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@@ -8,27 +8,32 @@ In this guide, you will learn how to implement OpenTelemetry in Python Applicati
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Lesson 1: Setting up the Environment
Set up a basic Flask application.
### Lesson 1: Setting up a basic Flask application
Lesson 2: Setting up SigNoz
Set up SigNoz to receive data collected from OpenTelemetry.
### Lesson 2: Setting up SigNoz
Lesson 3-1: Auto-instrumentation with OpenTelemetry
### Lesson 3-1: Auto-instrumentation with OpenTelemetry
Set up automatic traces, metrics and logs collection in our Flask application.
Lesson 3-2: Manual instrumentation with OpenTelemetry
### Lesson 3-2: Manual instrumentation with OpenTelemetry
Learn how to implement manual instrumentation with OpenTelemetry for more granular controls.
Lesson 4: Create spans manually in your Python application
Learn how to create manual spans and add metadata and attributes to them
### Lesson 4: Create spans manually in your Python application
Learn how to create manual spans and add metadata and attributes to them.
Lesson 5: Create custom metrics with OpenTelemetry
Learn how to create custom with OpenTelemetry
### Lesson 5: Create custom metrics with OpenTelemetry
Create custom metrics like counter, gauge, histogram in your application.
Lesson 6: Configure OpenTelemetry logging SDK in Python
Learn how to configure OpenTelemetry logging SDK in Python
### Lesson 6: Configure OpenTelemetry logging SDK in Python
Learn how to configure OpenTelemetry logging SDK in Python.
### Lesson 7: Customize metrics streams produced by OpenTelemetry SDK using views
---
At the end of this tutorial series, you will be able to use OpenTelemetry effectively to monitor your Python application.
![application-metrics](https://github.com/ankit01-oss/opentelemetry-python-example/assets/83692067/bfaf97e5-bc61-4922-b3cc-eb9b336ca925)
Lesson 7: Customize metrics streams produced by OpenTelemetry SDK using views