ReachForce Containerizes 200+ AWS Instances with Portworx to Reduce Data Center Footprint and CPU Utilization
公司规模
Mid-size Company
地区
- America
国家
- United States
产品
- Portworx Enterprise
- AWS ECS
- Docker
- Jenkins
- MongoDB
技术栈
- Docker
- AWS ECS
- Jenkins
- MongoDB
- etcd
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
技术
- 基础设施即服务 (IaaS) - 云计算
- 应用基础设施与中间件 - API 集成与管理
适用行业
- Software
适用功能
- 销售与市场营销
- 商业运营
用例
- 过程控制与优化
- 预测性维护
- 库存管理
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
ReachForce is a company that operates in the marketing automation space. Their main function is to make marketing leads more valuable and actionable. Most leads are limited to business card information such as first name, last name, title, company, street address, email address, and phone number. These leads flow into marketing automation systems from a variety of sources. ReachForce is partnered with Marketo, Eloqua, and Salesforce, and their service can validate, deduplicate and enrich these leads with many more fields of information about the business. This enriched information can make a salesperson more effective and can also make sales automation much more effective.
挑战
ReachForce, a company in the marketing automation space, was facing several challenges with their AWS data center. The data center, comprised of four environments (Dev, QA, Performance Lab, and Production), consisted of about 215 EC2 instances. The company had re-implemented their SaaS offering in a micro-services architecture, using a separate AWS instance for each microservice. However, this led to the need to maintain over 200 Linux OS instances, and their average CPU utilization was significantly below best industry practices. Additionally, their AWS EBS storage was severely under-utilized, with only 25% of purchased capacity being used. At the same time, EC2 instances were over-provisioned by 100%, increasing the cost of operating the ReachForce SaaS platform.
解决方案
To address these challenges, ReachForce decided to re-implement their data center as a containerized architecture. They believed that they could reduce their data center footprint from 215 EC2 instances down to as few as fifteen using containers. They aimed to reach a CPU utilization of 25%. They set up the first development cluster in November and were about to roll out a preview of their first application based on containers. This application is a customer portal and consists of a database, a two-container SSO solution, and a customer web portal that reinforces the value proposition of their SaaS service. They used etcd and confd for service discovery and environment-specific configuration. The CI/CD pipeline was built out using Jenkins, containerized and with its workspace on a Portworx volume. They elected to go with AWS ECS for container orchestration. They also used Portworx Enterprise for cloud native storage and data management.
运营影响
数量效益
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