OOM Killer Resolutions: Processes with High Risk of Memory Leak

Pay special attention to the processes in this group as to the most probable cause of your out-of-memory issues (sorted based on server role):

Load Balancers

Common recommendations


Allocate more RAM to a corresponding node - handled services could just require more memory for normal operability.

Related processes


ProcessResolution
varnishdAllocate more RAM to a node - handled services could just require more memory for normal operability

Application Servers

Click on points within the list below to view some common recommendations on dealing with memory shortage issues considering used programming language, as well as appropriate resolutions for the most demanding related processes:
  • Java

    Common recommendations

    Review the main memory management configurations for your Java machine and, if required, adjust them according to your application needs, e.g.:

    java -Xmx2048m -Xms256m

    where
    • Xmx flag specifies the maximum heap memory that could be allocated for a Java Virtual Machine (JVM)
    • Xms flag defines initial memory allocation pool

    Refer to the official documentation for more info on Java memory management system.

    Tip: Jelastic also implements supplementary automated memory management for Java containers using Garbage Collector. You are able to customize its settings considering your application specifics to avoid OOM issues and gain more efficient memory utilization.

    Also, take into consideration, that JVM needs more memory than just heap - read through Java Memory Structure reference to get deeper insights.

    Related processes


    ProcessResolution
    javaCheck the xmx, xms, xmn parameters of your Java machine and configure them according to your application needs
  • PHP

    Common recommendations

    1. If the problem occurs with the httpd (httpd.itk) service, adjust server memory management parameters as follows:
    • check the average amount of RAM, used by each httpd instance
    • remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    • decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM

    Note: In case you note persistent growth of memory usage per instance (leak), you need to decrease the MaxRequestsPerChild value (to around 1000-5000).
    2. For the nginx process, connect to your container via SSH and check the size of php-fpm instances (e.g. with ps or top tools):
    • if all of them consume ~50-100Mb of RAM, disable Jelastic auto configuration and decrease the max_children parameter
    • if instances size varies greatly or is over 200-300Mb, the process is probably leaking - inspect and optimize your code or,  alternatively, disable Jelastic auto configuration and decrease the max_requests_per_child parameter

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    lsyncdAllocate more RAM to a node - handled services could just require more memory for normal operability
    httpd.itk1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    nginxDisable Jelastic auto configuration and adjust the appropriate parameters according to your application specifics
    php
    php-fpm
    php-fpm7.0
    php7.0
  • Ruby

    Common recommendations

    Memory leak issues are rather common for Ruby, so, as the first thing to do, consider to inspect and optimize your code. Alternatively, try to increase RAM limit for an instance.

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    httpd.itk1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    bundleAllocate more RAM to a node - handled services could just require more memory for normal operability
    gem
    rubyConsider to inspect and optimize your code or add more RAM to a node
  • Python

    Common recommendations

    1. If the problem occurs with the httpd (httpd.itk) service, adjust server memory management parameters as follows:
    • check the average amount of RAM, used by each httpd instance
    • remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    • decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM

    Note: In case you note persistent growth of memory usage per instance (leak), decrease the MaxRequestsPerChild value (to around 1000-5000).
    2. Otherwise, allocate more RAM to a node - the main Python process could just require more memory for normal operability.

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    lsyncdAllocate more RAM to a node - handled application could just require more memory for normal operability
    httpd.itk1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    pipCan be caused by network issues (so that the download process stucks); otherwise, allocate more RAM to a node - handled application could just require more memory for normal operability
    pythonAllocate more RAM to a node - handled application could just require more memory for normal operability
    python2.7
  • NodeJS

    Common recommendations

    Restart container to restore the killed process(es). If the issue repeats, allocate more RAM to a node - handled application could just require more memory for normal operability.

    Related processes


    ProcessResolution
    lsyncd
    Allocate more RAM to a node - handled application could just require more memory for normal operability
    grunt
    node
    npm
    phantomjs

Database Servers

Click on the required DB stack within the list below to reveal appropriate common recommendations on coping with OOM issues, as well as resolutions for particular killed processes:
  • MySQL

    Common recommendations

    1. If using InnoDB engine (embedded since 5.5 MySQL version), check buffers size with the next command:

    SHOW ENGINE INNODB STATUS\G;

    In case of high buffers value (over 80% of total container RAM), reduce size of the allowed pool with the innodb_buffer_pool_size parameter in /etc/my.cnf file; otherwise, allocate more RAM to a server.

    2. Also, check MySQL logs for warnings and recommendations.

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    mysqld1. If using InnoDB engine (by default for MySQL 5.5 and higher), check buffers size with the SHOW ENGINE INNODB STATUS\G; command. In case of high buffers value (over 80% of total container RAM), reduce the allowed pool size with the innodb_buffer_pool_size parameter in /etc/my.cnf file
    2. Check MySQL logs for warnings and recommendations
  • MongoDB

    Common recommendations

    If the problem occurs with the httpd service, adjust server memory management parameters as follows:
    • check the average amount of RAM, used by each httpd instance
    • remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
    • decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM

    Note: In case you note persistent growth of memory usage per instance (leak), decrease the MaxRequestsPerChild value (to around 1000-5000).

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    mongodAllocate more RAM to a node - handled services could just require more memory for normal operability
  • PostgreSQL

    Common recommendations

    Allocate more RAM to a corresponding node - handled services could just require more memory for normal operability.

    Related processes


    ProcessResolution
    httpd1. Check the average amount of RAM, used by each httpd instance
    2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf file
    3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
    postgresAllocate more RAM to a node - handled services could just require more memory for normal operability
  • Redis

    Common recommendations

    Allocate more RAM to a corresponding node - handled services could just require more memory for normal operability.

    Related processes


    ProcessResolution
    redis-serverAllocate more RAM to a node - handled services could just require more memory for normal operability

Common Processes for Different-Type Stacks

Common recommendations

Processes in this section can be run and, subsequently, killed within different node types. Thus, OOM resolutions for them vary and depend on a process itself - see the table below to find the appropriate recommendations.

Related processes


ProcessStackResolution
httpdPHP
Ruby
Python
MySQL
MongoDB
PostgreSQL
1. Check the average amount of RAM, used by each httpd instance
2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
lsyncdPHP
NodeJS
Python
Allocate more RAM to a node - handled services could just require more memory for normal operability
httpd.itkPHP
Ruby
Python
1. Check the average amount of RAM, used by each httpd instance
2. Remove the Jelastic autoconfiguration mark within the /etc/httpd/httpd.conf  file
3. Decrease ServerLimit and MaxClients values according to the formula: (Total_RAM - 5%) / Average_RAM
procmailAnyRestart container in order to restore the process
vsftpdAny
yumAny
cc13rd partyAllocate more RAM to a node - handled services could just require more memory for normal operability
clamd3rd party
ffmpeg3rd party
firefox3rd party
newrelic-daemon3rd partyRestart the main stack service (nginx, tomcat, nodejs, etc)