The following sections describe how to tune WebLogic Server to match your application needs.
Java parameters must be specified whenever you start WebLogic Server. For simple invocations, this can be done from the command line with the weblogic.Server
command. However, because the arguments needed to start WebLogic Server from the command line can be lengthy and prone to error, BEA recommends that you incorporate the command into a script. To simply this process, you can modify the default values in the sample scripts that are provided with the WebLogic distribution to start WebLogic Server, as described in “
Specifying Java Options for a WebLogic Server Instance”.
If you used the Configuration Wizard to create your domain, the WebLogic startup scripts are located in the domain-name directory where you specified your domain. By default, this directory is BEA_HOME\user_projects\domain\
domain-name, where BEA_HOME is the directory that contains the product installation, and domain-name is the name of the domain directory defined by the selected configuration template. For more information about creating domains using the Configuration Wizard, see “
Creating Domains Using the Configuration Wizard”.
You need to modify some default Java values in these scripts to fit your environment and applications. The important performance tuning parameters in these files are the JAVA_HOME
parameter and the Java heap size parameters:
JAVA_HOME
to the location of your JDK
. For example:
set JAVA_HOME=C:\bea\jdk150_03
"%JAVA_HOME%\bin\java" -server – Xms512m – Xmx512m -classpath %CLASSPATH% -
See Specifying Heap Size Values for details about setting heap size options.
You can indicate whether a domain is to be used in a development environment or a production environment. WebLogic Server uses different default values for various services depending on the type of environment you specify. Specify the startup mode for your domain as shown in the following table.
Table 6-2 lists the performance-related configuration parameters that differ when switching from development to production startup mode.
You can use the demonstration digital certificates and the demonstration keystores provided by the WebLogic Server security services. With these certificates, you can design your application to work within environments secured by SSL.
For more information about managing security, see “
Configuring SSL” in Securing WebLogic Server.
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WebLogic Server instances can automatically deploy and update applications that reside in the domain_name/autodeploy directory (where domain_name is the name of a domain).
For more information, see “
Auto-Deploying Applications in Development Domains” in Deploying Applications to WebLogic Server.
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The auto-deployment feature is disabled, so you must use the WebLogic Server Administration Console, the weblogic.Deployer tool, or the WebLogic Scripting Tool (WLST). For more information, see Deploying Applications to WebLogic Server.
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For information on switching the startup mode from development to production, see Change to Production Mode in the Administration Console Online Help
WebLogic Server provides the following mechanisms to manage threads to perform work.
In this release, WebLogic Server allows you to configure how your application prioritizes the execution of its work. Based on rules you define and by monitoring actual runtime performance, WebLogic Server can optimize the performance of your application and maintain service level agreements (SLA).
You tune the thread utilization of a server instance by defining rules and constraints for your application by defining a Work Manger and applying it either globally to WebLogic Server domain or to a specific application component. The primary tuning considerations are:
See Using Work Managers to Optimize Scheduled Work in Configuring WebLogic Server Environments.
Each distinct SLA requirement needs a unique work manager.
Service level agreement (SLA) requirements are defined by instances of request classes. A request class expresses a scheduling guideline that a server instance uses to allocate threads. See “ Understanding Work Managers” in Configuring WebLogic Server Environments.
Note: | Execute Queues are deprecated in this release of WebLogic Server. BEA recommends migrating applications to use work managers. |
In previous versions of WebLogic Server, processing was performed in multiple execute queues. Different classes of work were executed in different queues, based on priority and ordering requirements, and to avoid deadlocks. See Using the WebLogic 8.1 Thread Pool Model.
The easiest way to conceptually visualize the difference between the execute queues of previous releases with work managers is to correlate execute queues (or rather, execute-queue managers) with work managers and decouple the one-to-one relationship between execute queues and thread-pools.
For releases prior to WebLogic Server 9.0, incoming requests are put into a default execute queue or a user-defined execute queue. Each execute queue has an associated execute queue manager that controls an exclusive, dedicated thread-pool with a fixed number of threads in it. Requests are added to the queue on a first-come-first-served basis. The execute-queue manager then picks the first request from the queue and an available thread from the associated thread-pool and dispatches the request to be executed by that thread.
For releases of WebLogic Server 9.0 and higher, there is a single priority-based execute queue in the server. Incoming requests are assigned an internal priority based on the configuration of work managers you create to manage the work performed by your applications. The server increases or decreases threads available for the execute queue depending on the demand from the various work-managers. The position of a request in the execute queue is determined by its internal priority:
Work managers provide you the ability to better control thread utilization (server performance) than execute-queues, primarily due to the many ways that you can specify scheduling guidelines for the priority-based thread pool. These scheduling guidelines can be set either as numeric values or as the capacity of a server-managed resource, like a JDBC connection pool.
