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Version: 1.2.0

Processors: Categorized

Processors are fundamental components in log processing pipelines that perform specific operations on log data. They are responsible for transforming, enriching, and manipulating log entries as they flow through the system. Each processor is designed to handle a specific type of operation, from simple field modifications to complex data transformations.

🧠 AI​

AI processors harness the power of artificial intelligence APIs for sophisticated content analysis and processing. These processors utilize various AI services to perform advanced text analysis, classification, and generation tasks. They enable intelligent processing of content, making it possible to extract insights and meaning from complex data.

💹 Analytics​

Analytics processors gather and manipulate data to render the data points suitable for metrics and analyses. They select the data points that reveal critical information about the generators of data, and process them to make the relevant information contained in them more visible.

🧮 Arithmetic​

Arithmetic processors perform mathematical operations and calculations on numeric field values within log data. They support basic mathematical functions like addition, subtraction, multiplication, and division, as well as more complex operations such as calculating percentages, averages, and statistical computations. These processors enable quantitative analysis of log data by transforming raw numbers into meaningful metrics and derived values.

⚙️ Control Flow​

Control Flow processors manage the execution paths and logic within processing pipelines. They direct how documents move through the system, handle conditional processing, and organize pipeline structure. These processors are essential for creating sophisticated processing logic and maintaining efficient pipeline organization.

⌚ Date and Time​

Date and Time processors handle temporal data operations including parsing, formatting, and manipulating date and time values. They convert between different date formats, extract time components, calculate time differences, and manage timezone conversions. These processors are essential for standardizing temporal data and performing time-based analysis on log entries.

💠 Enrich​

Enrichment processors enhance log data by incorporating additional context and information from external sources. They add value to existing data by integrating geographical information, performing DNS lookups, and adding domain intelligence. These processors connect with external databases and services to provide comprehensive context to your log data, making it more valuable for analysis and understanding.

🎯 Filter​

Filter processors selectively process or exclude data based on specific criteria. They help maintain data quality by removing unwanted information, applying pattern matching for selection, and standardizing content. These processors are crucial for ensuring that only relevant data continues through the pipeline, improving processing efficiency and data clarity.

✏️ Mutate​

Mutation processors modify existing data fields and values to ensure proper formatting and structure. They handle tasks such as appending values, converting data types, managing dates, and manipulating strings. These processors are fundamental for maintaining data consistency and preparing information for further processing or analysis.

🖧 Networking​

Networking processors handle network-related data operations and communications. They perform network protocol analysis, manage IP address operations, conduct DNS lookups, and handle network connectivity tasks. These processors are vital for processing network logs, analyzing network traffic patterns, and enriching data with network intelligence.

📋 Parse​

Parsing processors transform raw data into structured formats by extracting meaningful information from various input types. They handle multiple data formats and message types, converting them into structured data. These processors excel at converting unstructured or semi-structured data into well-organized, usable formats by applying patterns and rules to extract relevant fields.

🛡️ Security​

Security processors focus on protecting sensitive information and managing data security. They implement encryption and decryption operations, generate document signatures, and handle data masking and redaction. These processors ensure that sensitive information is properly protected while maintaining the utility of the data for analysis.

📝 Text Processing​

Text Processing processors specialize in advanced text manipulation and analysis operations beyond basic string handling. They perform sophisticated text operations such as natural language processing, text classification, sentiment analysis, and complex string transformations. These processors are designed to extract meaningful insights from textual content and perform advanced linguistic operations on text fields within log data.

🕵️ Threat Intelligence​

Threat Intelligence processors integrate with external security services to provide context about potential security threats. They connect with various threat intelligence providers to retrieve and incorporate security data. These processors are crucial for security analysis and threat detection, providing real-time intelligence about potential security risks.

🔄 Transform​

Transform processors handle structural changes to data by modifying how information is organized and represented. They manage tasks like expanding and nesting field structures, combining elements, and normalizing field names. These processors are essential for ensuring data consistency and maintaining proper data structure throughout the processing pipeline.