Goxe

Goxe is a high-performance log reduction tool written in Go, designed to decrease noise in observability pipelines. It ingests logs via Syslog/UDP, normalizes and filters them, and aggregates identical or repetitive messages into a single-line format with an occurrence counter.

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• Intelligent message aggregation. Goxe automatically groups identical log entries after normalizing them. It removes timestamps, converts text to lowercase, and suppresses redundant whitespace to ensure accurate aggregation, displaying each unique message only once alongside its repeat count.
• Selective pattern filtering. Allows configuration of pattern-based filters to exclude or include specific logs. It offers detailed control over which messages are processed, ignoring those irrelevant for analysis or monitoring.
• Real-time log normalization. The tool applies normalization rules to each incoming entry. It eliminates variations like case differences, superfluous whitespace, and variable timestamps, preparing logs for consistent aggregation.
• Safe concurrent operation. Designed with a robust concurrency model, Goxe enables safe operations across multiple worker threads. It is free of race conditions, guaranteeing data integrity during parallel processing.
• Automatic log burst detection. Implements detection of message spikes or bursts with configurable limits and thresholds. This functionality prevents system saturation during sudden increases in log volume.
• Hot configuration reloading. Goxe supports updating configuration files without needing to restart the service. Changes are applied instantly, allowing for continuous adjustments with no downtime.
• Syslog/UDP ingestion. The program receives log data via the standard Syslog protocol over UDP, integrating easily into existing infrastructures that send logs using this common method.
• High throughput and low latency. Optimized to perform minimal memory allocations and maximize processing throughput. It is capable of handling thousands of logs per second with microsecond latencies.
• Storage cost reduction. By consolidating repetitive logs into single entries, it drastically decreases the total data volume. This directly translates to lower storage and bandwidth costs.
• Improved system visibility. Cleaning and aggregating logs removes noise, making it easier to identify recurring problems. Teams can focus on significant events without losing track of incidents.

The development story of Goxe began with the need to optimize observability pipelines, reducing log volume and noise without sacrificing critical information. The project is developed and maintained by contributors under the alias dumbnoxx. The application is written in the Go programming language, chosen for its excellent performance, native concurrency, and ability to create efficient, low-resource tools.

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