Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a system for cloud service deployment and particularly to a system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates.
Description of Related Art
[002] Cloud infrastructure has evolved into a multi-provider environment, where organizations often depend on several cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) to support diverse operational needs. This shift has been driven by the desire to avoid vendor lock-in, increase system redundancy, and improve cost efficiency. Despite this growing trend, each cloud provider maintains its own proprietary syntax and configuration approach for Infrastructure as Code (IaC), which creates a highly fragmented ecosystem.
[003] Tools like Terraform, AWS CloudFormation, and Azure Resource Manager allow developers to define and manage infrastructure programmatically, but they remain constrained within their respective ecosystems. As a result, efforts to migrate or replicate IaC templates between platforms often require manual rewriting or deep expertise in each tools of provider. The lack of a standardized or interoperable format limits automation potential and increases operational overhead, especially when rapid deployment or environment replication becomes necessary.
[004] Additionally, while some monitoring and configuration platforms claim multi-cloud capabilities, most fail to deliver real-time, intelligent control across heterogeneous environments. Solutions that offer automation typically rely on predefined rules rather than adaptable, AI-informed responses to infrastructure changes. This results in delays, inefficiencies, and increased risk during service disruptions.
[005] There is thus a need for an improved and advanced system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide a system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates. The system comprising an input engine configured to receive a source IaC template associated with a first cloud provider. The system further comprising a parsing engine configured to analyze the source IaC template using natural language processing (NLP) and syntax analysis to extract resource definitions and configuration parameters. The system further comprising a translation engine configured to identify equivalent resources for a target cloud provider and generate a translated IaC template by mapping source cloud resources to corresponding target cloud resources. The system further comprising a compliance engine configured to evaluate the translated IaC template for adherence to a security and configuration standards of the target cloud provider. The system further comprising an optimization engine configured to optimize the translated IaC template using AI-driven recommendations. The system further comprising a validation engine configured to validate the optimized IaC template for one or more of syntax correctness, deployment feasibility, or a combination thereof using cloud-specific validators and simulators. The system further comprising a deployment engine configured to deploy the translated IaC template to the target cloud provider.
[007] Embodiments in accordance with the present invention further provide a method for translating intelligent cloud-agnostic Infrastructure as Code (IaC). The method comprising steps of receiving, via an input interface, a source IaC template associated with a first cloud provider; parsing the source IaC template using natural language processing (NLP) and syntax analysis to extract resource definitions and configuration parameters; applying a machine learning model trained on cloud resource specifications to identify equivalent resources for a target cloud provider; generating a translated IaC template by mapping source cloud resources to corresponding target cloud resources; performing compliance checks on the translated IaC template based on a security and configuration standards of the target cloud provider; optimizing the translated IaC template for cost-efficiency, performance, and security using an AI-based optimization module; validating the optimized IaC template for syntax correctness and deployment feasibility using cloud-specific validators; and deploying the optimized IaC template to the target cloud provider.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide a system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates.
[009] Next, embodiments of the present application may provide a system for translating IaC templates that automatically translate infrastructure definitions from one cloud service provider to another, such as from Amazon Web Services to Microsoft Azure or Google Cloud Platform.
[0010] Next, embodiments of the present application may provide a system for translating IaC templates that significantly reduces the need for manual intervention.
[0011] Next, embodiments of the present application may provide a system for translating IaC templates that enables quicker setup and rollout of infrastructure by automating translation, validation, and deployment steps.
[0012] Next, embodiments of the present application may provide a system for translating IaC templates that evaluates the translated templates for performance, resource consumption, and compliance with the pricing models of target cloud platforms.
[0013] Next, embodiments of the present application may provide a system for translating IaC templates that continuously improves its performance by learning from previous translations and user feedback.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor an exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates a schematic block diagram of a system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a data flow diagram of a system for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for translating intelligent cloud-agnostic Infrastructure as Code (IaC), according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a schematic block diagram of a system 100 for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates among different service providers, according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to translate cloud infrastructure spanning various cloud providers. The system 100 may streamline the translation process through sophisticated Artificial Intelligence (AI) and Natural Language Processing (NLP) algorithms to translate IaC templates from a format of a cloud provider to another cloud provider. The system 100 may further be configured to eliminate a necessity for manual configuration and translation. The system 100 may further lower an operational overhead and may decrease errors, along with speeding up deployment of cloud frameworks. The system 100 may further feature multi-cloud environments that may be utilized by organizations that may operate to provide consistent infrastructure management with compliance with provider-specific policies.
[0025] According to the embodiments of the present invention, the system 100 may incorporate non-limiting hardware components to enhance the processing speed and efficiency such as the system 100 may comprise an input engine 102, a parsing engine 104, a translation engine 106, a compliance engine 108, an optimization engine 110, a validation engine 112, a deployment engine 114, a feedback engine 116, an interaction unit 118, and a dashboard 120. In an embodiment of the present invention, the hardware components of the system 100 may be integrated with computer-executable instructions for overcoming the challenges and the limitations of the existing systems.
