Advanced Notification Orchestration¶

The Advanced Notifications module provides a comprehensive notification orchestration framework encompassing content-based routing, deduplication, rate limiting, and multi-level escalation policies. This document presents the theoretical foundations, algorithmic formulations, and practical implementation guidelines that underpin enterprise-scale notification management.

1. Introduction¶

1.1 Problem Statement¶

Contemporary data quality monitoring systems are observed to generate substantial volumes of alerts during routine operation. In the absence of appropriate orchestration mechanisms, organizations are subjected to a number of well-documented operational challenges:

Challenge	Impact
Alert Fatigue	Operators become desensitized to frequent notifications
Duplicate Notifications	Same issue triggers multiple redundant alerts
Notification Storms	Cascading failures overwhelm communication channels
Delayed Escalation	Critical issues not escalated to appropriate personnel

1.2 Solution Architecture¶

The aforementioned challenges are addressed through the provision of four complementary subsystems, each of which is supported by a corresponding module within the truthound library's checkpoint infrastructure:

Component	Truthound Module	Purpose
Routing	`truthound.checkpoint.routing`	Content-based notification distribution
Deduplication	`truthound.checkpoint.deduplication`	Duplicate suppression via fingerprinting
Throttling	`truthound.checkpoint.throttling`	Rate limiting via token bucket algorithms
Escalation	`truthound.checkpoint.escalation`	Progressive notification with state machine

1.3 Processing Pipeline¶

┌─────────────────────────────────────────────────────────────────────┐
│                  Notification Processing Pipeline                    │
├─────────────────────────────────────────────────────────────────────┤
│                                                                      │
│  ┌──────────────┐                                                   │
│  │    Event     │  ValidationFailedEvent, DriftDetectedEvent,       │
│  │   Trigger    │  ScheduleFailedEvent, SchemaChangedEvent          │
│  └──────┬───────┘                                                   │
│         │                                                            │
│         ▼                                                            │
│  ┌─────────────────────────────────────────────────────────────┐    │
│  │           TruthoundNotificationAdapter                       │    │
│  │  ┌────────────┐  ┌─────────────┐  ┌────────────┐            │    │
│  │  │  Routing   │→ │Deduplication│→ │ Throttling │            │    │
│  │  │(ActionRouter│  │(Fingerprint)│  │(TokenBucket)│           │    │
│  │  └────────────┘  └─────────────┘  └────────────┘            │    │
│  └─────────────────────────┬───────────────────────────────────┘    │
│                            │                                         │
│                            ▼                                         │
│  ┌─────────────────────────────────────────────────────────────┐    │
│  │              Channel Delivery Layer                          │    │
│  │  ┌──────┐ ┌───────┐ ┌───────┐ ┌─────────┐ ┌────────┐       │    │
│  │  │Slack │ │ Email │ │ Teams │ │PagerDuty│ │Webhook │       │    │
│  │  └──────┘ └───────┘ └───────┘ └─────────┘ └────────┘       │    │
│  └─────────────────────────┬───────────────────────────────────┘    │
│                            │                                         │
│                            ▼                                         │
│  ┌─────────────────────────────────────────────────────────────┐    │
│  │         Escalation Engine (State Machine)                    │    │
│  │  PENDING → ACTIVE → ESCALATING → ACKNOWLEDGED → RESOLVED    │    │
│  └─────────────────────────────────────────────────────────────┘    │
│                                                                      │
└─────────────────────────────────────────────────────────────────────┘

2. Routing Engine Architecture¶

2.1 Theoretical Foundation¶

Content-based routing (CBR) is a well-established message distribution paradigm in which routing decisions are determined by the content of messages rather than by predetermined destination addresses. The truthound routing engine implements a rule-based CBR system that is characterized by the following properties:

Declarative Rules: Routing rules are specified as predicates evaluated over event attributes
Priority-Ordered Evaluation: Rules are evaluated in strict priority order to ensure deterministic behavior
Composable Conditions: Rules may be combined through the application of standard logical operators

2.2 Rule Taxonomy¶

The truthound ActionRouter provides 11 built-in rule types and 3 combinators, which are enumerated below.

