Agentless GitOps Orchestration via Cloud SMO Platform
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Solution Overview
Problem
Traditional systems for cloud-based infrastructure and cluster orchestration using GitOps rely on agents that consume resources, pose security risks, and lack direct connection with Git repositories, making them inefficient and insecure for managing infrastructure and cluster lifecycles.
Innovation Solution
An agentless GitOps system with a Service Management and Orchestration (SMO) platform that uses Git webhooks for notifications and has read-only access to Git repositories, eliminating the need for agents on clusters and enabling secure, efficient management of infrastructure and cluster orchestrations through continuous delivery and life cycle operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional GitOps systems use agents for service orchestration, then service orchestration capability is improved, but computational resources (CPU and memory) are consumed and security risks increase
Solution Approach 1:
The patent extracts the GitOps agent from the edge cluster environment and relocates it to the cloud-based automation platform. This removes the computational burden from edge devices while maintaining orchestration capabilities. The agent now runs remotely, pulling configuration data from Git repositories and pushing updates without requiring local execution on resource-constrained edge clusters.
Solution Approach 2:
The patent introduces a cloud-based automation platform as an intermediary between the Git repository and edge clusters. This mediator handles all GitOps operations, including configuration management and service orchestration, eliminating the need for agents on edge devices. The platform uses webhooks and API interactions to communicate with clusters, providing orchestration capabilities without local resource consumption.
2Adaptability or versatility
If traditional GitOps systems use agents with read-write access, then service orchestration flexibility is improved, but security risks increase
Solution Approach 1:
The patent applies different access permissions to different components of the system. The cloud-based automation platform is granted read-write access to Git repositories for configuration management, while edge clusters receive only read-only access through webhook subscriptions. This localized permission assignment maintains operational flexibility for the platform while securing the edge environment against unauthorized modifications.
Solution Approach 2:
Instead of giving agents read-write access to edge clusters (traditional approach), the patent inverts the model by giving the cloud platform read-write access to Git repositories while edge clusters maintain read-only status. This reversal of access patterns achieves both flexibility and security by centralizing write operations in a controlled environment.
3Productivity
If agents are deployed on edge clusters for GitOps, then continuous delivery capability is improved, but device complexity increases
Solution Approach 1:
The patent merges the GitOps agent functionality with the cloud-based automation platform, combining configuration management, continuous delivery, and service orchestration capabilities into a single centralized system. This consolidation eliminates the need for separate agent installations on each edge cluster, reducing device complexity while maintaining continuous delivery capabilities through the unified platform.
4Extent of automation
If traditional systems use integrated agents for orchestration, then infrastructure management capability is improved, but resource availability for applications decreases
Solution Approach 1:
The patent extracts the orchestration agent from the edge cluster environment and places it in the cloud, removing the computational overhead from application-hosting devices. This extraction ensures that CPU, memory, and storage resources on edge clusters are fully available for running applications while the cloud platform handles all infrastructure management tasks remotely.
Data Source
AI summary
Systems and methods for agentless GitOps and custom resources for managing infrastructure orchestration and cluster orchestration. A system includes a plurality of bare metal servers forming an infrastructure orchestration for a cloud native platform, and a plurality of clusters running on the plurality of bare metal servers, wherein the plurality of clusters forms a cluster orchestration. The system includes a data center automation platform executed by one or more of the plurality of clusters, wherein the data center automation platform subscribes to a git repository to receive updates pertaining to one or more of the infrastructure orchestration or the cluster orchestration, and wherein the data center automation platform executes continuous delivery (CD) for each of the infrastructure orchestration and the cluster orchestration based at least in part on data received from the git repository.