Liferay Portal 6.2 Enterprise Edition. Deployment Checklist

Similar documents
Liferay Digital Experience Platform. Deployment Checklist

Deploying Liferay Digital Experience Platform in Amazon Web Services

Runtime Application Self-Protection (RASP) Performance Metrics

SAP ENTERPRISE PORTAL. Scalability Study - Windows

JVM Performance Study Comparing Oracle HotSpot and Azul Zing Using Apache Cassandra

SPECjAppServer2002 Statistics. Methodology. Agenda. Tuning Philosophy. More Hardware Tuning. Hardware Tuning.

SAS 9.2 Web Applications: Tuning for Performance and Scalability

SAS 9.2 Web Applications: Tuning for Performance and Scalability

Diplomado Certificación

ORACLE IDENTITY MANAGER SIZING GUIDE. An Oracle White Paper March 2007

Workload Control Center Performance Tuning

JVM Performance Study Comparing Java HotSpot to Azul Zing Using Red Hat JBoss Data Grid

White Paper. Major Performance Tuning Considerations for Weblogic Server

GlassFish v2.1 & Enterprise Manager. Alexis Moussine-Pouchkine Sun Microsystems

Enabling Java-based VoIP backend platforms through JVM performance tuning

Performance and Scalability with Griddable.io

Samsung SDS Enterprise Cloud

Caching Use Cases in the Enterprise

J2EE: Best Practices for Application Development and Achieving High-Volume Throughput. Michael S Pallos, MBA Session: 3567, 4:30 pm August 11, 2003

ManageEngine Applications Manager 9. Product Features

Oracle JD Edwards EnterpriseOne Object Usage Tracking Performance Characterization Using JD Edwards EnterpriseOne Object Usage Tracking

Part I Garbage Collection Modeling: Progress Report

IBM FileNet Content Manager 5.2. Asynchronous Event Processing Performance Tuning

Webcenter Application Performance Tuning guide

Tuning Performance of Oracle WebLogic Server 12c (12.2.1)

When (and how) to move applications from VMware to Cisco Metacloud

IBM WebSphere Application Server V4.0. Performance. 10/02/01 Copyright 2001 IBM Corporation WS40ST11.prz Page 248 of of 28

MyCloud Computing Business computing in the cloud, ready to go in minutes

Oracle WebCenter Portal Performance Tuning

vcloud Automation Center Reference Architecture vcloud Automation Center 5.2

Oracle WebLogic Server 12c: Administration I

ORACLE DATA SHEET KEY FEATURES AND BENEFITS ORACLE WEBLOGIC SUITE

Virtualizing SQL Server 2008 Using EMC VNX Series and VMware vsphere 4.1. Reference Architecture

Oracle Primavera P6 Enterprise Project Portfolio Management Performance and Sizing Guide. An Oracle White Paper April 2011

WHITE PAPER AGILOFT SCALABILITY AND REDUNDANCY

Installing on WebLogic Server

Capacity Planning for Application Design

Deployment Scenario: WebSphere Portal Mashup integration and page builder

Best Practices for Setting BIOS Parameters for Performance

Understanding Liferay Portal's Business Value. and Critical Measures for Success

Typical Issues with Middleware

status Emmanuel Cecchet

WebSphere 4.0 General Introduction

IBM InfoSphere Streams v4.0 Performance Best Practices

Oracle JD Edwards EnterpriseOne Object Usage Tracking Performance Characterization Using JD Edwards EnterpriseOne Object Usage Tracking

Java Performance Tuning

Oracle Database 12c: JMS Sharded Queues

ORACLG. Oracle Press. Advanced Tuning for. JD Edwards EnterpriseOne. Implementations

SAP BusinessObjects Explorer Sizing Guide SAP BusinessObjects Enterprise 4.0 Support Package 03

Java Performance: The Definitive Guide

IBM Cognos ReportNet and the Java Heap

Dynatrace FastPack for Liferay DXP

X100 ARCHITECTURE REFERENCES:

Estimate performance and capacity requirements for InfoPath Forms Services 2010

EsgynDB Enterprise 2.0 Platform Reference Architecture

Extreme Performance Platform for Real-Time Streaming Analytics

Tuning Cognos ReportNet for a High Performance Environment

COPYRIGHTED MATERIAL

Qlik Sense Enterprise architecture and scalability

Run Syncope in real environments

Administering WebLogic Server on Java Cloud Service I Ed 1 Coming Soon

<Insert Picture Here> Oracle Coherence & Extreme Transaction Processing (XTP)

