How do you manage application lifecycle for cloud-native applications?

The lifecycle management of cloud-native applications covers the entire process from development, deployment, and operation to termination, with the goal of achieving automation, elasticity, and efficiency. In an environment of microservices, containerization, and dynamic orchestration (such as Kubernetes), this management is crucial to ensure business continuity and iteration speed.

Its core consists of automated pipelines (CI/CD), declarative infrastructure (such as IaC), orchestration systems (such as Kubernetes controllers), service meshes, and monitoring/logging/alerting (the pillars of observability). Features include rolling updates, blue-green/canary deployments, automatic scaling (HPA), self-healing capabilities, and version control and synchronization of configurations and states through GitOps. The key principle is ""desired state management,"" where the system continuously drives the actual state to converge with the declaratively defined desired state.

Implementation steps:

1. CI/CD automation: Code commits trigger building, testing, and generation of immutable images.

2. Declarative deployment: Use Kubernetes YAML/Helm Charts/Kustomize to define the desired application state.

3. GitOps practice: Use Git as the single source of truth, with changes initiated through PRs and automatically synchronized to the cluster by tools such as Argo CD/Flux.

4. Progressive delivery and monitoring: Implement canary releases in conjunction with service meshes and monitor metrics/logs/SLOs in real time; HPA automatically adjusts resources; deployment strategies control risks.

5. Termination and rollback: Clean up old version resources according to policies; versioned deployments support one-click rollback. Its business value lies in enabling high-frequency and reliable releases, rapid fault recovery, resource optimization, and improving DevOps efficiency and system resilience.