Structured Log Analyzer

Structured Log Analyzer | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Data Processing
Input types: textarea, file, select, checkbox, text
Output type: html
Sample coverage: 4
API ready: Yes

Overview

The Structured Log Analyzer automatically detects and parses common log formats like JSONL, Apache, Nginx, and Syslog. It extracts core fields, infers data types, and lets you export the cleaned data as JSON, CSV, or SQL inserts for easier querying, spreadsheet analysis, and database ingestion.

When to use

When you need to convert raw, unstructured server logs into a tabular CSV format for spreadsheet analysis.
When migrating legacy log files into a relational database using generated SQL insert statements.
When troubleshooting application errors that span multiple lines, such as Java stack traces, and need them grouped as single entries.

How it works

1Paste your raw log entries into the text area or upload a log file up to 20MB.
2Select your desired export format: JSON, CSV, or SQL.
3Optionally, enable multiline aggregation for stack traces or provide a custom regex with named capture groups for proprietary formats.
4The tool parses the logs, extracts the fields, and generates the structured output.

Use cases

Converting mixed application logs into a CSV file to build charts and pivot tables in Excel.
Extracting specific error messages and timestamps from custom application logs using named regex groups.
Preparing Nginx access logs for database ingestion by generating SQL insert statements.

Examples

1. Convert Mixed Logs to CSV

System Administrator

Background

A sysadmin needs to review a mix of JSON application logs and standard syslog entries to identify a recurring service failure.

Problem

Reading raw, mixed-format logs in a terminal is difficult and prevents easy sorting by error level or timestamp.

How to use

Paste the mixed log entries into the input area, select 'CSV' as the export format, and enable multiline aggregation.

Export Format: CSV, Aggregate Multiline: True

Outcome

The tool normalizes the JSON and syslog entries into a single CSV structure, allowing the sysadmin to sort by timestamp and filter by error level in a spreadsheet.

2. Parse Custom Logs with Regex

Backend Developer

Background

A developer is debugging an older legacy application that writes logs in a proprietary, non-standard text format.

Problem

Standard parsers fail to extract the timestamp, severity, and message from the legacy log strings.

How to use

Upload the legacy log file and input a custom regex with named capture groups to define the exact field boundaries.

FAQ

Which log formats are supported automatically?

The tool automatically detects and parses common formats including JSON Lines (JSONL), Apache access logs, Nginx logs, and standard Syslog entries.

Can I parse a custom log format?

Yes, you can provide a custom regular expression with named capture groups (e.g., `(?<level>\w+)`) to extract specific fields from proprietary log formats.

How does the multiline aggregation work?

When enabled, the tool groups subsequent indented or unformatted lines, such as stack traces, with the preceding log entry instead of treating them as separate, broken records.

What is the maximum file size I can upload?

You can upload log files up to 20MB in size. For larger datasets, consider splitting your files before uploading.

Can I export the parsed logs to a database?

Yes, by selecting the SQL export format, the tool generates standard SQL INSERT statements based on the extracted fields and inferred data types.

Custom Regex: ^(?<timestamp>\S+) (?<level>\w+) (?<source>\w+) (?<message>.+)$, Export Format: JSON

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Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Convert Mixed Logs to CSV

2. Parse Custom Logs with Regex

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