Python tracing docs refresh

docs/platforms/python/profiling/index.mdx

@@ -51,10 +51,6 @@ For Profiling to work, you have to first enable [Sentry’s tracing](/concepts/k
 
 </Alert>
 
-### Upgrading from Older Python SDK Versions
-
-Profiling was experimental in SDK versions `1.17.0` and older. Learn how to upgrade <PlatformLink to="/profiling/troubleshooting/#ipgrading-from-older-sdk-versions">here</PlatformLink>.
-
 ## Enable Continuous Profiling
 
 <Include name="feature-stage-beta.mdx" />

docs/platforms/python/tracing/configure-sampling/index.mdx

@@ -0,0 +1,285 @@
+---
+title: Configure Sampling
+description: "Learn how to configure sampling in your app."
+sidebar_order: 40
+---
+
+If you find that Sentry's tracing functionality is generating too much data, for example, if you notice your spans quota is quickly being exhausted, you can choose to sample your traces.
+
+Effective sampling is key to getting the most value from Sentry's performance monitoring while minimizing overhead. The Python SDK provides two ways to control the sampling rate. You can review the options and [examples](#trace-sampler-examples) below.
+
+## Sampling Configuration Options
+
+### 1. Uniform Sample Rate (`traces_sample_rate`)
+
+`traces_sample_rate` is a floating-point value between `0.0` and `1.0`, inclusive, which controls the probability with which each transaction will be sampled:
+
+<PlatformContent includePath="/performance/traces-sample-rate" />
+
+With `traces_sample_rate` set to `0.25`, each transaction in your application is randomly sampled with a probability of `0.25`, so you can expect that one in every four transactions will be sent to Sentry. 
+
+### 2. Sampling Function (`traces_sampler`)
+
+For more granular control, you can provide a `traces_sampler` function. This approach allows you to:
+
+- Apply different sampling rates to different types of transactions
+- Filter out specific transactions entirely
+- Make sampling decisions based on transaction data
+- Control the inheritance of sampling decisions in distributed traces
+- Use custom attributes to modify sampling
+
+<Alert>
+
+It is strongly recommended when using a custom `traces_sampler` that you respect the parent sampling decision. This ensures your traces will be complete. 
+
+</Alert>
+
+In distributed systems, implement inheritance logic when trace information is propagated between services. This ensures consistent sampling decisions across your entire distributed trace
+
+<PlatformContent includePath="/performance/traces-sampler-as-sampler" />
+
+<details>
+<summary className="text-xl font-semibold">Trace Sampler Examples</summary>
+
+#### Trace Sampler Examples
+
+1. Prioritizing Critical User Flows
+
+```python
+def traces_sampler(sampling_context):
+    # Use the parent sampling decision if we have an incoming trace.
+    # Note: we strongly recommend respecting the parent sampling decision,
+    # as this ensures your traces will be complete!
+    parent_sampling_decision = sampling_context.get("parent_sampled")
+    if parent_sampling_decision is not None:
+        return float(parent_sampling_decision)
+
+    ctx = sampling_context.get("transaction_context", {})
+    name = ctx.get("name")
+
+    # Sample all checkout transactions
+    if name and ('/checkout' in name or 
+                ctx.get("op") == 'checkout'):
+        return 1.0
+
+    # Sample 50% of login transactions
+    if name and ('/login' in name or 
+                ctx.get("op") == 'login'):
+        return 0.5
+
+    # Sample 10% of everything else
+    return 0.1
+
+sentry_sdk.init(
+    dsn="your-dsn",
+    traces_sampler=traces_sampler,
+)
+```
+
+2. Handling Different Environments and Error Rates
+
+```python
+def traces_sampler(sampling_context):
+    # Use the parent sampling decision if we have an incoming trace.
+    # Note: we strongly recommend respecting the parent sampling decision,
+    # as this ensures your traces will be complete!
+    parent_sampling_decision = sampling_context.get("parent_sampled")
+    if parent_sampling_decision is not None:
+        return float(parent_sampling_decision)
+
+    ctx = sampling_context.get("transaction_context", {})
+    environment = os.environ.get("ENVIRONMENT", "development")
+
+    # Sample all transactions in development
+    if environment == "development":
+        return 1.0
+
+    # Sample more transactions if there are recent errors by using custom attributes
+    if ctx.get("data", {}).get("hasRecentErrors"): 
+        return 0.8
+
+    # Sample based on environment
+    if environment == "production":
+        return 0.05  # 5% in production
+    elif environment == "staging":
+        return 0.2   # 20% in staging
+
+    # Default sampling rate
+    return 0.1  
+
+sentry_sdk.init(
+    dsn="your-dsn",
+    traces_sampler=traces_sampler,
+)
+```
+
+3. Controlling Sampling Based on User and Transaction Properties
+
+```python
+def traces_sampler(sampling_context):
+    # Use the parent sampling decision if we have an incoming trace.
+    # Note: we strongly recommend respecting the parent sampling decision,
+    # as this ensures your traces will be complete!
+    parent_sampling_decision = sampling_context.get("parent_sampled")
+    if parent_sampling_decision is not None:
+        return float(parent_sampling_decision)
+
+    ctx = sampling_context.get("transaction_context", {})
+    data = ctx.get("data", {})
+
+    # Always sample for premium users
+    if data.get("user", {}).get("tier") == "premium":
+        return 1.0
+
+    # Sample more transactions for users experiencing errors
+    if data.get("hasRecentErrors"):
+        return 0.8
+
+    # Sample less for high-volume, low-value paths
+   if (ctx.get("name") or "").startswith("/api/metrics"):
