coverage is 0.0%, and in tests/, 0 requirements are cited by a test-side @traces. All 104 requirements have no citing symbol; untraced means no @traces names the ID, and the behaviour may still exist in code that was never annotated.

Requirements

Checkbox is the state recorded in the requirements checklist; Traced by is the count of src/ symbols whose @traces names the ID.

ID Done Requirement Traced by
REQ-100-001 - All log entries MUST conform to the LogEntry JSON Schema defined below, whose required fields are timestamp, level, logger, event, and component. none
REQ-100-002 - All error responses MUST conform to the ErrorResponse JSON Schema defined below, whose required fields are error, message, and timestamp. none
REQ-100-003 - The system MUST provide a structured logging framework that outputs JSON-formatted log entries with consistent field names and types. none
REQ-100-004 - All log entries SHALL include timestamp, level, logger, event, and component fields none
REQ-100-005 - Log entries SHALL be able to include optional context fields (request_id, user_id, trace_id, etc.) none
REQ-100-006 - Log format SHALL be configurable as JSON (production) or console (development) none
REQ-100-007 - Log levels SHALL be configurable via environment variable none
REQ-100-008 - The system MUST implement a hierarchical exception classification system with base and domain-specific exception classes. none
REQ-100-009 - A base exception class UltimateBaseError carrying a context dictionary SHALL be provided none
REQ-100-010 - Domain exception categories (ConfigurationError, ValidationError, etc.) SHALL be provided none
REQ-100-011 - Specialized exceptions (NotFoundError, TimeoutError, etc.) SHALL be provided none
REQ-100-012 - All exceptions SHALL be convertible to structured dictionary format none
REQ-100-013 - The system MUST support distributed tracing across component boundaries with trace context propagation. none
REQ-100-014 - Trace context SHALL be propagated via headers in HTTP requests and async context none
REQ-100-015 - Spans SHALL be created for major operations with configurable sampling none
REQ-100-016 - Span attributes SHALL include component, operation, and resource identifiers none
REQ-100-017 - Traces SHALL be correlated with logs via the trace_id field none
REQ-100-018 - The system MUST collect and expose operational metrics in Prometheus format. none
REQ-100-019 - Counter metrics SHALL be provided for request counts and error rates none
REQ-100-020 - Histogram metrics SHALL be provided for request durations with configurable buckets none
REQ-100-021 - Gauge metrics SHALL be provided for resource usage and active requests none
REQ-100-022 - Metrics SHALL be exposed at the /metrics endpoint with proper labeling none
REQ-100-023 - The system MUST implement standard error handling patterns including retry with exponential backoff and circuit breaker. none
REQ-100-024 - The retry mechanism SHALL support configurable attempts, delays, and backoff factor none
REQ-100-025 - The circuit breaker SHALL support configurable failure thresholds and reset timeouts none
REQ-100-026 - A graceful degradation decorator SHALL provide fallback behavior none
REQ-100-027 - All of these patterns SHALL support both sync and async operations none
REQ-100-028 - The system MUST automatically propagate log context (request_id, user_id, etc.) across async/thread boundaries. none
REQ-100-029 - Context SHALL be propagated via thread-local storage for sync operations none
REQ-100-030 - Context SHALL be propagated via contextvars for async operations none
REQ-100-031 - Context SHALL be automatically included in all log entries within request scope none
REQ-100-032 - Context SHALL be manually extensible with additional fields none
REQ-100-033 - The system MUST configure logging, tracing, and metrics via environment variables. none
REQ-100-034 - Log level SHALL be configurable via the LOG_LEVEL environment variable none
REQ-100-035 - Log format SHALL be configurable via the LOG_FORMAT environment variable none
REQ-100-036 - Tracing SHALL be enabled/disabled via the TRACING_ENABLED environment variable none
REQ-100-037 - Metrics port SHALL be configurable via the METRICS_PORT environment variable none
REQ-100-101 - The system MUST meet performance benchmarks for logging, tracing, and metrics operations. none
REQ-100-102 - Logging throughput SHALL be ≥10,000 logs/sec per component none
REQ-100-103 - Span creation latency SHALL be ≤100μs per span none
REQ-100-104 - Metric collection latency SHALL be ≤10ms per metric update none
REQ-100-105 - Error handling overhead SHALL be ≤5ms per error none
REQ-100-106 - The system MUST implement security and compliance requirements for observability data. none
REQ-100-107 - No PII SHALL be logged without explicit consent none
REQ-100-108 - Log data SHALL be encrypted in transit and at rest none
REQ-100-109 - Access controls SHALL be enforced for log data and metrics none
REQ-100-110 - Access to audit logs SHALL itself be audit-logged none
REQ-100-038 - The system MUST integrate with external observability services. none
REQ-100-039 - Logs SHALL be deliverable to a centralized aggregation service (Loki, ELK, etc.) none
REQ-100-040 - Traces SHALL be exportable to a tracing backend (Jaeger, Tempo, etc.) none
REQ-100-041 - Metrics SHALL be scrapable by Prometheus-compatible systems none
REQ-100-042 - Health checks SHALL be exposable at the /health endpoint none
REQ-100-043 - Structured logs SHALL satisfy the developer-debugging criteria below — component, request_id and user context on every log; filtering by severity, component and time range; stack traces and relevant state on error logs; correlation IDs connecting related entries across services; and log retention of 30 days minimum. none
REQ-100-044 - Health monitoring SHALL satisfy the system-administrator criteria below — key metrics exposed via the Prometheus endpoint; alerts configured for critical failures and performance degradation; dashboards showing system health and performance trends; capacity-planning metrics (memory, CPU, disk, network); and SLA/SLO tracking with error budgets. none
REQ-100-045 - Audit logging SHALL satisfy the security-auditor criteria below — all security-sensitive operations logged with user context; audit logs immutable and tamper-evident; before/after state recorded for mutations; access-control checks logged at DEBUG level; and audit-log retention of 90 days minimum. none
REQ-100-046 - Performance analysis SHALL satisfy the performance-engineer criteria below — distributed tracing with OpenTelemetry across all components; trace sampling configurable based on load; span durations and metadata for all major operations; performance metrics (latency, throughput, error rates); and correlation between traces, logs and metrics. none
REQ-100-047 - The error-handling surface SHALL satisfy the developer criteria below — a clear exception hierarchy with proper inheritance; context carried on every exception; error-recovery patterns (retry, fallback, circuit breaker); graceful degradation when dependencies fail; and comprehensive error documentation. none
REQ-100-048 - All log entries MUST include the fields listed below — timestamp, level, logger, event, component, request_id, and session_id (where applicable): none
REQ-100-049 - Error spans MUST include error.type, error.message, and error.stacktrace: none
REQ-100-050 - The system MUST expose the metrics enumerated below — requests_total, request_duration_seconds, active_requests, errors_total, memory_usage_bytes, and business_events_total — each with the stated metric type and labels. none
REQ-100-051 - MUST use structlog for all application logging none
REQ-100-052 - MUST output JSON format in production environments none
REQ-100-053 - MUST include correlation IDs in all log entries none
REQ-100-054 - MUST configure log levels via environment variable LOG_LEVEL none
REQ-100-055 - MUST use exception hierarchy defined in this specification none
REQ-100-056 - MUST include context dictionary in all custom exceptions none
REQ-100-057 - MUST log exceptions at appropriate level (ERROR for unexpected, WARNING for expected) none
REQ-100-058 - MUST preserve original exception chain using raise ... from ... none
REQ-100-059 - MUST include component label in all metrics none
REQ-100-060 - MUST track request duration for all external-facing operations none
REQ-100-061 - MUST propagate trace context across all async/thread boundaries none
REQ-100-062 - The system MUST read its observability configuration from the environment variables below, honouring the stated value domains and defaults (METRICS_PORT default 9090; TRACING_SAMPLE_RATE in 0.0-1.0, default 0.1): none
REQ-100-063 - Every error MUST be classified into one of the categories below and carry an error code drawn from that category's code range: AUTH (1000-1099), AUTHZ (1100-1199), VAL (1200-1299), RES (1300-1399), INT (1400-1499), SYS (1500-1599), GOV (1600-1699). none
REQ-100-064 - A minimum of 10 error conditions MUST be defined and handled; each condition below MUST be raised on its stated trigger, logged at its stated severity, and carry its stated log context. none
REQ-100-065 - The system MUST handle ERR-001: Authentication Failed (AUTH-1001) none
REQ-100-066 - The system MUST handle ERR-002: Rate Limit Exceeded (AUTHZ-1101) none
REQ-100-067 - The system MUST handle ERR-003: Invalid Input Validation (VAL-1201) none
REQ-100-068 - The system MUST handle ERR-004: Resource Not Found (RES-1301) none
REQ-100-069 - The system MUST handle ERR-005: Resource Conflict (RES-1302) none
REQ-100-070 - The system MUST handle ERR-006: External Service Timeout (INT-1401) none
REQ-100-071 - The system MUST handle ERR-007: External Service Error (INT-1402) none
REQ-100-072 - The system MUST handle ERR-008: Internal System Error (SYS-1501) none
REQ-100-073 - The system MUST handle ERR-009: Configuration Error (SYS-1502) none
REQ-100-074 - The system MUST handle ERR-010: Logging Infrastructure Unavailable (INT-1403) none
REQ-100-075 - The system MUST handle ERR-011: Trace Context Propagation Failed (SYS-1503) none
REQ-100-076 - The system MUST handle ERR-012: Metrics Collection Overload (SYS-1504) none
REQ-100-077 - MUST log all errors with appropriate severity level none
REQ-100-078 - MUST include error context for debugging none
REQ-100-079 - MUST map exceptions to error categories none
REQ-100-080 - MUST provide human-readable error messages none
REQ-100-081 - Observability data MUST be used for proactive alerting and monitoring, covering the alerts and thresholds below: none
REQ-100-082 - All three pillars of observability (logs, metrics, traces) MUST be correlated by the mechanisms below: none
REQ-100-111 - Log completeness: ≥99% of operations produce at least one log entry none
REQ-100-112 - Metric freshness: Metrics updated at least every 15 seconds none
REQ-100-113 - Trace sampling: ≥10% of requests sampled for traces in production none
REQ-100-114 - Alert coverage: All critical failure modes have corresponding alerts none
REQ-100-115 - Dashboard latency: Observability data available within 30 seconds of generation none
REQ-100-083 - The system MUST expose GET /api/v1/logging/config returning the current logging configuration in the shape below, whose required fields are level, format, and component. none
REQ-100-084 - All HTTP 4xx/5xx error responses MUST follow the contract below, whose required fields are error, message, and timestamp: none
REQ-100-085 - The system MUST expose GET /metrics returning metrics in Prometheus exposition text format. none
REQ-100-086 - The system MUST expose GET /health returning component health status in the shape below, whose required fields are status (one of healthy, degraded, unhealthy) and timestamp. none
REQ-100-087 - MUST validate error responses against schema in test suites none
REQ-100-088 - MUST document all logging configuration parameters none
REQ-100-089 - The test suite MUST cover the unit-testing areas below: logging configuration, exception hierarchy, metrics collection, and tracing context. none