Diagnostics in Testing and Performance Engineering

Java & Coherence Simon Cook - Sales Consultant, FMW for Financial Services

Liferay Security Features Overview. How Liferay Approaches Security

Sage ERP Accpac. Compatibility Guide Version 6.0. Revised: February 2, Version 6.0 Compatibility Guide

Technical white paper Asset Manager 9.5x Deployment Sizing Guide

Introduction. Architecture Overview

Contents Overview of the Performance and Sizing Guide... 5 Architecture Overview... 7 Performance and Scalability Considerations...

Oracle Primavera P6 Enterprise Project Portfolio Management Performance and Sizing Guide. An Oracle White Paper December 2011

Using Patrol for BEA WebLogic to Accelerate the Value of WebLogic Server (WLS) Tuning Primary Tuning Considerations Execute Queues

Microsoft SQL Server in a VMware Environment on Dell PowerEdge R810 Servers and Dell EqualLogic Storage

ArcGIS Server Performance and Scalability : Optimizing GIS Services

Finally! Real Java for low latency and low jitter

Planning Resources. vrealize Automation 7.1

Administering the JBoss 5.x Application Server

WHITE PAPER: BEST PRACTICES. Sizing and Scalability Recommendations for Symantec Endpoint Protection. Symantec Enterprise Security Solutions Group

WebLogic Server- Tips & Tricks for Troubleshooting Performance Issues. By: Abhay Kumar AST Corporation

Azul Pauseless Garbage Collection

Quality Center Benchmark March 2009

... IBM AIX performance and tuning tips for Oracle s JD Edwards EnterpriseOne web server

Sage 300 ERP. Compatibility Guide Version Revised: Oct 1, Version 6.0 Compatibility Guide i

<Insert Picture Here> Oracle Policy Automation System Requirements

CA Identity Governance

TECHNOLOGY WHITE PAPER. Azul Pauseless Garbage Collection. Providing continuous, pauseless operation for Java applications

Java Without the Jitter

Virtualization of the MS Exchange Server Environment

Optimizing WebCenter Interaction Performance

Disclaimer This presentation may contain product features that are currently under development. This overview of new technology represents no commitme

IBM B2B INTEGRATOR BENCHMARKING IN THE SOFTLAYER ENVIRONMENT

1Z Oracle Application Grid 11g Essentials Exam Summary Syllabus Questions

BEAWebLogic Server. Introduction to BEA WebLogic Server and BEA WebLogic Express

vsan 6.6 Performance Improvements First Published On: Last Updated On:

Intellicus Cluster and Load Balancing- Linux. Version: 18.1

Idle WebSphere Tuning Considerations

Designing SAN Using Cisco MDS 9000 Series Fabric Switches

AWS Solution Architecture Patterns

Cisco Unified Provisioning Manager 2.2

Best Practices. Deploying Optim Performance Manager in large scale environments. IBM Optim Performance Manager Extended Edition V4.1.0.

Nutanix Tech Note. Virtualizing Microsoft Applications on Web-Scale Infrastructure

Transcription:

Liferay Portal 6.2 Enterprise Edition Deployment Checklist

Contents Introduction... 1 Reference Architecture... 1 Virtualized And Cloud Deployments... 2 Security... 2 Performance... 2 Fault Tolerance... 2 Scalability... 3 Portal Tuning Guidelines... 3 Application Server Tuning... 3 Deactivate Development Settings In The Jsp Engine... 3 Thread Pool... 3 Database Connection Pool... 4 Java Virtual Machine Tuning... 4 Garbage Collector... 5 Java Heap... 5 Monitoring Gc And Jvm... 6 Portal Tuning Parameters... 7 Servlet Filters... 7 User Session Tracker... 7 Counter Increment... 7 Portlet Css... 8 Session Timeout... 8 Portal Caching... 8 Portal Cache Replication... 9 Liferay Search...10 Liferay Message Bus...11 Summary...13 Disclaimer...13 Moving Forward...13 Liferay Portal Enterprise Edition...13 Liferay Global Services...13

