Optimizing Systems for a Leading European Defence Manufacturing Company

About the Client

The client is a leading European Defence Manufacturing Company specializing in advanced defense systems, technologies, and manufacturing solutions. Following a significant merger and acquisition, the client faced challenges in consolidating disparate systems, migrating data, and streamlining operations. Additionally, they sought to optimize their software development lifecycle by reducing build and deployment times through predictive AI-based solutions.

Requirements

• System Consolidation and Migration: Consolidate and migrate legacy CRM, Sales, and Purchase Order (PO) systems post-merger.
• Cloud Infrastructure: Migrate systems and data to a standardized cloud-based infrastructure using Azure and Microsoft Dynamics 365.
• Legacy System Decommissioning: Decommission redundant systems to reduce operational costs and maintenance overhead.
• AIOps for CI/CD Pipelines: Build a Proof-of-Concept to use AI for predicting failures in CI/CD pipelines and reduce build and deployment times for engineers by identifying bottlenecks.
• Enhanced Data Integrity and Automation: Maintain data quality and integrity during migration while automating tasks to improve efficiency and operational consistency.

Solution

• System Consolidation and Data Migration: Enshire executed a comprehensive migration and consolidation strategy:
  • Platform Selection: Migrated CRM, Sales, and PO systems to Microsoft Dynamics 365 for unified data and process management.
  • Cloud Migration: Leveraged Microsoft Azure as the target infrastructure to ensure scalability, security, and cost efficiency.
  • Data Migration: Conducted extensive data mapping and cleansing to ensure smooth migration with no data loss or discrepancies. Automated ETL pipelines were used to transfer and validate data from legacy systems.
  • Legacy System Decommissioning: After successful migration, redundant systems were decommissioned, reducing maintenance costs and IT overhead.
• AIOps Proof-of-Concept for CI/CD Pipelines: Enshire delivered an AIOps-based solution to predict failures in the CI/CD pipeline and optimize build processes:
  • Data Collection: Historical CI/CD pipeline data, including logs, build failure patterns, and deployment metrics, were collected for analysis.
  • AI and ML Modeling: Developed a predictive analytics model to identify failure patterns, root causes, and bottlenecks in the pipeline. Leveraged machine learning algorithms to forecast potential failures and provide proactive alerts.
  • Outcome Optimization: The AIOps PoC reduced deployment delays by predicting issues early in the pipeline. Provided actionable insights to engineers, enabling faster root-cause analysis and resolution.

Key Technologies Used

• Cloud Platform: Microsoft Azure.
• CRM and Systems: Microsoft Dynamics 365.
• Data Migration: ETL Pipelines, SQL.
• AIOps: Machine Learning models, Python.
• CI/CD Pipelines: Jenkins, Azure DevOps.