2.2.1 Primitive Rules¶

Rule Type	Parameters	Matching Logic
`AlwaysRule`	None	Always matches (default route)
`NeverRule`	None	Never matches (disabled route)
`SeverityRule`	`min_severity`, `max_severity`, `min_count`	Matches issues by severity level
`IssueCountRule`	`min_issues`, `max_issues`, `count_type`	Matches by issue count threshold
`StatusRule`	`statuses`, `negate`	Matches by checkpoint status
`TagRule`	`tags`, `match_all`, `negate`	Matches by resource tags
`DataAssetRule`	`pattern`, `is_regex`, `case_sensitive`	Matches by data asset name pattern
`MetadataRule`	`key_path`, `expected_value`, `comparator`	Matches by metadata values
`TimeWindowRule`	`start_time`, `end_time`, `days_of_week`, `timezone`	Matches by time period
`PassRateRule`	`min_rate`, `max_rate`	Matches by validation pass rate
`ErrorRule`	`pattern`, `negate`	Matches by error message pattern

2.2.2 Logical Combinators¶

Combinator	Semantics	Example Use Case
`AllOf`	Logical conjunction (AND)	Critical AND Production
`AnyOf`	Logical disjunction (OR)	Critical OR Error
`NotRule`	Logical negation (NOT)	NOT Development environment

2.3 Evaluation Modes¶

The ActionRouter supports three distinct evaluation modes, each of which is suited to particular operational requirements:

Mode	Behavior	Use Case
`FIRST_MATCH`	Execute only the first matching route	Mutually exclusive channels
`ALL_MATCHES`	Execute all matching routes	Multi-channel broadcast
`PRIORITY_GROUP`	Execute all routes in the highest priority group	Tiered response

2.4 Route Context Specification¶

The RouteContext data class encapsulates the complete set of attributes that are made available for rule evaluation:

@dataclass(frozen=True)
class RouteContext:
    checkpoint_name: str      # Checkpoint identifier
    run_id: str               # Execution run identifier
    status: str               # Result status (success, failure, error)
    data_asset: str           # Data asset name
    run_time: datetime        # Execution timestamp
    total_issues: int         # Total issue count
    critical_issues: int      # Critical severity count
    high_issues: int          # High severity count
    medium_issues: int        # Medium severity count
    low_issues: int           # Low severity count
    info_issues: int          # Info severity count
    pass_rate: float          # Validation pass rate (0-100)
    tags: dict[str, str]      # Resource tags
    metadata: dict[str, Any]  # Additional metadata
    validation_duration_ms: float  # Execution duration
    error: str | None         # Error message if applicable

2.5 Implementation Guidelines¶

Principles for Effective Route Construction¶

Specificity Principle: It is recommended that more specific rules be assigned lower priority numbers to ensure preferential evaluation
Default Route Provision: A catch-all route configured with AlwaysRule should always be included to guarantee notification delivery
Pre-Deployment Validation: Rules should be validated using the /notifications/routing/rules/test endpoint prior to production deployment

Example Configuration¶

routes:
  - name: critical_production
    priority: 10
    rule:
      type: all_of
      rules:
        - type: severity
          min_severity: critical
        - type: tag
          tags: { env: production }
    actions:
      - pagerduty_channel_id
      - slack_critical_channel_id

  - name: high_severity_alerts
    priority: 50
    rule:
      type: severity
      min_severity: high
    actions:
      - slack_alerts_channel_id

  - name: default_route
    priority: 100
    rule:
      type: always
    actions:
      - email_team_channel_id

3. Deduplication Engine Architecture¶

3.1 Theoretical Foundation¶

Notification deduplication is concerned with the elimination of redundant alert generation. The approach employed herein is based on fingerprint-based duplicate detection within sliding time windows. This technique is analogous to content-addressable storage systems and bears similarity to bloom filter applications that have been widely studied in the context of distributed systems.

3.1.1 Fingerprint Generation¶

A notification fingerprint is defined as a unique identifier derived from a specified subset of notification attributes:

fingerprint = hash(checkpoint_name || action_type || severity || data_asset)

The fingerprint function is required to satisfy the following properties: - Determinism: Identical inputs must produce identical outputs across all invocations - Collision Resistance: Distinct notifications should yield distinct fingerprints with high probability - Computational Efficiency: Generation must be achievable in O(1) time complexity

3.2 Deduplication Policies¶

The truthound NotificationDeduplicator supports five policies, arranged in order of increasing specificity:

Policy	Fingerprint Components	Use Case
`NONE`	Disabled	No deduplication
`BASIC`	checkpoint_name + action_type	Suppress same alert to same channel
`SEVERITY`	BASIC + severity	Differentiate by severity level
`ISSUE_BASED`	SEVERITY + issue_types	Differentiate by issue categories
`STRICT`	Full notification hash	Maximum differentiation

3.3 Windowing Strategies¶

Four time-based windowing strategies are provided, each of which exhibits distinct temporal characteristics.

