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GCP Modernisation & Automation

About The Customer

Jindal Projects & Engineering (PPEL), a part of the JSP Group, is a specialized organization focused on delivering engineering, project management, and construction solutions across key sectors such as steel, power, mining, and infrastructure. The company plays a crucial role in supporting the group’s expansion by managing and executing large-scale projects efficiently.

With a strong team of experienced professionals and deep expertise in EPC (Engineering, Procurement, and Construction), the organization emphasizes optimized resource utilization, structured planning, and streamlined project execution. Headquartered in Kolkata, Jindal Projects & Engineering is involved in multiple ongoing and upcoming projects, both in India and globally, requiring robust operational and digital support systems.

The Customer Challenge

As JSPL continued to expand its digital footprint across multiple business units, foundations, and web platforms, its existing CMS platform (PPEL/JSP) started showing visible signs of strain. What was once a functional and stable system gradually became a limiting factor in achieving the organization’s growing expectations around scalability, agility, and digital experience.

The platform was originally built on a Virtual Machine-based monolithic architecture, which worked well in the early stages. However, as the number of tenants increased and business requirements evolved, the system struggled to keep up with the demand for faster releases, better customization, and efficient operations.

Over time, it became evident that the platform required not just incremental improvements, but a fundamental shift towards modernization and automation.

Modernization Strategy

Re-architecting the platform to align with modern cloud principles, combining serverless compute, managed services, and end-to-end automation.

Containerization

Monolithic application containerized using Docker to ensure consistency across all environments.

Serverless Compute

Migration to Google Cloud Run for automatic scaling and a pay-per-use cost model.

Infrastructure as Code

Cloud resources provisioned via Terraform to eliminate manual errors and ensure reproducibility.

Managed Databases

Migration to Google Cloud SQL for built-in high availability and automated maintenance.

Full CI/CD

Automated pipelines using Cloud Build and Artifact Registry for faster, reliable releases.

The Solution

Zero-Downtime

Revision-based deployment with Cloud Run enables blue-green models and quick rollbacks.

Modular Content

Introduction of reusable UI blocks for banners and testimonials to reduce duplication.

Managed SQL

Migration to Cloud SQL ensures zero data loss with automated backups and maintenance.

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Traditional Architecture and Scalability Limitations

  • One of the primary concerns was the reliance on a monolithic application architecture deployed on Virtual Machines.
  • The application components were tightly coupled, meaning even minor changes required extensive validation across the entire system.
  • This significantly slowed down development cycles and made releases more complex and risk-prone.
  • Scaling the application was not dynamic and required manual provisioning of Virtual Machines.
  • Resource utilization was inefficient, as entire VMs had to be scaled rather than specific components.

Complex Multi-Tenant Management

  • CMS lacked proper abstraction and isolation.
  • Tenant-specific configurations were not structured.
  • Changes for one tenant risked impacting others.
  • No streamlined tenant-level branding/content control.

Inefficient Content and Form Management

  • No modular content framework.
  • Repeated effort for UI components.
  • Inconsistent user experience.
  • Static forms with no flexibility or analytics.

Manual and Disruptive Deployment

  • Manual SSH-based deployments.
  • Frequent downtime during releases.
  • Highly error-prone process.

Lack of Standardization

  • No consistent environments across Dev/UAT/Prod.
  • Manual infra provisioning.
  • No version-controlled infrastructure.

Solution

To address these challenges, a comprehensive modernization strategy was implemented using Google Cloud Platform (GCP), focusing on scalability, automation, and cloud-native architecture.

Automation Strategy

  • Terraform (IaC): Version-controlled infrastructure provisioning.
  • CI/CD Pipeline: Cloud Build, Artifact Registry, Bitbucket integration.
  • Zero-Downtime Deployment: Blue-green deployment using Cloud Run.
  • Environment Standardization: Identical infra across all environments.

Outcome

The transformation converted a manually managed system into a scalable, resilient, and fully automated cloud-native platform.

Transformation Impact

  • Infrastructure effort reduced by ~60–70%
  • Deployment time reduced from hours to minutes
  • Scalability improved by ~50%
  • Cost reduced by ~30–40%
  • Incident frequency reduced by ~30–40%

Key Benefits

Business Benefits

  • Faster Time-to-Market
  • Rapid feature releases through automated pipelines
  • Improved responsiveness to business requirements
  • Improved User Experience
  • Zero-downtime deployments
  • Better performance and availability
  • Cost Optimization
  • Reduced infrastructure and operational costs
  • Efficient pay-per-use model
  • Scalability for Growth
  • Easily supports onboarding of new tenants
  • Handles increasing traffic without redesign

Technical Benefits

  • Cloud-Native Architecture
  • Serverless, container-based deployment model
  • Improved flexibility and scalability
  • Full Automation
  • Infrastructure as Code (Terraform)
  • CI/CD pipelines for end-to-end automation
  • High Availability and Reliability
  • Managed services like Cloud SQL
  • Fault isolation and improved uptime
  • Standardization and Consistency
  • Identical environments across all stages
  • Reduced deployment risks

Operational Benefits

  • Reduced Manual Effort
  • Automation minimized human intervention
  • Lower operational overhead
  • Improved Monitoring and Control
  • Better visibility into deployments and system behavior
  • Simplified Maintenance
  • No server management required
  • Reduced patching and maintenance tasks

Before vs After Transformation

AreaBefore (Legacy System)After (Modernized Platform)
ArchitectureMonolithic, tightly coupled [cite: 184]Containerized, modular architecture [cite: 184]
HostingVirtual Machines (manual scaling) [cite: 184]Cloud Run (serverless auto-scaling) [cite: 184]
DeploymentManual (SSH-based) [cite: 184]Fully automated CI/CD pipeline [cite: 184]
DowntimeFrequent during deployments [cite: 184]Zero-downtime deployments [cite: 184]
InfrastructureHigh manual effort [cite: 184]Fully automated via Terraform [cite: 184]
ScalabilityManual and slow [cite: 184]Automatic and real-time [cite: 184]
Resource UtilizationOver-provisioned VMs [cite: 184]Optimized, pay-per-use model [cite: 184]
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