OT Change Control Requirements
Factory floor systems require validated change processes — change freeze windows, production line approvals, and rollback plans — that standard software DevOps pipelines are not designed to enforce.
AWS DevOps Consulting
DevOps & CI/CD for Manufacturing Systems on AWS
We build DevOps pipelines for manufacturing that respect OT change control requirements: automated testing, staged rollouts to production equipment, and rollback mechanisms designed for environments where a bad deployment can stop a production line.
- A workload or account brief arrives.
- The AWS practice designs how it will run.
- Design covers the landing zone, IAM, and boundaries.
- Build covers the pipelines and services that carry the work.
- Production changes wait for a named owner.
- The workload runs on AWS with that roster still attached.
Key Challenges We Solve
Multi-Site IoT Firmware Deployment
Deploying updated Greengrass components, Lambda functions, and ML models to gateways across multiple factory sites requires orchestrated rollout capabilities with per-site health checks before proceeding.
Infrastructure-as-Code for OT/IT
Managing AWS IoT Core policies, Greengrass component configurations, and SiteWise asset models as versioned code — enabling repeatable deployments of new factory lines without manual console configuration.
Testing Environments for Industrial Software
Creating realistic test environments for industrial applications is difficult — SCADA simulators, synthetic sensor data generators, and staging IoT Core configurations require specialized setup.
Our Approach
AWS CodePipeline for OT Workloads
CI/CD pipelines with manufacturing-aware approval gates: automated testing stages, production freeze enforcement via Lambda-triggered compliance checks, and staged rollouts to non-critical lines before production equipment.
Terraform + Greengrass IaC
Terraform modules for provisioning IoT Core thing groups, Greengrass deployments, SiteWise asset model hierarchies, and Lambda edge functions — enabling repeatable, version-controlled factory-floor AWS configurations.
GitHub Actions + AWS for Manufacturing CI
GitHub Actions workflows that run automated tests against synthetic IoT data, validate Greengrass component configurations, and deploy to staging IoT environments before promoting to production gateways.
Frequently Asked Questions
How do we deploy Greengrass component updates safely across multiple factory sites?
AWS IoT Greengrass deployments support rolling updates with health check components — a new component version deploys to a canary group of gateways, runs a health check Lambda, and only proceeds to the full fleet if the check passes. Deployment targets are managed with IoT Core thing groups, enabling per-site or per-line rollout control.
Can we use Terraform to manage IoT SiteWise asset models?
Yes. The AWS Terraform provider includes resources for IoT SiteWise asset models, assets, and portals. This enables version-controlled, repeatable deployment of SiteWise configurations when adding new production lines or factory sites.
How do we create test environments for industrial IoT pipelines?
AWS IoT Core supports virtual device simulators using the AWS IoT Device SDK. For SiteWise testing, you can publish synthetic time-series data via the SiteWise API or use AWS IoT Core message routing rules to replay historical telemetry — allowing full pipeline testing without physical sensors.
What change management controls should we add to our manufacturing CI/CD pipeline?
Manufacturing pipelines should include: (1) automated deployment freeze checks (reject pipeline runs during production hours unless emergency-tagged), (2) manual approval gates for production-line-affecting changes, (3) automatic rollback triggered by CloudWatch alarms monitoring IoT message rates post-deployment, and (4) deployment records written to an immutable S3 audit log.
Ready to Get Started?
Talk to our AWS experts about devops & ci/cd for manufacturing systems on aws.