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--- devops:monitoring:datadog:ddtrace [2025/02/14 14:07] – created 85.219.17.206
+++ devops:monitoring:datadog:ddtrace [2025/02/14 14:11] (current) – 85.219.17.206
@@ Line 9: / Line 9: @@
    pip install ddtrace
+Once installed, you can begin instrumenting your application.
+==== Basic Usage ====
+After installation, you need to import ddtrace and initialize it. The easiest way to start tracing is by adding this at the entry point of your application:
+<code:python>
+from ddtrace import tracer
+# Example: tracing a simple function
+@tracer.wrap()
+def my_function():
+    # Function logic
+    pass
+</code>
+Alternatively, you can use ddtrace to automatically instrument various libraries, such as Flask, Django, Celery, and more, with minimal configuration.
+<code:python>
+from ddtrace import patch_all
+patch_all()  # This will automatically trace supported libraries
+</code>
+==== Configuration ====
+The Datadog tracer can be configured with several options, such as setting the agent host, enabling/disabling certain integrations, and adjusting sampling rates.
+Here are some common configuration options:
+      * Datadog Agent Host:
+  *     Set the Datadog Agent host to which traces should be sent.
+<code:python>
+from ddtrace import tracer
+tracer.configure(hostname='localhost', port=8126)
+</code>
+==== Supported Libraries ====
+ddtrace supports a wide range of libraries and frameworks out of the box. Some popular integrations include:
+     *  Flask: For tracing HTTP requests in Flask applications.
+  *     Django: For monitoring Django-based applications.
+  *     Celery: For tracing background tasks with Celery.
+  *     SQLAlchemy: For tracing database queries.
+  *     Redis: For tracing Redis interactions.
+To enable tracing for these frameworks, simply import the relevant module, and ddtrace will automatically instrument them.