How would you design a CI/CD pipeline for a data and image service, ensuring that deployments are validated, configurations are integrated, and data is not lost during rollbacks or rotations?

For a data and image service, the CI/CD pipeline must handle both code and large binary assets while preserving data integrity. Start with a source‑control system that stores code and image manifests; use a container registry for image layers and an artifact repository for data snapshots. In the build stage, run unit tests, security scans, and image linting. In the test stage, deploy to a staging environment that mirrors production, including the same database schema and storage buckets. Use automated integration tests that ingest sample data and verify image processing pipelines. For deployment validation, implement a canary release: roll out to a small percentage of traffic, monitor health checks, and use feature flags to toggle new features. Data integrity is ensured by performing database migrations in a transactional manner and backing up critical tables before changes. If a rollback is needed, use a blue‑green strategy: keep the old environment live while the new one is validated; if issues arise, switch traffic back instantly. Configuration management is handled via a tool like HashiCorp Vault or AWS Parameter Store, ensuring secrets are injected at runtime. Finally, monitor logs, metrics, and alerts across the pipeline, and maintain a rollback plan that includes restoring previous data snapshots and image layers. This design guarantees that deployments are safe, validated, and data‑safe.