Code that traces this spec

No src/ symbol cites a requirement of this spec.

Checklists

checklists/README.md

Logging and Exception Handling Checklists

Overview

This directory contains compliance checklists for the Global Logging and Exception Handling specification (SPEC-100). These checklists ensure that all components of the orchestrata-ultimate system implement consistent logging, exception handling, and observability patterns.

Checklist Files
File Purpose Status
constitutional.md Compliance with Orchestrata Constitution articles related to observability and error handling Draft
requirements.md Functional and non-functional requirements verification Draft
testing.md Test scenarios and verification procedures Draft
Usage
  1. During Development: Developers should reference these checklists when implementing new components or modifying existing ones
  2. Code Review: Reviewers should use these checklists to ensure compliance
  3. QA Verification: QA engineers should verify implementation against testing checklist
  4. Audit: Security and compliance teams should review against constitutional checklist
Checklist Status Legend
Quick Start

For new component implementation:

  1. Start with requirements.md to understand what needs to be implemented
  2. Refer to constitutional.md to ensure compliance with governance policies
  3. Use testing.md to create test cases for your implementation
  4. Update checklist status as you complete items
Updates

These checklists should be updated when:

Contact

For questions or updates to these checklists, contact the specification author (Mohamed).

checklists/constitutional.md

Logging and Exception Handling Constitutional Compliance Checklist

Spec: 100-logging-exception-handling
Component: System-wide (all components)
Status: Specification Phase

Overview

This checklist ensures that logging and exception handling implementation complies with all 11 articles of the Orchestrata Constitution. Each article includes specific compliance requirements and verification steps for observability and error management.

Total Compliance Items: 180+ checkboxes

Article I: Separation of Concerns

Principle: Each component has a single, well-defined responsibility

Compliance Requirements
Implementation Verification
Article II: Prolog as Source of Truth

Principle: All governance rules, ownership, and policies are defined in Prolog

Compliance Requirements
Implementation Verification
Article III: Volk Autonomy with Orchestration

Principle: Volks operate autonomously but coordinate through the kernel

Compliance Requirements
Implementation Verification
Article IV: CXP as Universal Protocol

Principle: All communication between components uses CXP protocol

Compliance Requirements
Implementation Verification
Article V: Multi-Model Architecture

Principle: System supports multiple AI models with flexible routing

Compliance Requirements
Implementation Verification
Article VI: Proactive Governance (PAM++)

Principle: Governance policies proactively prevent issues

Compliance Requirements
Implementation Verification
Article VII: Immutable Audit Trail

Principle: All system actions create immutable audit records

Compliance Requirements
Implementation Verification
Article VIII: Real-Time Collaboration

Principle: Multiple agents can collaborate in real-time

Compliance Requirements
Implementation Verification
Article IX: Knowledge Graph Integration

Principle: All system knowledge is stored in the knowledge graph

Compliance Requirements
Implementation Verification
Article X: Progressive Enhancement

Principle: System capabilities enhance progressively based on context

Compliance Requirements
Implementation Verification
Article XI: Truthfulness and Verification

Principle: System prioritizes truthfulness and verification

Compliance Requirements
Implementation Verification
Summary
Article Total Items Completed Pending Status
I 20 0 20 📋
II 20 0 20 📋
III 20 0 20 📋
IV 20 0 20 📋
V 20 0 20 📋
VI 20 0 20 📋
VII 20 0 20 📋
VIII 20 0 20 📋
IX 20 0 20 📋
X 20 0 20 📋
XI 20 0 20 📋
Total 220 0 220 📋
Next Steps
  1. Review checklist with architecture team
  2. Assign implementation responsibilities
  3. Create detailed implementation plan
  4. Begin with Article I (Separation of Concerns)
  5. Progress through articles in order
  6. Regular compliance reviews
  7. Update checklist as implementation progresses
Last Updated

2026-04-09

checklists/requirements.md

The requirement list above comes from this file; 0 of 0 checkbox items are ticked.

checklists/testing.md

Logging and Exception Handling Testing Checklist

Spec: 100-logging-exception-handling
Component: System-wide (all components)
Status: Specification Phase

Overview

This checklist defines test scenarios and verification procedures for the logging and exception handling implementation. It covers unit tests, integration tests, performance tests, and security tests.

Total Test Scenarios: 200+ checkboxes

Unit Test Scenarios
UT-001: Exception Hierarchy Tests

Test Data:

Assertions:

UT-002: Structured Logging Configuration Tests

Test Data:

Assertions:

UT-003: Metrics Collection Tests

Test Data:

Assertions:

UT-004: Tracing Implementation Tests

Test Data:

Assertions:

UT-005: Error Handling Pattern Tests

Test Data:

Assertions:

Integration Test Scenarios
IT-001: End-to-End Logging Integration

Test Setup:

Assertions:

IT-002: Distributed Tracing Integration

Test Setup:

Assertions:

IT-003: Metrics Integration

Test Setup:

Assertions:

IT-004: Error Handling Integration

Test Setup:

Assertions:

IT-005: Security and Audit Integration

Test Setup:

Assertions:

Performance Test Scenarios
PT-001: Logging Performance Tests

Test Methodology:

Acceptance Criteria:

PT-002: Tracing Performance Tests

Test Methodology:

Acceptance Criteria:

PT-003: Metrics Performance Tests

Test Methodology:

Acceptance Criteria:

PT-004: Error Handling Performance Tests

Test Methodology:

Acceptance Criteria:

Security Test Scenarios
ST-001: Logging Security Tests

Test Methodology:

Acceptance Criteria:

ST-002: Metrics Security Tests

Test Methodology:

Acceptance Criteria:

ST-003: Tracing Security Tests

Test Methodology:

Acceptance Criteria:

ST-004: Error Handling Security Tests

Test Methodology:

Acceptance Criteria:

Test Environment Requirements
Hardware Requirements
Software Requirements
Data Requirements
Environment Configuration
Test Automation Strategy
Continuous Integration
Test Reporting
Test Maintenance
Risk Assessment
High Risk Areas
Mitigation Strategies
Contingency Plans
Test Schedule
Test Type Frequency Duration Environment Owner
Unit Tests On commit 5 minutes CI Mohamed
Integration Tests On PR 30 minutes Staging Mohamed
Performance Tests Nightly 2 hours Performance Mohamed
Security Tests Weekly 4 hours Security Mohamed
Compliance Tests Monthly 8 hours Compliance Mohamed
Full Regression Before release 1 day Production-like Mohamed
Last Updated

2026-04-09

Other tracked files

Full spec text

Verbatim from specs/100-logging-exception-handling/spec.md; headings are pushed down two levels.

