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chore(docs): consolidate troubleshooting docs on a single page (Python SDK) #12711

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chore(docs): consolidate troubleshooting docs on a single page (Pytho…
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43 changes: 0 additions & 43 deletions docs/platforms/python/crons/troubleshooting.mdx
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240 changes: 163 additions & 77 deletions docs/platforms/python/troubleshooting.mdx
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Expand Up @@ -4,114 +4,114 @@ description: "While we don't expect most users of our SDK to run into these issu
sidebar_order: 9000
---

We expect most users of the Python SDK not to run into any of the problems
documented here.
## General

Use the information in this page to help answer these questions:

- "What do I do if scope data is leaking between requests?"
- "What do I do if my transaction has nested spans when they should be parallel?"
- "What do I do if the SDK has trouble sending events to Sentry?"

## Addressing Concurrency Issues
<Expandable title="Addressing Concurrency Issues">
The short answer to the first two questions: make sure your `contextvars` work and
that your isolation scope was cloned for each concurrency unit.

The short answer to the first two questions: make sure your `contextvars` work and
that your isolation scope was cloned for each concurrency unit.
Python supports several distinct solutions to concurrency, including threads and
coroutines.

Python supports several distinct solutions to concurrency, including threads and
coroutines.
The Python SDK does its best to figure out how contextual data such as tags set
with `sentry_sdk.set_tags` is supposed to flow along your control flow. In most
cases it works perfectly, but in a few situations some special care must be
taken. This is specially true when working with a code base doing concurrency
outside of the provided framework integrations.

The Python SDK does its best to figure out how contextual data such as tags set
with `sentry_sdk.set_tags` is supposed to flow along your control flow. In most
cases it works perfectly, but in a few situations some special care must be
taken. This is specially true when working with a code base doing concurrency
outside of the provided framework integrations.
The general recommendation is to have one isolation scope per "concurrency unit"
(thread/coroutine/etc). The SDK ensures every thread has an independent scope via the `ThreadingIntegration`.
If you do concurrency with `asyncio` coroutines, make sure to use the `AsyncioIntegration`
which will clone the correct scope in your `Task`s.

The general recommendation is to have one isolation scope per "concurrency unit"
(thread/coroutine/etc). The SDK ensures every thread has an independent scope via the `ThreadingIntegration`.
If you do concurrency with `asyncio` coroutines, make sure to use the `AsyncioIntegration`
which will clone the correct scope in your `Task`s.
The general pattern of usage for creating a new isolation scope is:

The general pattern of usage for creating a new isolation scope is:
```python
with sentry_sdk.isolation_scope() as scope:
# In this block scope refers to a new fork of the original isolation scope,
# with the same client and the same initial scope data.
```

```python
with sentry_sdk.isolation_scope() as scope:
# In this block scope refers to a new fork of the original isolation scope,
# with the same client and the same initial scope data.
```

See the <PlatformLink to="/integrations/default-integrations/#threading">Threading</PlatformLink> section
for a more complete example that involves forking the isolation scope.
See the <PlatformLink to="/integrations/default-integrations/#threading">Threading</PlatformLink> section
for a more complete example that involves forking the isolation scope.
</Expandable>

## Context Variables vs Thread Locals
<Expandable title="Context Variables vs Thread Locals">

The Python SDK uses [thread
locals](https://docs.python.org/3/library/threading.html#thread-local-data) to
keep contextual data where it belongs. There are a few situations where this
approach fails.
The Python SDK uses [thread locals](https://docs.python.org/3/library/threading.html#thread-local-data) to
keep contextual data where it belongs. There are a few situations where this
approach fails.

Read along if you cannot figure out why contextual data is leaking across HTTP
requests, or data is missing or popping up at the wrong place and time.
Read along if you cannot figure out why contextual data is leaking across HTTP
requests, or data is missing or popping up at the wrong place and time.

### Python 2: Thread Locals and gevent
#### Python 2: Thread Locals and gevent

If the SDK is installed on Python 2, there is not much else to use than the
aforementioned thread locals, so the SDK will use just that.
If the SDK is installed on Python 2, there is not much else to use than the
aforementioned thread locals, so the SDK will use just that.

Code that uses async libraries such as **`twisted` is not supported** in the
sense that you will experience context data leaking across tasks/any logical
boundaries, at least out of the box.
Code that uses async libraries such as **`twisted` is not supported** in the
sense that you will experience context data leaking across tasks/any logical
boundaries, at least out of the box.

