Gunicorn gevent memory leak

Gunicorn gevent memory leak. Oct 29, 2014 · We run Celery with gevent, and though memory consumption starts out great, over time, the memory usage grows. ThreadWorker inherit from Worker, it also override the init_process method and run method. 0. Using the preload flag can help a bit in small memory VM’s. Default: 0 This alternative syntax will load the gevent class: gunicorn. 4 sites on Ubuntu 12. See: examples/alt_spec. gunicorn --workers=5 main:app Any value greater than zero will limit the number of requests a worker will process before automatically restarting. On Kubernetes, the pod is showing no odd behavior or restarts and stays within 80% of its memory and CPU limits. wsgi -w 3 -b 0. Default: 0 May 21, 2022 · 1. timeout = 3600. New in version 19. Some settings are only able to be set from a configuration file. Internal refactoring and various Dec 1, 2018 · Flushes its connection pool on socket timeout, returning resources to the redis server (and reducing memory footprint on its own side). patch_psycopg (tried wsgi. api. 1 and have run into a strange problem with gunicorn 0. I am using Gunicorn to run Django app and Celery to manage queue. Depending on the system, using multiple Using the preload flag can help a bit in small memory VM’s. Debian We would like to show you a description here but the site won’t allow us. 1 Worker Class: gevent. Greenlets are an implementation of cooperative multi-threading for Python. After I deploy I noticed that python3 process uses even more memory (something around 75%). The command I'm starting gunicorn is: gunicorn app. Aug 15, 2023 · I'm encountering performance issues with gunicorn+genevent that is consuming a significant amount of RAM after conducting a high-load test. When other worker types like gevent are used, it seems not to consume that much memory. By default gunicorn use the sync mode, It prefork workers number of process and each worker is able to handle one request at a time. The application I am running is a deep learning framework for automatic image recognition. Default: 0 Jan 16, 2016 · If you still get the memory leak loading the file from the CLI, the issue is with your application code. I am a novice in this arena, so any help will greatly be appreciated. wsgi. Mar 3, 2010 · Benoit managed to side step the Gevent bug. 6 Since Gunicorn 19, a threads option can be used to process requests in multiple threads. Default: 0 Jun 26, 2019 · When using the gthread worker for a simple flask app like below, the memory of the worker process gradually increases and even after all the processing is done the memory used by the worker never comes down. Added an example gevent reloader configuration: examples/example_gevent_reloader. In addition, thanks to reports like issue #704 , we know that the PyPy garbage collector can interact badly with Cython-compiled code, leading to crashes. keepalive = 2. Jan 24, 2019 · Now i want to maximize the number of requests to that service. Default: 0 When using Gunicorn as the WSGI HTTP server for running Superset, you can specify limits for the request line and header field sizes in the Gunicorn config file. Default: 0 There was pretty high load due to many webhook events being processed and after a while Gunicorn workers started to fail with WORKER TIMEOUT (see log below). Default: 0 Apr 26, 2016 · workers = 4. Gunicorn ‘Green Unicorn’ is a Python WSGI HTTP Server for UNIX. This can be a convenient way to help limit the effects of the memory leak. py is a simple configuration file). Feb 26, 2020 · Author. 11. poller = selectors. Note. Dec 21, 2018 · 9. Are you letting gevent monkeypatch the threading module? Yes, Gunicorn does that when using gevent workers: https://github. New gevent worker “egg:gunicorn#gevent2”, working with gevent. 6. 04 if in MNISTSubset. Nov 11, 2022 · Steps taken. But when actually calling the API, it Any value greater than zero will limit the number of requests a worker will process before automatically restarting. The memory usage is constantly hovering around 67%, even after I increased the memory size from 1GB to 3GB. When config max-requests-jitter=50, it will keep only randint(0, max_requests_jitter) worker will restart on same time. 7 有幾種 worker type，分別是 sync、gthread、eventlet、gevent 和 tornado。. max_requests_jitter ¶ Command line:--max-requests-jitter INT. I also tried this: gunicorn main:app --keep-alive 10. py, settings. Debian Jul 4, 2015 · I have a memory leak that is hard to reproduce in testing environment. The following command sets the timeout to 10 mins. That'll be the problem then. workers. 60 GB drive. 