3.3.1 Sliding Window Strategy¶

The sliding window approach maintains a fixed-duration window that advances continuously with time:

Time: ─────────────────────────────────────────────►
      │◄──── Window (5 min) ────►│
      │                          │
      │  Notification A          │  Notification B (duplicate)
      │  t=0                     │  t=2 min → SUPPRESSED
      │                          │

Characteristics: - The window is initiated from each notification event - The implementation is straightforward in nature - Memory consumption is considered efficient

3.3.2 Tumbling Window Strategy¶

This strategy employs non-overlapping fixed-duration buckets:

Time: ─────────────────────────────────────────────►
      │◄── Bucket 1 ──►│◄── Bucket 2 ──►│
      │   15 minutes    │   15 minutes    │
      │                 │                 │
      │  A (allowed)    │  A (allowed)    │
      │  A (suppressed) │                 │

Characteristics: - Bucket boundaries are fixed and predetermined - Suppression behavior is predictable and deterministic - Potential edge effects may be observed at bucket boundaries

3.3.3 Session Window Strategy¶

This approach employs event-driven sessions with gap-based expiration semantics:

Time: ─────────────────────────────────────────────►
      │◄─ Session 1 ─►│  gap  │◄─ Session 2 ─►│
      │               │ >10min │               │
      │ A B C         │        │ A             │
      │ (A,B,C dedup) │        │ (new session) │

Characteristics: - Window duration is dynamically determined based on notification activity - This strategy is particularly well-suited to bursty notification patterns - Elevated memory consumption may be observed relative to other strategies

3.4 Implementation Guidelines¶

Configuration Parameters¶

Parameter	Recommended Value	Rationale
Window Duration	300 seconds (5 min)	Balances suppression vs. visibility
Policy	`SEVERITY`	Good balance of differentiation
Strategy	`sliding`	Simplest, most predictable behavior

Observational Metrics¶

Metric	Formula	Target Range
Suppression Ratio	suppressed / total_evaluated	10-40%
Active Fingerprints	Count of active entries	< 1000

4. Throttling Engine Architecture¶

4.1 Theoretical Foundation¶

Rate limiting constitutes a fundamental technique for the protection of systems against overload conditions. The truthound throttling engine implements the Token Bucket Algorithm, a well-established approach that has been extensively studied and deployed in the domains of network traffic shaping and API rate limiting.

4.1.1 Token Bucket Algorithm¶

The token bucket model maintains a bucket with a maximum capacity of B tokens. Tokens are replenished at a rate of r tokens per second. Each notification consumes exactly one token upon processing. In the event that no tokens are available, the notification is subjected to throttling.

Mathematical Formulation:

tokens(t) = min(B, tokens(t-1) + r × Δt)

Where: - B = burst capacity - r = token replenishment rate - Δt = time elapsed since the last state update

Algorithmic Behavior:

Tokens: ████████████ (12 tokens, capacity)
        ─────────────────────────────────────►
        │ Request │ Request │ Request │ ...
        │ 12→11   │ 11→10   │ 10→9    │
        │         │         │ +0.5/sec │  (replenishment)

4.2 Throttler Implementations¶

Five throttler implementations are provided within the truthound library, each based on a distinct algorithmic approach:

Throttler	Algorithm	Characteristics
`TokenBucketThrottler`	Token Bucket	Allows burst, smooth rate limiting
`SlidingWindowThrottler`	Sliding Window	More accurate, no boundary effects
`FixedWindowThrottler`	Fixed Window	Simple, potential 2x burst at boundaries
`CompositeThrottler`	Multi-level	Combines multiple rate limits
`NoOpThrottler`	Pass-through	Testing/disable mode

4.3 Rate Limit Scopes¶

Rate limits may be applied at varying levels of granularity, as enumerated in the following table:

Scope	Bucket Key	Use Case
`GLOBAL`	Single bucket	Total notification limit
`PER_ACTION`	action_type	Per-channel limits
`PER_CHECKPOINT`	checkpoint_name	Per-source limits
`PER_ACTION_CHECKPOINT`	action + checkpoint	Fine-grained control
`PER_SEVERITY`	severity	Severity-based limits
`PER_DATA_ASSET`	data_asset	Asset-specific limits