Code that uses more "magical" async libraries such as **`gevent` or `eventlet`
will work just fine** provided those libraries are configured to monkeypatch
the stdlib. If you are only using those libraries in the context of running
`gunicorn` that is the case, for example.
Code that uses more "magical" async libraries such as **`gevent` or `eventlet`
will work just fine** provided those libraries are configured to monkeypatch
the stdlib. If you are only using those libraries in the context of running
`gunicorn` that is the case, for example.

### Python 3: Context Variables or Thread Locals
#### Python 3: Context Variables or Thread Locals

Python 3 introduced `asyncio`, which, just like Twisted, had the problem of not
having any concept of attaching contextual data to your control flow. That
means in Python 3.6 and lower, the SDK is not able to prevent leaks of
contextual data.
Python 3 introduced `asyncio`, which, just like Twisted, had the problem of not
having any concept of attaching contextual data to your control flow. That
means in Python 3.6 and lower, the SDK is not able to prevent leaks of
contextual data.

Python 3.7 rectified this problem with the `contextvars` stdlib module which is
basically thread locals that also work in asyncio-based code. The SDK will
attempt to use that module instead of thread locals if available.
Python 3.7 rectified this problem with the `contextvars` stdlib module which is
basically thread locals that also work in asyncio-based code. The SDK will
attempt to use that module instead of thread locals if available.

**For Python 3.6 and older, install `aiocontextvars` from PyPI** which is a
fully-functional backport of `contextvars`. The SDK will check for this package
and use it instead of thread locals.
**For Python 3.6 and older, install `aiocontextvars` from PyPI** which is a
fully-functional backport of `contextvars`. The SDK will check for this package
and use it instead of thread locals.

## Context Variables vs gevent/eventlet
</Expandable>

If you are using `gevent` (older than 20.5) or `eventlet` in your application and
have configured it to monkeypatch the stdlib, the SDK will abstain from using
`contextvars` even if it is available.
<Expandable title="Context Variables vs gevent/eventlet">
If you are using `gevent` (older than 20.5) or `eventlet` in your application and
have configured it to monkeypatch the stdlib, the SDK will abstain from using
`contextvars` even if it is available.

The reason for that is that both of those libraries will monkeypatch the
`threading` module only, and not the `contextvars` module.
The reason for that is that both of those libraries will monkeypatch the
`threading` module only, and not the `contextvars` module.

The real-world usecase where this actually comes up is if you're using Django
3.0 within a `gunicorn+gevent` worker on Python 3.7. In such a scenario the
monkeypatched `threading` module will honor the control flow of a gunicorn
worker while the unpatched `contextvars` will not.
The real-world usecase where this actually comes up is if you're using Django
3.0 within a `gunicorn+gevent` worker on Python 3.7. In such a scenario the
monkeypatched `threading` module will honor the control flow of a gunicorn
worker while the unpatched `contextvars` will not.

It gets more complicated if you're using Django Channels in the same app, but a
separate server process, as this is a legitimate usage of `asyncio` for which
`contextvars` behaves more correctly. Make sure that your channels websocket
server does not import or use gevent at all (and much less call
`gevent.monkey.patch_all`), and you should be good.
It gets more complicated if you're using Django Channels in the same app, but a
separate server process, as this is a legitimate usage of `asyncio` for which
`contextvars` behaves more correctly. Make sure that your channels websocket
server does not import or use gevent at all (and much less call
`gevent.monkey.patch_all`), and you should be good.

Even then there are still edge cases where this behavior is flat-out broken,
such as mixing asyncio code with gevent/eventlet-based code. In that case there
is no right, _static_ answer as to which context library to use. Even then
gevent's aggressive monkeypatching is likely to interfere in a way that cannot
be fixed from within the SDK.
Even then there are still edge cases where this behavior is flat-out broken,
such as mixing asyncio code with gevent/eventlet-based code. In that case there
is no right, _static_ answer as to which context library to use. Even then
gevent's aggressive monkeypatching is likely to interfere in a way that cannot
be fixed from within the SDK.

