CASE STUDY 1

Multi-Cloud Setup for IoT Based Real Time Asset Tracking

Client

The Client is an IOT based product company that provides continuous visibility into the context, condition, timing and location of material and assets throughout your supply chain.

Need

The client needed a real-time asset tracking, monitoring, and analytics solution using Azure Native Services to improve visibility, efficiency, and decision-making throughout their supply chain.

Solution

Application Migration to Azure:

Migrated applications from AWS to Azure, adopting a multi-cloud strategy.

Kubernetes Cluster Deployment:

Created a 6-node Kubernetes cluster across 8 different environments.

Metrics Collection:

Set up Grafana and Prometheus for collecting metrics from containers, nodes, and pods.

Autoscaling:

Implemented node and application autoscaling across all clusters.

Alert Mechanism:

Established a robust alerting system to prevent application outages by publishing notifications.

Result

  • RBAC set-up to restrict Kubernetes access
  • Secured application binaries
  • Implemented ELK stack
  • Applied SSL certificates

Key Services

  • Hybrid Cloud Enablement
  • Cloud Migration and Setup
  • Cloud Security

Technologies

  • Azure
  • ELK Stack
  • Elastic Container Registry
  • Grafana
  • Prometheus
  • RBAC
  • SSL

CASE STUDY 2

Optimize Migration and Consolidation to AWS from Public Clouds

Client

Client is a leading provider of independent investment research which consistently identifies actionable opportunities from which clients can gain an investment edge and avoid risk.

Client’s Need

The client needed the implementation of serverless architecture using AWS Lambda and the consolidation and migration of their infrastructure to AWS.

Solution

Event-Driven Architecture:

Delivered new design and architecture from batch processing.

Automated Deployments:

Used AWS SAM framework for automation.

Configuration Management:

Applied industry-standard YAML for AWS services.

Flexible Workflows:

Utilized AWS Step Functions for workflow management.

Re-architected Data Flow:

Implemented new design for end-to-end data processing.

Results

  • Implemented comprehensive financial calculations
  • Managed equity data refreshes
  • Completed end-to-end PDF testing

Key Services

  • Big Data & Analytics
  • Reporting and Dashboards

Technologies

  • Java
  • Python
  • Glue
  • AWS Lambda
  • SNS
  • ECS
  • EKS

CASE STUDY 3

Optimize Cloud Operations with Migration, Architecture, and Automation

Client

The client is a leading health management platform for employers, offering wellness programs, coaching, benefits integration, and wellness incentives.

Need

The client needed a comprehensive cloud solution for HIPAA compliance, including migration, architecture, automation, and 24/7 operations management to enhance efficiency and security.

Solution

Cloud Migration:

Migrated from Heroku to Rackspace and AWS for HIPAA compliance.

Cloud Architecture and Design:

Architected a secure, high-availability cloud with best practices and cost optimization.

Cloud Automation:

Implemented CI/CD, cloud orchestration, configuration management, and infrastructure-as-code.

Cloud Operations Management:

Managed environments 24x7 with a dual-shore shared services model and analytics for efficient operations.

Result

  • Achieved HIPAA compliance
  • Maintained 99.99% uptime
  • Optimized cloud operations
  • Ensured seamless major releases

Technology

  • AWS
  • S3
  • Chef
  • NewRelic
  • Nagios
  • HAProxy
  • NGINX
  • Redis

CASE STUDY 4

Accelerate Cloudification and Refactoring of Data Integration Platform with Containerization on Public Clouds

Client

The client provides a remotely configurable software application designed for Microsoft Windows-based platforms, offering intelligent convergence of network-aware assets.

Client’s Need

The client needed to refactor its Data Integration platform to improve scalability through native cloud features.

Solution

Docker Images Creation:

Built Docker images for both the server instance and lightweight web application interface.

Kubernetes Setup:

Configured and deployed Kubernetes container clusters on-premises and in Microsoft Azure.

High-Availability Setup:

Explored and analysed Apache Ignite for high availability and cluster configuration.

Auto-Scaling Testing:

Tested auto-scaling by spawning multiple nodes within the cluster.

Result

  • Cloudification and containerized deployment
  • On-demand node scalability enabled

Key Services

  • Dockerization
  • Cloud Deployment
  • Quality Engineering

Technologies

  • Docker
  • Kubernetes
  • Azure Kubernetes Service (AKS)