+        return 0.01
+
+    # Sample more for slow transactions
+    if data.get("duration_ms", 0) > 1000:  # Transactions over 1 second
+        return 0.5
+
+    # Default sampling rate
+    return 0.2
+
+sentry_sdk.init(
+    dsn="your-dsn",
+    traces_sampler=traces_sampler,
+)
+```
+
+4. Complex Business Logic Sampling
+
+```python
+def traces_sampler(sampling_context):
+    # Use the parent sampling decision if we have an incoming trace.
+    # Note: we strongly recommend respecting the parent sampling decision,
+    # as this ensures your traces will be complete!
+    parent_sampling_decision = sampling_context.get("parent_sampled")
+    if parent_sampling_decision is not None:
+        return float(parent_sampling_decision)
+
+    ctx = sampling_context.get("transaction_context", {})
+    data = ctx.get("data", {})
+
+    # Always sample critical business operations
+    if ctx.get("op") in ["payment.process", "order.create", "user.verify"]:
+        return 1.0
+
+    # Sample based on user segment
+    user_segment = data.get("user", {}).get("segment")
+    if user_segment == "enterprise":
+        return 0.8
+    elif user_segment == "premium":
+        return 0.5
+
+    # Sample based on transaction value
+    transaction_value = data.get("transaction", {}).get("value", 0)
+    if transaction_value > 1000:  # High-value transactions
+        return 0.7
+
+    # Sample based on error rate in the service
+    error_rate = data.get("service", {}).get("error_rate", 0)
+    if error_rate > 0.05:  # Error rate above 5%
+        return 0.9
+
+    # Default sampling rate
+    return 0.1
+
+sentry_sdk.init(
+    dsn="your-dsn",
+    traces_sampler=traces_sampler,
+)
+```
+
+5. Performance-Based Sampling
+
+```python
+def traces_sampler(sampling_context):
+    # Use the parent sampling decision if we have an incoming trace.
+    # Note: we strongly recommend respecting the parent sampling decision,
+    # as this ensures your traces will be complete!
+    parent_sampling_decision = sampling_context.get("parent_sampled")
+    if parent_sampling_decision is not None:
+        return float(parent_sampling_decision)
+
+    ctx = sampling_context.get("transaction_context", {})
+    data = ctx.get("data", {})
+
+    # Sample all slow transactions
+    if data.get("duration_ms", 0) > 2000:  # Over 2 seconds
+        return 1.0
+
+    # Sample more transactions with high memory usage
+    if data.get("memory_usage_mb", 0) > 500:  # Over 500MB
+        return 0.8
+
+    # Sample more transactions with high CPU usage
+    if data.get("cpu_percent", 0) > 80:  # Over 80% CPU
+        return 0.8
+
+    # Sample more transactions with high database load using custom attributes
+    if data.get("db_connections", 0) > 100:  # Over 100 connections
+        return 0.7
+
+    # Default sampling rate
+    return 0.1
+
+sentry_sdk.init(
+    dsn="your-dsn",
+    traces_sampler=traces_sampler,
+)
+```
+</details>
+
+## The Sampling Context Object
+
+When the `traces_sampler` function is called, the Sentry SDK passes a `sampling_context` object with information from the relevant span to help make sampling decisions:
+
+```python
+{
+    "transaction_context": {
+        "name": str,                    # transaction title at creation time
+        "op": str,                      # short description of transaction type, like "http.request"
+        "data": Optional[Dict[str, Any]] # other transaction data
+    },
+    "parent_sampled ": Optional[bool],  # whether the parent transaction was sampled, `None` if no parent or if the parent has no sampling decision
+    "parent_sample_rate": Optional[float], # the sample rate used by the parent (if any)
+    "transaction_context": Optional[Dict[str, Any]],  # custom context data
+    "custom_sampling_context": Optional[Dict[str, Any]]  # additional custom data for sampling
+}
+```
+
+<b>Additional common types used in</b> `sampling_context`<b>:</b>
+    - str: for text values (names, operations, etc.)
+    - bool: for true/false values
+    - float: for decimal numbers (like sample rates)
+    - Dict[str, Any]: for dictionaries with string keys and any type of values
+    - Optional[Type]: for values that might be None
+
+## Sampling Decision Precedence
+
+When multiple sampling mechanisms could apply, Sentry follows this order of precedence:
+
+1. If a sampling decision is passed to `start_transaction`, that decision is used
+2. If `traces_sampler` is defined, its decision is used. Although the `traces_sampler` can override the parent sampling decision, most users will want to ensure their `traces_sampler` respects the parent sampling decision
+3. If no `traces_sampler` is defined, but there is a parent sampling decision from an incoming distributed trace, we use the parent sampling decision 
+4. If neither of the above, `traces_sample_rate` is used
+5. If none of the above are set, no transactions are sampled. This is equivalent to setting `traces_sample_rate=0.0`
+
+## How Sampling Propagates in Distributed Traces
+
+Sentry uses a "head-based" sampling approach:
+
+- A sampling decision is made in the originating service (the "head")
+- This decision is propagated to all downstream services 
+
+The two key headers are:
+- `sentry-trace`: Contains trace ID, span ID, and sampling decision
+- `baggage`: Contains additional trace metadata including sample rate
+
+The Sentry Python SDK automatically attaches these headers to outgoing HTTP requests when using auto-instrumentation with libraries like `requests`, `urllib3`, or `httpx`. For other communication channels, you can manually propagate trace information. Learn more about customizing tracing in [custom trace propagation](/platforms/python/tracing/distributed-tracing/custom-trace-propagation/)