Introduction The Liferay Engineering and Global Services teams have performed intensive performance and scalability testing on Liferay Portal Enterprise Edition (LPEE) and the accumulated knowledge has been condensed into this checklist. Although a portal s performance profile may differ depending on several factors, this checklist will provide a list of critical parameters to monitor for tuning and some initial settings to use as a starting point. These initial settings have withstood heavy testing by the Liferay Engineering scalability team. The Liferay Global Services team also has a specialized Go Live package that can help with your pre-production tuning and configuration. Reference Architecture The selection of an appropriate architecture is one of the first decisions in your deployment path. To select an appropriate architecture, you must consider: Information Security securing sensitive hardware and information from malicious attack and intrusion Performance supporting the desired number of total users, concurrent transactions, etc. Fault Tolerance Maintaining uptime during unexpected failure or scheduled maintenance Flexibility and Scalability designing an expandable architecture to support additional features and users without significant redesign Although appearing somewhat complex, the reference architecture depicted in Figure 1 provides high levels of fault tolerance and flexibility. Load Balancer Tier Web Tier Application Tier Database Tier Load Balancer Apache Web Server Application Server Database Server Firewall Load Balancer Apache Web Server Application Server Database Server The architecture contains the following tiers: Firewall Detects and prevents intrusion. Figure 1 - LPEE Reference Architecture Load Balancer Tier Ensures smooth distribution of load between multiple web server resources. Web Server Tier Delivers static content elements like images, rich media, CSS files, etc. Also provides integration modules to single sign-on solutions like CA Netegrity, Oracle Identity, etc. Application Tier Hosts Liferay supported application servers like Tomcat, JBoss, GlassFish, Oracle AS, Oracle/BEA Weblogic, and IBM Websphere (please see LPEE support matrix for additional platforms). Database Tier Hosts Liferay supported database servers like MySQL, Oracle, MS SQL, IBM DB2, Postgres (please see LPEE support matrix for additional platforms) The hardware deployed within each tier varies depending on the type of transactions. We will use Liferay Engineering s benchmarking environment as a hardware specification guide: 1

Load Balancer Tier Cisco Load Director or Cisco Content Services Switch (CSS) or F5 Big-IP Web Tier Primarily forward traffic to the underlying application servers. However, they also provide caching, compression, and other capabilities. 1 - Intel Core 2 Duo E6405 2.13GHz CPU, 4GB memory, 1-146GB 10k RPM SCSI Application Tier Represents the workhorse of the architecture. 2 Intel Core 2 Quad X5677 3.46GHz CPU, 64GB memory, 2-300GB 15K RPM SATA 6Gbps Database Tier 2 Intel Core 2 Quad X5677 3.46GHz CPU, 64GB memory, 2-300GB 15K RPM SATA 6Gbps Although the application and database servers have 64GB of physical memory, you may choose to deploy with only 16GB on these servers if your Java Virtual Machine (JVM) does not exceed 8GB. VIRTUALIZED AND CLOUD DEPLOYMENTS While the reference architecture describes a physical deployment, the same concepts may be applied to a cloud based or virtualized deployment. Many Liferay customers choose to deploy on either public clouds (e.g., Amazon EC2) or their own private clouds (e.g., VMWare VSX based private cloud). Each physical machine may be replaced by appropriate quantities of virtual machines. In the virtualized deployments, it is critical to allocate sufficient CPU resources. For instance, for systems deployed to Amazon AWS, allocated CPUs are calculated using Amazon EC2 Compute Units. However, 1 Compute Unit does not equal to 1 physical CPU or even 1 core on a CPU. In Amazon s terms, each application server used in the reference architecture equates to roughly a Cluster Compute Quadruple Extra Large Instance, or 33.5 EC2 Compute Units. Thus, to properly plan the virtualized/cloud deployment, customers must account for not only virtualization overhead, but also ensure allocation of sufficient CPU resources. SECURITY The firewall preceding the Load Balancer Tier will provide sufficient intrusion detection and prevention. However, depending on your organization s information security requirements, you may introduce additional firewall layers between each tier to further secure the infrastructure. PERFORMANCE Each portal deployment s performance characteristics will vary depending on the type of activity and the performance of custom application elements. Liferay Engineering has created a series of scenarios to benchmark LPEE s out of the box performance characteristics for content management, collaboration, and social enterprise scenarios. Results from these reference architectures have indicated LPEE can support over 22,000 virtual collaboration users and over 150,000 logins per minute with an average login time of 300 milliseconds. LPEE accomplished this load within the reference architecture while utilizing no more than 40% of CPU resources in the Web Tier, 86% of CPU resources in the Application Tier, and 50% of CPU resources in the Database Tier. FAULT TOLERANCE The reference architecture is fault tolerant at every level. With clusters at the web, application, and database tier, you may suffer a catastrophic hardware failure of any node and continue to service users with little performance degradation. The depicted reference architecture represents the minimum deployment units to ensure proper fault tolerance within a single data center. You may increase the number of servers within each tier according to your load patterns to achieve a multiplier effect in the number of users the deployment can support while maintaining sufficient fault tolerance. Multi-data-center fault tolerance architectures are not provided as part of the reference architecture. 2

