Updated content and screenshots till lesson 5

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url - `opentelemetry-python-example`
---
# Lesson 3.2: OpenTelemetry Manual Instrumentation of Python Application
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.
@ -67,7 +65,7 @@ Now, let's see how to run the application.
```bash
OTEL_RESOURCE_ATTRIBUTES=service.name=my-application \
OTEL_EXPORTER_OTLP_ENDPOINT="https://ingest.in.signoz.cloud:443" \
OTEL_EXPORTER_OTLP_HEADERS="signoz-access-token=72282c07-60ad-45ff-9131-3b8819f9cdc3" \
OTEL_EXPORTER_OTLP_HEADERS="signoz-access-token=<SIGNOZ_INGESTION_KEY>" \
python lesson-3-2/app.py
```
@ -77,7 +75,9 @@ Interact with the Flask application to generate tracing data and send it to SigN
## Step 5: See Trace Data in SigNoz
<Insert screenshots showing actual spans from the code>
Once you've created some dummy telemetry by interacting with your application, you will be able to find your application under the `Services` tab of SigNoz.
![Application being monitored in SigNoz](static/images/application-monitored.png)
## Next Steps

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@ -88,7 +88,7 @@ def action():
desc = request.values.get("desc")
date = request.values.get("date")
pr = request.values.get("pr")
span.set_attribute("name", name)
span.set_attribute("task_name", name)
span.add_event("Adding a Task")
todos_coll.insert_one(
{"name": name, "desc": desc, "date": date, "pr": pr, "done": "no"}

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url - `opentelemetry-python-manual-instrumentation`
---
# Lesson 4: Create Manual Spans in Python application using OpenTelemetry
In the previous tutorials, we set up out of the box tracing, metrics and logs in our Flask application. In this tutorial, we will show you how to manually create spans.
@ -187,7 +185,22 @@ def my_function():
## Step 6: See your Spans in SigNoz
<screenshots showing exact spans that was created with manual instrumentation>
The sample code for lesson 4 has a manual span named `add_task` which gets created whenever you create a new task in the to-do application. To see this span go to the `Traces` tab and apply filters for your application.
```bash
OTEL_RESOURCE_ATTRIBUTES=service.name=my-application \
OTEL_EXPORTER_OTLP_ENDPOINT="https://ingest.{region}.signoz.cloud:443" \
OTEL_EXPORTER_OTLP_HEADERS="signoz-access-token=<SIGNOZ_INGESTION_KEY>" \
python lesson-4/app.py
```
Once you run the application and add a task, you will be able to see it in SigNoz.
![Manual span in the list view of traces](static/images/manual-spans.png)
You can see your span in the trace detail view too which will show how the request flowed and how much it took for the `add_task` operation.
![See your span in detailed trace view](static/images/manual-spans.png)
## Next Steps

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url - `opentelemetry-python-manual-instrumentation`
---
# Lesson 5: Creating custom metrics in Python Application using OpenTelemetry
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 create custom metrics using OpenTelemetry.
@ -101,7 +99,33 @@ The `create_gauge()` method creates a gauge instrument with the given name, unit
## Step 6: See your metrics in SigNoz
<screenshots showing exact metrics that was created with manual instrumentation>
The sample code for lesson 5 has a custom metric named `todo_counter` which keeps a track of number of To-Dos added by the user. You can create customized dashboards to monitor your custom metrics.
In order to see your custom metric in SigNoz, run the updated code with custom metric in Lesson 5.
```bash
OTEL_RESOURCE_ATTRIBUTES=service.name=my-application \
OTEL_EXPORTER_OTLP_ENDPOINT="https://ingest.{region}.signoz.cloud:443" \
OTEL_EXPORTER_OTLP_HEADERS="signoz-access-token=<SIGNOZ_INGESTION_KEY>" \
python lesson-5/app.py
```
Let's suppose you add 6 tasks in your to-do application.
![6 tasks added in the to-do application](static/images/6-tasks.png)
You can go to `Dashboards` in SigNoz and create a new panel to monitor the number of tasks in your to-do application using the `todo_counter` metric.
![todo_counter metric](static/images/custom-metrics-opentelemetry-python.png)
You can create a value panel type and monitor the number of tasks being created.
![Value panel type](static/images/no-of-tasks-added.png)
You can also set alerts on metrics based on your use-case directly from these panels.
![Value panel type](static/images/create-alerts-custom-metrics.png)
## Next Steps

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