Orchestration Pipeline for Segmented Computing Resources
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Solution Overview
Problem
Organizations face challenges in configuring and managing computing infrastructure as they grow, often encountering inadequate or excessive resources, leading to inefficiencies and resource wastage, and there is a need for a system that can efficiently deploy, maintain, and modify computing platforms while ensuring security and resource optimization.
Innovation Solution
The implementation of computing platform definitions that outline the devices and executables to be deployed, along with build dependencies, deployment sequences, test cases, code standards, and enforcement standards, facilitated by an orchestration pipeline that automates the build, deploy, test, scan, and enforce stages, ensuring alignment with defined specifications and standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration and management of computing infrastructure is performed, then flexibility and control are maintained, but time consumption and operational complexity increase significantly
Solution Approach 1:
The system enables self-service through automated orchestration pipelines that automatically execute build, deploy, test, scan, and enforce operations without manual intervention. The pipeline reads computing platform definitions, retrieves necessary artifacts, and performs all deployment steps autonomously, eliminating the need for manual configuration while maintaining full control through defined parameters and standards.
Solution Approach 2:
The system performs preliminary action by pre-defining computing platform specifications, build dependencies, deployment sequences, test cases, code standards, and enforcement standards before actual deployment. These predefined configurations are stored and readily available, allowing the orchestration pipeline to execute deployments rapidly without ad-hoc configuration during the deployment process.
2Adaptability or versatility
If computing resources are increased to meet growing organizational needs, then system capacity and performance improve, but resource wastage and cost increase
Solution Approach 1:
The system implements dynamics by enabling flexible adjustment of computing platform configurations through parameterized definitions. Organizations can dynamically scale resources up or down based on actual needs, and the orchestration pipeline can reconfigure platforms by retrieving updated definitions and re-executing deployment sequences, ensuring resources match organizational requirements without wastage.
Solution Approach 2:
The system utilizes parameter changes by modifying computing platform definition parameters (such as device specifications, executable configurations, resource allocations) to adapt infrastructure to changing organizational needs. The orchestration pipeline reads updated parameters from definitions and automatically adjusts resource provisioning, maintaining optimal resource efficiency while supporting growth.
3Reliability
If comprehensive security measures and compliance standards are implemented, then system security and reliability improve, but system complexity and implementation difficulty increase
Solution Approach 1:
The system merges security measures and compliance checks into the unified orchestration pipeline. Security scanning, code standard verification, and enforcement standard validation are combined with build, deploy, and test operations in a single automated workflow. This integration maintains comprehensive security and reliability while reducing implementation complexity by managing all security aspects through one coordinated system rather than separate manual processes.
4Productivity
If automated orchestration pipelines are implemented, then deployment efficiency and consistency improve, but initial system setup complexity and resource requirements increase
Solution Approach 1:
The orchestration pipeline implements universality by designing a multi-functional system that handles build, deploy, test, scan, and enforce operations through a single unified workflow. The pipeline uses standardized definitions and parameters that can apply across multiple computing platforms and scenarios, reducing setup complexity through reuse and standardization while maintaining high deployment efficiency and consistency across diverse platforms.
Data Source
AI summary
Aspects of the disclosure are directed to utilizing a computing platform definition to operate an orchestration pipeline for a computing platform conforming to that computing platform definition. The computing platform definition may indicate the devices and the executables to be deployed to the computing platform. The orchestration pipeline may include multiple stages such as a build stage that builds the executables, a deploy stage that deploys the executables, a test stage that initiates execution of test cases, an scan stage that applies code standards to the source code of the executables, and an enforce stage that determines an extent to which the computing platform deviates from the computing platform definition. Performing a stage of the orchestration pipeline may include detecting a trigger for the stage, retrieving entries associated with the stage from the computing platform definition, and controlling execution of the stage based on the entries retrieved.