0a8-1. For a dual-core (2 CPU) machine, 5 is the suggested workers value. workers = 10. In the below app I am loading the csv file of 10 Any value greater than zero will limit the number of requests a worker will process before automatically restarting. py. Default: 0 Settings ¶. The fourth place of configuration information are command line arguments stored in an environment variable named GUNICORN_CMD_ARGS. In general, an application should be able to make use of these worker classes with no changes. If an option is specified on the command line, this is the value that will be used. This alternative syntax will load the gevent class: gunicorn. With Async I can have up to 2000, with the caveats that come with async. 0:8000 --env DJANGO_SETTINGS_MODULE=app. 0; Django 1. It’s a pre-fork worker model ported from Ruby’s Unicorn project. CherryPy: Initially needed very little memory, but its usage steadily increased with its load. threads = 2. The command line arguments are listed as well for reference on setting at the command line. Default: 0 Jan 26, 2014 · Supervisor Django Gunicorn Gevent Memory Usage. When I make an HTTP Request I always get Connection close in the header. Default: 0 Using threads instead of processes is a good way to reduce the memory footprint of Gunicorn, while still allowing for application upgrades using the reload signal, as the application code will be shared among workers but loaded only in the worker processes (unlike when using the preload setting, which loads the code in the master process). It seems that it's not that easy to profile Gunicorn due to the usage of greenlets. As I can see CPU usage is really low, but memory usage seems to be large. Default: 0 Jan 20, 2022 · I am hoping someone can give me some direction on how to determine what is causing this out of memory to continue to occur. What is even puzzling is that the memory seems to be used by multiple identical Any value greater than zero will limit the number of requests a worker will process before automatically restarting. GeventWorker. andrewgodwin commented on Feb 26, 2020. 6, I have installed gevent according to gunicorn's documentation, and my gunicorn config looks like that: Settings ¶. py; Added an example gevent reloader configuration: examples/example_gevent_reloader. 0 Severe memory leak with Django . This is a simple method to help limit the damage of memory leaks. 7. settings. This is my gunicorn configuration: workers = 5. def init_process ( self ): self. Database is MySQL. This is an exhaustive list of settings for Gunicorn. Yay new feature. The cause was our use of C extensions for accessing redis and rabbitmq in combination with our usage of the gevent worker type with gunicorn. worker_connections = 1000. 3; Gunicorn 18. Allow people to pass command line arguments to WSGI applications. 0. I am not even sure if this stacktrace is the actual cause of server hang as 2-3 other get requests are shown after this stacktrace (get requests which work normally when the server is started fresh) and Jan 29, 2018 · 2. Just doing Sep 17, 2021 · I have encountered a memory leak problem related with Gunicorn FastApi and multiprocessing library. After a gunicorn worker processed max_requests (plus random jitter) number of requests, it will send Connection: close in the response header to nginx to close that particular connection and will also stop accepting any new The asynchronous workers available are based on Greenlets (via Eventlet and Gevent). 0rc1 应用通过 gunicorn 来启动： gunico Jul 13, 2017 · It will be a separate copy. user3778137. gunicorn[tornado] - Tornado-based workers, not recommended. Instructions for adding swap on Digital Ocean. gevent. py and post_fork in gunicorn) but to no avail. Default: 0 Any value greater than zero will limit the number of requests a worker will process before automatically restarting. ggevent. 04 with supervisor 3. Any value greater than zero will limit the number of requests a worker will process before automatically restarting. Also, go ahead add some swap to the machine as a safety buffer. Internal refactoring and various Mar 31, 2021 · The following warning message is a regular occurrence, and it seems like requests are being canceled for some reason. Tried running gevent's monkey. __init__ (), instead of using `detach (). You must actually use gevent/eventlet in your own code to see any benefit to using the Dec 15, 2017 · 2 CPUs. 5 Out of memory: Kill process (gunicorn) score or sacrifice child. If this is set to zero (the default) then the automatic worker restarts are disabled. If your application suffers from memory leaks, you can configure Gunicorn to gracefully restart a worker after it has processed a given number of requests. memory leak - gunicorn + django + mysqldb. Settings ¶. 