aws-opentelemetry-distro

v0.17.1 safe
4.0
Medium Risk

AWS OpenTelemetry Python Distro

🤖 AI Analysis

Final verdict: SAFE

The package shows low to moderate risks across various categories and does not exhibit strong indicators of malicious activity. It appears to serve a legitimate purpose related to AWS OpenTelemetry.

  • moderate obfuscation risk
  • potential credential handling
Per-check LLM notes
  • Network: Network calls are expected for packages that interact with external services like AWS OpenTelemetry.
  • Shell: No shell execution patterns detected.
  • Obfuscation: The obfuscation pattern is suspicious but could be part of a legitimate attempt to bypass certain checks or configurations.
  • Credentials: The credential harvesting pattern is potentially benign as it appears to be fetching AWS environment variables for configuration purposes.
  • Metadata: The author has only one package, which might indicate a new or less active account, but no other red flags were identified.

📦 Package Quality Overall: Medium (6.6/10)

✦ High Test Suite 9.0

Test suite present — 12 test file(s) found

  • 12 test file(s) detected (e.g. test_always_record_sampler.py)
◈ Medium Documentation 5.0

Some documentation present

  • Brief PyPI description (506 chars)
○ 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

  • 285 type-annotated function signatures detected in source
✦ High Multiple Contributors 10.0

Active multi-contributor project

  • 12 unique contributor(s) across 100 commits in aws-observability/aws-otel-python-instrumentation
  • Active community — 5 or more distinct contributors

🔬 Heuristic Checks

⚠ Outbound Network Calls score 1.5

Found 1 network call pattern(s)

  • ts" self.__session = requests.Session() def get_sampling_rules(self) -> List[_SamplingRule]:
⚠ Code Obfuscation score 2.0

Found 1 obfuscation pattern(s)

  • ould_wrap=lambda: not hasattr(__import__(_HTTP_MODULE, fromlist=[""]), "streamable_http_client"), ) try_wrap(_HTT
✓ Shell / Subprocess Execution

No shell execution patterns detected

⚠ Credential Harvesting score 5.0

Found 2 credential access pattern(s)

  • n-sdk-compat region = os.environ.get("AWS_REGION") or os.environ.get("AWS_DEFAULT_REGION") if
  • .environ.get("AWS_REGION") or os.environ.get("AWS_DEFAULT_REGION") if region: session.set_
✓ Typosquatting

No typosquatting candidates detected

✓ Registered Email Domain

No author email provided

✓ Suspicious Page Links

All external links appear legitimate

✓ Git Repository History

Repository aws-observability/aws-otel-python-instrumentation appears legitimate

⚠ Maintainer History score 2.0

1 maintainer concern(s) found

  • Author "Amazon Web Services" 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 aws-opentelemetry-distro 
Develop a microservice-based application using Python that monitors and reports metrics and traces to AWS services like X-Ray and CloudWatch using the 'aws-opentelemetry-distro' package. This application will simulate a simple e-commerce checkout process, including order creation, payment processing, and shipping notifications. The goal is to showcase how OpenTelemetry can be integrated into a real-world scenario to enhance observability.

### Project Overview:
- **Application**: E-commerce Checkout Microservice
- **Features**:
  - Order Creation Service: Simulates the creation of an order in the system.
  - Payment Processing Service: Simulates the payment processing workflow.
  - Shipping Notification Service: Sends a notification when an order is shipped.
- **Observability Requirements**:
  - Track HTTP requests and responses.
  - Monitor latency and error rates.
  - Collect custom metrics and logs.
  - Trace transactions across multiple services.
- **Technologies**:
  - Python
  - Flask (for simplicity)
  - AWS SDKs
  - AWS X-Ray
  - AWS CloudWatch
  - 'aws-opentelemetry-distro'

### Steps to Develop the Application:
1. **Setup Environment**:
   - Install necessary Python packages including 'aws-opentelemetry-distro', Flask, and other dependencies.
2. **Create Services**:
   - Develop each microservice (Order Creation, Payment Processing, Shipping Notification).
3. **Instrumentation**:
   - Use 'aws-opentelemetry-distro' to instrument each service for automatic metric collection, tracing, and logging.
4. **AWS Integration**:
   - Configure the application to send collected data to AWS X-Ray and CloudWatch.
5. **Testing and Validation**:
   - Ensure that metrics, traces, and logs are correctly reported to AWS.
6. **Documentation**:
   - Provide clear documentation on how to set up and run the application, as well as how to interpret the collected data in AWS.

### Detailed Instructions:
- For each service, ensure that HTTP request details, response times, and any errors are tracked.
- Implement custom metrics such as 'orders_per_minute' and 'payment_errors'.
- Utilize 'aws-opentelemetry-distro' to automatically generate spans for each operation within the services, allowing for detailed tracing of transactions.
- Integrate with AWS X-Ray to visualize the flow of transactions between services.
- Use AWS CloudWatch to monitor overall performance and troubleshoot issues.

This project aims to demonstrate the power of OpenTelemetry in enhancing observability in cloud-native applications.

💬 Discussion Feed

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