Principle:Bentoml BentoML Deployment Lifecycle Management
Overview
Deployment Lifecycle Management is the principle of providing comprehensive APIs to manage the full lifecycle of cloud deployments, including updating, monitoring, listing, and scaling operations.
Concept
Managing the full lifecycle of cloud deployments requires APIs for updating running deployments, querying deployment status, listing all deployments, and monitoring health. These operations enable zero-downtime updates, fleet management, and operational visibility across a portfolio of deployed services.
Theory
Deployment lifecycle management provides APIs to update running deployments (rolling updates with new Bento versions), query deployment status, list all deployments, and monitor health. This supports zero-downtime updates and fleet management. The key capabilities include:
- Rolling updates - Deploy new Bento versions to running services without downtime using rolling update strategies that gradually replace old instances with new ones
- Status monitoring - Query the current state of any deployment to understand whether it is running, scaling, or experiencing issues
- Fleet management - List and filter deployments across clusters to maintain operational awareness of all running services
- Configuration updates - Modify scaling parameters, instance types, environment variables, and other settings on running deployments without redeployment
Update Operations
Updating a deployment allows changing:
- Bento version - Deploy a new version of the service code and model
- Scaling parameters - Adjust min/max replicas based on traffic patterns
- Instance type - Change compute resources (e.g., upgrade GPU type)
- Environment variables - Update configuration without code changes
- Secrets - Rotate or add new secret references
Updates are applied as rolling updates by default, ensuring zero downtime during the transition.
Query Operations
Get
Retrieve detailed information about a specific deployment by name, including:
- Current status and health
- Bento version running
- Scaling configuration
- Endpoint URL
- Creation and last update timestamps
List
Retrieve all deployments with optional filtering:
- By cluster - Filter to a specific cluster
- By search term - Full-text search across deployment names
- By query - Structured query filtering
- By labels - Filter by key-value metadata labels
Operational Workflow
- Deploy - Create initial deployment with
create() - Monitor - Check status with
get() - Update - Push new versions or adjust config with
update() - Scale - Adjust scaling parameters as traffic patterns emerge
- List - Review fleet status across all deployments with
list()
Metadata
| Property | Value |
|---|---|
| Principle | Deployment Lifecycle Management |
| Domain | ML_Serving, Cloud_Deployment, Operations |
| Workflow | BentoCloud_Deployment |
| Related Concepts | Rolling Updates, Fleet Management, Service Monitoring, Zero-Downtime Deployment |
| Implementation | Implementation:Bentoml_BentoML_Deployment_Update_Get_List |