SPEC-100: Global Logging and Exception Handling

Metadata

Overview

This specification defines project-wide standards for structured logging, exception handling, and observability across the orchestrata-ultimate system. It establishes consistent patterns for error management, logging contexts, metrics collection, and distributed tracing.

What

A unified logging and exception handling framework using structlog for structured logging, custom exception hierarchy, context propagation, and observability integration.

Why
How

Visual Architecture

Class Diagram

Diagram source shown as text: Mermaid could not parse it (Error: Parse error on line 6:).

classDiagram-direction LR
    class AuditAction {
    }
    class AuditStatus {
    }
    <<dataclass>>
    class AuditEvent <<dataclass>> {
        -action: AuditAction
        -timestamp: datetime = field(default_factory=datetime.now)
        -status: AuditStatus = AuditStatus.SUCCESS
        -actor_id: str | None = None
        -actor_type: str = 'user'
        -actor_ip: str | None = None
        -actor_user_agent: str | None = None
        -resource_type: str | None = None
        -resource_id: str | None = None
        -resource_path: str | None = None
        -operation_id: str | None = None
        -operation_name: str | None = None
        -operation_duration_ms: float | None = None
        -before_state: dict[str, Any] | None = None
        -after_state: dict[str, Any] | None = None
        -changes: list[str] | None = None
        -request_id: str | None = None
        -session_id: str | None = None
        -trace_id: str | None = None
        -span_id: str | None = None
        -component: str | None = None
        -severity: str = 'info'
        -details: dict[str, Any] | None = None
        -error_message: str | None = None
        -error_stack: str | None = None
        -event_hash: str | None = None
        -previous_hash: str | None = None
        ---
        +__post_init__()
        +calculate_hash(): str
        #_json_serializer(obj)
        +to_dict(): dict[str, Any]
        +verify_hash(): bool
    }
    class AuditLogger {
        +__init__(component: str | None = None)
        +log_event(event: AuditEvent): str
        +log_action(action: AuditAction | str, status: AuditStatus | str = AuditStatus.SUCCESS, resource_type: str | None = None, resource_id: str | None = None, before_state: dict[str, Any] | None = None, after_state: dict[str, Any] | None = None, actor_id: str | None = None, actor_type: str = 'user', details: dict[str, Any] | None = None, error_message: str | None = None, operation_duration_ms: float | None = None, severity: str | None = None): str
    }
    <<dataclass>>
    class AuditOperation <<dataclass>> {
        -action: AuditAction | str
        -resource_type: str | None = None
        -resource_id: str | None = None
        -before_state: dict[str, Any] | None = None
        -actor_id: str | None = None
        -actor_type: str = 'user'
        -component: str | None = None
        -details: dict[str, Any] | None = None
        ---
        +__enter__()
        +__exit__(exc_type, exc_val, exc_tb)
    }
    <<dataclass>>
    class LoggingContext <<dataclass>> {
        -request_id: str | None = None
        -session_id: str | None = None
        -trace_id: str | None = None
        -span_id: str | None = None
        -user_id: str | None = None
        -user_email: str | None = None
        -user_role: str | None = None
        -component: str | None = None
        -operation: str | None = None
        -extra: dict[str, Any] = field(default_factory=dict)
        -created_at: datetime = field(default_factory=datetime.now)
        ---
        +to_dict(): dict[str, Any]
    }
    class ContextManager {
        {@staticmethod} +get_current_context(): LoggingContext
        {@staticmethod} +set_current_context(context: LoggingContext): None
        {@staticmethod} +clear_context(): None
        {@staticmethod} +update_context(**kwargs): LoggingContext
        {@staticmethod} +create_child_context(**updates): LoggingContext
    }
    class AsyncContext {
        +__init__(**context_updates)
        +async __aenter__(): LoggingContext
        +async __aexit__(exc_type, exc_val, exc_tb)
    }
    class Context {
        +__init__(**context_updates)
        +__enter__(): LoggingContext
        +__exit__(exc_type, exc_val, exc_tb)
    }
    class LogLevel {
    }
    class LogContext {
        +__init__(logger: BoundLogger, **context)
        +__enter__()
        +__exit__(exc_type, exc_val, exc_tb)
    }
    class MetricsConfig {
        +__init__(enabled: bool = True, port: int = 9090, host: str = '0.0.0.0', include_system_metrics: bool = True, system_metrics_interval: float = 30.0)
    }
    class RetryStrategy {
        +__init__(max_retries: int = 3, initial_delay: float = 0.1, max_delay: float = 10.0, backoff_factor: float = 2.0, jitter: float = 0.1)
        +calculate_delay(attempt: int): float
    }
    class CircuitState {
    }
    class CircuitBreaker {
        +__init__(failure_threshold: int = 5, reset_timeout: timedelta = timedelta(seconds=30), half_open_max_requests: int = 3, name: str | None = None)
        {@property} +is_closed(): bool
        {@property} +is_open(): bool
        {@property} +is_half_open(): bool
        +record_success(): None
        +record_failure(): None
        +should_allow_request(): bool
        +async execute(operation: Callable[[], T]): T
    }
    class Bulkhead {
        +__init__(max_concurrent: int = 10, max_queue_size: int = 100, name: str | None = None)
        +async execute(operation: Callable[[], T]): T
    }
    <<dataclass>>
    class TraceInfo <<dataclass>> {
        -spec: str = ''
        -story: str = ''
        -reqs: List[str] = field(default_factory=list)
        -module: str = ''
        -class_name: str = ''
        -method: str = ''
        -file_path: str = ''
        -line_number: int = 0
        ---
        +to_dict(): Dict[str, Any]
    }
    <<dataclass>>
    class Requirement <<dataclass>> {
        -id: str
        -description: str
        -story_id: str = ''
        -spec_id: str = ''
        -priority: str = 'NORMAL'
        -category: str = ''
        ---
    }
    <<dataclass>>
    class UserStory <<dataclass>> {
        -id: str
        -title: str
        -as_a: str = ''
        -i_want: str = ''
        -so_that: str = ''
        -acceptance_criteria: List[str] = field(default_factory=list)
        -requirements: List[Requirement] = field(default_factory=list)
        -spec_id: str = ''
        ---
        +to_dict(): Dict[str, Any]
    }
    <<dataclass>>
    class ValidationReport <<dataclass>> {
        -verified: List[str] = field(default_factory=list)
        -missing: List[str] = field(default_factory=list)
        -orphan: List[str] = field(default_factory=list)
        -duplicates: Dict[str, List[str]] = field(default_factory=dict)
        ---
        {@property} +total_verified(): int
        {@property} +total_missing(): int
        {@property} +total_orphan(): int
        {@property} +coverage_percent(): float
        +to_dict(): Dict[str, Any]
    }
    <<dataclass>>
    class RTMReport <<dataclass>> {
        -entries: List[Dict[str, Any]] = field(default_factory=list)
        -validation: Optional[ValidationReport] = None
        -generated_at: str = ''
        -project: str = ''
        ---
        +to_dict(): Dict[str, Any]
    }
    str <|-- AuditAction
    Enum <|-- AuditAction
    str <|-- AuditStatus
    Enum <|-- AuditStatus
    str <|-- LogLevel
    Enum <|-- LogLevel
    str <|-- CircuitState
    Enum <|-- CircuitState
    AuditEvent *-- AuditAction "1" "action" "1"
    AuditEvent *-- AuditStatus "1" "status" "1"
    UserStory *-- Requirement "1" "requirements" "1"
    RTMReport *-- ValidationReport "1" "validation" "1"
    AuditLogger ..> AuditEvent "log_event(event)"
    ContextManager ..> LoggingContext "get_current_context returns"
    ContextManager ..> LoggingContext "set_current_context(context)"
    ContextManager ..> LoggingContext "update_context returns"
    ContextManager ..> LoggingContext "create_child_context returns"
    AsyncContext ..> LoggingContext "__aenter__ returns"
    Context ..> LoggingContext "__enter__ returns"
    AuditLogger ..> AuditEvent "AuditEvent"
    AuditLogger ..> AuditAction "AuditAction"
    AuditLogger ..> AuditStatus "AuditStatus"
    ContextManager ..> LoggingContext "LoggingContext"
Logging Flow

