Success Story – Large Energy Company2017-11-27T22:02:36+00:00

SUCCESS STORY

Plans to increase presence in Europe and Asia but had a big barrier to entry because of datacenter costs (CAPEX)

PROBLEM STATEMENT

A large energy company had plans to increase its presence in Europe and Asia but had a barrier to entry because of datacenter costs(Capex).  System utilization was less than 10%.  Most of the utilization was towards the end of the month when energy reports were being generated and distributed to all customers which caused system issues affecting customers and impacting credibility.

Client:

Large Energy company with offices in 100 countries and 33B in revenues

Infrastructure Overview:

Datacenter hosted in Sunnyvale, CA. Provides usage monitoring, management and analytics of energy data to customers worldwide.

SLA: 99%

Application:

3 tier application with Web, App and Database in the back end

Problem: Increasing CAPEX and Support Costs

  • Cost of running operations in Datacenter was increasing with new hardware purchases
  • Legacy network architecture which was not flexible requiring specialized network engineers to maintain and troubleshoot
  • Enterprise storage software for database with high support costs
  • Expensive virtualization licensing
  • Additional hardware and support cost for disaster recovery
  • Inconsistent software environments created unstable production code leading to increased support costs

Business Driver:

  • Plans to increase presence in Europe and Asia but had a big barrier to entry because of datacenter costs(Capex)
  • System utilization was less than 10%
  • Most of the utilization was towards the end of the month when energy reports were being generated and distributed to all customers which caused system issues affecting customers impacting credibility

Solution: Move to Amazon Web Services (AWS).

Benefits include:

  • Capex vs Opex: Pay only for what you use
  • Databases are automatically backed up saving proprietary vendor storage cost
  • New network architecture with SDN which provides isolation and better security
  • Independently scale any resource or service with on-demand elasticity and auto scaling

Architecture Plan & Implementation:

  • Separation of 3 tier architecture into segments with security groups and dedicated network subnets provides isolation and management
  • Separate VPC for Dev, Stage and Prod environment built using templates to eliminate variance
  • Flexible compute sizing: Chose m3.medium and m3.large instances for web and app tier and c3 for database with a commitment of reserved instances to guarantee base performance and use on-demand instances for variable workloads thereby minimizing Opex costs
  • Moved from hardware firewall & load balancers to *aaS with ELB and security groups
  • AWS Glacier to store historical data for compliance purposes

Savings & Improvements:

  • Reduced the monthly cost by 70% due to reserved instances and using AWS inherent capabilities of snapshot and backups

  • Software releases are easier to roll out due to reduced risk of losing instances (with custom AMI’s) which led to increased SLA

  • Eliminate licensing costs for Virtualization software

  • Reduced storage support costs

  • Easy/Automatic updates and patching of software leads to increased stability in App

  • DR & BCP made easy with tools and requires zero maintenance