Container Backup Jobs Using Mount Propagation for Persistent Volumes
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Solution Overview
Problem
In containerized systems, traditional data protection methods require agents installed alongside applications and struggle to adapt to dynamic environments where pods are rescheduled, leading to challenges in efficiently backing up and restoring data.
Innovation Solution
Implementing a job controller to spin up backup and restore jobs that utilize mount propagation to access persistent volumes, ensuring scheduling on the same worker node through node affinity rules, and storing deduplicated backup artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data protection systems with agents are used in containerized environments, then backup and restore operations can be performed, but the systems cannot adapt to pod rescheduling and dynamic node changes
Solution Approach 1:
The patent introduces a job controller as an intermediary component that mediates between the data protection system and the dynamic containerized environment. The job controller monitors pod status, tracks volume locations, and dynamically adjusts backup operations when pods are rescheduled, enabling the system to adapt to changes while maintaining data protection reliability
Solution Approach 2:
The system implements dynamic adaptation mechanisms where the job controller continuously monitors the containerized environment, detects pod rescheduling events, and automatically updates backup job configurations. This dynamic response to environmental changes allows the system to maintain reliability despite the mobility of pods across nodes
2Reliability
If pods are rescheduled to different nodes for load balancing and fault tolerance, then system reliability is improved, but data protection systems lose track of volume locations and cannot perform backup operations
Solution Approach 1:
The job controller implements a feedback mechanism that continuously monitors pod status and volume location information. When pods are rescheduled to different nodes, the feedback loop detects these changes and triggers automatic updates to backup job configurations, ensuring that backup operations can always locate and access the required volumes regardless of their current node location
Solution Approach 2:
The system performs preliminary actions by pre-configuring backup jobs with volume location information and establishing monitoring mechanisms before rescheduling events occur. This proactive approach ensures that when pods are moved to different nodes, the data protection system is already prepared to track and access the volumes at their new locations
3Productivity
If backup artifacts are stored without deduplication, then storage speed is improved, but storage space is wasted and efficiency decreases
Solution Approach 1:
The system changes the storage parameter from raw duplicate storage to deduplicated storage by implementing deduplication algorithms that identify and eliminate redundant data blocks. This parameter change reduces the quantity of stored data while maintaining backup efficiency, as the deduplication process is performed during the backup operation without significantly impacting overall productivity
Data Source
AI summary
Methods and systems for backing up and restoring data on a worker node are described. According to some embodiments, the method includes using a job controller to spin up one or more backup jobs in the worker node. The method further includes utilizing, by the backup jobs, mount propagation to access one or more persistent volumes of a pod on the worker node. The method further includes performing, by the backup jobs, backup tasks on the persistent volumes. The method further includes applying a set of rules used by a scheduler to determine a location of the pod in order to ensure the backup jobs are scheduled on a same worker node. The method further includes storing, by the backup jobs, backup artifacts generated by the backup tasks, wherein the backup artifacts include deduplicated data.