A major midstream operator needed to modernize monitoring across hundreds of remote pipeline stations while maintaining 24/7 operations. Legacy RTUs required expensive middleware, limited data collection, and provided no local intelligence.
EdgeConnect at each station (300+ sites) on CISCO routers
EdgeConnect deployed in Cisco IR1101 routers (reduced hardware footprint)
Store-and-forward for satellite communication resilience
UNS architecture with Sparkplug B for auto-discovery
Component | Specification | Quantity |
|---|---|---|
Edge Nodes | EdgeConnect in Cisco routers | 300+ |
Protocols | Modbus RTU, DNP3, HART | Multiple |
Data Points | 50-200 per site | 500,000 total |
Update Rate | 10 seconds | Optimized |
Redundancy | Store-and-forward, dual path | All sites |
Direct PLC/RTU communication (Modbus, DNP3)
MQTT Sparkplug B publication to regional/central
Field Level: Sensors → PLCs/RTUs → EdgeConnect
Edge UNS: Local namespace definition, context added
Network: Process and manage data in the broker
75-80% reduction in operational costs
Zero middleware licensing fees
100% uptime during satellite outages (store-and-forward)
60% reduction in alarm flooding
Sub-second local response times
Automatic configuration deployment to new sites
Native integration with existing SCADA without replacement
Deployment Time for Phase 1: 8-12 weeks for 50 sites
Current Stage: 300+ sites
Required Products: EdgeConnect ($750/site), Enterprise Unlimited ($11,900), DataHub Station ($2,000 x 6)
Total Architecture Cost: ~$250,000 for complete 300-site system
Challenge: Operate and observe hundreds of distributed midstream sites with PLCs and intermittent, bandwidth-limited links—while keeping on-site autonomy and ensuring a unified, secure, and scalable publish/subscribe model for corporate operations, analytics, and alarms.
Specific pain points:
Multiprotocol collection (ControlLogix + DF1) into a single publish model without custom middleware.
Reliable delivery over satellite with high latency/jitter and strict bandwidth budgets.
Broker high-availability and end-to-end observability at scale (350 sites, 500k+ tags).
Simple, repeatable deployment on router-class Linux hardware with unattended recovery.
Impact: Without a standardized, resilient gateway + MQTT pattern, sites face delayed event visibility, manual correlation, higher truck-rolls, and longer MTTR during incidents.
Example: “Prior to MQTT + EdgeConnect, engineers had to manually pull logs from PLCs after outages; post-event diagnostics stretched MTTR and risked SLA breaches.”
Edge tier (site): EdgeConnect on Linux (router) polls ControlLogix (CIP/EtherNet/IP) and DF1 devices, and publishes via MQTT/Sparkplug B.
Backhaul: Satellite or constrained WAN with store-and-forward, rate limiting, compression, and payload batching.
Broker tier: Redundant MQTT brokers (N=4).
Clients/consumers: Third-Party brokers consumers.
| Scada & Enterprise Applications |
| ↑↓ |
| Redundant Brokers |
| ↑↓ |
| EdgeConnect Product Edition |
| ↑↓ |
| PLCs on field: DF1, ControlLogix, etc... |
Layer | Component | Role | Notes |
|---|---|---|---|
Field | ControlLogix (CIP), DF1 devices | Signals/controls | - |
Edge (Site) | EdgeConnect (Linux) | Collection, buffer, publish | Runs on router/IPC; AutoStart; Watchdog; local logging |
Transport | Satellite / WAN | Telemetry backhaul | - |
Brokers | MQTT brokers (HA, N=4) | Pub/Sub backbone | Persistent sessions, retained health topics |
Consumers | SCADA/Historian/Analytics | Enterprise visibility & actions | - |
Segmented per site VLANs; secure egress to broker endpoints only.
Backpressure control: publish rate limiting, payload compression, delta/exception reporting.
Brokers: 4-node HA cluster with client failover and session persistence.
Edge: Store-and-forward with disk queues; automatic reconnect & replay; service watchdog and OS autostart.
Links: Multi-endpoint broker list with exponential backoff and jitter to avoid thundering herd.
Drivers/Interfaces: ControlLogix (CIP/EtherNet/IP), DF1 (serial), TCP/IP.
Messaging: MQTT, MQTT Sparkplug B (birth/death, metrics, model).
Sparkplug namespaces per site/asset; Group ID, Node ID and Device ID.
Sites: ~350
Points/Tags: 500,000+
Ingestion/Publish rate: 10 seconds
Concurrent sessions: 1
Edge and broker watchdogs.
Heartbeats (LWT/BIRTH), latency and backlog metrics per site; topic-level delivery KPIs.
Multiprotocol edge collection (ControlLogix + DF1) with a unified MQTT/Sparkplug output.
Router-grade Linux runtime enabling low footprint deployment close to the PLCs.
Store-and-Forward + AutoStart + Watchdog for unattended resilience over satellite.
Broker HA (N=4) and access governance to prevent network overflow and ensure continuity.
Real-time broker/edge monitoring with alarms on heartbeat loss, queue growth, or reconnect storms.
Why it’s non-trivial elsewhere: The combination of CIP + DF1 ingestion, Sparkplug governance at scale, true edge resilience over high-latency links, and 4-node broker HA across 350 sites typically requires significant custom engineering; EdgeConnect standardizes it.
Reduced MTTR by 70%: Eliminated manual log collection from PLCs post-outage through real-time MQTT telemetry, enabling immediate incident visibility and faster root cause analysis.
Achieved 99.5% uptime across 350 sites: 4-node broker HA cluster with store-and-forward edge resilience maintained continuous operations despite satellite link interruptions and bandwidth constraints.
Standardized deployment at scale: Single EdgeConnect solution replaced custom middleware across all sites, reducing deployment complexity and enabling consistent 500k+ tag collection from mixed ControlLogix/DF1 environments.
Enhanced operational visibility: Real-time publish/subscribe model with Sparkplug B provided enterprise-wide monitoring and analytics capabilities, replacing reactive maintenance with proactive incident management.