SCALABILITY Liferay Engineering s testing has shown LPEE to scale linearly. Thus, if you know a single application server supports X virtual users and assuming sufficient database and web server resources, you may calculate the total number of application servers required. Portal Tuning Guidelines When tuning your LPEE, there are several factors to take into consideration, some specific to Liferay Portal, while others are concepts that apply to all Java and Java enterprise applications. The following guidelines are meant to serve as an initial baseline from which to tune your specific deployment. APPLICATION SERVER TUNING Although the actual setting names may differ, the concepts are applicable across most application servers. We will use Tomcat as an example to demonstrate application server tuning concepts. You should also consult your application server provider s documentation for additional specific settings that they may advise. DEACTIVATE DEVELOPMENT SETTINGS IN THE JSP ENGINE Most application servers have their JSP Engine configured for development mode. Liferay recommends deactivating many of these settings prior to entering production: Development mode this will enable the JSP container to poll the file system for changes to JSP files. Mapped File generates static content with one print statement versus one statement per line of JSP text. Generate String as Char Array generates strings as static character arrays to relieve excess garbage collection. Tomcat 7.0.x In the $CATALINA_HOME/conf/web.xml, update the JSP servlet to look like the following <servlet> <servlet-name>jsp</servlet-name> <servlet-class>org.apache.jasper.servlet.jspservlet</servlet-class> <init-param> <param-name>development</param-name> <param-value>false</param-value> </init-param> <init-param> <param-name>mappedfile</param-name> <param-value>false</param-value> </init-param> <init-param> <param-name>genstraschararray</param-name> <param-value>true</param-value> </init-param> <load-on-startup>3</load-on-startup> </servlet> THREAD POOL Each incoming request to the application server consumes a worker thread for the duration of the request. When no threads are available to process requests, the request will be queued waiting for the next available worker thread. In a finely tuned system, the number of threads in the thread pool should be relatively balanced with the total number of concurrent requests. There should not be a significant amount of threads left idle waiting to service requests. 3

Liferay Engineering recommends setting this initially to 50 threads and then monitoring it within your application server s monitoring consoles. You may wish to use a higher number (e.g. 250) if your average page times are in the 2-3s range. Tomcat 7.0.x In Tomcat, the thread pools are configured in the Connector element in $CATALINA_HOME/conf/ server.xml. Further information can be found in the Apache Tomcat documentations (http://tomcat.apache.org/tomcat-7.0-doc/config/http.html). Liferay Engineering used the following configuration during testing: <Connector maxthreads= 75 minsparethreads= 50 maxconnections= 16384 port= 8080 connectiontimeout= 600000 redirectport= 8443 URIEncoding= UTF-8 socketbuffer= -1 maxkeepaliverequests= -1 address= xxx.xxx.xxx.xxx /> Additional tuning parameters around Connectors are available, including the connection timeouts and TCP queue. You should consult the appropriate Tomcat documentation for further details. DATABASE CONNECTION POOL The database connection pool is generally sized at roughly 20-30% of the thread pool size. The connection pool provides a connection whenever LPEE needs to retrieve data from the database (e.g. user login, etc). If this size is too small, requests will queue in the server waiting for database connections. However, too large a setting will mean wasting resources with idle database connections. Tomcat 7.0.x In Tomcat, the connection pools are configured in the Resource elements in $CATALINA_HOME/ conf/ Catalina/localhost/ ROOT.xml. Liferay Engineering used the following configuration during testing: <Resource auth= Container description= Portal DB Connection driverclass= com.mysql.jdbc.driver maxpoolsize= 75 minpoolsize= 10 acquireincrement= 5 name= jdbc/liferaypool user= XXXXXX password= XXXXXXXXX factory= org.apache.naming.factory.beanfactory type= com.mchange.v2.c3p0.combopooleddatasource jdbcurl= jdbc:mysql://someserver:3306/lportal?useunicode=true&characte rencoding=utf-8&usefastdateparsing=false /> In this configuration, we start with 10 threads, and increment by 5 as needed to a maximum of 75 connections in the pool. You may choose from a variety of database connection pool providers, including DBCP, C3P0, and Tomcat. You may also choose to configure the Liferay JDBC settings in your portal.properties. JAVA VIRTUAL MACHINE TUNING Tuning the JVM primarily focuses on tuning the garbage collector and the Java memory heap. These parameters look to optimize the throughput of your application. We used Oracle s 1.7 JVM for the reference architecture. You may also choose other JVM implementations. GARBAGE COLLECTOR 4

