Log Analysis Tool
Upload and analyze application logs with detailed statistics, charts, and a report generator. All parsing and analysis run locally in the browser.
Key features:
- Error, warning, info, and debug counts with time range insights.
- Interactive charts and searchable log table.
- Non persistent log handling and privacy controls.
Upload Log File
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Summary Snapshot
Total Entries
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Errors
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Warnings
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Info
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Debug
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Time Range
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Health Status
Awaiting log upload.
Privacy Protected. Log data is processed in the browser and never stored on the server. Only aggregate statistics may be cached locally for session experience.
AI Usage Note. Report generation can be optionally enhanced with AI. Do not embed API keys in the browser. Route AI calls through a secure backend endpoint.
Upload a log file to view summary insights including volume by level, detected critical errors, and basic health indicators.
Audit Trail Investigator
Inspect ProjectWise audit trail exports to track file activity, security events, deletions, and missing files with clear categorization.
Key investigation areas:
- Deletion and purge events.
- Movement and replacement of files.
- User and security related actions.
Upload Audit Trail CSV
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Summary Snapshot
Total Events
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Deletions
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Missing Files
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Security Events
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Privacy Protected. Audit content is never stored or transmitted. Only analysis metadata may be retained in local browser storage during this session.
Upload a ProjectWise audit trail CSV to view a high level overview of actions such as deletions, movements, and security events.
Knowledge Base
Implementation notes, privacy details, and integration hints for bringing this tool into ServiceNow or other enterprise platforms.
Architecture
This single page application runs entirely in the browser using HTML, CSS, and JavaScript with Chart.js for visualizations. Log and audit files are parsed client side and never persisted to a server. For production and ServiceNow integration you would wrap this logic inside Now Experience components and map uploads to Scripted REST APIs if you require centralization, while keeping the privacy model where raw data is either transient or strictly controlled.
AI Integration Pattern
If you want AI assisted report generation, expose a backend endpoint that accepts statistics or anonymized snippets, calls your AI provider with secure server side credentials, and returns the generated text. Never embed API keys in front end JavaScript.
Example Backend Endpoint
POST /api/ai/report
Content-Type: application/json
{
"mode": "log",
"stats": {
"errors": 12,
"warnings": 4,
"info": 93
},
"context": "Short description of the system"
}
The browser calls this endpoint instead of calling the AI vendor directly. The server holds the secret key and can apply redaction or filtering rules.