If you upgrade application domains from prior releases that contain execute queues, the resulting 9.x domain will contain execute queues.
dispatch-policy
.dispatch-policy
use the self-tuning thread pool. For more information on migrating a domain, see Upgrading WebLogic Application Environments.
WebLogic Server automatically detects when a thread in an execute queue becomes “stuck.” Because a stuck thread cannot complete its current work or accept new work, the server logs a message each time it diagnoses a stuck thread.
WebLogic Server diagnoses a thread as stuck if it is continually working (not idle) for a set period of time. You can tune a server’s thread detection behavior by changing the length of time before a thread is diagnosed as stuck, and by changing the frequency with which the server checks for stuck threads. Although you can change the criteria WebLogic Server uses to determine whether a thread is stuck, you cannot change the default behavior of setting the “warning” and “critical” health states when all threads in a particular execute queue become stuck. For more information, see “ Configuring WebLogic Server to Avoid Overload Conditions” in Configuring WebLogic Server Environments. To configure stuck thread detection behavior, see “ Tuning execute thread detection behavior” in Administration Console Online Help.
The following sections provide information on network communication between clients and servers (including T3 and IIOP protocols, and their secure versions):
WebLogic Server uses software modules called muxers to read incoming requests on the server and incoming responses on the client. These muxers are of two primary types: the Java muxer or native muxer.
A Java muxer has the following characteristics:
Native muxers use platform-specific native binaries to read data from sockets. The majority of all platforms provide some mechanism to poll a socket for data. For example, Unix systems use the poll system and the Windows architecture uses completion ports. Native provide superior scalability because they implement a non-blocking thread model. When a native muxer is used, the server creates a fixed number of threads dedicated to reading incoming requests. BEA recommends using the default setting of selected for the Enable Native IO
parameter which allows the server automatically selects the appropriate muxer for the server to use.
If the Enable Native IO
parameter is not selected, the server instance exclusively uses the Java muxer. This maybe acceptable if there are a small number of clients and the rate at which requests arrive at the server is fairly high. Under these conditions, the Java muxer performs as well as a native muxer and eliminate Java Native Interface (JNI) overhead. Unlike native muxers, the number of threads used to read requests is not fixed and is tunable for Java muxers by configuring the Percent Socket Readers
parameter setting in the Administration Console. See Changing the Number of Available Socket Readers. Ideally, you should configure this parameter so the number of threads roughly equals the number of remote concurrently connected clients up to 50% of the total thread pool size. Each thread waits for a fixed amount of time for data to become available at a socket. If no data arrives, the thread moves to the next socket.
Benchmarks show major performance improvements when you use native performance packs on machines that host WebLogic Server instances. Performance packs use a platform-optimized, native socket multiplexor to improve server performance. For example, the native socket reader multiplexor threads have their own execute queue and do not borrow threads from the default execute queue, which frees up default execute threads to do application work
To see which platforms currently have performance packs available:
The use of native performance packs are enabled by default in the configuration shipped with your distribution. You can use the Administration Console to verify that performance packs are enabled. See “ Enable native IO” in Administration Console Online Help.
If you must use the pure-Java socket reader implementation for host machines, you can improve the performance of socket communication by configuring the proper number of socket reader threads for each server instance and client machine. See “ Tuning the number of available socket readers” in Administration Console Online Help.
Network channels, also called network access points, allow you to specify different quality of service (QOS) parameters for network communication. Each network channel is associated with its own exclusive socket using a unique IP address and port. By default, requests from a multi-threaded client are multiplexed over the same remote connection and the server instance reads requests from the socket one at a time. If the request size is large, this becomes a bottleneck.
Although the primary role of a network channel is to control the network traffic for a server instance, you can leverage the ability to create multiple custom channels to allow a multi-threaded client to communicate with server instance over multiple connections, reducing the potential for a bottleneck. To configure custom multi-channel communication, use the following steps:
t3://
<ip1>:
<port1>,
<ip2>:
<port2>
See “ Understanding Network Channels” in Configuring WebLogic Server Environments.
WebLogic Server allows you to specify a maximum incoming request size to reduce the potential for Denial of Service (DoS) attacks by preventing a server from being bombarded by a series of large requests. You can set a global value or set specific values for different protocols and network channels. Although it does not directly impact performance, JMS applications that aggregate messages before sending to a destination may be refused if the aggregated size is greater than specified value. See “ Servers: Protocols: General” in Administration Console Online Help and Tuning Applications Using Unit-of-Order.