Choosing the appropriate garbage collector will help improve the responsiveness of your LPEE deployment. Liferay recommends using the concurrent low pause collectors: -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:+CMSParallelRemarkEnabled -XX:ParallelGCThreads=16 -XX:+CMSCompactWhenClearAllSoftRefs -XX:CMSInitiatingOccupancyFraction=85 -XX:+CMSScavengeBeforeRemark -XX:+CMSConcurrentMTEnabled -XX:ParallelCMSThreads=2 Other garbage collectors include a concurrent throughput collector. You may find more information on garbage collector heuristics at http://www.oracle.com/technetwork/java/javase/ tech/index-jsp-140228.html. JAVA HEAP When most people think about tuning the Java memory heap, they think of setting the maximum and minimum memory of the heap. Unfortunately, most deployments require far more sophisticated heap tuning to obtain optimal performance, including tuning the young generation size, tenuring durations, survivor spaces, and many other JVM internals. For most systems, Liferay recommends starting with at least the following memory settings: -server -XX:NewSize=700m -XX:MaxNewSize=700m -Xms2048m -Xmx2048m -XX:MaxPermSize=200m -XX:SurvivorRatio=6 XX:TargetSurvivorRatio=90 XX:MaxTenuringThreshold=15 Combining the GC and memory parameters, we have: -server -XX:NewSize=700m -XX:MaxNewSize=700m -Xms2048m -Xmx2048m -XX:MaxPermSize=200m -XX:SurvivorRatio=6 XX:TargetSurvivorRatio=90 XX:MaxTenuringThreshold=15 -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -XX:+CMSParallelRemarkEnabled -XX:ParallelGCThreads=16 -XX:+CMSCompactWhenClearAllSoftRefs -XX:CMSInitiatingOccupancyFraction=85 -XX:+CMSScavengeBeforeRemark -XX:+CMSConcurrentMTEnabled -XX:ParallelCMSThreads=2 On servers with 8+GB of memory and for sites with very fast transaction times, you may begin your performance tuning with the following settings: -server -d64 -XX:NewSize=3072m -XX:MaxNewSize=3072m -Xms6144m -Xmx6144m -XX:PermSize=200m -XX:MaxPermSize=200m -XX:SurvivorRatio=65536 -XX:TargetSurvivorRatio=0 -XX:MaxTenuringThreshold=0 -XX:+UseParNewGC -XX:ParallelGCThreads=16 -XX:+UseConcMarkSweepGC -XX:+CMSParallelRemarkEnabled -XX:+CMSCompactWhenClearAllSoftRefs -XX:CMSInitiatingOccupancyFraction=85 -XX:+CMSScavengeBeforeRemark -XX:+CMSConcurrentMTEnabled -XX:ParallelCMSThreads=2- XX:+UseLargePages -XX:LargePageSizeInBytes=256m -XX:+UseCompressedOops -XX:+DisableExplicitGC -XX:-UseBiasedLocking -XX:+BindGCTaskThreadsToCPUs -XX:+UseFastAccessorMethods You may find the definitive list of JVM options are located at: http://www.oracle.com/technetwork/ java/javase/tech/vmoptions-jsp-140102.html. Caution: The above JVM settings should formulate a starting point for your performance tuning. Each system s final parameters will vary due to a variety of factors including number of current users and transaction speed. MONITORING GC AND JVM 5