Diagram projects-orchestrata-ultimate-specs-100-logging-exception-handling-mdc1fd91738

Exception Hierarchy

Diagram projects-orchestrata-ultimate-specs-100-logging-exception-handling-mb72b54578a

Observability Data Flow

Diagram projects-orchestrata-ultimate-specs-100-logging-exception-handling-m8e0cfdd81c

Terminology and Glossary

Term Definition
Structured Logging Logging where each log entry is a structured data object (JSON) rather than plain text
Log Context Additional metadata attached to log entries (request ID, user, component, etc.)
Exception Hierarchy Organized exception classes with inheritance relationships for proper error handling
Distributed Tracing Tracking requests across service/component boundaries with unique trace IDs
Span A single operation within a trace with start/end time and metadata
Log Aggregation Collecting logs from multiple sources into a central system for analysis
Metrics Numerical measurements of system behavior over time (counters, gauges, histograms)
Alerting Automated notifications when metrics cross defined thresholds
Audit Trail Immutable record of system actions for compliance and forensic analysis

Data Models

Log Entry Schema

REQ-100-001: All log entries MUST conform to the LogEntry JSON Schema defined below, whose required fields are timestamp, level, logger, event, and component.

{
  "$schema": "http://json-schema.org/draft/2020-12/schema",
  "title": "LogEntry",
  "type": "object",
  "required": ["timestamp", "level", "logger", "event", "component"],
  "properties": {
    "timestamp": {
      "type": "string",
      "format": "date-time",
      "description": "ISO 8601 timestamp"
    },
    "level": {
      "type": "string",
      "enum": ["TRACE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
    },
    "logger": {
      "type": "string",
      "description": "Logger name (module path)"
    },
    "event": {
      "type": "string",
      "description": "Descriptive event message"
    },
    "component": {
      "type": "string",
      "description": "Component identifier"
    },
    "request_id": {
      "type": "string",
      "description": "Correlation ID for request/operation"
    },
    "session_id": {
      "type": "string",
      "description": "User session identifier"
    },
    "user_id": {
      "type": "string",
      "description": "Authenticated user identifier"
    },
    "trace_id": {
      "type": "string",
      "description": "Distributed trace identifier"
    },
    "span_id": {
      "type": "string",
      "description": "Current span identifier"
    },
    "duration_ms": {
      "type": "number",
      "description": "Operation duration in milliseconds"
    },
    "status": {
      "type": "string",
      "description": "Operation status"
    },
    "error": {
      "type": "object",
      "properties": {
        "type": { "type": "string" },
        "message": { "type": "string" },
        "stacktrace": { "type": "string" }
      }
    }
  }
}
Error Response Schema

REQ-100-002: All error responses MUST conform to the ErrorResponse JSON Schema defined below, whose required fields are error, message, and timestamp.

{
  "$schema": "http://json-schema.org/draft/2020-12/schema",
  "title": "ErrorResponse",
  "type": "object",
  "required": ["error", "message", "timestamp"],
  "properties": {
    "error": {
      "type": "string",
      "description": "Error category/code"
    },
    "message": {
      "type": "string",
      "description": "Human-readable error message"
    },
    "timestamp": {
      "type": "string",
      "format": "date-time"
    },
    "context": {
      "type": "object",
      "description": "Additional error context"
    },
    "trace_id": {
      "type": "string",
      "description": "Distributed trace identifier"
    },
    "request_id": {
      "type": "string",
      "description": "Correlation ID for request"
    },
    "code": {
      "type": "string",
      "description": "Machine-readable error code (e.g., AUTH-1001)"
    },
    "documentation_url": {
      "type": "string",
      "description": "URL to error documentation"
    }
  }
}
Exception Hierarchy

(See Exception Hierarchy section below for detailed class definitions.)

Functional Requirements

FR-001: Structured Logging Framework

REQ-100-003: The system MUST provide a structured logging framework that outputs JSON-formatted log entries with consistent field names and types.

Acceptance Criteria:

FR-002: Exception Hierarchy

REQ-100-008: The system MUST implement a hierarchical exception classification system with base and domain-specific exception classes.

Acceptance Criteria:

FR-003: Distributed Tracing

REQ-100-013: The system MUST support distributed tracing across component boundaries with trace context propagation.

Acceptance Criteria:

FR-004: Metrics Collection

REQ-100-018: The system MUST collect and expose operational metrics in Prometheus format.

Acceptance Criteria:

FR-005: Error Handling Patterns

REQ-100-023: The system MUST implement standard error handling patterns including retry with exponential backoff and circuit breaker.

Acceptance Criteria:

FR-006: Log Context Propagation

REQ-100-028: The system MUST automatically propagate log context (request_id, user_id, etc.) across async/thread boundaries.

Acceptance Criteria:

FR-007: Configuration Management

REQ-100-033: The system MUST configure logging, tracing, and metrics via environment variables.

Acceptance Criteria:

FR-008: Performance Requirements

REQ-100-101: The system MUST meet performance benchmarks for logging, tracing, and metrics operations.

Acceptance Criteria:

FR-009: Security and Compliance

REQ-100-106: The system MUST implement security and compliance requirements for observability data.

Acceptance Criteria:

FR-010: Integration Requirements

REQ-100-038: The system MUST integrate with external observability services.

Acceptance Criteria:

User Scenarios

US-001: Developer Debugging Production Issues

As a developer I want to search and analyze structured logs with rich context So that I can quickly diagnose and fix production issues

Acceptance Criteria:

REQ-100-043: Structured logs SHALL satisfy the developer-debugging criteria below — component, request_id and user context on every log; filtering by severity, component and time range; stack traces and relevant state on error logs; correlation IDs connecting related entries across services; and log retention of 30 days minimum.

US-002: System Administrator Monitoring Health

As a system administrator I want to monitor system health through metrics and alerts So that I can proactively address issues before they impact users

Acceptance Criteria:

REQ-100-044: Health monitoring SHALL satisfy the system-administrator criteria below — key metrics exposed via the Prometheus endpoint; alerts configured for critical failures and performance degradation; dashboards showing system health and performance trends; capacity-planning metrics (memory, CPU, disk, network); and SLA/SLO tracking with error budgets.

US-003: Security Auditor Investigating Incidents

As a security auditor I want to trace user actions through audit logs So that I can investigate security incidents and ensure compliance

Acceptance Criteria:

REQ-100-045: Audit logging SHALL satisfy the security-auditor criteria below — all security-sensitive operations logged with user context; audit logs immutable and tamper-evident; before/after state recorded for mutations; access-control checks logged at DEBUG level; and audit-log retention of 90 days minimum.

US-004: Performance Engineer Analyzing Bottlenecks

As a performance engineer I want to analyze distributed traces and performance metrics So that I can identify and optimize performance bottlenecks

Acceptance Criteria:

REQ-100-046: Performance analysis SHALL satisfy the performance-engineer criteria below — distributed tracing with OpenTelemetry across all components; trace sampling configurable based on load; span durations and metadata for all major operations; performance metrics (latency, throughput, error rates); and correlation between traces, logs and metrics.

US-005: Developer Writing Error-Resilient Code

As a developer I want to use consistent exception patterns and error handling So that my code is robust and failures are properly communicated

Acceptance Criteria:

REQ-100-047: The error-handling surface SHALL satisfy the developer criteria below — a clear exception hierarchy with proper inheritance; context carried on every exception; error-recovery patterns (retry, fallback, circuit breaker); graceful degradation when dependencies fail; and comprehensive error documentation.

