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Pluto7 assisted a client in notable infrastructure cost saving of approximately 15-20% by setting up the Virtual Machines on Google Cloud

Introduction

The client is a major solutions provider in financial/technological sectors with global recognition. They comprise several teams structured to work in different domains of software development including support, implementation, development, quality assurance, report development, technical writing, and much more. Their journey has been innovative with an explicit focus on the emerging market requirements.

Why did they choose Pluto7?

Pluto7 is a tech services and solutions company, specialized in Smart Analytics, Artificial Intelligence, and Machine Learning. Pluto7’s Infrastructure and Security team works strategically leveraging Cloud and industry best practices that enable and improve the customer experience.  With unique capabilities for helping the organizations in different domains to leverage Machine Learning, Artificial Intelligence, and analytics on Google Cloud, we have delivered many complex predictive analytics solutions. We are among the top 1% of the Google cloud partners worldwide. Having worked with multiple industries, Pluto7 has a rich experience in understanding the challenges and solving global-scale problems. 

Solutions

The client provides solutions/software to banks across the globe. Keeping in mind the data security and integrity, banks prefer to keep their data within their geographical locations. 

However, in this case, the workloads are served from the machines hosted out of the region due to the unavailability of proper infrastructure within the region where the customer was located. 

The main objectives were:

  • To transfer all the workload to the client’s location.
  • Provide security by restricting the movement of data between any other geographical region other than the client’s region.
  • Helping the client move their infrastructure to the GCP environment. 
  • Scaling the application based on the incoming traffic using the Cloud Load Balancer.

Our team proposed the client to migrate to a GCP architecture, having a virtual private cloud for their infrastructure as security was a major concern for them. Our goal was to set up private subnets for the client to keep their database in those subnets so that the outside world has no access to their data. Setting up security groups solved the problem of data security for the client. 

The client has an inbuilt three-tier application system, including the app server, web servers, and database server for which they wanted a firewall restriction for the incoming traffic. Pluto7 assisted the client in deploying their applications on GCP by creating the virtual machines for them. On the security front, our team worked on firewall restrictions and assigning policies. 

Results

By building up the GCP architecture, the client was able to work on the cost efficiency front while establishing a robust and secure infrastructure. Leveraging Google Cloud,  the data can be accessed in a trouble-free and secure manner. There was a notable cost saving in infrastructure setup, of approximately 15-20% by setting up the Virtual Machines on Google Cloud as a result of attaching the load balancer. 

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Challenges

  • The complete database of the client was placed outside the geographical region of their presence which they wanted to migrate to their existing location. The major issue here was that the security of the data was vital and to be taken care of.
  • Helping the client to migrate their database infrastructure on Google cloud using virtual machines so that they could access the data in their own geographical region.
  • Security being the utmost priority, they wanted the incoming traffic to be restricted so that the essential information is not accessed by any outsider which was fulfilled by using firewall restrictions.
  • A configuration for the VPN connectivity was required to be done while setting up the VPC.

Results

  • The cost-effectiveness of nearly 15-20% was achieved by migrating the infrastructure to the Google Cloud Platform.
  • We were successful in restricting the incoming traffic by using a firewall with geo-restrictions and defining various policies aligning to which the data could only be accessed by the concerned persons in the organization.
  • A private cloud was built to focus on the three-tier application system to maintain data security.

Products Used

  • Virtual Private Cloud
  • Cloud VPN
  • Stackdriver
  • Cloud Load Balancing
  • Compute engine
  • Cloud Armor