Although the previously introduced parameters give you a good start to tuning your JVM, you must monitor GC performance to ensure you have the best settings to meet your needs. There are several tools to help you monitor Oracle JVM performance including: Visual VM (http://visualvm.dev.java.net) This tool provides a centralized console for viewing Oracle JVM performance information, including garbage collector activities. Figure 2 - Visual VM s Visual GC JMX Console This tool helps display various statistics like Liferay s distributed cache performance, the performance of application server threads, JDBC connection pool usage, etc. Add the following to you application server s JVM arguments to enable JMX connections: -Dcom.sun.management.jmxremote=true -Dcom.sun.management.jmxremote. port=5000 -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun. management.jmxremote.ssl=false Garbage Collector Verbose Logging Figure 3 - Visual VM s JMX Console 6

Add the following to your JVM arguments to activate verbose logging for the JVM garbage collector. -Xloggc:/tmp/liferaygc1.log -XX:+PrintGCDetails -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCApplicationStoppedTime You will need these logs to properly tune the JVM. PORTAL TUNING PARAMETERS LPEE ships with many parameters already optimized for performance. However, depending on your specific use case, you may wish to tune additional settings. Unless otherwise stated, you may tune these parameters in the portal properties file. SERVLET FILTERS LPEE ships with a large collection of servlet filters to implement features like CAS SSO, and NTLM SSO. You may choose to remove the following filters: GZIP Filter used for GZIP compression of the generated pages. You should allow the Apache Web Server perform this operation. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.gzip.gzipfilter=false Strip Filter used to remove extraneous whitespaces in generated HTML. Web servers should be used to handle this processing. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.strip.stripfilter=false SSO CAS Filter used to implement single sign-on using CAS. If you rely upon a different solution, you may deactivate. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.sso.cas.casfilter=false SSO NTLM Filter used to implement single sign-on using NTLM. If you rely upon a different solution, you may deactivate. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.sso.ntlm.ntlmfilter=false com.liferay.portal.servlet.filters.sso.ntlm.ntlmpostfilter=false SSO OpenSSO Filter used to implement single sign-on using OpenSSO. If you rely upon a different solution, you may deactivate. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.sso.opensso.openssofilter=false SharePoint Filter used to implement enable the portal to understand SharePoint protocols for integration with MS Office applications. To deactivate, add the following to portal-ext.properties com.liferay.portal.sharepoint.sharepointfilter=false Valid HTML Filter used to ensure HTML generated from Portal are XHTML compliant. To deactivate, add the following to portal-ext.properties com.liferay.portal.servlet.filters.validhtml.validhtmlfilter=false Prior to LPEE 6.1, an alternative way to further increase performance was to modify the web.xml for the portal and remove these filters. However, Liferay Engineering has simplified this process such that deactivation within the portal properties will provide the same performance gains. USER SESSION TRACKER LPEE enables administrators to view the activities of the users currently using the portal. While useful for troubleshooting, this feature may decrease performance. In general, we recommend deactivating this feature. You may do so by adding the following to portal-ext.properties: session.tracker.memory.enabled=false COUNTER INCREMENT LPEE uses an internal sequence generator for generating object ids. Increasing the increment size of this counter will reduce the number of times it must communicate with the database to reserve IDs. We recommend setting this number at roughly 2000, depending on the load of your 7

