Automated Disaster Recovery Workflow Generation
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Solution Overview
Problem
Current disaster recovery operations in enterprise IT environments are labor-intensive and time-consuming, particularly for non-virtualized and non-cloud-based systems, where manual codification of recovery processes is required, lacking effective automation solutions.
Innovation Solution
A Recovery as a Service (RaaS) system that includes a Resource Planning System (RPS), Configuration Management Database (CMDB), and Asset Reservation System (ARS), enabling automated generation and execution of disaster recovery plans by specifying recovery scope at a high level, such as applications, and programmatically generating recovery workflows for orchestration engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual codification of recovery processes is used for each application and data center scenario, then disaster recovery can be achieved, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The system performs preliminary actions by automatically discovering production infrastructure components and their relationships before disasters occur. The CMDB is pre-populated with configuration information about applications, servers, storage, and networking devices, along with their dependencies. Recovery workflows are pre-defined based on this discovered topology, so when a disaster occurs, the system can immediately execute appropriate recovery procedures without manual codification or analysis.
Solution Approach 2:
The system enables self-service disaster recovery by automatically discovering infrastructure, generating recovery workflows, and executing recovery operations without requiring manual intervention. The automated discovery process identifies production components and their relationships, the workflow generator creates recovery procedures based on this information, and the execution system automatically carries out recovery when disasters occur, eliminating the need for manual codification of recovery processes for each scenario.
2Ease of operation
If task level automation tools are used to free human operators, then operators can focus on orchestration coding, but the overall solution still requires manual programming of procedures and task sequences
Solution Approach 1:
The system performs self-service by automatically generating recovery workflows from discovered infrastructure topology. The workflow generator component analyzes the CMDB data containing production components and their relationships, then automatically creates appropriate recovery procedures and task sequences without requiring human programmers. This eliminates the need for manual programming of orchestration logic while still providing comprehensive automated recovery capabilities.
Solution Approach 2:
The system replaces the mechanical process of manual programming with an automated generation process. Instead of human operators writing procedural code to define task sequences and orchestration logic, the workflow generator automatically creates these artifacts by analyzing infrastructure configuration data from the CMDB. This substitution transforms a manual, error-prone programming task into an automated, consistent generation process.
3Extent of automation
If point-to-point integration with Run Book Automation solutions is implemented, then automated management can be achieved, but coordination becomes complex involving multiple products and services
Solution Approach 1:
The system merges multiple automation capabilities into a unified integrated platform. The automated discovery process, CMDB population, workflow generation, and recovery execution are combined into a single cohesive system rather than requiring separate point-to-point integrations between multiple products. This unified approach eliminates the coordination complexity that arises from integrating provisioning engines, functional products, and security solutions separately.
Solution Approach 2:
The system provides universal functionality by implementing a comprehensive automated disaster recovery solution that handles infrastructure discovery, configuration management, workflow generation, and execution within a single platform. This multi-functional approach replaces the need for multiple specialized tools that would require complex point-to-point integration, as the unified system can perform all necessary functions for automated disaster recovery across diverse infrastructure scenarios.
Data Source
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AI summary
A Recovery as a Service (RaaS) system including a Configuration Management Database (CMDB), a Resource Planning System (RPS), a Recovery Execution System (RES), and an Asset Reservation System (ARS). A scope for a test or recovery is specified as one or more applications. In one implementation, the RPS can request, from the CMDB, identification of which protected resources are within the requested scope and request the ARS to only reserve assets within that scope. At time of test or disaster, the RES programmatically generates a recovery workflow and initiates its orchestration such as provisioning and/or configuring operating systems, file systems, networks, applications, and data, and executing startup processes. If there are exceptions to automated workflow, then operations personnel may perform corresponding manual operations such as through a ticketing system.