Exception Hierarchy

Base Exception Classes
class UltimateBaseError(Exception):
    """Base exception for all orchestrata-ultimate errors."""
    
    def __init__(self, message: str, context: Optional[Dict[str, Any]] = None):
        self.message = message
        self.context = context or {}
        self.timestamp = datetime.now()
        super().__init__(message)
    
    def to_dict(self) -> Dict[str, Any]:
        """Convert exception to structured dictionary."""
        return {
            "type": self.__class__.__name__,
            "message": self.message,
            "context": self.context,
            "timestamp": self.timestamp.isoformat(),
        }
Domain-Specific Exception Categories
class ConfigurationError(UltimateBaseError):
    """Configuration-related errors."""

class ValidationError(UltimateBaseError):
    """Input validation errors."""

class AuthenticationError(UltimateBaseError):
    """Authentication failures."""

class AuthorizationError(UltimateBaseError):
    """Authorization/access control failures."""

class ResourceError(UltimateBaseError):
    """Resource-related errors (not found, conflict, etc.)."""

class IntegrationError(UltimateBaseError):
    """External integration failures."""

class GovernanceError(UltimateBaseError):
    """Governance policy violations."""

class SystemError(UltimateBaseError):
    """System/internal errors (bugs, invariants violated)."""
Specialized Exceptions
class NotFoundError(ResourceError):
    """Requested resource not found."""

class ConflictError(ResourceError):
    """Resource conflict (e.g., duplicate, already exists)."""

class RateLimitError(AuthorizationError):
    """Rate limit exceeded."""

class TimeoutError(IntegrationError):
    """Operation timeout."""

class CircuitBreakerOpenError(IntegrationError):
    """Circuit breaker is open, preventing requests."""

Structured Logging

Log Levels and Usage
Level When to Use Example
TRACE Extremely detailed debugging Function entry/exit with parameters
DEBUG Detailed debugging information State transitions, decision logic
INFO Normal operational messages Service startup, configuration loaded
WARNING Unexpected but handled situations Deprecated API usage, performance warnings
ERROR Error conditions that affect single operation Failed request, validation error
CRITICAL System-level failures Out of memory, disk full, unrecoverable state
Log Context Requirements

REQ-100-048: All log entries MUST include the fields listed below — timestamp, level, logger, event, component, request_id, and session_id (where applicable):

Optional context based on operation type:

Log Configuration
# Example configuration
import structlog
from structlog.processors import JSONRenderer, TimeStamper
from structlog.stdlib import add_log_level, filter_by_level

def configure_logging(level: str = "INFO", json_output: bool = True):
    """Configure structured logging for the application."""
    
    processors = [
        filter_by_level,
        add_log_level,
        structlog.processors.StackInfoRenderer(),
        structlog.processors.format_exc_info,
        TimeStamper(fmt="iso"),
        structlog.processors.UnicodeDecoder(),
    ]
    
    if json_output:
        processors.append(JSONRenderer())
    else:
        processors.append(structlog.dev.ConsoleRenderer())
    
    structlog.configure(
        processors=processors,
        wrapper_class=structlog.stdlib.BoundLogger,
        context_class=dict,
        logger_factory=structlog.stdlib.LoggerFactory(),
        cache_logger_on_first_use=True,
    )
    
    # Configure standard library logging
    import logging
    logging.basicConfig(level=getattr(logging, level.upper()))

Distributed Tracing

Trace Context Propagation
from opentelemetry import trace
from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator

class TracingContext:
    """Manage distributed tracing context."""
    
    def __init__(self):
        self.tracer = trace.get_tracer(__name__)
        self.propagator = TraceContextTextMapPropagator()
    
    def start_span(self, name: str, context: Optional[Dict] = None) -> trace.Span:
        """Start a new span with optional parent context."""
        return self.tracer.start_span(name, context=context)
    
    def inject_context(self, carrier: Dict):
        """Inject trace context into carrier for propagation."""
        self.propagator.inject(carrier)
    
    def extract_context(self, carrier: Dict) -> trace.SpanContext:
        """Extract trace context from carrier."""
        return self.propagator.extract(carrier)
Span Attributes

All spans SHOULD include:

REQ-100-049: Error spans MUST include error.type, error.message, and error.stacktrace:

Metrics Collection

Required Metrics

REQ-100-050: The system MUST expose the metrics enumerated below — requests_total, request_duration_seconds, active_requests, errors_total, memory_usage_bytes, and business_events_total — each with the stated metric type and labels.

Metric Type Name Description Labels
Counter requests_total Total number of requests method, endpoint, status
Histogram request_duration_seconds Request duration in seconds method, endpoint
Gauge active_requests Currently active requests component
Counter errors_total Total number of errors component, error_type
Gauge memory_usage_bytes Memory usage in bytes component
Counter business_events_total Business events counter event_type, component
Metrics Configuration
from prometheus_client import Counter, Histogram, Gauge

# Define metrics
REQUESTS_TOTAL = Counter(
    'orchestrata_requests_total',
    'Total number of requests',
    ['method', 'endpoint', 'status']
)

REQUEST_DURATION = Histogram(
    'orchestrata_request_duration_seconds',
    'Request duration in seconds',
    ['method', 'endpoint'],
    buckets=(0.01, 0.05, 0.1, 0.5, 1.0, 5.0)
)

ACTIVE_REQUESTS = Gauge(
    'orchestrata_active_requests',
    'Currently active requests',
    ['component']
)

Error Handling Patterns

Retry with Exponential Backoff
import asyncio
from typing import Callable, TypeVar, Optional
from datetime import datetime, timedelta

T = TypeVar('T')

async def retry_with_backoff(
    operation: Callable[[], T],
    max_retries: int = 3,
    initial_delay: float = 0.1,
    max_delay: float = 10.0,
    backoff_factor: float = 2.0,
    retryable_errors: Optional[tuple] = None,
) -> T:
    """Execute operation with retry and exponential backoff."""
    
    retryable_errors = retryable_errors or (TimeoutError, IntegrationError)
    last_error = None
    
    for attempt in range(max_retries + 1):
        try:
            return await operation() if asyncio.iscoroutinefunction(operation) else operation()
        except retryable_errors as e:
            last_error = e
            
            if attempt == max_retries:
                logger.warning(
                    "Operation failed after max retries",
                    attempt=attempt,
                    error=str(e),
                    max_retries=max_retries,
                )
                raise
            
            delay = min(initial_delay * (backoff_factor ** attempt), max_delay)
            logger.debug(
                "Operation failed, retrying",
                attempt=attempt,
                error=str(e),
                next_retry_ms=delay * 1000,
            )
            
            await asyncio.sleep(delay)
    
    raise last_error
Circuit Breaker Pattern
from enum import Enum
from datetime import datetime, timedelta

class CircuitState(Enum):
    CLOSED = "closed"
    OPEN = "open"
    HALF_OPEN = "half_open"

class CircuitBreaker:
    """Circuit breaker pattern for integration calls."""
    
    def __init__(
        self,
        failure_threshold: int = 5,
        reset_timeout: timedelta = timedelta(seconds=30),
    ):
        self.state = CircuitState.CLOSED
        self.failure_count = 0
        self.failure_threshold = failure_threshold
        self.reset_timeout = reset_timeout
        self.last_failure_time = None
    
    async def execute(self, operation: Callable) -> Any:
        """Execute operation with circuit breaker protection."""
        
        if self.state == CircuitState.OPEN:
            if datetime.now() - self.last_failure_time > self.reset_timeout:
                self.state = CircuitState.HALF_OPEN
                logger.info("Circuit breaker transitioning to half-open")
            else:
                raise CircuitBreakerOpenError(
                    f"Circuit breaker is open. Next reset in {self.reset_timeout.total_seconds()}s"
                )
        
        try:
            result = await operation() if asyncio.iscoroutinefunction(operation) else operation()
            
            if self.state == CircuitState.HALF_OPEN:
                self.state = CircuitState.CLOSED
                self.failure_count = 0
                logger.info("Circuit breaker reset to closed")
            
            return result
            
        except Exception as e:
            self.failure_count += 1
            self.last_failure_time = datetime.now()
            
            if self.failure_count >= self.failure_threshold:
                self.state = CircuitState.OPEN
                logger.error(
                    "Circuit breaker opened",
                    failure_count=self.failure_count,
                    threshold=self.failure_threshold,
                    error=str(e),
                )
            
            raise
Graceful Degradation
from typing import Optional, Callable, Any
from functools import wraps

def graceful_degradation(fallback_value: Any = None, fallback_func: Optional[Callable] = None):
    """Decorator for graceful degradation when primary operation fails."""
    
    def decorator(func: Callable):
        @wraps(func)
        async def async_wrapper(*args, **kwargs):
            try:
                return await func(*args, **kwargs)
            except Exception as e:
                logger.warning(
                    "Primary operation failed, using graceful degradation",
                    func=func.__name__,
                    error=str(e),
                )
                
                if fallback_func:
                    return await fallback_func(*args, **kwargs) if asyncio.iscoroutinefunction(fallback_func) else fallback_func(*args, **kwargs)
                return fallback_value
        
