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# Lesson 3.2: OpenTelemetry Manual Instrumentation of Python Application
# Lesson 3.2: Manually configure OpenTelemetry agent
In the previous tutorial, we set up auto-instrumentation for our Flask application with OpenTelemetry without any code changes. In this tutorial, we will manually configure the agent.

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url - `opentelemetry-python-manual-instrumentation`
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# Lesson 6: Configure OpenTelemetry logging SDK in Python
In the previous tutorials, we have seen how to manually create spans in a Python application. In this tutorial, we will look at how to configure OTel logging SDK in Python application.

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The programs show how to customize the metric streams produced by the SDK using Views.
# Lesson 7: Customize metrics streams produced by OpenTelemetry SDK using views
The above code tutorials show how to customize the metric streams produced by the SDK using Views.
* change_aggregation.py: Shows how to configure to change the default aggregation using name of the instrument
* configure_temporality.py: Shows how to have multiple exporter with different temporalities

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# Guide on implementing OpenTelemetry in Python Applications
OpenTelemetry is an an open-source observability framework that aims to standardize the generation, collection, and management of telemetry data(Logs, metrics, and traces). It is incubated under Cloud Native Computing Foundation(Cloud Native Computing Foundation), the same foundation which incubated Kubernetes.
OpenTelemetry is quietly becoming the default standard for generating, transmitting and managing observability data and new-age companies are embracing it for future-proof instrumentation of their applications.
In this guide, you will learn how to implement OpenTelemetry in Python Applications. Following lessons cover everything you need to know about using OpenTelemetry to implement observability.
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Lesson 1: Setting up the Environment
Set up a basic Flask application.
Lesson 2: Setting up SigNoz
Lesson 3-1: Auto-instrumentation with OpenTelemetry
Set up SigNoz to receive data collected from 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
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 5: Create custom metrics with OpenTelemetry
Learn how to create custom with OpenTelemetry
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