Fournine Cloud

Fournine Cloud is presented under the name Fournine Cloud and operates as a cloud services and DevOps consultancy. Headquarters country is not stated. Client references and case descriptions indicate work with organisations in multiple regions, including a Saudi Arabia-based company and a UK-based financial technology firm, as well as clients in the logistics and telecommunications sectors, suggesting international operations.

Services and Capabilities

• Cloud migration: planning and executing migrations from one cloud provider to another and from on-premises to cloud, including database migration and application modernization.
• DevOps and CI/CD: implementation of development pipelines, automated deployments, infrastructure-as-code, and continuous monitoring systems.
• Managed services and 24/7 operations: ongoing infrastructure management, monitoring, alerting, and support for cloud and container environments.
• Data engineering and analytics: data warehouse and data lake design, ETL processes, report generation using cloud data platforms, and predictive analytics workflows.
• Machine learning and AI: generative AI strategy, custom ML solution development, ML engineering for model deployment and operations, and synthetic data generation for model training.
• Container and Kubernetes services: Kubernetes consulting, implementation, migration, monitoring, and container security measures.
• Cloud security and cost management: security configuration for cloud and containers, database security practices, and cloud cost optimization.

Industry Focus

• Financial services and fintech: cloud migrations, unified security dashboards, and cost optimization for payment and risk-management platforms.
• Logistics: monitoring, reporting improvements, and data processing to support operational visibility and report generation.
• Telecommunications: log monitoring, observability solutions, and Kubernetes monitoring to support multi-region operations.
• General enterprise IT: modernization of legacy applications, managed Prometheus monitoring, and database administration across sectors.

Technology and Delivery Approach

• Integration of cloud platforms and provider-to-provider migrations, including work across AWS and GCP.
• Use of container orchestration with Kubernetes for application modernization, deployment, and monitoring.
• Observability and monitoring toolchains such as Prometheus and ELK for log aggregation, metrics, and alerting.
• Data platform work involving data warehouses, data lakes, BigQuery-based report generation, and analytics pipelines.
• Machine learning lifecycle practices encompassing model development, synthetic data generation, deployment, and ML operations.
• Delivery through managed services and ongoing operations with 24/7 monitoring, incident response, and cloud cost management processes.