        @wraps(func)
        def sync_wrapper(*args, **kwargs):
            try:
                return func(*args, **kwargs)
            except Exception as e:
                logger.warning(
                    "Primary operation failed, using graceful degradation",
                    func=func.__name__,
                    error=str(e),
                )
                
                if fallback_func:
                    return fallback_func(*args, **kwargs)
                return fallback_value
        
        return async_wrapper if asyncio.iscoroutinefunction(func) else sync_wrapper
    
    return decorator

Implementation Requirements

Logging Library Requirements
  1. REQ-100-051: MUST use structlog for all application logging
  2. REQ-100-052: MUST output JSON format in production environments
  3. REQ-100-053: MUST include correlation IDs in all log entries
  4. REQ-100-054: MUST configure log levels via environment variable LOG_LEVEL
  5. SHOULD use async log handlers for high-throughput scenarios
  6. SHOULD include source location (file, line) for DEBUG/TRACE levels
Exception Requirements
  1. REQ-100-055: MUST use exception hierarchy defined in this specification
  2. REQ-100-056: MUST include context dictionary in all custom exceptions
  3. REQ-100-057: MUST log exceptions at appropriate level (ERROR for unexpected, WARNING for expected)
  4. REQ-100-058: MUST preserve original exception chain using raise ... from ...
  5. SHOULD convert library exceptions to domain exceptions at boundary layers
Metrics Requirements
  1. MUST expose Prometheus metrics at /metrics endpoint (stated as REQ-100-022)
  2. REQ-100-059: MUST include component label in all metrics
  3. REQ-100-060: MUST track request duration for all external-facing operations
  4. SHOULD track business metrics relevant to domain operations
  5. SHOULD use histogram with appropriate buckets for latency metrics
Tracing Requirements
  1. REQ-100-061: MUST propagate trace context across all async/thread boundaries
  2. MUST include trace ID in all log entries when available (stated as REQ-100-017)
  3. SHOULD sample traces based on configurable sampling rate
  4. SHOULD include domain-specific attributes in spans
  5. MAY disable tracing in development environments for performance
Configuration

REQ-100-062: The system MUST read its observability configuration from the environment variables below, honouring the stated value domains and defaults (METRICS_PORT default 9090; TRACING_SAMPLE_RATE in 0.0-1.0, default 0.1):

Error Conditions

Error Categories

REQ-100-063: Every error MUST be classified into one of the categories below and carry an error code drawn from that category's code range: AUTH (1000-1099), AUTHZ (1100-1199), VAL (1200-1299), RES (1300-1399), INT (1400-1499), SYS (1500-1599), GOV (1600-1699).

Category Code Range Description Examples
AUTH 1000-1099 Authentication errors Invalid credentials, token expired
AUTHZ 1100-1199 Authorization errors Insufficient permissions, rate limit
VAL 1200-1299 Validation errors Invalid input, missing required field
RES 1300-1399 Resource errors Not found, conflict, unavailable
INT 1400-1499 Integration errors External service failure, timeout
SYS 1500-1599 System errors Internal error, bug, invariant violation
GOV 1600-1699 Governance errors Policy violation, escalation required
Specific Error Conditions

REQ-100-064: A minimum of 10 error conditions MUST be defined and handled; each condition below MUST be raised on its stated trigger, logged at its stated severity, and carry its stated log context.

  1. REQ-100-065: The system MUST handle ERR-001: Authentication Failed (AUTH-1001)
    Trigger: Invalid credentials or expired token
    Severity: ERROR
    Recovery: Re-authenticate with valid credentials
    Log Context: user_id, auth_method, reason

  2. REQ-100-066: The system MUST handle ERR-002: Rate Limit Exceeded (AUTHZ-1101)
    Trigger: Request rate exceeds configured limit
    Severity: WARNING
    Recovery: Wait for rate limit window to reset
    Log Context: user_id, endpoint, limit, window_sec

  3. REQ-100-067: The system MUST handle ERR-003: Invalid Input Validation (VAL-1201)
    Trigger: Request validation fails (missing fields, type mismatches)
    Severity: WARNING
    Recovery: Correct request payload
    Log Context: field, expected, actual, validation_rule

  4. REQ-100-068: The system MUST handle ERR-004: Resource Not Found (RES-1301)
    Trigger: Requested resource does not exist
    Severity: WARNING
    Recovery: Check resource identifier and retry
    Log Context: resource_type, resource_id, operation

  5. REQ-100-069: The system MUST handle ERR-005: Resource Conflict (RES-1302)
    Trigger: Resource already exists or version conflict
    Severity: WARNING
    Recovery: Use update instead of create, or resolve conflict
    Log Context: resource_type, resource_id, conflict_type

  6. REQ-100-070: The system MUST handle ERR-006: External Service Timeout (INT-1401)
    Trigger: External service does not respond within timeout
    Severity: ERROR
    Recovery: Retry with exponential backoff, implement circuit breaker
    Log Context: service, endpoint, timeout_ms, attempt

  7. REQ-100-071: The system MUST handle ERR-007: External Service Error (INT-1402)
    Trigger: External service returns error response
    Severity: ERROR
    Recovery: Validate request, check service status, retry if transient
    Log Context: service, endpoint, status_code, error_message

  8. REQ-100-072: The system MUST handle ERR-008: Internal System Error (SYS-1501)
    Trigger: Bug, invariant violation, or unexpected state
    Severity: CRITICAL
    Recovery: Requires developer intervention, system may be unstable
    Log Context: component, file, line, stack_trace, state

  9. REQ-100-073: The system MUST handle ERR-009: Configuration Error (SYS-1502)
    Trigger: Invalid or missing configuration
    Severity: ERROR
    Recovery: Update configuration file or environment variables
    Log Context: config_key, expected, actual, source

  10. REQ-100-074: The system MUST handle ERR-010: Logging Infrastructure Unavailable (INT-1403)
    Trigger: Log aggregation service unreachable
    Severity: WARNING
    Recovery: Buffer logs locally, retry periodically, degrade gracefully
    Log Context: log_service, endpoint, error, buffer_size

  11. REQ-100-075: The system MUST handle ERR-011: Trace Context Propagation Failed (SYS-1503)
    Trigger: Distributed trace context cannot be propagated
    Severity: WARNING
    Recovery: Generate new trace context, continue without parent trace
    Log Context: operation, carrier_type, error, new_trace_id

  12. REQ-100-076: The system MUST handle ERR-012: Metrics Collection Overload (SYS-1504)
    Trigger: Metrics collection causing performance degradation
    Severity: WARNING
    Recovery: Reduce metrics cardinality, increase collection interval
    Log Context: metric, cardinality, collection_interval, impact

Error Handling Requirements
  1. REQ-100-077: MUST log all errors with appropriate severity level
  2. REQ-100-078: MUST include error context for debugging
  3. REQ-100-079: MUST map exceptions to error categories
  4. REQ-100-080: MUST provide human-readable error messages
  5. SHOULD include recovery suggestions in error responses
  6. SHOULD track error rates per category for monitoring

Observability

Logging Observability

Logging forms the foundation of observability, providing structured, contextual data about system behavior. See Structured Logging section for log format requirements and Log Context Requirements for mandatory fields.

Metrics Observability

Metrics provide quantitative measurements of system performance and health. See Metrics Collection section for required metrics and Metrics Configuration for implementation details.

Tracing Observability

Distributed tracing enables end-to-end request flow analysis across component boundaries. See Distributed Tracing section for trace context propagation and span attributes.

Alerting and Monitoring

REQ-100-081: Observability data MUST be used for proactive alerting and monitoring, covering the alerts and thresholds below:

  1. Critical Error Alerts: Alert on error rate spikes (>5% error rate)
  2. Performance Alerts: Alert on latency degradation (>P95 threshold)
  3. Resource Alerts: Alert on memory/CPU/Disk usage (>80% utilization)
  4. Business Metric Alerts: Alert on key business metric anomalies
Observability Integration

REQ-100-082: All three pillars of observability (logs, metrics, traces) MUST be correlated by the mechanisms below:

Observability Quality Gates
  1. REQ-100-111: Log completeness: ≥99% of operations produce at least one log entry
  2. REQ-100-112: Metric freshness: Metrics updated at least every 15 seconds
  3. REQ-100-113: Trace sampling: ≥10% of requests sampled for traces in production
  4. REQ-100-114: Alert coverage: All critical failure modes have corresponding alerts
  5. REQ-100-115: Dashboard latency: Observability data available within 30 seconds of generation

API Contracts

Logging Configuration API

REQ-100-083: The system MUST expose GET /api/v1/logging/config returning the current logging configuration in the shape below, whose required fields are level, format, and component.

