Global Insurance Kubernetes, Azure and OpenEBS
公司规模
1,000+
国家
- United States
产品
- Kubernetes
- Azure
- OpenEBS
技术栈
- Docker Swarm
- Azure Kubernetes Service
- Azure managed disks
- Azure file
- ElasticSearch
实施规模
- Enterprise-wide Deployment
影响指标
- Digital Expertise
- Productivity Improvements
技术
- 基础设施即服务 (IaaS) - 云计算
- 基础设施即服务 (IaaS) - 云存储服务
- 平台即服务 (PaaS) - 连接平台
适用功能
- 商业运营
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
The customer is a leading insurance company that competes globally in wholesale and retail markets. Software development is crucial for retaining and competitive advantages. Software is used in all pieces of the business from retail consumer apps to the financial modeling of risk exposures and regulatory reporting. Data can be thought of as the “lifeblood” of the organization, used along with software to make more intelligent decisions in all pieces of the business from marketing to pricing and design of products.
挑战
The insurance company was looking to improve their development agility by accelerating their adoption of containers as a service for their internal teams. They had been using Docker Swarm for stateless workloads, but with the emergence of Kubernetes and Kubernetes services such as Azure Kubernetes Services, they felt it was appropriate to begin to run stateful workloads on containers. However, they faced limitations in the performance and flexibility of underlying Azure storage, and Azure managed disks. They also encountered technical and performance limitations of Azure file, which is limited with SMB protocol only and can be tricky to manage.
解决方案
The company adopted Kubernetes on their premises via Azure connected cloud plus a Kubernetes distribution and on the cloud via Azure Kubernetes Service. OpenEBS was used across each of these Kubernetes environments to better perform CI/CD and other workloads in a manner that is consistent across environments. OpenEBS was selected to address a number of initial challenges in their increased usage of Kubernetes, including limitations in the performance and flexibility of underlying Azure storage, and Azure managed disks, technical and performance limitations of Azure file, and limitations in the flexibility of ElasticSearch services from Azure.
运营影响
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