atoti-server-observability

v0.9.15 suspicious
3.0
Low Risk

Experimental resources providing observability of Atoti sessions

⚠ Tarball exceeded 25 MB — source code analysis was limited to package metadata only.

🤖 AI Analysis

Final verdict: SUSPICIOUS

The package shows minimal risks across all checks except for metadata, where the author's single package raises a flag. This could suggest a less established or new developer, warranting closer scrutiny before use.

  • Author has only one package
  • Minimal risk in network, shell, and obfuscation checks
Per-check LLM notes
  • Network: No network calls detected, which is normal unless the package requires external services.
  • Shell: No shell execution patterns detected, indicating no direct system command execution.
  • Obfuscation: No obfuscation patterns detected, indicating low risk.
  • Credentials: No credential harvesting patterns detected, indicating low risk.
  • Metadata: The author has only one package, which might indicate a new or less active account, raising some suspicion but not conclusive evidence of malice.

📦 Package Quality Overall: Low (3.4/10)

○ Low Test Suite 1.0

No test suite detected

  • No test files or test-runner configuration detected
○ Low Documentation 1.0

No documentation detected

  • No documentation URL, doc files, or meaningful description found
○ Low Contributing Guide 4.0

No contributing guide or governance files found

  • Development Status classifier >= Beta
◈ Medium Type Annotations 5.0

Partial type annotation coverage

  • Classifier: Typing :: Typed
◈ Medium Multiple Contributors 6.0

Limited contributor diversity

  • 2 unique contributor(s) across 100 commits in atoti/atoti
  • Two distinct contributors found

🔬 Heuristic Checks

✓ Outbound Network Calls

No suspicious network call patterns found

✓ Code Obfuscation

No obfuscation patterns detected

✓ Shell / Subprocess Execution

No shell execution patterns detected

✓ Credential Harvesting

No credential harvesting patterns detected

✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

Email domain looks legitimate: activeviam.com>

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository atoti/atoti appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "ActiveViam" appears to have only 1 package on PyPI (new or inactive account)
✓ Known CVE Vulnerabilities

No known vulnerabilities found in OSV database.

💡 AI App Starter Prompt

Use this prompt to build a project with atoti-server-observability 
Create a real-time monitoring dashboard for Atoti server sessions using the 'atoti-server-observability' package. This application will allow users to visualize and analyze the performance and health of their Atoti server sessions in a dynamic and interactive manner. Here’s a step-by-step guide on how to develop this application:

1. **Set Up the Environment**: Ensure you have Python installed along with the necessary packages including 'atoti-server-observability'. Additionally, install a web framework like Flask or FastAPI to serve your dashboard.

2. **Data Collection**: Use the 'atoti-server-observability' package to collect metrics such as session load times, query execution times, memory usage, and other relevant observability data from Atoti server sessions.

3. **Data Processing**: Process the collected data to ensure it is clean and ready for visualization. Consider implementing functions to aggregate data over time intervals or group by specific session attributes.

4. **Visualization**: Choose a charting library like Plotly or Matplotlib to create visualizations. Design the dashboard to include widgets for filtering and interacting with the data dynamically. For example, users should be able to select a date range, filter sessions by type, and view detailed information about individual sessions.

5. **Real-Time Updates**: Implement functionality to update the dashboard in real-time as new data becomes available. This could involve setting up periodic refreshes or using websockets to push updates directly to the client.

6. **User Interface**: Develop an intuitive user interface that allows users to easily navigate through different views and interact with the data. Consider adding tooltips, legends, and other UI elements to enhance usability.

7. **Testing and Deployment**: Thoroughly test the application to ensure all features work as expected. Once satisfied, deploy the application using a cloud service provider or a local server.

Suggested Features:
- Real-time graphs showing session activity and performance metrics.
- Detailed session logs accessible via a dropdown menu.
- Alerts and notifications for critical issues or anomalies.
- Customizable dashboards where users can add or remove charts based on their needs.

By utilizing the 'atoti-server-observability' package, you will gain deep insights into Atoti server sessions, enabling proactive management and optimization of server resources.

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