Batch Logging in Distributed Memory for Cluster Performance
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Solution Overview
Problem
Centralized logging in computing clusters faces performance bottlenecks and complexity in diagnosing failures due to the accumulation of log messages across multiple hosts, leading to time-consuming and error-prone manual processes, especially in dynamic cloud environments where hosts are transient.
Innovation Solution
Implementing a distributed memory system for logging across multiple hosts, where log messages are intercepted by handlers and communicated through log proxy logic to a decentralized memory, allowing for scalable and dynamic handling of log data without bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If centralized logging is used to collect all log messages in a cluster system, then log collection completeness is improved, but system performance deteriorates due to bottlenecks at the single host responsible for capturing and writing logs
Solution Approach 1:
The patent divides the centralized logging system into multiple distributed logging hosts that collectively capture log messages from cluster components. Instead of a single host handling all logging, the system segments logging responsibilities across multiple hosts, with each host maintaining a portion of the log data. This segmentation eliminates the performance bottleneck while preserving complete log collection through the distributed architecture.
2Measurement precision
If manual collection and correlation of log files from multiple hosts is performed, then diagnostic accuracy is improved, but time consumption increases significantly
Solution Approach 1:
The patent implements preliminary action by automatically collecting, correlating, and organizing log messages from multiple hosts before diagnostic analysis is needed. The system proactively gathers log data, establishes temporal and causal relationships between events, and prepares diagnostic information in advance. This preliminary processing eliminates the need for manual log collection and correlation when failures occur, significantly reducing diagnostic time while maintaining accuracy.
3Measurement precision
If administrators manually view and correlate log files to find the root cause of failures, then diagnostic thoroughness is improved, but complexity of the process increases
Solution Approach 1:
The patent implements feedback mechanisms that automatically analyze log messages, identify anomalies, and provide diagnostic recommendations to administrators. The system continuously monitors log data, compares it against expected patterns, and feeds back diagnostic insights that guide the investigation process. This automated feedback reduces the complexity of manual log analysis while maintaining thorough diagnostic capability by highlighting relevant information and potential root causes.
4Reliability
If log files are stored in isolated locations for each component, then logging independence is improved, but ease of operation deteriorates due to difficulty in accessing and correlating logs across hundreds of hosts
Solution Approach 1:
The patent implements a universal logging interface that allows components to maintain independent logging while providing standardized access to log data across the distributed system. The system uses a common protocol and data format that enables log messages from different components and hosts to be uniformly accessed and correlated. This universal interface preserves logging independence at the component level while dramatically improving ease of operation for administrators needing to access logs across the entire cluster.
Data Source
AI summary
Systems, methods, and other embodiments associated with logging event messages in a computing grid using a distributed memory are described. In one embodiment, a method includes storing, in a distributed memory, a batch of log messages received from one of a plurality of handlers. Storing the batch in the distributed memory includes storing the batch in one of a plurality of memories that are part of the distributed memory and storing the batch with a group of batches from the plurality of handlers. The example method may also include generating, after a predefined period of time has elapsed, a formal log from the group of batches. The predefined period of time is an amount of time after a reporting period within which batches from the reporting period are expected to arrive in the distributed memory. The formal log includes sorted messages from the group of batches.