Distributed Log Collector Architecture for Scalable Event Data Management
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Solution Overview
Problem
Existing logging systems, particularly those with a single server or replicated database, face challenges in scalability and fault tolerance when handling large volumes of event logs generated by security appliances like firewalls, leading to storage and retrieval inefficiencies.
Innovation Solution
A distributed log collector system with clustered log collectors that utilize virtual loggers, load balancing, and data replication to manage and store event logs efficiently, allowing for incremental scalability and high availability by distributing data across multiple servers and enabling seamless addition or removal of storage capacity without disrupting operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single server or replicated database is used for logging, then the system structure is simple, but scalability and fault tolerance are limited
Solution Approach 1:
The system divides the logging infrastructure into multiple independent log collector servers, each capable of receiving and processing log data. This segmentation allows the system to scale horizontally by adding more servers while maintaining fault tolerance, as each server operates independently and can continue functioning even if others fail.
Solution Approach 2:
The patent introduces log data storage and management as an intermediary layer between log sources and analysis tools. This intermediary handles data distribution, storage, and retrieval across multiple servers, enabling scalable architecture without requiring complex direct connections between all system components.
2Device complexity
If a single server or replicated database is used for logging, then the system structure is simple, but scalability is limited
Solution Approach 1:
The logging system is segmented into multiple independent log collector servers that can be added or removed based on demand. Each server handles a portion of the log data load, enabling linear scalability as more servers are introduced to the distributed system.
Solution Approach 2:
The system transitions from vertical scaling (adding more resources to a single server) to horizontal scaling (adding more servers to the network). This dimensional shift enables unlimited scalability by simply adding more log collector servers to handle increasing log data volumes.
3Device complexity
If log data is stored centrally, then retrieval is simplified, but storage capacity and performance are constrained
Solution Approach 1:
Log data storage is segmented across multiple distributed servers rather than concentrated in a single central repository. Each server stores a portion of the log data, collectively providing massive distributed storage capacity that scales with the number of servers in the system.
Solution Approach 2:
The system moves from single-point central storage to distributed multi-point storage across the network. This transformation enables storage capacity to scale horizontally with the addition of more servers, eliminating the storage constraints of a single central system.
4Reliability
If a distributed system is implemented, then scalability and fault tolerance are improved, but system complexity increases
Solution Approach 1:
The patent introduces standardized log data formats and protocols as intermediaries that simplify communication between distributed log collectors and management systems. This standardization layer abstracts the complexity of distributed operations, making the system easier to manage despite its distributed nature.
Solution Approach 2:
Each log collector server is designed as a universal, multi-functional unit that can independently receive, store, process, and forward log data. This universality reduces system complexity by eliminating the need for specialized components, as any server can perform any logging function.
Data Source
AI summary
A distributed log collector and report generation architecture is disclosed. In some embodiments, a received query to generate a log report is forwarded to each of a plurality of log collector clusters, and responses to the query received from each of at least a subset of the plurality of log collector clusters are aggregated to generate the log report.