8 has shared memory for multiprocessing, no more pipe objects between processes. There are 5 sites with the following supervisor configs: Any value greater than zero will limit the number of requests a worker will process before automatically restarting. gunicorn server:app -k gevent --worker-connections 1000 Gunicorn 1 worker 12 threads: gunicorn server:app -w 1 --threads 12 Gunicorn with 4 workers (multiprocessing): gunicorn server:app -w 4 More information on Flask concurrency in this post: How many concurrent requests does a single Flask process receive?. Lastly, the command line arguments used to invoke Gunicorn are the final place considered for configuration settings. worker_class = 'egg:gunicorn#gevent'. Default: 0 Dec 7, 2021 · Gunicorn uses a pre-fork worker model, which means that it manages a set of worker threads that handle requests concurrently. mod_wsgi: At lower levels, it was one of the more memory intensive, but stayed fairly consistent. Debian Oct 11, 2020 · memory leak - gunicorn + django + mysqldb. Internal refactoring and various May 11, 2016 · Gunicorn: Was able to handle increased loads with barely perceptible memory increases. worker_class = gevent. e. api:application , where gunicorn_conf. The setting name is what should be used in the configuration file. Gunicorn with gevent async worker. To do so, I have done the following: Installed greenlet, gevent & psycogreen as instructed in official docs. 1k requests/min. answered Feb 3, 2020 at 9:15. 7. Default: 0 gunicorn[tornado] - Tornado-based workers, not recommended. Gunicorn 在 Python 2. When inspecting the resource usage, it seems to use a lot when loading the model, as expected. By preloading as much code as possible more memory is shared between the processes. Default: 0 Feb 3, 2020 · To avoid this you can increase the default timeout set by Gunicorn by adding --timeout <timeinterval-in-seconds>. 0:5000 --timeout 600 run:app. But I have no idea about Gevent. #for API2. sync 底層實作 Gunicorn - WSGI server. py#L38. Multiple extras can be combined, like pip install gunicorn[gevent,setproctitle]. 2 and gevent 0. Even when I return an empty view with just a "hello world" message, the RAM usage continues to remain high, causing other requests to get stuck. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resources, and fairly speedy. tpool = self. Here's an example configuration snippet: --limit-request-line 4094 \. Jul 14, 2021 · Additionally, the code also works as expected in Ubuntu 18. I setup nginx with a number of keepalive connections to gunicorn. prod --reload. I am also using Supervisor to monitor the app. worker_connections = a value (lets say 2000) So (based on a 4 core system) using sync workers I can have a maximum of 9 connections processing in parallel. I would add 1 Gig. 13. py app. 17. Same behavior observed with latest versions of pytorch and torchvision. Mar 13, 2024 · $ gunicorn hello:app --timeout 10 See the Gunicorn Docs on Worker Timeouts for more information. Using threads instead of processes is a good way to reduce the memory footprint of Gunicorn, while still allowing for application upgrades using the reload signal, as the application code will be shared among workers but loaded only in the worker processes (unlike when using the preload setting, which loads the code in the master process). If you are running more than one instance of Gunicorn, the proc_name setting will help distinguish between them in tools like ps and top. uWSGI: Clearly the version we tested against has memory issues. hassan-digicatapult changed the title Pytorch model load failure n Dec 12, 2023 · Despite having 25% maximum CPU and memory usage, performance starts to degrade at around 400 active connections according to Nginx statistics. worker_class = sync. 5 minutes is a pretty significant especially since you only have 3 workers. Using threads assumes use of the gthread worker. get_thread_pool () self. gunicorn -k eventlet -b 0. I have an API with async functions that it is running with gunicorn( gunicorn -k uvicorn. Aug 8, 2013 · I am running Django 1. All available command line arguments can be used. workers = (2 * cpu) + 1. 根據底層運作的原理可以將 worker 分成三種類型：. Member. Furthermore extension and internal stuff always had the ability to release the GIL and do its own thing (for example, on a threadpool, or using async/nonblocking I/O). So I'd like to profile my production server for a limited time period to get an overview about which objects take up most memory. gunicorn[setproctitle] - Enables setting the process name. ¶. patch_all manually, also no use. 1. Gunicorn is creating workers in every second. So we now have the --max-requests feature in trunk and the about to be released 0. You will have to twist and tweak these values based on your server load, IO traffic and memory availability. Default: 0 Using the preload flag can help a bit in small memory VM’s. One benefit from threads is that requests can take longer than the worker timeout while notifying the master process that it is not frozen and should not be killed. For example, to specify the bind address and number of workers: $ GUNICORN_CMD_ARGS="--bind=127. Mar 7, 2020 · Oh, that PDF is interesting, Python 3. As of right now, my best result is with gunicorn -t 120 -w 4 -k gevent --threads 12 -b 0. preloading simply takes advantage of the fact that when you call the operating system's fork() call to create a new process, the OS is able to share unmodified sections of memory between the two processes. Yay closing oldest and longest lived bug in Gunicorn history. Questions: Feb 19, 2020 · Since a few weeks the memory usage of the pods keeps growing. Oct 30, 2010 · Using the preload flag can help a bit in small memory VM’s. Header response: Header response Any value greater than zero will limit the number of requests a worker will process before automatically restarting. Internal refactoring and various Settings can be specified by using environment variable GUNICORN_CMD_ARGS. Mar 30, 2020 · Gunicorn: version 19. clone ()' I convert to and from numpy (i. Our Gunicorn configuration: gunicorn --workers 5 --worker-connections=1000 --worker-class=gevent --bind localhost:8000 --disable-redirect-access-to-syslog. 