Build data-driven applications with containers and Kubernetes

Data powers intelligent applications

Across industries, cloud-native applications can help organizations differentiate themselves to gain a competitive advantage. Financial services firms use cloud-native applications to deliver mobile services, analyze business metrics, assess risk, and apply artificial intelligence (AI) and machine learning (ML) to operations.

All these use cases rely on data to deliver business value, and databases and data analytics capabilities are an integral part of intelligent, cloud-native applications. Consequently, databases and data analytics workloads must share many of the same characteristics as the applications they support. They must:

• Be designed in a manner that allows rapid deployment, updates, and changes.

• Scale elastically to meet changing demand.

• Run consistently across datacenter, cloud, and edge IT infrastructure.

Speed database and data analytics workload development and deployment

Through agile deployment, management, and scaling, containers and Kubernetes can help you accelerate cloud-native development of key architecture components, including databases and data analytics.

A container is a basic unit of software that packages applications with all of their dependencies. Containers simplify application build processes and allow applications to be deployed across different environments without change.

Kubernetes is an open source, extensible container orchestrator. Container orchestration involves managing the creation, deployment, and life cycle of containers across your environment. Self-service capabilities let developers easily and quickly provision the resources and services they need to build cloud-native applications.

Together, these technologies provide the agility, scalability, and portability cloud-native database and data analytics workloads need.