4.4 Hierarchical Multi-Level Rate Limiting¶

The CompositeThrottler facilitates the construction of hierarchical rate limit configurations:

throttling:
  per_minute_limit: 10    # Short-term burst control
  per_hour_limit: 100     # Medium-term control
  per_day_limit: 500      # Long-term budget
  burst_multiplier: 1.5   # 50% burst allowance

Evaluation Logic:

Request arrives
  │
  ├─► Check per_minute limit
  │     │
  │     ├─► PASS → Check per_hour limit
  │     │           │
  │     │           ├─► PASS → Check per_day limit
  │     │           │           │
  │     │           │           ├─► PASS → ALLOWED
  │     │           │           └─► FAIL → THROTTLED
  │     │           └─► FAIL → THROTTLED
  │     └─► FAIL → THROTTLED

4.5 Implementation Guidelines¶

Recommended Configuration Parameters¶

Channel Type	per_minute	per_hour	per_day	Rationale
PagerDuty	5	20	100	On-call fatigue prevention
Slack	20	200	1000	Chat noise reduction
Email	5	50	200	Inbox management

Priority Bypass Mechanism¶

It is possible to configure critical notifications to bypass throttling constraints entirely:

priority_bypass: true
priority_threshold: critical

When this mechanism is enabled, notifications bearing severity=critical are permitted to bypass all rate limits.

5. Escalation Engine Architecture¶

5.1 Theoretical Foundation¶

Escalation management is implemented through a Finite State Machine (FSM) that governs the lifecycle of incident tracking. This approach is derived from established incident management frameworks, including ITIL, as well as contemporary Site Reliability Engineering (SRE) practices.

5.1.1 Formal State Machine Definition¶

The escalation state machine is formally defined as follows:

FSM = (S, Σ, δ, s₀, F)

Where:
  S = {PENDING, ACTIVE, ESCALATING, ACKNOWLEDGED, RESOLVED, CANCELLED, TIMED_OUT, FAILED}
  Σ = {start, ack, resolve, cancel, timeout, escalate, error}
  s₀ = PENDING
  F = {RESOLVED, CANCELLED, TIMED_OUT, FAILED}

5.1.2 State Transition Diagram¶

                    ┌─────────────────────────┐
                    │        PENDING          │
                    └────────────┬────────────┘
                                 │ start()
                                 ▼
        ┌───────────────────────────────────────────────┐
        │                    ACTIVE                     │
        └────┬─────────────┬────────────────┬───────────┘
             │             │                │
             │ ack()       │ timeout        │ escalate()
             ▼             ▼                ▼
    ┌────────────┐  ┌────────────┐  ┌────────────────┐
    │ACKNOWLEDGED│  │ TIMED_OUT  │  │   ESCALATING   │
    └──────┬─────┘  └────────────┘  └───────┬────────┘
           │                                │
           │ resolve()                      │ next_level
           ▼                                ▼
    ┌────────────┐                  ┌────────────────┐
    │  RESOLVED  │                  │     ACTIVE     │
    └────────────┘                  │ (next level)   │
                                    └────────────────┘

        cancel() from any state → CANCELLED
        error from any state → FAILED

5.2 Escalation Level Configuration¶

Each escalation level is defined by the following parameter set:

Parameter	Type	Description
`level`	int	Level number (1 = first)
`delay_minutes`	int	Delay before escalating to next level
`targets`	list[EscalationTarget]	Notification recipients
`repeat_count`	int	Number of times to repeat at this level
`repeat_interval_minutes`	int	Interval between repeats
`require_ack`	bool	Whether acknowledgment is required
`auto_resolve_minutes`	int	Auto-resolve timeout (0 = disabled)

5.3 Target Type Classification¶

Escalation targets represent the notification recipients to which alerts are dispatched:

Target Type	Identifier Format	Description
`user`	User ID	Individual user
`team`	Team ID	Team/group
`channel`	Channel ID	Slack channel, etc.
`schedule`	Schedule ID	On-call schedule
`webhook`	URL	Webhook endpoint
`email`	Email address	Direct email
`phone`	Phone number	SMS/voice call

5.4 Trigger Condition Taxonomy¶

Escalation may be initiated by a variety of conditions, which are categorized as follows:

