Solution
Infrastructure automation
Infrastructure-as-code modules and deployment pipelines. Provisioning of networks, servers and containers, followed by environment-specific configuration for development, testing and production.
Architecture and implementation
Infrastructure as code
Modules and configurations defining platform resources.
Service deployment
Pipelines for installing and configuring applications, databases and services.
Development integration
Environment integration with code repositories and software delivery workflows.
Design decisions
Definition of resources and dependencies through Infrastructure as Code (IaC), including parameters, secrets and Terraform state. A module can be reused for development, testing and production with environment-specific parameters.
Illustrative implementation
A network or service change can be reviewed as a plan, applied through a pipeline and compared with the actual deployed state.
Engineering outputsInfrastructure modules, environment parameters, pipeline and state-management procedure
A web and mobile application uses .NET services hosted on Azure, connected to PostgreSQL, Business Central and Microsoft 365. One example is a custom business portal for following quotations and orders, with access to related documents and records from the business management system.
Azure App Service
Azure Database for PostgreSQL
Business Central
.NET
Microsoft Entra ID
GitHub
Microsoft Graph
JavaScript
Kotlin
Microsoft 365
n8n
Power BI
Terraform
Components and flows
- Web and mobile access to .NET application services, with Entra ID authentication
- n8n integrations with Business Central and Microsoft 365 through their APIs
- Azure App Service and PostgreSQL deployment, with private data access and Power BI publishing
A local gateway collects equipment measurements and events, then a Kafka and Spark platform combines them with SAP data for applications and analytics. One example is a production line whose current state is available through an application, alongside analysis of its production and quality history.
Docker- .NET
- GitHub
Apache Kafka- Kotlin
Linux
PostgreSQL- Power BI
Python
SAP
Snowflake
Apache Spark- Terraform
Components and flows
- Equipment data read by a Python gateway on Linux; transmission to Kafka through a controlled network interface
- Spark time series processing and loading into PostgreSQL and Snowflake
- Enrichment with SAP data, .NET applications and Power BI analytics
A compute platform runs Python and R analyses of genomic sample batches in containers. Each run retains references to input files, the Git commit, container image and parameters so results can be compared and the pipeline rerun on another dataset.
Apache Airflow- Docker
- GitHub
Kubernetes- Linux
- PostgreSQL
Pure Storage- Python
R- Terraform
Components and flows
- PostgreSQL catalogue for datasets, parameters and provenance; shared storage for files and results
- Docker images built from identified GitHub versions, then executed through Airflow and Kubernetes
- Python and R processing, result publishing and execution records
Development and integration
- Terraform and automated configuration
- Containers and orchestration
- Continuous integration and delivery
- Data and AI platform deployment
Systems involved
- Azure, Google Cloud and private infrastructure
- GitHub and deployment tools
- Applications, databases and compute services
Service lineAzure and Google Cloud →
Services by sector
Explore the engineering services offered across different sectors.
Banking and insurance
Platform deployment and operations
Infrastructure as Code, CI/CD pipelines and deployment of databases, APIs and processing services. Job monitoring, load checks and recovery procedures support replaying a feed without duplicating operations already integrated.
Energy and utilities
Processing deployment and monitoring
Containerised services, scheduled jobs and cloud or private pipelines. Collection, delay and error monitoring, with processing recovery and database-update checks.
Manufacturing
Infrastructure and data-flow operations
Deployment of gateways, databases and analytical services in the selected environments. Configuration management, job monitoring and recovery procedures coordinated with equipment operating constraints.
To go deeper
Four decisions for cloud access across Google Cloud, Azure, AWS and Infomaniak
Permission scope, temporary privileges, workload identities and traceability let a team compare platforms against the same requirements.
Testing whether backups can restore the business service
A complete restore checks the data, applications and dependencies. Its measured result shows how recovery capacity compares with the organisation’s needs.
Discuss your project
A discussion of your project’s design, development and production deployment.