# GET /api/v1/logging/config
# Response: Current logging configuration
response:
  type: object
  required:
    - level
    - format
    - component
  properties:
    level:
      type: string
      enum: [TRACE, DEBUG, INFO, WARNING, ERROR, CRITICAL]
    format:
      type: string
      enum: [json, console]
    component:
      type: string
    filters:
      type: array
      items:
        type: string
    sampling_rate:
      type: number
      minimum: 0.0
      maximum: 1.0
Error Response API

REQ-100-084: All HTTP 4xx/5xx error responses MUST follow the contract below, whose required fields are error, message, and timestamp:

# HTTP 4xx/5xx Error Response
response:
  type: object
  required:
    - error
    - message
    - timestamp
  properties:
    error:
      type: string
      description: Error category/code
    message:
      type: string
      description: Human-readable error message
    timestamp:
      type: string
      format: date-time
    request_id:
      type: string
      description: Correlation ID for request
    trace_id:
      type: string
      description: Distributed trace identifier
    documentation_url:
      type: string
      format: uri
      description: URL to error documentation
    details:
      type: array
      items:
        type: object
        properties:
          field:
            type: string
          message:
            type: string
          code:
            type: string
Metrics Export API

REQ-100-085: The system MUST expose GET /metrics returning metrics in Prometheus exposition text format.

# GET /metrics
# Response: Prometheus metrics in text format
response:
  type: string
  format: prometheus-text
  description: Prometheus exposition format
Health Check API

REQ-100-086: The system MUST expose GET /health returning component health status in the shape below, whose required fields are status (one of healthy, degraded, unhealthy) and timestamp.

# GET /health
# Response: Component health status
response:
  type: object
  required:
    - status
    - timestamp
  properties:
    status:
      type: string
      enum: [healthy, degraded, unhealthy]
    timestamp:
      type: string
      format: date-time
    components:
      type: object
      additionalProperties:
        type: string
        enum: [healthy, degraded, unhealthy]
    version:
      type: string
    uptime_seconds:
      type: number
Contract Compliance Requirements
  1. REQ-100-087: MUST validate error responses against schema in test suites
  2. REQ-100-088: MUST document all logging configuration parameters
  3. MUST expose metrics endpoint at /metrics (stated as REQ-100-022)
  4. MUST expose health endpoint at /health (stated as REQ-100-042)
  5. SHOULD version APIs using path prefix (/api/v1/)
  6. SHOULD provide OpenAPI/Swagger documentation for all APIs

Testing Requirements

Unit Testing Requirements

REQ-100-089: The test suite MUST cover the unit-testing areas below: logging configuration, exception hierarchy, metrics collection, and tracing context.

  1. Logging Configuration Tests

    • Test all log levels produce appropriate output
    • Test JSON vs console format switching
    • Test log filtering by component and level
    • Test structured log field inclusion

  2. Exception Hierarchy Tests

    • Test exception inheritance relationships
    • Test context preservation in exceptions
    • Test error code mapping
    • Test exception serialization to dict

  3. Metrics Collection Tests

    • Test counter increment/decrement
    • Test histogram bucket distribution
    • Test gauge value updates
    • Test label consistency across metrics

  4. Tracing Context Tests

    • Test trace context propagation
    • Test span creation and attributes
    • Test parent-child span relationships
    • Test trace sampling behavior
Integration Testing Requirements

  1. Log Aggregation Integration

    • Test log delivery to aggregation service
    • Test log buffering during service outages
    • Test log format compatibility with aggregator
    • Test log volume and performance under load

  2. Metrics Integration

    • Test metrics scraping by Prometheus
    • Test metric label cardinality limits
    • Test long-running metric consistency
    • Test alert rule evaluation based on metrics

  3. Tracing Integration

    • Test trace export to tracing backend
    • Test trace sampling configuration
    • Test span attribute inclusion in traces
    • Test trace correlation with logs
Performance Testing Requirements

  1. Logging Performance

    • Measure log throughput (logs/sec)
    • Measure log latency impact on application
    • Measure memory usage of log buffering
    • Measure disk I/O for local log storage

  2. Metrics Performance

    • Measure metrics collection overhead
    • Measure memory usage per metric series
    • Measure scrape duration under high cardinality
    • Measure alert evaluation performance

  3. Tracing Performance

    • Measure span creation overhead
    • Measure trace export throughput
    • Measure memory usage of span buffers
    • Measure sampling impact on performance
Test Data Requirements

  1. Log Test Data

    • Generate synthetic log entries with varied contexts
    • Include edge cases (unicode, large payloads, special characters)
    • Include error conditions and stack traces
    • Include high-cardinality label combinations

  2. Metric Test Data

    • Generate time-series data with realistic patterns
    • Include spike, dip, and seasonal patterns
    • Include outlier values for histogram testing
    • Include label combinations at cardinality limits
Test Automation Requirements

  1. CI/CD Integration

    • Run logging tests on every commit
    • Run performance tests nightly
    • Run integration tests against staging environments
    • Generate test coverage reports for observability code

  2. Test Reporting

    • Report test results to monitoring system
    • Track test flakiness and reliability
    • Alert on test performance regressions
    • Generate compliance reports for audit purposes

Performance Benchmarks

Logging Performance Targets
Metric Target Measurement Method
Log throughput ≥10,000 logs/sec per component Load testing with synthetic log generation
Log latency ≤1ms P99 for local logging Microbenchmark with high-resolution timers
Memory overhead ≤1MB per 10,000 log entries Memory profiling during sustained logging
CPU overhead ≤5% CPU utilization at max throughput CPU profiling under load
Disk I/O ≤10 MB/sec write throughput I/O monitoring during log buffering
Metrics Performance Targets
Metric Target Measurement Method
Metric collection latency ≤10ms per metric update Microbenchmark of metric instrumentation
Metric export latency ≤100ms for full scrape Prometheus scrape duration measurement
Memory per metric series ≤1KB per unique time series Memory profiling with varying cardinality
Label cardinality limit ≤10,000 unique label combinations Stress testing with high-cardinality labels
Tracing Performance Targets
Metric Target Measurement Method
Span creation latency ≤100μs per span Microbenchmark of span creation
Trace export throughput ≥1,000 spans/sec Load testing with trace generation
Trace sampling overhead ≤1% CPU at 100% sampling CPU profiling with sampling disabled/enabled
Context propagation latency ≤10μs per propagation Microbenchmark of trace context operations
Error Handling Performance Targets
Metric Target Measurement Method
Exception creation ≤50μs per exception Microbenchmark of exception instantiation
Error logging latency ≤5ms P99 for error logging Load testing with error injection
Circuit breaker overhead ≤1ms per protected call Microbenchmark of circuit breaker execution
Retry mechanism overhead ≤2ms per retry attempt Microbenchmark of retry with backoff
Scalability Benchmarks
  1. Horizontal Scaling: System must maintain performance targets when scaled to 100 instances
  2. Load Increase: Performance degradation must be linear (not exponential) with load increase
  3. Memory Leak: Zero memory leak over 72-hour continuous operation
  4. GC Impact: Garbage collection pauses ≤100ms P99 for observability operations
Benchmark Validation Requirements
  1. MUST run performance benchmarks as part of CI/CD pipeline
  2. MUST track benchmark results over time for regression detection
  3. MUST alert on performance regression >10%
  4. SHOULD automate benchmark execution with reproducible environment
  5. SHOULD include real-world workload patterns in benchmarks