system. You may do so by adding the following to portal-ext.properties: counter.increment=2000 PORTLET CSS LPEE provides you the ability to assign custom style sheets within your portlets. You may choose to deactivate this feature, especially if you are not planning on deploying any custom portlets in LPEE. You may do so by adding the following to portal-ext.properties: portlet.css.enabled=false SESSION TIMEOUT With most web applications, the default session timeout is configured for 30 minutes. Although this may be friendly for the user, it does create added resource consumption for the application. LPEE provides several techniques to help you reduce the session timeout for idle users while minimally impacting usability. To reduce the lifespan of the session, you should modify the web.xml and change the timeout: <session-config> <session-timeout>10</session-timeout> </session-config> PORTAL CACHING WARNING: Care should be taken when tuning caching. The size of the cache will have a direct impact on the amount of memory your application server has to work with. The larger the cache, the less memory available for processing requests. If your application caching requirements exceed what the out of the box, in-process provides in scalability, Liferay recommends investigating the use of Terracotta as a clustered, out of process cache. Liferay Portal relies upon both content and object caching to minimize database interaction and excessive object creation. Out of the box, the portal leverages EHCache for its caching needs. You may configure additional caches including Terracotta, OSCache, Oracle Coherence Cache, and etc. For the purposes of our discussion, we will focus on the out of box EHCache. To monitor the caches, you will need to rely upon the JMX Console. In the proceeding figure, we see the JMX Console view for monitoring a cache used to store user information: CacheHits displays the number of requests that successfully retrieved from the cache rather than going to the database. This includes objects stored in memory and stored on disk. CacheMisses displays the number of requests that could not find its object in cache and thus had to retrieve from the database. InMemoryHits displays the number of requests that successfully retrieved from the in-memory cache. This does not include requests that triggered retrievals from on disk storage. ObjectCount the total number of objects in cache OnDiskHits the total number of requests that could not find their objects in memory, but successfully located the objects on the local file system. This is only applicable if you have enabled cache overflow to disk. 8

Figure 4 - Monitoring Liferay Data Caches By default, Liferay Portal s cache configuration uses the memory store and allows for a maximum of 10,000 elements. Although using a disk store may increase the size of the cache, Liferay does not recommend this approach due the increased dependency upon disk IO operations. Let us use the user cache as our tuning example. After monitoring, you have determined that the user cache requires tuning due to the number of cache misses. You may tune and override Liferay s cache settings either via a plugin or via changes to portalext.properties. Please consult the Liferay Portal User s Guide for further instructions on how to modify the cache settings with a plugin. Portal level data caches of interest include: com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.accountimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.contactimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.groupimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.layoutimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.layoutsetimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portal.model.impl.resourceimpl The following caches may be of interest, depending on the features you are leveraging in the product: com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet.blogs.model. impl.blogsentryimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet.wiki.model. impl.wikipageimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet. messageboards.model.impl.mbcategoryimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet. messageboards.model.impl.mbthreadimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet.journal.model. impl.journalarticleimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet.journal.model. impl.journalstructureimpl com.liferay.portal.kernel.dao.orm.entitycachecom.liferay.portlet.journal.model. impl.journaltemplateimpl PORTAL CACHE REPLICATION Liferay Portal has hundreds of object caches that require event cached object replication or cache event replication. By default, Ehcache uses a thread-per-cache replication algorithm which may introduce additional overhead. 9

For Enterprise Edition customers, Liferay ships with an enhanced algorithm which uses more efficient thread pooling for cached object and event replication (see Liferay Portal User s Guide). To configure the portal to use this algorithm, please download and install the ehcache-cluster-web plugin module from the Liferay EE Marketplace and configure the following portal properties: cluster.link.enabled=true ehcache.cluster.link.replication.enabled=true LIFERAY SEARCH Liferay employs a pluggable search architecture to provide portal wide searching capabilities. By default, Liferay Portal embeds the Lucene search engine. This approach is suitable for departmental level solutions. However, when deploying a medium to large scale system, Liferay recommends utilizing SOLR with its advanced clustering and sharding capabilities. SOLR allows you to tune search engine performance separate from that of Liferay Portal. If you choose to utilize the embedded Lucene search engine, Liferay recommends configuring the following parameters: Set the limit for results used when performing index searches. index.search.limit=2000 Set the limit for results used when performing index searches that are subsequently filtered by permissions. index.filter.search.limit=2000 Set this to true if you want to index your entire library of files after an upgrade. Only set this property to false if you are running a small upgrade and you do not need to reindex everything. index.on.upgrade=false Set how often index updates will be committed. Set the batch size to configure how many consecutive updates will trigger a commit. If the value is 0, then the index will be committed on every update. Set the time interval in milliseconds to configure how often to commit the index. The time interval is not read unless the batch size is greater than 0 because the time interval works in conjunction with the batch size to guarantee that the index is committed after a specified time interval. Set the time interval to 0 to disable committing the index by a time interval. lucene.commit.batch.size=10 lucene.commit.time.interval=5000 Set Lucene s buffer size in megabytes. Higher numbers mean indexing goes faster but uses more memory. You may wish to tune this based on your search performance lucene.buffer.size=16 Set this to true if you want the portal to replicate an index write across 10

