Topic 3, 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
2 4 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 availably 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 application 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 polices.
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 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 and reduce costs.

https://cloud.google.com/solutions/pci-dss-compliance-
ingcp#using_data_loss_prevention_api_to_sanitize_data

Explanation
https://cloud.google.com/solutions/data-analytics-partner-ecosystem
https://zulily-tech.com/2015/08/10/leveraging-google-cloud-dataflow-for-clickstream-processing/ Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
* Low-latency read/write access
* High-throughput analytics
* Native time series support
* Common workloads:
* IoT, finance, adtech
* Personalization, recommendations
* Monitoring
* Geospatial datasets
* Graphs

Explanation
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations Google Cloud Dedicated Interconnect provides direct physical connections and RFC 1918 communication between your on-premises network and Google's network. Dedicated Interconnect enables you to transfer large amounts of data between networks, which can be more cost effective than purchasing additional bandwidth over the public Internet or using VPN tunnels.
Benefits:
* Traffic between your on-premises network and your VPC network doesn't traverse the public Internet.
Traffic traverses a dedicated connection with fewer hops, meaning there are less points of failure where traffic might get dropped or disrupted.
* Your VPC network's internal (RFC 1918) IP addresses are directly accessible from your on-premises network. You don't need to use a NAT device or VPN tunnel to reach internal IP addresses. Currently, you can only reach internal IP addresses over a dedicated connection. To reach Google external IP addresses, you must use a separate connection.
* You can scale your connection to Google based on your needs. Connection capacity is delivered over one or more 10 Gbps Ethernet connections, with a maximum of eight connections (80 Gbps total per interconnect).
* The cost of egress traffic from your VPC network to your on-premises network is reduced. A dedicated connection is generally the least expensive method if you have a high-volume of traffic to and from Google's network.
References: https://cloud.google.com/interconnect/docs/details/dedicated

Reference:
https://cloud.google.com/kubernetes-engine/docs/tutorials/http-balancer
https://cloud.google.com/kubernetes-engine/docs/concepts/network-overview#ext-lb