[0026] In an embodiment of the present invention, the input engine 102 may be configured to receive a source IaC template associated with a first cloud provider. The source IaC template may comprise of preformats such as, but not limited to, a user input, a visible output, an invisible output, a data storage, a meta collection, and so forth. Embodiments of the present invention are intended to include or otherwise cover any pre-formats of the source IaC template, including known, related art, and/or later developed technologies. The first cloud provider may be, but not limited to, a Terraform, an Amazon Web Services (AWS) CloudFormation, an Azure Resource Manager (ARM), a Google Cloud Deployment Manager, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the first cloud provider, including known, related art, and/or later developed technologies.
[0027] In an embodiment of the present invention, the parsing engine 104 may be configured to analyze the source IaC template using natural language processing (NLP) and syntax analysis. The syntax analysis of the IaC template may extract resource definitions, configuration parameters, resources, dependencies, configurations, and so forth of the source IaC template.
[0028] In an embodiment of the present invention, the translation engine 106 may be configured to identify equivalent resources for a target cloud provider and generate a translated IaC template by mapping source cloud resources to corresponding target cloud resources.
[0029] The equivalent resources for the target cloud provider, with respect to the source cloud may be, but not limited to, virtual machines, storage instances, network configurations, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the resources, including known, related art, and/or later developed technologies, that may be considered equivalent for the target cloud provider.
[0030] Further, the translation engine 106 may be configured to link the translated IaC template with the target cloud provider. The linkage may be carried out using Application Programming Interfaces (APIs) of the target cloud provider.
[0031] In an embodiment of the present invention, the compliance engine 108 may be configured to evaluate the translated IaC template for adherence to a security and configuration standards of the target cloud provider.
[0032] Further, the compliance engine 108 may be configured to execute Artificial Intelligence (AI) computational techniques for AI verification of the translated IaC template. The verification may ensure a compliance with best practices and security policies of the target cloud provider.
[0033] Further, the compliance engine 108 may be configured to deploy contextual learning algorithms to detect errors in the translated IaC template. The detected errors may be further corrected and may offer suggestions for improved performance of the translated IaC template. The detected errors may be, but not limited to, misinterpretation of meta information, a syntax error, an edge case error, a time-inducing region based error, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the errors, including known, related art, and/or later developed technologies, that may be detected by the contextual learning algorithms.
[0034] In an embodiment of the present invention, the optimization engine 110 may be configured to optimize the translated IaC template using AI-driven recommendations.
[0035] The AI-driven recommendations may be, but not limited to, performance, cost, utilization of resources, reduction of cost, enhancement of resource efficiency, ensuring reliability, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the AI-driven recommendations, including known, related art, and/or later developed technologies.
[0036] In an embodiment of the present invention, the validation engine 112 may be configured to validate the optimized IaC template. The validation and optimization of the IaC template may induce functionality such as, but not limited to, syntax correctness, deployment feasibility, and so forth. The validation and optimization of the IaC template may be carried out using cloud-specific validators and simulators.
[0037] The cloud-specific validators may be, but not limited to, syntax errors, policy breaches, compatibility problems, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the cloud-specific validators, including known, related art, and/or later developed technologies.
[0038] In an embodiment of the present invention, the deployment engine 114 may be configured to deploy the translated IaC template to the target cloud provider.
[0039] In an embodiment of the present invention, the feedback engine 116 may be adapted to gather a real-time feedback from the target cloud provider.
[0040] The gathered feedback may be, but not limited to, an uptime, a downtime, a compatibility, a feasibility, and so forth. Embodiments of the present invention are intended to include or otherwise cover any gartered feedback, including known, related art, and/or later developed technologies.
[0041] The gathered feedback may further be applied enhance future translations and debug errors in the collected real-time feedback using a machine learning model. The machine learning model may be a reinforced learning model.
[0042] In an embodiment of the present invention, the interaction unit 118 may be adapted to enable a developer to modulate and visualize a progress of an ongoing translation. The interaction unit 118 may comprise the dashboard 120. In an embodiment of the present invention, the dashboard 120 may be adapted to enable a developer to monitor a status of an ongoing translation. The interaction unit 118 may be, but not limited to, a laptop, a smartphone, a server, a firmware, and so forth. In a preferred embodiment of the present invention, the interaction unit 118 may be an Augmented Reality (AR) based device. Embodiments of the present invention are intended to include or otherwise cover any type of the interaction unit 118, including known, related art, and/or later developed technologies.
[0043] FIG. 2 illustrates a data flow 200 diagram of the system 100, according to an embodiment of the present invention.
[0044] At step 202, the system 100 may receive the source IaC template from the input interface.
[0045] At step 204, the system 100 may preprocess and parse the source IaC template using the natural language processing (NLP) and the syntax analysis to extract the resource definitions and the configuration parameters.
[0046] At step 206, the system 100 may generate the translated IaC template by mapping the source cloud resources to the corresponding target cloud resources.
[0047] At step 208, the system 100 may conduct a cloud analysis of the translated IaC template.