docs/platforms/python/tracing/trace-propagation/custom-instrumentation/index.mdx → docs/platforms/python/tracing/distributed-tracing/custom-trace-propagation/index.mdx

@@ -1,6 +1,6 @@
 ---
-title: Custom Instrumentation
-sidebar_order: 40
+title: Custom Trace Propagation
+sidebar_order: 10
 ---
 
 <PlatformContent includePath="distributed-tracing/custom-instrumentation/" />

docs/platforms/python/tracing/trace-propagation/index.mdx → docs/platforms/python/tracing/distributed-tracing/index.mdx

@@ -1,10 +1,10 @@
 ---
-title: Trace Propagation
+title: Set Up Distributed Tracing
 description: "Learn how to connect events across applications/services."
-sidebar_order: 3000
+sidebar_order: 30
 ---
 
-If the overall application landscape that you want to observe with Sentry consists of more than just a single service or application, distributed tracing can add a lot of value.
+<PlatformContent includePath="distributed-tracing/explanation" />
 
 ## What is Distributed Tracing?
 

docs/platforms/python/tracing/instrumentation/index.mdx

@@ -1,7 +1,21 @@
 ---
 title: Instrumentation
-description: "Learn how to instrument tracing in your app."
-sidebar_order: 20
+description: "Learn what Sentry instruments automatically, and how to configure spans to capture tracing data on any action in your app."
+sidebar_order: 50
 ---
 
-<PageGrid />
+<Alert>
+
+To capture transactions and spans customized to your organization's needs, you must first <PlatformLink to="/tracing/">set up tracing</PlatformLink>.
+
+</Alert>
+
+There are two ways that instrumentation is applied to your application:
+
+## Automatic Instrumentation
+
+Many integrations for popular frameworks automatically capture transactions that can be sent to Sentry. Read more about automatic instrumentation [here](/platforms/python/tracing/instrumentation/automatic-instrumentation/).
+
+## Custom Instrumentation
+To add custom performance data to your application, you need to add custom instrumentation in the form of [spans](/concepts/key-terms/tracing/distributed-tracing/#traces-transactions-and-spans). Spans are a way to measure the time it takes for a specific action to occur. For example, you can create a span to measure the time it takes for a function to execute. Learn more about span lifecycles [here](/platforms/python/tracing/span-lifecycle/). 
+