A chunk is a unit of memory that the WebLogic Server network layer, both on the client and server side, uses to read data from and write data to sockets. To reduce memory allocation costs, a server instance maintains a pool of these chunks. For applications that handle large amounts of data per request, increasing the value on both the client and server sides can boost performance. The default chunk size is about 4K. Use the following properties to tune the chunk size and the chunk pool size:
weblogic.Chunksize
—Sets the size of a chunk (in bytes). The primary situation in which this may need to be increased is if request sizes are large. It should be set to values that are multiples of the network’s maximum transfer unit (MTU), after subtracting from the value any Ethernet or TCP header sizes. Set this parameter to the same value on the client and server.weblogic.utils.io.chunkpoolsize
—Sets the maximum size of the chunk pool. The default value is 2048. The value may need to be increased if the server starts to allocate and discard chunks in steady state. To determine if the value needs to be increased, monitor the CPU profile or use a memory/ heap profiler for call stacks invoking the constructor weblogic.utils.io.Chunk
.weblogic.PartitionSize
—Sets the number of pool partitions used (default is 4). The chunk pool can be a source of significant lock contention as each request to access to the pool must be synchronized. Partitioning the thread pool spreads the potential for contention over more than one partition.
You can tune the number of connection requests that a WebLogic Server instance will accept before refusing additional requests. The Accept Backlog
parameter specifies how many Transmission Control Protocol (TCP) connections can be buffered in a wait queue. This fixed-size queue is populated with requests for connections that the TCP stack has received, but the application has not accepted yet. For more information on TCP tuning, see Basic OS Tuning Concepts.
You can tune the number of connection requests that a WebLogic Server instance will accept before refusing additional requests, see “ Tune connection backlog buffering” in Administration Console Online Help.
You may improve performance by tuning your server’s compiler options.
Use the weblogic.appc utility to compile EJB container classes. If you compile Jar files for deployment into the EJB container, you must use weblogic.appc to generate the container classes. By default, ejbc uses the javac compiler. You may be able to improve performance by specifying a different compiler (such as IBM Jikes) using the -compiler flag or using the Administration console. For more information, see:
WebLogic Server uses Javelin to compile JSPs. In the weblogic.xml file, the jsp-descriptor element defines parameter names and values for servlet JSPs. Use the precompile parameter to configure WebLogic Server to precompile your JSPs when WebLogic Server starts up. See the jsp-descriptor element.
If you receive the following error message received when compiling JSP files on a UNIX machine:
failed: java.io.IOException: Not enough space
Try any or all of the following solutions:
A WebLogic Server cluster is a group of WebLogic Servers instances that together provide fail-over and replicated services to support scalable high-availability operations for clients within a domain. A cluster appears to its clients as a single server but is in fact a group of servers acting as one to provide increased scalability and reliability.
A domain can include multiple WebLogic Server clusters and non-clustered WebLogic Server instances. Clustered WebLogic Server instances within a domain behave similarly to non-clustered instances, except that they provide failover and load balancing. The Administration Server for the domain manages all the configuration parameters for the clustered and non-clustered instances.
For more information about clusters, see “ Understanding WebLogic Server Clustering”.
Scalability is the ability of a system to grow in one or more dimensions as more resources are added to the system. Typically, these dimensions include (among other things), the number of concurrent users that can be supported and the number of transactions that can be processed in a given unit of time.
Given a well-designed application, it is entirely possible to increase performance by simply adding more resources. To increase the load handling capabilities of WebLogic Server, add another WebLogic Server instance to your cluster—without changing your application. Clusters provide two key benefits that are not provided by a single server: scalability and availability.
WebLogic Server clusters bring scalability and high-availability to J2EE applications in a way that is transparent to application developers. Scalability expands the capacity of the middle tier beyond that of a single WebLogic Server or a single computer. The only limitation on cluster membership is that all WebLogic Servers must be able to communicate by IP multicast. New WebLogic Servers can be added to a cluster dynamically to increase capacity.
A WebLogic Server cluster guarantees high-availability by using the redundancy of multiple servers to insulate clients from failures. The same service can be provided on multiple servers in a cluster. If one server fails, another can take over. The ability to have a functioning server take over from a failed server increases the availability of the application to clients.