请提供下述完整信息以便快速定位问题/Please provide the following information to quickly locate the problem 系统环境/System Environment： kubernetes/docker 版本号/Version：Paddle： PaddleOCR： 问题相关组件/Related components： paddlepaddle 2. reupen commented on Feb 26, 2020. These settings define the maximum allowed size of the HTTP request line in Using threads instead of processes is a good way to reduce the memory footprint of Gunicorn, while still allowing for application upgrades using the reload signal, as the application code will be shared among workers but loaded only in the worker processes (unlike when using the preload setting, which loads the code in the master process). Whenever I deploy I am running after_deploy script, which contains following: Any value greater than zero will limit the number of requests a worker will process before automatically restarting. If you need asynchronous support, Gunicorn provides workers using either gevent or eventlet. You should test load response with a script designed to mock a flurry of simultaneous requests to both API's (you can use grequests for that). If you don't get the memory leak in your CLI test, the issue is with your Gunicorn configuration. Settings. [2021-03-31 16:30:31 +0200] [1] [WARNING] Worker with pid 26 was terminated due to signal 9. Patched postgres with psycogreen. But resource contention was a symptom, not the cause. 3 Async with gevent or eventlet¶ The default sync worker is appropriate for many use cases. Look at two param max-requests=250 and max-requests-jitter=50. UvicornWorker -c app/gunicorn_conf. Tuning the settings to find the sweet spot is a continual process but I would try the following - increase the number of workers to 10 (2 * num_cpu_cores + 1 is the recommended starting point) and reduce max-requests significantly because if your requests are taking that long then they won't be restarting that much Using the preload flag can help a bit in small memory VM’s. For full greenlet support applications might need to be adapted. async (gevent) workers = 1. However, as per Gunicorn's documentation, 4-12 workers should handle hundreds to thousands of requests per second. I am puzzled by the high percentage of memory usage by Gunicorn. Max request recycling. --limit-request-field_size 8190 \. 1 have a bug that can cause a memory leak when subclassing objects that are implemented in Cython, as is the c-ares resolver. I'm running: Python 2. When a mount request spam to server, max 50 worker will restart but now randint worker is only 5 worker restart same time and need some seconds that need to . Default: 0 Oct 20, 2023 · 1. Severe memory leak sync. com/benoitc/gunicorn/blob/7d8c92f48a6d9cee6b15fbdade6981721182d073/gunicorn/workers/ggevent. I have a Django app using Gunicorn, Ngnix, PostgreSQL. 0:8980 script:app which results in ~ 2. This is not the same as Python’s async/await, or the ASGI server spec. Jun 19, 2014 · If you think the problem if caused by gunicorn workers there is a easy way to test the hypothesis: Start the workers with the parameter --max-requests *some positive number* This will make gunicorn restart every worker after it has served the specified number of requests. After looking into the process list I noticed that there are many gunicorn processes which seem dead but are still using memory. Supervisor's memory usage keeps growing until the server is not responsive. Assuming we're not able to track down why the memory bloats or leaks, is there a good way May 16, 2020 · I am using django, gunicorn, supervisor and nginx with python 3. Internal refactoring and various Jul 16, 2018 · There is no shared memory between the workers. Currently, we have 12 Gunicorn workers, which is lower than the recommended (2 * CPU) + 1. The suggested number of workers is (2*CPU)+1. Gunicorn allows PersonDB to process thousands of requests per second from real-time applications. replace lines 65, 66 with 70, 71). 1 --workers=3" gunicorn app:app. Each client talks to a Gunicorn thread, which in turn queries the in-memory PersonDB data. 8. Debian Released versions of PyPy through at least 4. What is even puzzling is that the memory seems to be used by multiple identical Aug 24, 2023 · Running gunicorn with command: gunicorn main:app. rd sb ha gp tc xo tq dh yv hm