Service Plan DAG Generation for Deterministic Data Center Bootstrapping
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Solution Overview
Problem
Conventional tools for building data centers in cloud infrastructure require significant manual effort, are prone to errors, and lack deterministic planning, leading to increased time and complexity in the region build process.
Innovation Solution
The implementation of Service Plans and Manifests (SPAMs) to generate a deterministic specification for bootstrapping data centers, utilizing directed acyclic graphs to identify the expected order of releases and dependencies, along with the use of skills to track progress and improve root cause analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional tools are used for building data centers, then manual effort can be applied flexibly, but the process is prone to errors and lacks deterministic planning
Solution Approach 1:
The patent segments the complex data center build process into discrete, manageable components represented as nodes in a directed acyclic graph. Each node represents a specific task or milestone, and edges represent dependencies between them. This segmentation enables deterministic planning by breaking down the orchestration process into structured, traceable units that can be automatically managed.
Solution Approach 2:
The patent introduces an intermediary system that automatically generates and manages the service plan based on the directed acyclic graph. This intermediary layer sits between the manual input and the execution process, providing deterministic planning by automatically determining the correct sequence of operations and dependencies, thereby reducing manual orchestration complexity while improving reliability.
2Productivity
If manual effort is used for orchestrating provisioning and deployment, then flexibility is maintained, but significant time and effort are required
Solution Approach 1:
The patent applies preliminary action by pre-defining the directed acyclic graph structure that represents all possible tasks and their dependencies before actual execution. The service plan is generated in advance based on this graph, allowing the system to automatically determine the optimal execution sequence without requiring manual orchestration during the actual build process, thereby significantly reducing orchestration time while maintaining high productivity.
3Adaptability or versatility
If the number of service teams and regions grows, then service coverage increases, but the tasks for orchestrating provisioning and deployment drastically increase
Solution Approach 1:
The patent creates a universal directed acyclic graph framework that can accommodate multiple service teams and regions through a single standardized structure. The graph nodes and edges represent generic task dependencies that can be instantiated for different services and regions without requiring separate orchestration logic for each, thereby enabling service coverage expansion without proportionally increasing orchestration complexity.
4Ease of operation
If conventional tools are used for region build, then existing processes can be maintained, but accuracy and ease of use are compromised
Solution Approach 1:
The patent implements self-service by enabling the system to automatically generate the service plan and determine the correct execution sequence without requiring manual intervention. The directed acyclic graph structure allows the system to self-determine dependencies and orchestrate tasks automatically, improving ease of use by eliminating complex manual orchestration while simultaneously improving build accuracy through deterministic, rule-based execution planning.
Data Source
AI summary
System, methods, and devices are disclosed for generating code segments of a service plan that represents a process for bootstrapping a service. A first directed acyclic graph (DAG) comprising a first plurality of edges and a first plurality of nodes representing releases and dependencies between releases of a process for bootstrapping a plurality of services may be obtained. A second DAG may be generated from the first based on executing a clustering procedure. A third DAG that is specific to the service may be generated based on traversing the second DAG. Code segments of a service plan may be generated based at least in part on the third DAG.