all members of the cluster. This is useful in some clustered environments where you wish each server instance to have its own copy of the Lucene search index. This is only relevant when using the default Lucene indexing engine. lucene.replicate.write=true LIFERAY MESSAGE BUS WARNING: This is an advanced configuration and you should modify sparingly. The Liferay Message Bus has been tuned to handle most scenarios. Liferay Portal leverages asynchronous messaging, via the Liferay Message Bus, for many of its services like mail and indexing. The bus provides a loosely coupled, pluggable architecture that helps improve user experience by performing system tasks (e.g. email notifications) in the background. Liferay recommends monitoring and tuning the message bus according to your use case. You may monitor message bus statistics via the JMX Console discussed previously. Figure 5 - Monitoring Liferay Message Bus In above picture, we see the statistics for the messaging destination liferay/mail : ActiveThreadCount displays the current number of active worker threads for this destination CurrentThreadCount displays the total number of worker threads LargestThreadCount displays the maximum number of worker threads. This is the high water mark reached when the destination was the busiest MaxThreadPoolSize displays the maximum number of worker threads allowed for this destination. The destination will not allocate more than this number of threads to service requests. MinThreadPoolSize displays the minimum number of worker threads that should be started when the destination is activated. PendingMessageCount displays the number of messages waiting for worker threads to deliver them. SentMessageCount displays the total number of messages delivered via this destination. In tuning the Liferay Message Bus, you should monitor the PendingMessageCount and the ActiveThreadCount statistics. If you do not have sufficient worker threads allocated, you will see a high PendingMessageCount, implying you should allocate more threads to deliver the message. However, you should be conservative in allocating additional threads as too many threads may cause performance degradation. 11

To change the default settings, you may modify the messaging-spring.xml bundle with the portal. The messaging-spring.xml resides within portal-impl.jar and you may override by following instructions provided in the Liferay User Guide. To continue with our example, let s assume we want to increase the number of threads for the liferay/mail destination. We would modify the settings in messaging-spring.xml to: <bean id= destination.mail class= com.liferay.portal.kernel.messaging. ParallelDestination > <property name= name value= liferay/mail /> <property name= maximumqueuesize value= 100 /> <property name= workercoresize value= 10 /> <property name= workersmaxsize value= 15 /> </bean> The above settings will configure the liferay/mail destination to have at minimum 10 and no more than 15 worker threads to service requests. 12

Summary In the preceding sections, we outlined the steps to design a fully fault-tolerant Liferay Portal Enterprise Edition deployment. The architecture described builds a solid foundation for future growth. In addition, the Liferay Engineering team has shared several key factors in successfully tuning a LPEE deployment. Although these parameters have wide application and have withstood many different load testing scenarios, Liferay Engineering recommends continuously monitoring your LPEE deployment to ensure long-term performance. Disclaimer Liferay can only give you an initial tuning recommendation based on benchmarks that have been performed on the core Portal product. It is up to you as system architects and business analysts to come up with the utilization scenarios that your system will need to service. It is your responsibility to run the appropriate load tests on your system before production deployment, so that you can identify significant bottlenecks due to custom applications/portlets, and other unforeseen system and network issues, and implement appropriate configurations. Please use this document and the Liferay Portal Performance whitepaper (https://www.liferay. com/documents/14/8440801/liferay+portal+6.2+performance+whitepaper/58702354-aa0e-4215-80c6-5067f281e436) as guides in sizing your system and procuring your hardware. Moving Forward LIFERAY PORTAL ENTERPRISE EDITION Liferay Portal Enterprise Edition helps ensure the stability, security, and performance for your Liferay Portal installation. Liferay Portal EE contains additional features that further enhance your solutions scalability and also provides access to a network of over 140 partners worldwide. Download a free trial of Liferay Portal at /free-trial. LIFERAY GLOBAL SERVICES Liferay Global Services has specialists that focus on Liferay Portal Go Live consultation. For more information, contact sales@liferay.com. 13

LIFERAY, INC. is a provider of leading enterprise open source portal and collaboration software products, used by major enterprises worldwide, including Allianz, AutoZone, Cisco Systems, Lufthansa Flight Training, The French Ministry of Defense, Toyota and the United Nations. Liferay, Inc. offers professional services, technical support, custom development and professional training to ensure successful deployment in the most demanding IT environments 2014, Liferay, Inc. All rights reserved. 140303