CLOUD ARCHITECT

Sample Case Study: JencoMart

This is a sample case study that may be used on the Google Cloud Architect Certification exam. It describes a fictitious business and solution concept to provide additional context to exam questions.

JencoMart Case Study

Company Overview

JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company’s core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.

Company Background

JencoMart started as a general store in 1931, and has grown into one of the world’s leading brands, known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.

Solution Concept

JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.

Existing Technical Environment

JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe; most applications are dual-homed.

JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.

Application: Customer loyalty portal

LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S. data centers.

Database

  • Oracle Database stores user profiles
    • 20 TB
    • Complex table structure
    • Well maintained, clean data
    • Strong backup strategy
  • PostgreSQL database stores user credentials
    • Single-homed in US West
    • No redundancy
    • Backed up every 12 hours
    • 100% uptime service level agreement (SLA)
    • Authenticates all users

Compute

  • 30 machines in US West Coast, each machine has:
    • Twin, dual core CPUs
    • 32GB of RAM
    • Twin 250 GB HDD (RAID 1)
  • 20 machines in US East Coast, each machine has:
    • Single, dual-core CPU
    • 24 GB of RAM
    • Twin 250 GB HDD (RAID 1)

Storage

  • Access to shared 100 TB SAN in each location
  • Tape backup every week

Business Requirements

  • Optimize for capacity during peak periods and value during off-peak periods.
  • Guarantee service availability and support.
  • Reduce on-premises footprint and associated financial and environmental impact.
  • Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase.
  • Expand services into Asia.

Technical Requirements

  • Assess key application for cloud suitability.
  • Modify applications for the cloud.
  • Move applications to a new infrastructure.
  • Leverage managed services wherever feasible.
  • Sunset 20% of capacity in existing data centers.
  • Decrease latency in Asia.

CEO Statement

JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large, global company, we also have a responsibility to the environment through “green” initiatives and policies.

CTO Statement

The challenges of operating data centers prevents focus on key technologies critical to our long-term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service to customers.

CFO Statement

Since its founding, JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long-term success. This model will allow us to respond to increasing customer demand during peak periods and reduce costs during off-peak periods.

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