Declarative Deployment Scheduling for Single-Tenant Cloud Systems
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Solution Overview
Problem
In multi-tenant cloud platforms, deploying updates and upgrades in single-tenant environments is challenging due to geographical dispersion of clients, varying customer preferences, and the risk of service interruptions during peak hours, which can lead to customer dissatisfaction and loss.
Innovation Solution
A declarative deployment file, referred to as a release train definition (RTD), is used to schedule and implement software updates by identifying maintenance windows, approved versions, and upgrade paths, ensuring that updates are deployed only when systems are not actively running processes, thereby minimizing downtime and optimizing processor and memory efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If updates are deployed in single-tenant environments to ensure data privacy and security, then reliability is improved, but deployment complexity increases due to geographical dispersion and varying client preferences
Solution Approach 1:
The patent segments the deployment process into distinct phases: identifying maintenance windows, validating deployment configurations, and executing updates. This segmentation allows complex deployment operations to be broken down into manageable steps, reducing overall deployment complexity while maintaining the reliability benefits of single-tenant environments.
Solution Approach 2:
The patent implements preliminary actions by first identifying maintenance windows and validating deployment configurations before executing updates. This preliminary validation phase ensures that updates are prepared and verified in advance, reducing the complexity of real-time deployment operations and ensuring successful updates in single-tenant environments.
2Productivity
If updates are deployed during peak hours to minimize downtime, then productivity is improved, but service interruptions and errors increase
Solution Approach 1:
The patent performs preliminary identification of maintenance windows and validation of deployment configurations before executing updates. This preliminary action ensures that updates are scheduled during appropriate time windows and validated in advance, preventing service interruptions during peak hours while maintaining productivity.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor system state and deployment progress. By receiving feedback about system status and deployment outcomes, the system can adjust deployment timing and configuration to avoid service interruptions during peak hours while maintaining efficient update cycles.
3Productivity
If deployment schedules are optimized to reduce maintenance windows, then productivity is improved, but system stability during peak hours deteriorates
Solution Approach 1:
The patent executes preliminary validation of deployment configurations and identification of maintenance windows before actual updates. This preliminary action allows the system to optimize deployment schedules efficiently while ensuring that updates are executed during appropriate time windows, maintaining system stability during peak hours.
Solution Approach 2:
The patent implements dynamic deployment scheduling that adapts to system load and operational requirements. The system dynamically adjusts deployment timing and duration based on real-time conditions, optimizing productivity while maintaining system stability during peak hours through flexible, adaptive scheduling.
Data Source
AI summary
A compute container system may support logical partitions for various single tenant systems. These logical partitions may be referred to as logical single-tenant system stacks. An operator or release manager for a logical partition may identify a declarative deployment file defining a deployment configuration for one or more of a plurality of logical single-tenant system stacks. The operator may determine a deployment schedule for implementing one or more system updates for the plurality of logical single-tenant system stacks based on the declarative deployment file and implement the system updates based on the determined deployment schedule.