Containerized Application Recovery Workflow From Legacy Backup Plans
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Solution Overview
Problem
Current data protection methods for containerized applications fail to provide guidance on creating tailored data protection plans and recovery workflows, especially for imperative applications lacking known workflow artifacts, requiring users with deep knowledge to manually create backup and restore processes.
Innovation Solution
A system comprising a processor that executes components to identify new imperative applications, analyze required resources, determine recovery steps, and iteratively update recovery plans using legacy plans until a failure-free plan is developed, leveraging generative AI for optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current data protection methods are used to move data to storage targets, then data can be backed up, but recovery guidance and tailored protection plans are not provided
Solution Approach 1:
The system automatically generates recovery workflows and protection plans by analyzing application metadata and dependencies, eliminating the need for manual recovery guidance creation. The automated analysis component extracts recovery information from application manifests and generates tailored workflows without requiring user expertise.
Solution Approach 2:
The system performs preliminary analysis of application metadata, dependencies, and resource requirements before actual recovery operations are needed. This advance preparation enables the system to generate appropriate recovery workflows and protection plans in advance, so they are ready when needed without requiring manual intervention.
2Adaptability or versatility
If manual recovery workflows are created for imperative applications, then recovery can be customized, but deep user knowledge is required
Solution Approach 1:
The automated analysis component examines application metadata, container configurations, and dependency relationships to automatically generate customized recovery workflows. This eliminates the need for users to manually create recovery plans while still achieving application-specific customization through automated analysis of the application's actual structure and requirements.
Solution Approach 2:
The system changes the parameters of recovery workflow generation by automatically analyzing application-specific metadata, resource requirements, and dependency graphs. This allows the system to adapt recovery plans to specific applications without requiring manual configuration, as the analysis component automatically extracts and processes application parameters to generate appropriate recovery strategies.
3Reliability
If all application resources are backed up, then complete recovery is ensured, but unnecessary backups consume resources
Solution Approach 1:
The analysis component extracts and identifies only the essential application resources and dependencies that are actually required for successful recovery. By separating critical resources from non-essential ones, the system generates protection plans that backup only what is necessary, eliminating redundant backup operations and reducing resource consumption while maintaining recovery completeness.
Solution Approach 2:
The system applies partial action by backing up only the specific subset of resources identified as essential for recovery, rather than backing up all possible application resources. The automated analysis determines the minimum necessary resources to restore the application, avoiding excessive backup operations on unnecessary components.
4Reliability
If recovery workflows are created for new imperative applications, then application recovery is enabled, but workflow development time is required
Solution Approach 1:
The system performs preliminary automated analysis of application metadata, container configurations, and dependency relationships before recovery is needed. This advance analysis generates the recovery workflow and protection plan automatically, eliminating the time-consuming manual workflow development process while ensuring recovery capability is in place before actual recovery operations are required.
Solution Approach 2:
The system generates recovery workflows autonomously by analyzing application-specific metadata and dependency graphs, eliminating the need for manual workflow creation time. The automated analysis component processes application information and generates tailored recovery plans instantly, reducing workflow development time to near zero while maintaining application-specific recovery capability.
Data Source
AI summary
A system includes a processor that executes computer executable components stored in a memory. The computer executable components include an application identification component that identifies a new imperative application where recovery workflow for the new imperative application is unavailable. The computer executable components include an analysis component that analyzes the new imperative application to determine resources required to be protected; the analysis component determines an order of steps to be performed within a workflow to guarantee recovery of the new imperative application. The computer executable components include a recovery design component that utilizes a subset of legacy recovery plans to create, at least in part, a preliminary recovery plan for the new imperative application; the recovery design component tests the preliminary recovery plan and iteratively updates the preliminary recovery plan until a failure-free recovery plan is developed for the new imperative application.