Trigger	Description
`UNACKNOWLEDGED`	Alert not acknowledged within timeout
`UNRESOLVED`	Incident not resolved within timeout
`SEVERITY_UPGRADE`	Severity level increased
`REPEATED_FAILURE`	Same issue recurring
`THRESHOLD_BREACH`	Metric exceeded threshold
`MANUAL`	Manual trigger by operator
`SCHEDULED`	Time-based trigger

5.5 Automated Escalation by Event Severity¶

The NotificationDispatcher is configured to automatically initiate escalation procedures for events of elevated severity:

Event Type	Condition	Escalation Policy
`ValidationFailedEvent`	`has_critical=true`	`critical_alert`
`ValidationFailedEvent`	`has_high=true`	`high_alert`
`DriftDetectedEvent`	`has_high_drift=true`	`high_alert`
`ScheduleFailedEvent`	Always	`high_alert`
`SchemaChangedEvent`	`has_breaking_changes=true`	`high_alert`

5.6 Implementation Guidelines¶

Principles for Escalation Policy Design¶

Principle	Recommendation
Level Count	3-4 levels typically sufficient
Timeout Progression	Exponential backoff (5min → 15min → 30min)
Final Level	Must reach decision makers
Acknowledgment	Require ack at all levels

Example Policy Configuration¶

escalation_policies:
  - name: critical_production
    description: Critical production issue escalation
    levels:
      - level: 1
        delay_minutes: 0
        targets:
          - type: user
            identifier: team-lead
            name: Team Lead
          - type: channel
            identifier: "#alerts-critical"
            name: Critical Alerts
        repeat_count: 2
        repeat_interval_minutes: 5
        require_ack: true

      - level: 2
        delay_minutes: 15
        targets:
          - type: user
            identifier: engineering-manager
            name: Engineering Manager
          - type: schedule
            identifier: primary-oncall
            name: Primary On-call

      - level: 3
        delay_minutes: 30
        targets:
          - type: user
            identifier: director
            name: Director of Engineering
          - type: email
            identifier: leadership@company.com
            name: Leadership Team

    triggers:
      - unacknowledged
    severity_filter:
      - critical
      - high
    cooldown_minutes: 60
    max_escalations: 5

6. Notification Channel Integration¶

6.1 Supported Channels¶

The dashboard is integrated with the following notification action implementations provided by the truthound library:

Channel	Truthound Action	Protocol
Slack	`SlackNotification`	Incoming Webhook
Email	`EmailNotification`	SMTP/SendGrid/SES
Microsoft Teams	`TeamsNotification`	Adaptive Cards
Discord	`DiscordNotification`	Embed Webhook
Telegram	`TelegramNotification`	Bot API
PagerDuty	`PagerDutyAction`	Events API v2
OpsGenie	`OpsGenieAction`	REST API
Webhook	`WebhookAction`	HTTP POST
GitHub	`GitHubAction`	Issues API

6.2 Channel Configuration Specifications¶

Each channel type is associated with specific configuration requirements, as detailed below.

Slack Configuration¶

Parameter	Required	Description
`webhook_url`	Yes	Slack Incoming Webhook URL
`channel`	No	Channel override (#channel)
`username`	No	Bot display name
`icon_emoji`	No	Bot icon (:emoji:)
`mention_on_failure`	No	User IDs to mention

Email Configuration¶

Parameter	Required	Description
`from_address`	Yes	Sender email address
`to_addresses`	Yes	Recipient email addresses
`smtp_host`	Conditional	SMTP server (if provider=smtp)
`provider`	No	smtp, sendgrid, or ses
`api_key`	Conditional	API key (if provider=sendgrid/ses)

7. Statistical Monitoring and Observability¶

7.1 Metric Categories¶

The Advanced Notifications system exposes two distinct categories of operational metrics:

Category	Source	Description
Dashboard Stats	SQLite Database	Configuration counts
Runtime Stats	Truthound Library	Processing metrics

7.2 Key Performance Indicators¶

KPI	Formula	Target	Action if Exceeded
Dedup Ratio	suppressed / evaluated	10-40%	Review fingerprint strategy
Throttle Rate	throttled / checked	< 10%	Increase rate limits
Ack Rate	acknowledged / triggered	> 80%	Review escalation timeouts
MTTA	avg(ack_time - trigger_time)	< 15 min	Review escalation targets
MTTR	avg(resolve_time - trigger_time)	< 60 min	Review resolution process