This [issue has been fixed with gevent 20.5](https://github.com/gevent/gevent/issues/1407) but continues to be one for
eventlet.
This [issue has been fixed with gevent 20.5](https://github.com/gevent/gevent/issues/1407) but continues to be one for
eventlet.
</Expandable>

## Network Issues
<Expandable title="Network Issues">

Your SDK might have issues sending events to Sentry. You might see
`"Remote end closed connection without response"`, `"Connection aborted"`,
Expand All @@ -136,8 +136,9 @@ sentry_sdk.init(

If you need more fine-grained control over the behavior of the socket, check out
<PlatformLink to="/configuration/options/#socket-options">socket-options</PlatformLink>.
</Expandable>

## Multiprocessing deprecation after Python 3.12
<Expandable title="Multiprocessing deprecation after Python 3.12">

If you're on Python version 3.12 or greater, you might see the following deprecation warning on Linux environments since the SDK spawns several threads.

Expand All @@ -160,3 +161,88 @@ if __name__ == "__main__":
pool = concurrent.futures.ProcessPoolExecutor()
pool.submit(sentry_sdk.capture_message, "world")
```
</Expandable>

<Expandable title="Why was my tag value truncated?">

Currently, every tag has a maximum character limit of 200 characters. Tags over the 200 character limit will become truncated, losing potentially important information. To retain this data, you can split data over several tags instead.

For example, a 200+ character tagged request:

`https://empowerplant.io/api/0/projects/ep/setup_form/?user_id=314159265358979323846264338327&tracking_id=EasyAsABC123OrSimpleAsDoReMi&product_name=PlantToHumanTranslator&product_id=161803398874989484820458683436563811772030917980576`

The 200+ character request above will become truncated to:

`https://empowerplant.io/api/0/projects/ep/setup_form/?user_id=314159265358979323846264338327&tracking_id=EasyAsABC123OrSimpleAsDoReMi&product_name=PlantToHumanTranslator&product_id=1618033988749894848`

<PlatformContent includePath="performance/control-data-truncation" />

</Expandable>


## Profiling

<Expandable title="Why am I not seeing any profiling data?">

If you don't see any profiling data in [sentry.io](https://sentry.io), you can try the following:

- Ensure that <PlatformLink to="/tracing/">Tracing is enabled</PlatformLink>.
- Ensure that the automatic instrumentation is sending performance data to Sentry by going to the **Performance** page in [sentry.io](https://sentry.io).
- If the automatic instrumentation is not sending performance data, try using <PlatformLink to="/tracing/instrumentation/custom-instrumentation">custom instrumentation</PlatformLink>.
- Enable <PlatformLink to="/configuration/options/#debug">debug mode</PlatformLink> in the SDK and check the logs.

### Upgrading From Older SDK Versions

The feature was experimental prior to version `1.17.0`. To update your SDK to the latest version, remove `profiles_sample_rate` from `_experiments` and set it in the top-level options.

```python
sentry_sdk.init(
dsn="___PUBLIC_DSN___",
traces_sample_rate=1.0,
_experiments={
"profiles_sample_rate": 1.0, # for versions before 1.17.0
},
)
```
</Expandable>


## Crons

<PlatformContent includePath="crons/troubleshooting" />

<Expandable title="Why aren't recurring job errors showing up on my monitor details page?">

You may not have <PlatformLink to="/crons/#connecting-errors-to-cron-monitors">linked errors to your monitor</PlatformLink>.

</Expandable>

<Expandable title="Why are my monitors showing up as failed?">

The SDK might be experiencing network issues. Learn more about <PlatformLink to="/troubleshooting/#network-issues">troubleshooting network issues</PlatformLink>.

</Expandable>

<Expandable title="Why am I not receiving alerts when my monitor fails?">

You may not have <PlatformLink to="/crons/#alerts">set up alerts for your monitor</PlatformLink>.

</Expandable>

<Expandable title="What is the crons data retention policy for check-ins?">

Our current data retention policy is 90 days.

</Expandable>

<Expandable title="Do you support a monitor schedule with a six-field crontab expression?">

Currently, we only support crontab expressions with five fields.

</Expandable>

<Expandable title="Can I monitor async tasks as well?">

Yes, just make sure you're using SDK version `1.44.1` or higher since that's when support for monitoring async functions was added.

</Expandable>
4 changes: 4 additions & 0 deletions redirects.js
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Expand Up @@ -964,6 +964,10 @@ const userDocsRedirects = [
source: '/product/explore/feature-flags/:path*',
destination: '/product/issues/issue-details/feature-flags/:path*',
},
{
source: '/platforms/python/:productfeature/troubleshooting/:path*',
destination: '/platforms/python/troubleshooting/:path*',
},
{
source: '/platforms/ruby/guides/:guide/:productfeature/troubleshooting/:path*',
destination: '/platforms/ruby/guides/:guide/troubleshooting/:path*',
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