Software Deployment Control via Desired State Comparison
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Solution Overview
Problem
The complexity of deploying software components in distributed networks makes conventional manual installation tedious and prone to errors, and existing solutions require all components to be deployed simultaneously, limiting testing and scalability.
Innovation Solution
A method that uses a description file to define the desired state of a computer infrastructure, allowing for the generation of a plan script to deploy only necessary software components, enabling partial execution and optimization for efficiency and testability, with a deployment control system that compares the desired and live states to determine deltas and generate deployment commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual installation of software components is performed by system administrators, then deployment can be performed, but the process becomes tedious and susceptible to human error
Solution Approach 1:
The system enables self-service deployment by allowing administrators to define desired state through description files without manually writing deployment scripts. The deployment control center automatically parses the description file, compares it with live state, and generates execution plans, eliminating the need for administrators to manually edit deployment scripts and reducing human error in the process
Solution Approach 2:
The patent replaces manual mechanical operations (typing commands, editing scripts) with automated computational processes. The deployment control center uses automated parsing, comparison, and code generation mechanisms to substitute for manual script writing and execution, thereby improving reliability while maintaining ease of operation
2Productivity
If ad hoc series of scripts are coded by administrators to deploy software components, then deployment can be automated, but the scripts are hard to maintain and scale poorly
Solution Approach 1:
The system segments the deployment process into distinct phases: describing desired state via description files, determining live state, comparing states to identify deltas, and generating execution plans. This segmentation separates the high-level deployment logic from low-level execution details, making the system easier to maintain and scale compared to monolithic ad hoc scripts
Solution Approach 2:
The deployment control center serves multiple functions within a single system: parsing description files, determining live state, comparing states, generating plans, and executing deployments. This multi-functionality eliminates the need for multiple separate scripts and tools, reducing complexity and improving maintainability while maintaining automation
3Reliability
If all software components are deployed at once, then complete system deployment is achieved, but the capability to test individual component deployment is limited
Solution Approach 1:
The system segments software deployment into individual component-level operations. By comparing live state with desired state, the system identifies which specific components need deployment and can execute them independently. This enables testing of individual component deployment without requiring deployment of the entire system, thereby improving both completeness and adaptability
4Reliability
If infrastructure is made unavailable during software component deployment, then deployment can be performed, but infrastructure downtime increases
Solution Approach 1:
The system dynamically adjusts deployment timing and sequencing based on component dependencies and infrastructure availability. Rather than requiring complete infrastructure unavailability, the deployment control center can schedule deployments during appropriate windows and sequence operations to minimize disruption, thereby reducing downtime while maintaining deployment success
Data Source
AI summary
Systems and methods of deploying one or more software components to a target computer infrastructure are disclosed. A descriptor file that declares a desired state of one or more target computing devices of a target computer infrastructure is parsed. A live state of the one or more target computing devices is obtained. A set of target computing devices having the live state different from the desired state is identified. A plan script that includes deployment commands configured to deploy one or more software components to each computing device is generated. The plan script can be optimized such that when executed the software components are deployed with higher efficiency, system stability, minimum downtime, etc.