7.3 Statistics API¶

GET /notifications/advanced/stats

Response:

{
  "routing": {
    "total_routes": 12,
    "mode": "all_matches"
  },
  "deduplication": {
    "total_evaluated": 1250,
    "suppressed": 340,
    "suppression_ratio": 0.272,
    "active_fingerprints": 45
  },
  "throttling": {
    "total_checked": 1250,
    "total_allowed": 1150,
    "total_throttled": 100,
    "throttle_rate": 0.08
  },
  "escalation": {
    "total_escalations": 23,
    "active_escalations": 2,
    "acknowledged_count": 18,
    "resolved_count": 15,
    "acknowledgment_rate": 0.78,
    "avg_time_to_acknowledge": 420
  }
}

8. Configuration Management¶

8.1 Configuration Export¶

All Advanced Notification configurations may be exported via the following endpoint:

GET /notifications/config/export?include_routing_rules=true&include_deduplication=true&include_throttling=true&include_escalation=true

8.2 Configuration Import¶

Configurations may be imported with configurable conflict resolution semantics:

POST /notifications/config/import
Content-Type: application/json

{
  "bundle": { ... },
  "conflict_resolution": "skip" | "overwrite" | "rename"
}

8.3 Configuration Bundle Schema¶

{
  "version": "1.0",
  "exported_at": "2025-01-29T12:00:00Z",
  "routing_rules": [...],
  "deduplication_configs": [...],
  "throttling_configs": [...],
  "escalation_policies": [...]
}

9. Template Library¶

The Template Library constitutes a curated registry of pre-built notification configurations, thereby enabling the rapid deployment of proven orchestration patterns without the necessity for manual parameter tuning.

9.1 Overview¶

Each template encapsulates a complete configuration for one of the four notification subsystems. Templates are organized by their target subsystem and are annotated with descriptive metadata to facilitate efficient discovery.

Attribute	Description
Name	Human-readable template identifier
Category	Target subsystem (routing, deduplication, throttling, escalation)
Description	Functional summary of the template's purpose
Tags	Searchable keywords for discovery
Configuration	Pre-defined parameter values for the target subsystem

9.2 Available Template Categories¶

Category	Purpose	Example Templates
Routing	Content-based notification distribution rules	Severity-based routing, source-type routing
Deduplication	Duplicate suppression configurations	Aggressive dedup, conservative dedup
Throttling	Rate limiting presets	Burst-friendly throttle, strict rate limit
Escalation	Multi-level alert policies	On-call escalation, business-hours policy

9.3 Template Selection Workflow¶

The Template Library implements an integrated workflow that bridges template selection with configuration editing. The process is conducted as follows:

Browse and Search: The Template Library panel is opened to browse available templates. The search field or category tabs may be employed to locate a relevant template.
Preview: The template's description, tags, and configuration summary are reviewed prior to selection.
Apply: A template is selected to initiate the application process. The system performs the following actions automatically:
Tab Navigation: The active tab is switched to the subsystem matching the template's category (e.g., selecting a throttling template activates the Throttling tab).
Dialog Auto-Open: The corresponding configuration dialog is opened with the template's pre-filled values, thereby allowing the user to review and adjust parameters before saving.
Quick Templates Hidden: When a template is applied from the Template Library, the in-dialog Quick Templates selector is hidden to avoid confusion between the externally applied template and the dialog's built-in presets.
Save or Discard: The pre-filled values may be modified and saved, or the dialog may be closed to discard the template application.

9.4 Active Template Indicator¶

When a template has been actively applied, the Template Library panel displays an indicator banner comprising the following elements:

Element	Description
Category Icon	Visual icon corresponding to the template's subsystem
Template Name	Name of the currently applied template
Category Badge	Labeled badge showing the target subsystem
Dismiss Button	Allows the user to clear the active template selection

This indicator persists for the duration of the current page session. Navigation away from the Advanced Notifications page results in the clearance of the active template state, as templates are designed to serve as ephemeral configuration aids rather than persistent selections.

