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Bylastic: A Log Classifier Compatible with Elastic

Introduction

Bylastic is an advanced AI-based log classification model specifically designed to categorize records into three levels: ERROR, WARNING, and INFO. Created by Byviz Analytics, this model is fully optimized for integration with Elastic, offering an efficient and accurate solution for log management and analysis.

Key Features

  • Accurate Classification: Bylastic classifies logs into three critical categories: ERROR, WARNING, and INFO, helping to quickly identify problems, warnings, and general system information.
  • Full Elastic Compatibility: Designed to seamlessly integrate with Elastic, Bylastic facilitates data ingestion and analysis within the Elastic ecosystem.
  • High Performance: Optimized to process large volumes of logs, ensuring fast and efficient performance even in high-demand environments.
  • Easy Integration: Bylastic can be easily integrated into your existing log processing pipelines, reducing implementation time and associated costs.

Precision Bylastic vs Bert

Precision in categorizing logs with example data, Bert cannot identify the categories image/png

Requeriments Bylastic vs Bert

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How It Works

Bylastic utilizes advanced natural language processing (NLP) techniques, a branch of artificial intelligence (AI), to analyze and categorize logs. The model has been trained with a diverse set of log data, ensuring high accuracy in classification.

Log Categories

  • ERROR: Logs indicating critical failures or serious problems that require immediate attention.
  • WARNING: Logs indicating potential issues that could become errors if not properly managed.
  • INFO: Informational logs that provide details about the normal functioning of the system.

Integration with Elastic

Integrating Bylastic with Elastic is straightforward and direct. Here is a quick guide to integrate the model into your Elastic environment:

  1. Installation: Download Bylastic from Hugging Face.
  2. Upload the Model: Use eland to upload the model to your Elastic cluster.
  3. Create an inference pipeline in Elastic

Benefits

  • Improved Log Management: Facilitates the identification and resolution of issues by automatically classifying logs.
  • Time Savings: Reduces the time required to manually review and categorize logs.
  • Higher Accuracy: Minimizes human errors in log classification.
  • Easy Integration: Seamlessly integrates with Elastic, leveraging Elastic's advanced search and analysis capabilities.

Load model directly

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("byviz/bylastic_classification_logs")
model = AutoModelForSequenceClassification.from_pretrained("byviz/bylastic_classification_logs")

Test with Elastic

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Contact

If you need AI models with personalized training and compatible with elastic or have any suggestions, you can contact:

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