Examples

Example 1: Complete Log Entry
{
  "timestamp": "2026-04-10T14:30:45.123456Z",
  "level": "ERROR",
  "logger": "orchestrata.ultimate.orchestrator",
  "event": "Failed to process intent",
  "component": "orchestrator",
  "request_id": "req_abc123def456",
  "session_id": "sess_xyz789",
  "user_id": "user_987654",
  "trace_id": "trace_00f067aa0ba902b7",
  "span_id": "span_00f067aa0ba902b7",
  "duration_ms": 125.5,
  "status": "failure",
  "error": {
    "type": "IntegrationError",
    "message": "External service timeout",
    "stacktrace": "Traceback (most recent call last):\n  File \"orchestrator.py\", line 456, in process_intent\n    result = await external_service.call()\n  File \"external.py\", line 123, in call\n    raise TimeoutError(\"Service timeout after 5s\")\nIntegrationError: External service timeout"
  },
  "intent_id": "intent_12345",
  "agent_id": "agent_67890",
  "attempt": 3,
  "max_retries": 5
}
Example 2: Error Response
{
  "error": "INT-1401",
  "message": "External service timeout after 5 seconds",
  "timestamp": "2026-04-10T14:30:45.123456Z",
  "context": {
    "service": "payment_gateway",
    "endpoint": "/api/v1/process",
    "timeout_ms": 5000,
    "attempt": 3,
    "max_retries": 5
  },
  "trace_id": "trace_00f067aa0ba902b7",
  "request_id": "req_abc123def456",
  "code": "INT-1401",
  "documentation_url": "https://docs.orchestrata-ultimate.com/errors/INT-1401",
  "details": [
    {
      "field": "payment_gateway_endpoint",
      "message": "Service did not respond within timeout",
      "code": "TIMEOUT"
    }
  ]
}
Example 3: Structured Log Configuration
# config/logging_config.py
import structlog
from structlog.processors import JSONRenderer, TimeStamper
from structlog.stdlib import add_log_level, filter_by_level

def configure_logging(level: str = "INFO", json_output: bool = True):
    """Configure structured logging for the application."""
    
    processors = [
        filter_by_level,
        add_log_level,
        structlog.processors.StackInfoRenderer(),
        structlog.processors.format_exc_info,
        TimeStamper(fmt="iso"),
        structlog.processors.UnicodeDecoder(),
        structlog.processors.EventRenamer("event"),
    ]
    
    if json_output:
        processors.append(JSONRenderer())
    else:
        processors.append(structlog.dev.ConsoleRenderer())
    
    structlog.configure(
        processors=processors,
        wrapper_class=structlog.stdlib.BoundLogger,
        context_class=dict,
        logger_factory=structlog.stdlib.LoggerFactory(),
        cache_logger_on_first_use=True,
    )
    
    # Configure standard library logging
    import logging
    logging.basicConfig(level=getattr(logging, level.upper()))

# Usage
log = structlog.get_logger()
log.info("User authenticated", user_id="user_123", method="oauth2", success=True)
Example 4: Exception Usage
from exceptions import IntegrationError, TimeoutError, retry_with_backoff

async def process_payment(amount: float, currency: str) -> dict:
    """Process payment with retry and circuit breaker."""
    
    async def call_payment_gateway():
        # Simulate external service call
        response = await http_client.post(
            "https://api.payment.example/charge",
            json={"amount": amount, "currency": currency},
            timeout=5.0
        )
        if response.status_code >= 500:
            raise IntegrationError(
                "Payment gateway service error",
                context={
                    "status_code": response.status_code,
                    "service": "payment_gateway"
                }
            )
        return response.json()
    
    try:
        # Use retry with exponential backoff
        return await retry_with_backoff(
            call_payment_gateway,
            max_retries=3,
            initial_delay=0.1,
            retryable_errors=(TimeoutError, IntegrationError)
        )
    except IntegrationError as e:
        log.error("Payment processing failed", error=e.to_dict())
        raise
Example 5: Metrics Collection
from prometheus_client import Counter, Histogram, generate_latest

# Define metrics
REQUESTS_TOTAL = Counter(
    'orchestrata_requests_total',
    'Total number of requests',
    ['method', 'endpoint', 'status']
)

REQUEST_DURATION = Histogram(
    'orchestrata_request_duration_seconds',
    'Request duration in seconds',
    ['method', 'endpoint'],
    buckets=(0.01, 0.05, 0.1, 0.5, 1.0, 5.0)
)

# Instrument a function
import time
from functools import wraps

def instrument_request(method: str, endpoint: str):
    """Decorator to instrument request metrics."""
    def decorator(func):
        @wraps(func)
        async def wrapper(*args, **kwargs):
            start_time = time.time()
            try:
                result = await func(*args, **kwargs)
                status = "success"
                return result
            except Exception:
                status = "error"
                raise
            finally:
                duration = time.time() - start_time
                REQUEST_DURATION.labels(method=method, endpoint=endpoint).observe(duration)
                REQUESTS_TOTAL.labels(method=method, endpoint=endpoint, status=status).inc()
        return wrapper
    return decorator

# Usage
@instrument_request(method="POST", endpoint="/api/v1/payments")
async def create_payment(request):
    """Create payment endpoint."""
    # ... implementation
    pass

Compliance Requirements

GDPR/Privacy
Security
Performance

Dependencies

External Dependencies
Dependency Version Purpose License
structlog >=23.0.0 Structured logging framework MIT
opentelemetry-api >=1.25.0 Distributed tracing API Apache-2.0
opentelemetry-sdk >=1.25.0 Distributed tracing SDK Apache-2.0
prometheus-client >=0.20.0 Metrics collection and exposition Apache-2.0
python-json-logger >=2.0.0 JSON formatter for structlog BSD-2-Clause
uvloop >=0.19.0 Async event loop for performance (optional) MIT
Internal Dependencies
Component Spec ID Purpose
Configuration Manager SPEC-001 Logging configuration management
Service Discovery SPEC-003 Log aggregation service discovery
Authentication/Authorization SPEC-004 User context for audit logs
Monitoring Dashboard SPEC-012 Metrics visualization and alerting
Environmental Assumptions
  1. Log Storage: Centralized log aggregation service (Loki, ELK, Datadog) available
  2. Metrics Storage: Prometheus-compatible metrics storage available
  3. Tracing Backend: OpenTelemetry-compatible tracing backend (Jaeger, Tempo) available
  4. Network: All components can reach logging/metrics/tracing endpoints
  5. Clock Synchronization: NTP-synchronized clocks for accurate timestamps
  6. Disk Space: Sufficient disk space for local log buffering (default: 1GB)

Migration Plan

Phase 1: Foundation (Current)
Phase 2: Integration
Phase 3: Advanced Features
Phase 4: Optimization

References

  1. Structlog Documentation
  2. OpenTelemetry Python SDK
  3. Prometheus Client Library
  4. 12-Factor App: Logs
  5. Microservices Patterns: Observability
  6. Google SRE: Monitoring Distributed Systems

Definition of Done

Completion Criteria

The logging and exception handling implementation is considered DONE when all of the following criteria are met:

  1. Code Implementation

    • [ ] Exception hierarchy implemented as defined in spec
    • [ ] Structured logging with structlog configured
    • [ ] Distributed tracing with OpenTelemetry integrated
    • [ ] Metrics collection with Prometheus implemented
    • [ ] Error handling patterns (retry, circuit breaker, graceful degradation) implemented
    • [ ] Configuration via environment variables

  2. Testing

    • [ ] Unit test coverage ≥90% for observability modules
    • [ ] Integration tests with log aggregation service
    • [ ] Performance tests meeting throughput/latency targets
    • [ ] Error injection tests for resilience validation
    • [ ] Security tests for log data protection

  3. Documentation

    • [ ] API documentation for logging configuration
    • [ ] Developer guide for exception handling
    • [ ] Operations guide for monitoring and alerting
    • [ ] Troubleshooting guide for common issues
    • [ ] Compliance documentation for audit purposes

  4. Deployment

    • [ ] Log aggregation service deployed and configured
    • [ ] Metrics dashboard deployed with key metrics
    • [ ] Alerting rules configured for critical errors
    • [ ] Tracing backend deployed and integrated
    • [ ] Backup/retention policies implemented

  5. Quality Gates

    • [ ] All tests passing in CI/CD pipeline
    • [ ] Code review completed by at least 2 developers
    • [ ] Security review completed
    • [ ] Performance benchmarks meeting targets
    • [ ] Documentation reviewed by technical writer

  6. Operational Readiness

    • [ ] Monitoring dashboards verified
    • [ ] Alert notifications tested
    • [ ] Log retention and rotation verified
    • [ ] Disaster recovery procedures documented
    • [ ] Rollback procedures tested
Acceptance Criteria Verification
Criterion Verification Method Responsible Role
Exception hierarchy Unit tests, code review Developer
Structured logging Log analysis, integration tests QA Engineer
Distributed tracing Trace visualization, integration tests DevOps Engineer
Metrics collection Dashboard verification, scraping tests SRE
Error handling Error injection tests, resilience tests QA Engineer
Configuration Environment variable tests, deployment tests DevOps Engineer
Exit Criteria

The specification is considered COMPLETE when:

Revision History

Version Date Author Changes
1.0.0 2026-04-09 Mohamed Initial specification

Approval

Role Name Date Approval
Architect Mohamed 2026-04-09 ✅
QA Lead
Security
DevOps