9.5 Relationship to Quick Templates¶

Each tab's configuration dialog also provides an independent Quick Templates selector for rapid in-context configuration. The Template Library and Quick Templates serve complementary roles, as delineated below:

Feature	Template Library	Quick Templates
Scope	Cross-subsystem, centralized	Per-subsystem, contextual
Access	From the page header	Within each configuration dialog
Behavior	Switches tab + opens dialog	Fills form within current dialog
Visibility	Always visible	Hidden when Template Library applies a template

10. API Reference¶

10.1 Routing Rules API¶

Endpoint	Method	Description
`/notifications/routing/rules`	GET	List routing rules
`/notifications/routing/rules`	POST	Create routing rule
`/notifications/routing/rules/{id}`	GET	Get routing rule
`/notifications/routing/rules/{id}`	PUT	Update routing rule
`/notifications/routing/rules/{id}`	DELETE	Delete routing rule
`/notifications/routing/rules/types`	GET	List available rule types
`/notifications/routing/rules/test`	POST	Test rule against context

10.2 Deduplication API¶

Endpoint	Method	Description
`/notifications/deduplication/configs`	GET	List configs
`/notifications/deduplication/configs`	POST	Create config
`/notifications/deduplication/configs/{id}`	GET	Get config
`/notifications/deduplication/configs/{id}`	PUT	Update config
`/notifications/deduplication/configs/{id}`	DELETE	Delete config
`/notifications/deduplication/stats`	GET	Get runtime stats

10.3 Throttling API¶

Endpoint	Method	Description
`/notifications/throttling/configs`	GET	List configs
`/notifications/throttling/configs`	POST	Create config
`/notifications/throttling/configs/{id}`	GET	Get config
`/notifications/throttling/configs/{id}`	PUT	Update config
`/notifications/throttling/configs/{id}`	DELETE	Delete config
`/notifications/throttling/stats`	GET	Get runtime stats

10.4 Escalation API¶

Endpoint	Method	Description
`/notifications/escalation/policies`	GET	List policies
`/notifications/escalation/policies`	POST	Create policy
`/notifications/escalation/policies/{id}`	GET	Get policy
`/notifications/escalation/policies/{id}`	PUT	Update policy
`/notifications/escalation/policies/{id}`	DELETE	Delete policy
`/notifications/escalation/incidents`	GET	List incidents
`/notifications/escalation/incidents/active`	GET	List active incidents
`/notifications/escalation/incidents/{id}`	GET	Get incident
`/notifications/escalation/incidents/{id}/acknowledge`	POST	Acknowledge incident
`/notifications/escalation/incidents/{id}/resolve`	POST	Resolve incident
`/notifications/escalation/stats`	GET	Get runtime stats

11. Recommended Operational Practices¶

11.1 Routing Practices¶

Practice	Description
Prioritize specificity in rule ordering	Lower priority numbers should be assigned to more specific conditions
Ensure provision of a default route	All notifications must be guaranteed a destination
Conduct pre-deployment validation	The test endpoint should be utilized to validate rules prior to deployment
Maintain comprehensive documentation	Routing logic should be documented for team reference and auditability

11.2 Deduplication Practices¶

Practice	Description
Commence with moderate window durations	A 5-minute default is recommended, with subsequent adjustment based on observed data
Monitor the suppression ratio	A ratio of 10-40% is indicative of healthy deduplication behavior
Employ the SEVERITY policy	This policy provides an appropriate balance between deduplication and visibility
Review active fingerprint counts	Elevated counts may be indicative of memory pressure

11.3 Throttling Practices¶

Practice	Description
Establish conservative initial limits	It is considered preferable to relax constraints than to tighten them retrospectively
Configure per-channel limits	Channels of differing urgency levels necessitate distinct limit configurations
Enable the priority bypass mechanism	Critical alerts should not be subjected to throttling
Monitor the throttle rate	A rate exceeding 10% may be indicative of configuration deficiencies

11.4 Escalation Practices¶

Practice	Description
Design for progressive urgency	Subsequent levels should be configured to reach personnel of higher authority
Employ reasonable timeout intervals	A progression of 5-15-30 minutes has been found to be effective in practice
Mandate acknowledgment at all levels	This ensures that human operators remain engaged in the resolution process
Conduct periodic escalation path testing	Regular testing is essential to verify continued operational functionality
Configure appropriate cooldown periods	Cooldowns are necessary to prevent the occurrence of escalation storms

References¶

Beyer, B., et al. (2016). Site Reliability Engineering. O'Reilly Media.
Turner, J. (1986). New directions in communications (or which way to the information age?). IEEE Communications Magazine, 24(10), 8-15. [Token Bucket Algorithm]
ITIL Foundation (2019). ITIL 4 Foundation. Axelos.
truthound Documentation. https://truthound.readthedocs.io/