Prioritizing Microservices for Container Restore Operations
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Solution Overview
Problem
Containerized applications, which consist of multiple microservices, pose challenges in data protection operations due to their complex and dynamic nature, requiring systems and methods to discover and understand the components and relationships within these applications to effectively perform backup, restore, and replication operations.
Innovation Solution
The solution involves using a container platform and a service mesh platform to discover the topology of containerized applications by identifying components such as microservices, and prioritizing them for data protection operations, such as restore operations, by leveraging APIs and monitoring traffic patterns to determine the relationships and relative importance of these components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If containerized applications are updated frequently with multiple microservices, then application scalability and flexibility are improved, but data protection operation complexity increases
Solution Approach 1:
The patent segments the containerized application into individual microservices and further into components (containers, images, repositories). This segmentation allows the data protection system to manage each component independently, reducing the overall complexity of protecting the entire application. The system can discover, prioritize, and protect individual microservices rather than treating the application as a monolithic unit.
Solution Approach 2:
The patent implements preliminary discovery and prioritization actions before data protection operations. The system proactively discovers the topology of containerized applications, identifies microservices and their components, and prioritizes them based on importance metrics before backup or restore operations begin. This preliminary characterization simplifies subsequent data protection operations by having the work already organized and ranked.
2Ease of operation
If multiple microservices are updated independently, then application maintenance flexibility is improved, but understanding component relationships becomes more difficult
Solution Approach 1:
The patent implements feedback mechanisms that monitor and track relationships between microservices and their components. The system continuously discovers topology information, traffic patterns, and dependency relationships, using this feedback to update the prioritization metrics and understanding of component relationships. This ongoing feedback loop maintains accurate knowledge of how independently updated microservices relate to each other.
Solution Approach 2:
The patent introduces an intermediary data protection system that sits between the independently updated microservices and the protection operations. This intermediary discovers and maps the relationships between microservices, serving as a mediator that understands the topology and dependencies even when microservices are updated independently. It translates independent microservice updates into coordinated protection operations.
3Measurement precision
If comprehensive discovery of application components is performed, then data protection accuracy is improved, but system processing time increases
Solution Approach 1:
The patent applies local quality by prioritizing discovery and protection efforts for specific high-value components rather than uniformly processing all components. The system identifies and focuses on critical microservices and their essential components, allocating discovery and protection resources based on local importance metrics. This selective approach maintains data protection accuracy for critical components while reducing overall processing time.
Solution Approach 2:
The patent changes parameters by using prioritization metrics and rankings to dynamically adjust the scope and depth of discovery for different components. High-priority microservices receive comprehensive discovery and protection, while lower-priority components receive streamlined processing. This parameter-based differentiation maintains accuracy where needed while reducing processing time for less critical elements.
Data Source
AI summary
Systems and methods for discovering applications. An application may be discovered by determining a topology of the application in a containerized platform. Discovering the topology may include determining the components of the application and then determining relationships between the components. The relationships may include whether a component (e.g., a microservice) is user facing and may be based on traffic patterns between the components. The components or microservices may be prioritized or ranked based on the topology. The topology can be used when performing a data protection operation such as a restore operation.