Caution: | Provided that you have resolved all application and environment bottleneck issues, adding additional servers to a cluster should provide linear scalability. When doing benchmark or initial configuration test runs, isolate issues in a single server environment before moving to a clustered environment. |
Clustering in the Messaging Service is provided through distributed destinations; connection concentrators, and connection load-balancing (determined by connection factory targeting); and clustered Store-and-Forward (SAF). Client load-balancing with respect to distributed destinations is tunable on connection factories. Distributed destination Message Driven Beans (MDBs) that are targeted to the same cluster that hosts the distributed destination automatically deploy only on cluster servers that host the distributed destination members and only process messages from their local destination. Distributed queue MDBs that are targeted to a different server or cluster than the host of the distributed destination automatically create consumers for every distributed destination member. For example, each running MDB has a consumer for each distributed destination queue member.
In general, any operation that requires communication between the servers in a cluster is a potential scalability hindrance. The following sections provide information on issues that impact the ability to linearly scale clustered WebLogic servers:
In many cases where a cluster of WebLogic servers fails to scale, the database is the bottleneck. In such situations, the only solutions are to tune the database or reduce load on the database by exploring other options. See DataBase Tuning and Tuning JDBC Applications.
User session data can be stored in two standard ways in a J2EE application: stateful session EJBs or HTTP sessions. By themselves, they are rarely a impact cluster scalability. However, when coupled with a session replication mechanism required to provide high-availability, bottlenecks are introduced. If a J2EE application has Web and EJB components, you should store user session data in HTTP sessions:
See Session Management.
This applies to entity EJBs that use a concurrency strategy of Optimistic
or ReadOnly
with a read-write pattern.
Optimistic
—When an Optimistic
concurrency bean is updated, the EJB container sends a multicast message to other cluster members to invalidate their local copies of the bean. This is done to avoid optimistic concurrency exceptions being thrown by the other servers and hence the need to retry transactions. If updates to the EJBs are frequent, the work done by the servers to invalidate each other’s local caches become a serious bottleneck. A flag called cluster-invalidation-disabled
(default false) is used to turn off such invalidations. This is set in the rdbms
descriptor file.
ReadOnly
with a read-write pattern—In this pattern, persistent data that would otherwise be represented by a single EJB are actually represented by two EJBs: one read-only and the other updateable. When the state of the updateable bean changes, the container automatically invalidates corresponding read-only EJB instance. If updates to the EJBs are frequent, the work done by the servers to invalidate the read-only EJBs becomes a serious bottleneck.
Similar to Invalidation of Entity EJBs, HTTP sessions can also be invalidated. This is not as expensive as entity EJB invalidation, since only the session data stored in the secondary server needs to be invalidated. BEA advises users to not invalidate sessions unless absolutely required.
In general, JNDI binds, unbinds and rebinds are expensive operations. However, these operations become a bigger bottleneck in clustered environments because JNDI tree changes have to be propagated to all members of a cluster. If such operations are performed too frequently, they can reduce cluster scalability significantly.
With multi-processor machines, additional consideration must be given to the ratio of the number of available CPUs to clustered WebLogic Server instances. Because WebLogic Server has no built-in limit to the number of server instances that reside in a cluster, large, multi-processor servers, such as Sun Microsystems’ Sun Enterprise 10000, can potentially host very large clusters or multiple clusters.
In order to determine the optimal ratio of CPUs to WebLogic server instances, you must first ensure that an application is truly CPU-bound, rather than network or disk I/O-bound. Use the following steps to determine the optional ratio of CPUs to server instances:
If you discover that an application is primarily network I/O-bound, consider measures to increase network throughput before increasing the number of available CPUs. For truly network I/O-bound applications, installing a faster network interface card (NIC) may increase performance more than additional CPUs, because most CPUs would remain idle while waiting to read available sockets.
If you discover that an application is primarily disk I/O-bound, consider upgrading the number of disk spindles or individual disks and controllers before allocating additional CPUs.
The following sections provide information on how to monitor WebLogic Server domains:
The tool for monitoring the health and performance of your WebLogic Server domain is the Administration Console. See “ Monitor servers” in Administration Console Online Help.
WebLogic Server® provides its own set of MBeans that you can use to configure, monitor, and manage WebLogic Server resources. See “Developing Custom Management Utilities with JMX”.
The WebLogic Scripting Tool (WLST) is a command-line scripting interface that system administrators and operators use to monitor and manage WebLogic Server instances and domains. See “WebLogic Scripting Tool”.
dev2dev.bea.com provides product downloads, articles, sample code, product documentation, tutorials, white papers, news groups, and other key content for WebLogic Server.
BEA partners with other companies that provide production monitoring and management tools. See Production Performance Management.