AI Analysis
The package shows minimal risk indicators with no network calls, shell executions, or obfuscation detected. The main concern is the maintainer's single package history, but this alone does not suggest a supply-chain attack.
- Low network, shell, and obfuscation risks
- Maintainer has only one package
Per-check LLM notes
- Network: No network calls detected, which is normal if the package does not require external communication.
- Shell: No shell execution patterns detected, indicating no direct system command execution is taking place.
- Obfuscation: No obfuscation patterns detected, indicating low risk of malicious activity related to code obfuscation.
- Credentials: No credential harvesting patterns detected, suggesting no immediate risk of secret or credential theft.
- Metadata: The maintainer has only one package, suggesting it may be a new or less active account.
Package Quality Overall: Low (4.2/10)
No test suite detected
No test files or test-runner configuration detected
Some documentation present
Documentation URL: "Documentation" -> https://docs.activeviam.com/products/atoti/python-sdk/0.9.15
No contributing guide or governance files found
Development Status classifier >= Beta
Partial type annotation coverage
Classifier: Typing :: Typed
Limited contributor diversity
2 unique contributor(s) across 100 commits in atoti/atotiTwo distinct contributors found
Heuristic Checks
No suspicious network call patterns found
No obfuscation patterns detected
No shell execution patterns detected
No credential harvesting patterns detected
No typosquatting candidates detected
Email domain looks legitimate: activeviam.com>
All external links appear legitimate
Repository atoti/atoti appears legitimate
1 maintainer concern(s) found
Author "ActiveViam" appears to have only 1 package on PyPI (new or inactive account)
No known vulnerabilities found in OSV database.
AI App Starter Prompt
Create a comprehensive monitoring dashboard for a fleet of microservices using Spring Boot and Python. Your task is to develop a mini-application that leverages the 'atoti-server-spring-boot-admin' package to monitor the health and performance of these services. This application will serve as a centralized hub where system administrators can track key metrics such as uptime, memory usage, CPU load, and error rates for each service instance. ### Step-by-Step Development Guide: 1. **Set Up Your Environment:** Begin by setting up your development environment with Python and Java installed. Ensure you have the necessary tools like Maven for building Java applications and pip for managing Python packages. 2. **Spring Boot Services Setup:** Create a few sample Spring Boot services that mimic real-world applications. Each service should have endpoints that return simulated data about its status (e.g., uptime, memory usage). 3. **Integrate Spring Boot Admin:** Use the 'atoti-server-spring-boot-admin' package to integrate Spring Boot Admin into one of your Spring Boot services. This service will act as the dashboard server, providing an interface for monitoring other services. 4. **Dashboard Customization:** Customize the Spring Boot Admin dashboard to display specific metrics that are relevant to your services. For example, you might want to create custom dashboards or widgets that show graphs of memory usage over time. 5. **API Integration:** Develop a simple Python script that queries the Spring Boot Admin API to fetch live metrics from the monitored services. Display these metrics in a human-readable format, such as printing them to the console or writing them to a file. 6. **Alerting System:** Implement a basic alerting system within your Python script that triggers notifications (e.g., via email or SMS) when certain thresholds are breached (e.g., if a service's uptime drops below a specified percentage). 7. **Testing and Deployment:** Test your application thoroughly to ensure all components work as expected. Deploy your Spring Boot services and the dashboard server to a staging environment before moving to production. ### Suggested Features: - Real-time metric updates on the dashboard. - Historical data storage for trend analysis. - Customizable alerts based on different metrics. - Support for multiple user roles with varying levels of access. - Integration with external logging services for error tracking. ### Utilizing 'atoti-server-spring-boot-admin': This package simplifies the integration of Spring Boot Admin into your application, allowing you to focus more on customizing the dashboard and less on plumbing. It provides essential resources and configurations needed to get started with monitoring Spring Boot applications efficiently.
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