Only Depend On `opentelemetry_proto`

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Introduction

In the pursuit of simplicity and maintainability, it's essential to minimize dependencies in our codebase. The current implementation of PyOCI relies on opentelemetry_sdk and opentelemetry in addition to opentelemetry_proto. This article explores the possibility of simplifying these dependencies by only relying on opentelemetry_proto. We'll delve into the current implementation, identify areas for improvement, and propose a solution to achieve this goal.

Current Implementation

opentelemetry_proto provides the generated opentelemetry gRPC objects as Rust types. On the other hand, PyOCI currently depends on opentelemetry_sdk and opentelemetry. Let's examine the role of each of these dependencies:

opentelemetry_sdk

opentelemetry_sdk is used for generating a SpanId and TraceId. These identifiers are crucial for providing a consistent span/trace ID. However, we can generate these identifiers using opentelemetry_proto types, eliminating the need for opentelemetry_sdk.

opentelemetry

opentelemetry defines SpanId and TraceId and uses its Value as an intermediate to AnyValue. The Value type is used to cast into opentelemetry_proto types, which can be simplified to stay within opentelemetry_proto types.

Simplifying Dependencies

The current implementation can be simplified by removing the dependency on opentelemetry_sdk and opentelemetry. We can achieve this by using opentelemetry_proto types to generate SpanId and TraceId. This approach eliminates the need for intermediate types and reduces the complexity of the code.

Example Use Case

Let's consider the following code snippet from the PyOCI repository:

https://github.com/AllexVeldman/pyoci/blob/fe070dc74af85925d5c3fd655eedccbf29985da5/src/otlp/trace.rs#L235

This code uses opentelemetry::Value to cast into opentelemetry_proto types. We can simplify this code by using opentelemetry_proto types directly, eliminating the need for the intermediate Value type.

Proposed Solution

To simplify the dependencies and reduce the complexity of the code, we propose the following solution:

  1. Remove the dependency on opentelemetry_sdk and opentelemetry.
  2. Use opentelemetry_proto types to generate SpanId and TraceId.
  3. Simplify the code by eliminating intermediate types and reducing the complexity of the code.

Benefits

By simplifying the dependencies and reducing the complexity of the code, we can achieve several benefits:

  • Improved maintainability: Simplifying the dependencies makes the code easier to maintain and understand.
  • Reduced complexity: Eliminating intermediate types and reducing the complexity of the code makes it easier to debug and optimize.
  • Increased flexibility: Using opentelemetry_proto types directly provides more flexibility in terms of customization and extension.

Conclusion

Introduction

In our previous article, we explored the possibility of simplifying dependencies in PyOCI by only relying on opentelemetry_proto. We discussed the current implementation, identified areas for improvement, and proposed a solution to achieve this goal. In this article, we'll answer some frequently asked questions (FAQs) related to this topic.

Q&A

Q: Why do we need to simplify dependencies?

A: Simplifying dependencies makes the code easier to maintain and understand. It reduces the complexity of the code, making it easier to debug and optimize. Additionally, it provides more flexibility in terms of customization and extension.

Q: What are the benefits of relying only on opentelemetry_proto?

A: By relying only on opentelemetry_proto, we can achieve several benefits, including:

  • Improved maintainability: Simplifying the dependencies makes the code easier to maintain and understand.
  • Reduced complexity: Eliminating intermediate types and reducing the complexity of the code makes it easier to debug and optimize.
  • Increased flexibility: Using opentelemetry_proto types directly provides more flexibility in terms of customization and extension.

Q: How do we generate SpanId and TraceId using opentelemetry_proto?

A: We can generate SpanId and TraceId using opentelemetry_proto types. This approach eliminates the need for intermediate types and reduces the complexity of the code.

Q: What about the code snippet from the PyOCI repository?

A: The code snippet from the PyOCI repository uses opentelemetry::Value to cast into opentelemetry_proto types. We can simplify this code by using opentelemetry_proto types directly, eliminating the need for the intermediate Value type.

Q: How do we remove the dependency on opentelemetry_sdk and opentelemetry?

A: To remove the dependency on opentelemetry_sdk and opentelemetry, we need to:

  1. Remove the import statements for these dependencies.
  2. Replace the usage of these dependencies with opentelemetry_proto types.
  3. Test the code to ensure that it works as expected.

Q: What are the potential challenges of relying only on opentelemetry_proto?

A: Some potential challenges of relying only on opentelemetry_proto include:

  • Limited functionality: opentelemetry_proto may not provide all the functionality required by the application.
  • Customization limitations: Relying only on opentelemetry_proto may limit the ability to customize the code.
  • Compatibility issues: There may be compatibility issues with other dependencies or libraries that rely on opentelemetry_sdk and opentelemetry.

Q: How do we address these challenges?

A: To address these challenges, we need to:

  • Assess the requirements: Assess the requirements of the application and determine if opentelemetry_proto meets those requirements.
  • Customize the code: Customize the code to work with opentelemetry_proto and address any limitations.
  • Test the code: Test the code to ensure that it as expected and addresses any compatibility issues.

Conclusion

In conclusion, simplifying dependencies by only relying on opentelemetry_proto can improve the maintainability, reduce the complexity, and increase the flexibility of the code. By answering these FAQs, we've provided a better understanding of the benefits and challenges of this approach.