Cloud Scheduler for Multitenant Automation
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Solution Overview
Problem
Existing data center automation solutions, such as cron, face challenges in efficiently managing scheduling across multiple cloud services and platforms, leading to increased manual overhead and limited scalability.
Innovation Solution
A cloud scheduler service that provides a fully managed scheduler, supporting multitenancy and integration with various platforms, enabling centralized and convenient scheduling of tasks across multiple cloud services and platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing data center automation solutions such as cron are used, then basic scheduling functionality is provided, but manual overhead increases and scalability is limited
Solution Approach 1:
The cloud scheduler service enables self-service scheduling by providing a centralized platform where users can define, manage, and execute scheduled tasks without manual intervention in the scheduling mechanism itself. The system automatically handles task dispatching, timing, and coordination across multiple cloud services, eliminating the need for manual overhead associated with traditional cron-based solutions.
2Productivity
If centralized scheduling is implemented, then scalability is improved, but system complexity increases
Solution Approach 1:
The cloud scheduler service segments the scheduling system into independent, modular components that can be distributed across multiple cloud services and platforms. Each cloud service maintains its own scheduling instances while coordinating through standardized interfaces, enabling scalability without requiring complete system reconfiguration. This segmentation allows the system to handle tens of thousands of automations across multiple tenants while maintaining manageable complexity through standardized protocols.
3Adaptability or versatility
If multi-tenant scheduling is supported, then versatility is improved, but resource allocation complexity increases
Solution Approach 1:
The cloud scheduler service implements universality by providing a single centralized platform that serves multiple tenants and cloud services through standardized scheduling interfaces. The system uses uniform resource allocation mechanisms that work across different cloud providers and service types, allowing diverse scheduling needs to be met through a common framework. This universal approach enables support for tens of thousands of automations across multiple tenants while managing resource allocation complexity through standardized protocols and shared infrastructure.
Data Source
AI summary
The present disclosure is related to devices, systems, and methods for a cloud scheduler. An example method can include receiving a schedule associated with an automation task to be performed in a virtualized environment via a REST API, wherein the task is associated with a target, associating the schedule with a partition, storing the schedule in a cache store responsive to determining that the schedule is to be invoked within a threshold time period, and receiving the schedule from the cache store and invoking the target responsive to the schedule becoming overdue.