Backend & APIs
AuraScore 81/100

SCADA Critical Alarm Dispatcher and Webhook Engine Specification

Design a high-availability alarm routing and webhook dispatch microservice for safety-critical SCADA environments.

Use this template when designing backend dispatch engines that process, debounce, prioritize, and fan out critical plant floor alarms to on-call engineers, paging systems, and safety dashboards. It guarantees deterministic delivery, prioritization, and failover routing.

Template

Role: Lead Industrial Reliability & Backend Engineer specializing in safety-critical SCADA systems, real-time message routing, and fault-tolerant dispatch architectures.

Context

  • Alarm Ingress Rate: Polling and receiving raw alarm states at {{scada_polling_interval_ms}}.
  • Priority Taxonomy: Alarm severity categorized across {{alarm_priority_tiers}}.
  • Network Boundary: Isolated industrial network topology adhering to {{plant_network_segmentation}}.
  • Delivery Retries: Webhook backoff configured using {{webhook_retry_backoff_model}}.
  • Poison & Failure Handling: Unroutable alarm state dispatched to {{dead_letter_target}}.

Task

Draft an exhaustive engineering specification for a mission-critical SCADA alarm dispatch engine that deduplicates raw alarm storms, enforces strict priority queuing, and reliably dispatches webhook notifications to downstream safety and paging systems without dropping safety-critical events.

Method

  1. Define the ingress parser that validates incoming SCADA alarm frames, timestamp integrity, and source station identifiers.
  2. Design the sliding-window debouncing and alarm-storm suppression algorithm to prevent notification flooding.
  3. Architect the multi-tiered priority queue infrastructure that ensures Tier-1 emergency alarms bypass all operational queues.
  4. Specify the worker pool execution model for webhook dispatches, including connection pooling, DNS caching, and timeout policies.
  5. Detail the circuit-breaker and dead-letter queue forwarding logic when downstream endpoints experience outages.
  6. Formulate mutual authentication, HMAC signature generation, and webhook security headers for outgoing requests.
  7. Define health checking, hot-standby failover mechanisms, and memory-safe backpressure throttling.

Constraints

  • MUST guarantee that safety-critical alarms are dispatched within 250 milliseconds of edge receipt.
  • MUST NOT discard unacknowledged alarms during failover across redundant instances.
  • Outbound webhook payloads must be signed using SHA-256 HMAC tokens.
  • Alarm storm suppression must dynamically throttle noisy sensors without dropping state change events.
  • Memory usage during sustained alarm floods must not exceed allocated process boundaries.

Output format

  1. Ingress & Storm Suppression Logic: Algorithm details, sliding-window pseudo-logic, and threshold configurations.
  2. Priority Queue & Worker Pool Architecture: Queue design, concurrency parameters, and latency bounds by tier.
  3. Webhook Delivery Specification: Payload schema, HMAC signature headers, HTTP status handling, and retry timeline.
  4. Network Isolation & Security Spec: Gateway traversal, mTLS configuration, and egress firewall rules for {{plant_network_segmentation}}.
  5. Failover & Dead-Letter Handling: Active-passive failover state machine, replay runbook, and {{dead_letter_target}} alerting.

Self-review

  • Confirm that the priority queuing mechanism completely prevents starvation of highest {{alarm_priority_tiers}}.
  • Verify that retry backoff curves precisely match {{webhook_retry_backoff_model}} specifications.
  • Ensure that all network paths respect the physical zoning defined in {{plant_network_segmentation}}.
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

developers
developers-backend-apis
manufacturing-industrial
scada
alarms
webhooks