01
Software & Product Engineering
Full-stack applications, APIs, analytical systems, and complex technical products—from architecture through production.
- Angular
- TypeScript
- JavaScript
- .NET
- C#
- C++
- REST
- OpenAPI
- Linux
Craig Chandler
Solution Architect · Decision Intelligence Specialist
Analytical software, cloud architecture, and operational modelling for complex systems.
From operational problem definition through modelling, architecture, implementation, deployment, and decision support.
System span Operation → Decision
The whole system
Architecture grounded in how operations actually work.
The difficult part of an analytical system is rarely a single technology. It is understanding the operation well enough to model it, choosing an architecture that will hold up, and turning the result into dependable software.
Operational knowledge, analytical models, application boundaries, cloud infrastructure, and decision outputs are treated as one connected architecture.
Expertise
Four disciplines. One connected practice.
The strongest solutions come from treating product, platform, model, and operation as one architecture.
02
Cloud Architecture
Cloud-native and distributed systems designed around security, reliability, operability, and proportionate cost. Deepest platform experience is in Azure.
- Azure
- AWS
- Google Cloud
- Containers
- Serverless
- API Management
- Identity
- Multi-tenancy
- Secrets
- Monitoring
- CI/CD
- Cost optimisation
03
Decision Intelligence
Models and analytical products that expose constraints, test scenarios, and make operational trade-offs easier to understand.
- Discrete-event simulation
- Rail modelling
- Supply chains
- Capacity
- Scheduling
- Monte Carlo
- Fatigue risk
04
Solution Architecture
Translating difficult operational problems into maintainable technical systems, with a clear path from intent to operation.
- Discovery
- System design
- Integration
- Security
- Delivery
- Operations
- Decision support
Selected work
Systems built around consequential decisions.
A focused selection across analytical products, cloud platforms, control systems, and operational models.
01Analytical implementation, product architecture and integration
FAID Quantum
- Problem
- Deliver two fatigue-analysis algorithms through web, API and native integration models.
- Role
- Product + integration architecture and engineering
- Complexity
- Angular · .NET · Azure · Auth0 · API Management · C++ · licensing
02Cloud simulation and analysis workflows
DASH-X
- Problem
- Prepare simulation scenarios, run seeded repetitions and consolidate outputs for analysis.
- Role
- Product workflow + application and cloud architecture
- Complexity
- Angular · .NET · Azure Container Instances · Cosmos DB · Blob Storage
03Railway simulation capability and integration
Moving Block Train Control
- Problem
- Model realistic train separation and network interactions across changing rail topology.
- Role
- Engineering direction + Planimate integration and validation
- Complexity
- C++ · moving block · rail topology · Planimate integration · Windows · Linux
04Operational modelling and decision support
Rail & Bulk Supply Chain Modelling
- Problem
- Assess capacity, operating plans and redesign options across rail, bulk-material and distribution systems.
- Role
- Simulation design + client scoping and decision support
- Complexity
- Planimate · reusable components · configurable networks · scenario analysis
05Legacy software recovery and modernisation
Wizball Remake — Legacy C++ Revival
- Problem
- Bring a recovered C++ game remake to a Linux handheld, adapting its runtime, rendering and save behaviour to the device.
- Role
- Recovery + engineering direction + validation
- Complexity
- C++ · SDL2 · legacy migration · Linux · ARM handhelds · build/release engineering
Latest article
Modelling Moving-Block Train Control in a Discrete-Event Simulation
Why train length, changing separation and network topology make the problem harder than it first appears.
Read articleApproach
From operational reality to working system.
A disciplined path through the problem—without losing sight of the people who will use the answer.
Understand the operation
Start with the real system: its decisions, constraints, actors, data, and failure modes.
Model the problem
Choose the right abstraction and make assumptions, boundaries, and uncertainty explicit.
Design the architecture
Shape components, contracts, security, data, and deployment around the work the system must do.
Build the system
Implement the smallest coherent product with strong engineering boundaries and feedback loops.
Deploy and operate
Treat identity, observability, delivery, cost, and support as part of the architecture.
Support better decisions
Return useful evidence to the people deciding what happens next.
Technology landscape
Tools chosen by responsibility, not fashion.
A practical technology range, organised around the role each part plays in the system.
Application
Angular · TypeScript · RxJS · Signals · Angular Material
Backend
.NET · C# · C++ · REST · OpenAPI
Cloud
Azure · AWS · Google Cloud · Firebase
Platform
Docker · Linux · GitHub Actions · CI/CD
Data
Cosmos DB · SQL · MySQL · Analytical datasets
Identity & Security
Auth0 · OAuth 2.0 · OpenID Connect · RBAC · Key Vault
Decision Systems
Discrete-event simulation · Operational modelling · Scheduling · Capacity analysis · Rail modelling
Experience
A career spent where software meets operations.
More than twenty-five years building decision-support systems and the software platforms around them.
1999Present
InterDynamics Pty Ltd
Senior Decision Support Specialist / Solution Architect
Work spanning software engineering, solution architecture, cloud platforms, and operational modelling across transport, mining, logistics, manufacturing, and fatigue-risk systems.
- Architecture and delivery of customer-facing analytical products from operational concept to production.
- Full-stack system design across Angular and .NET, including identity, tenancy, APIs, and analytical workflows.
- Simulation and decision-support modelling for rail, mine-to-port supply chains, capacity, and scheduling.
- Cross-platform implementation of biomathematical fatigue algorithms and contributions to the Planimate platform.
- Cloud architecture across Azure, AWS, and Google Cloud, with Azure as the principal platform.
Representative work
Across systems where capacity, time, and risk matter.
Rail & transport
BHP Billiton · Aurizon · Queensland Rail · Bowen Rail · Roy Hill · CBG
Mining & bulk logistics
Mineral Resources · Alcoa · Orica Explosives · mine-to-port supply chains
Supply chain & manufacturing
Coles Myer · Hitachi · operational capacity and network strategy
Workforce risk
Fatigue analysis · biomathematical models · schedule risk management
Infrastructure logistics
Port Authority of NY & NJ · World Trade Center truck arrival scheduling
About Craig
Mechanical engineer by education. Systems architect by practice.
Based in Adelaide, I approach software as an engineer: understand the physical operation, make assumptions explicit, and design around the decisions that matter.
A Bachelor of Mechanical Engineering from the University of Adelaide provides a useful foundation for reasoning about physical operations as well as software systems.
Independent engineering
Engineering beyond client work.
Continued hands-on work across small operational services and the modernisation of a recovered C++ codebase.
Infrastructure & Developer Tooling
Small, production-minded Go services for self-hosted infrastructure and developer workflows: Australian weather feeds, QNAP health over SNMP, and a focused view of GitHub work requiring attention.
Go · Linux · systemd · Docker · HTTP APIs · SNMP · credential handling · release packaging
Legacy Software Revival
Recovery and modernisation of a 2007 C++ codebase for current Linux and handheld targets, replacing legacy runtime dependencies while hardening resources, execution, and packaging.
C++ · SDL2 · CMake · Linux · runtime hardening · PortMaster
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