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Global Insurance Kubernetes, Azure and OpenEBS
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Infrastructure as a Service (IaaS) - Cloud Storage Services
- Platform as a Service (PaaS) - Connectivity Platforms
Applicable Functions
- Business Operation
Services
- Cloud Planning, Design & Implementation Services
- System Integration
The Challenge
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.
About The Customer
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.
The Solution
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.
Operational Impact