What is a Cloud-native solution?
“Cloud Native” is an approach to building and running applications that takes advantage of the cloud computing delivery model.
It involves several key characteristics and practices, including:
Microservices Architecture: Cloud-native applications are typically built as a collection of loosely coupled microservices, each responsible for a specific function. This architecture enables easier scalability, maintainability, and rapid development.
Containerization: Applications and their dependencies are packaged in lightweight, portable containers, such as Docker containers. Containers provide consistency across different environments, making it easier to deploy applications across various cloud providers.
Dynamic Orchestration: Cloud-native applications are often managed by container orchestration platforms like Kubernetes. These platforms automate the deployment, scaling, and management of containers, ensuring high availability and efficient resource utilization.
Infrastructure as Code (IaC): Cloud-native development emphasizes the use of code to define and manage infrastructure, allowing for automated provisioning and configuration of cloud resources.
DevOps and Continuous Integration/Continuous Deployment (CI/CD): Cloud-native teams embrace DevOps practices and implement CI/CD pipelines to continuously deliver updates and improvements to applications, reducing time-to-market and enhancing agility.
Scalability and Resilience: Cloud-native applications are designed to scale dynamically based on demand, allowing them to handle varying workloads efficiently. They are also engineered to be resilient, able to recover from failures, and maintain availability.
Cloud Services Utilization: Cloud-native applications make extensive use of cloud services and managed offerings provided by the cloud provider, such as databases, storage, messaging, and AI/ML services.
Monitoring and Observability: Cloud-native applications are instrumented with monitoring and observability tools to track performance, identify issues, and gain insights into application behavior.