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1. The Problem

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.”

2. The Solution

2.1 Overview

  • 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.

2.2 Logical Diagram (high level)


[PLC Layer: ControlLogix / DF1]           [Edge Layer: Per-Site Gateway]                [Network Layer]
  • CIP/EtherNet/IP (CLX)                   • FrameworX (EdgeConnect on Linux)         • MQTT brokers (HA, N=4)
  • DF1 (serial)                            • Poll ? Buffer ? Publish                  • Subscribers: Third-Party brokers consumers
                                            • Watchdog, AutoStart                      

   ????TCP/IP ???????????????????????????????  Router  ???????????????????????????????????  Broker




[PLC Layer: ControlLogix / DF1] [Edge Layer: Per-Site Gateway] [Network Layer] • CIP/EtherNet/IP (CLX) • FrameworX (EdgeConnect on Linux) • MQTT brokers (HA, N=4) • DF1 (serial) • Poll → Buffer → Publish • Subscribers: Third-Party brokers consumers • Watchdog, AutoStart ????TCP/IP ??????????????????????????????? Router ??????????????????????????????????? Broker

2.3 Topology

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

-

2.4 Network Architecture

  • Segmented per site VLANs; secure egress to broker endpoints only.

  • Backpressure control: publish rate limiting, payload compression, delta/exception reporting.

2.5 Redundancy & Failover

  • 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.

2.6 Protocols & Equipment

  • Drivers/Interfaces: ControlLogix (CIP/EtherNet/IP), DF1 (serial), TCP/IP.

  • Messaging: MQTT, MQTT Sparkplug B (birth/death, metrics, model).

2.7 Data Model & Topics

  • Sparkplug namespaces per site/asset; Group ID, Node ID and Device ID.

2.8 Scale & Capacity

  • Sites: ~350

  • Points/Tags: 500,000+

  • Ingestion/Publish rate: 10 seconds

  • Concurrent sessions: 1

2.9 Observability & Health

  • Edge and broker watchdogs.

  • Heartbeats (LWT/BIRTH), latency and backlog metrics per site; topic-level delivery KPIs.

3. Key Enablers

  • 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.

4. The Results

  • 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.

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