[0048] At step 210, the system 100 may analyze and validate the translated IaC template by conducting compliance checks. Upon successful validation, the data flow 200 may proceed to a step 212. Else, the data flow 200 may proceed to a step 214.
[0049] At step 212, the system 100 may deploy the translated IaC template to the target cloud provider.
[0050] At step 214, the system 100 may re-translate the IaC template.
[0051] At step 216, the system 100 may monitor the deployment of the translated IaC template. Upon interruption of the deployed translated IaC template, the data flow 200 may proceed to a step 218. Else, the data flow 200 may conclude.
[0052] At step 218, the system 100 may optimize the translated IaC using the AI-based optimization module.
[0053] FIG. 3 depicts a flowchart of a method 300 for translating the intelligent cloud-agnostic Infrastructure as Code (IaC), according to an embodiment of the present invention.
[0054] At step 302, the system 100 may receive the source IaC template associated with the first cloud provider from the input interface.
[0055] At step 304, the system 100 may parse the source IaC template using the natural language processing (NLP) and the syntax analysis to extract the resource definitions and the configuration parameters.
[0056] At step 306, the system 100 may apply the machine learning model trained on the cloud resource specifications to identify the equivalent resources for the target cloud provider.
[0057] At step 308, the system 100 may generate the translated IaC template by mapping the source cloud resources to the corresponding target cloud resources.
[0058] At step 310, the system 100 may perform the compliance checks on the translated IaC template based on the security and the configuration standards of the target cloud provider.
[0059] At step 312, the system 100 may optimize the translated IaC template for cost-efficiency, performance, and security using the AI-based optimization module.
[0060] At step 314, the system 100 may validate the optimized IaC template for the syntax correctness and the deployment feasibility using the cloud-specific validators.
[0061] At step 316, the system 100 may deploy the optimized IaC template to the target cloud provider.
[0062] At step 318, the system 100 may gather the feedback from the target cloud provider for applying the gathered feedback to enhance the future translations using the machine learning model.
[0063] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0064] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. A system (100) for translating intelligent cloud-agnostic Infrastructure as Code (IaC) templates, the system (100) comprising:
an input engine (102) configured to receive a source IaC template associated with a first cloud provider;
a parsing engine (104) configured to analyze the source IaC template using natural language processing (NLP) and syntax analysis to extract resource definitions and configuration parameters;
a translation engine (106) configured to identify equivalent resources for a target cloud provider and generate a translated IaC template by mapping source cloud resources to corresponding target cloud resources;
a compliance engine (108) configured to evaluate the translated IaC template for adherence to a security and configuration standards of the target cloud provider;
an optimization engine (110) configured to optimize the translated IaC template using AI-driven recommendations;
a validation engine (112) configured to validate the optimized IaC template for one or more of syntax correctness, deployment feasibility, or a combination thereof using cloud-specific validators and simulators; and
a deployment engine (114) configured to deploy the translated IaC template to the target cloud provider.
2. The system (100) as claimed in claim 1, comprising a feedback engine (116) adapted to gather a feedback from the target cloud provider for applying the gathered feedback to enhance future translations using a machine learning model.
3. The system (100) as claimed in claim 1, wherein the first cloud provider is selected from a Terraform, an Amazon Web Services (AWS) CloudFormation, an Azure Resource Manager (ARM), a Google Cloud Deployment Manager, or a combination thereof.
4. The system (100) as claimed in claim 1, comprising a dashboard (120) adapted to enable a developer to monitor a status of an ongoing translation.
5. The system (100) as claimed in claim 1, comprising an interaction unit (118) adapted to enable a developer to modulate and visualize a progress of an ongoing translation.
6. A method (300) for translating intelligent cloud-agnostic Infrastructure as Code (IaC), the method (300) is characterized by steps of:
receiving, via an input interface, a source IaC template associated with a first cloud provider;
parsing the source IaC template using natural language processing (NLP) and syntax analysis to extract resource definitions and configuration parameters;
applying a machine learning model trained on cloud resource specifications to identify equivalent resources for a target cloud provider;
generating a translated IaC template by mapping source cloud resources to corresponding target cloud resources;
performing compliance checks on the translated IaC template based on a security and configuration standards of the target cloud provider;
optimizing the translated IaC template for cost-efficiency, performance, and security using an AI-based optimization module;
validating the optimized IaC template for syntax correctness and deployment feasibility using cloud-specific validators; and
deploying the optimized IaC template to the target cloud provider.
7. The method (300) as claimed in claim 6, comprising a step of gathering a feedback from the target cloud provider for applying the gathered feedback to enhance future translations using the machine learning model.
8. The method (300) as claimed in claim 6, wherein the first cloud provider is selected from a Terraform, an Amazon Web Services (AWS) CloudFormation, an Azure Resource Manager (ARM), a Google Cloud Deployment Manager, or a combination thereof.
9. The method (300) as claimed in claim 6, comprising a dashboard (120) adapted to enable a developer to monitor a status of an ongoing translation.
10. The method (300) as claimed in claim 6, comprising an interaction unit (118) adapted to enable a developer to modulate and visualize a progress of an ongoing translation.
Date: June 03, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant