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Oracle GlassFish Server 3.1-3.1.1 High Availability Administration Guide
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Document Information

Preface

1.  High Availability in GlassFish Server

Overview of High Availability

HTTP Load Balancer Plug-in

High Availability Session Persistence

High Availability Java Message Service

RMI-IIOP Load Balancing and Failover

How GlassFish Server Provides High Availability

Storage for Session State Data

Highly Available Clusters

Clusters, Instances, Sessions, and Load Balancing

SSH for Centralized Cluster Administration

Recovering from Failures

Recovering the Domain Administration Server

Recovering GlassFish Server Instances

Recovering the HTTP Load Balancer and Web Server

Recovering Message Queue

Recovering From Power Failure and Failures Other Than Disk Storage

Recovering from Failure of Disk Storage

More Information

2.  Setting Up SSH for Centralized Administration

3.  Administering GlassFish Server Nodes

4.  Administering GlassFish Server Clusters

5.  Administering GlassFish Server Instances

6.  Administering Named Configurations

7.  Configuring Web Servers for HTTP Load Balancing

8.  Configuring HTTP Load Balancing

9.  Upgrading Applications Without Loss of Availability

10.  Configuring High Availability Session Persistence and Failover

11.  Configuring Java Message Service High Availability

12.  RMI-IIOP Load Balancing and Failover

Index

Overview of High Availability

High availability applications and services provide their functionality continuously, regardless of hardware and software failures. To make such reliability possible, GlassFish Server provides mechanisms for maintaining application state data between clustered GlassFish Server instances. Application state data, such as HTTP session data, stateful EJB sessions, and dynamic cache information, is replicated in real time across server instances. If any one server instance goes down, the session state is available to the next failover server, resulting in minimum application downtime and enhanced transactional security.

GlassFish Server provides the following high availability features:

HTTP Load Balancer Plug-in

The HTTP Load Balancer Plug-in for Oracle GlassFish Server 3.1 accepts HTTP/HTTPS requests and forwards them to application server instances in a cluster. If an instance fails, becomes unavailable (due to network faults), or becomes unresponsive, the load balancer redirects requests to existing, available hosts. The load balancer can also recognize when a failed instance has recovered and redistribute the load accordingly. The Load Balancer Plug-in is compatible with the Oracle iPlanet Web Server, Oracle HTTP Server, Apache HTTP Server, and Microsoft Internet Information Server.

By distributing workload among multiple physical hosts, the load balancer increases overall system throughput. It also provides higher availability through failover of HTTP requests. For HTTP session information to persist, you must configure HTTP session persistence.

For simple, stateless applications a load-balanced cluster may be sufficient. However, for mission-critical applications with session state, use load balanced clusters with replicated persistence.

Server instances and clusters participating in load balancing have a homogenous environment. Usually that means that the server instances reference the same server configuration, can access the same physical resources, and have the same applications deployed to them. Homogeneity assures that before and after failures, the load balancer always distributes load evenly across the active instances in the cluster.

For information on configuring load balancing and failover for the HTTP Load Balancer Plug-in, see Chapter 7, Configuring Web Servers for HTTP Load Balancing and Chapter 8, Configuring HTTP Load Balancing.

High Availability Session Persistence

GlassFish Server provides high availability of HTTP requests and session data (both HTTP session data and stateful session bean data).

Java EE applications typically have significant amounts of session state data. A web shopping cart is the classic example of a session state. Also, an application can cache frequently-needed data in the session object. In fact, almost all applications with significant user interactions need to maintain session state. Both HTTP sessions and stateful session beans (SFSBs) have session state data.

Preserving session state across server failures can be important to end users. If the GlassFish Server instance hosting the user session experiences a failure, the session state can be recovered, and the session can continue without loss of information. High availability is implemented in GlassFish Server by means of in-memory session replication on GlassFish Server instances running in a cluster.

For more information about in-memory session replication in GlassFish Server, see How GlassFish Server Provides High Availability. For detailed instructions on configuring high availability session persistence, see Chapter 10, Configuring High Availability Session Persistence and Failover.

High Availability Java Message Service

GlassFish Server supports the Java Message Service (JMS) API and JMS messaging through its built-in jmsra resource adapter communicating with GlassFish Server Message Queue as the JMS provider. This combination is often called the JMS Service.

The JMS service makes JMS messaging highly available as follows:

Message Queue Broker Clusters

By default, when a GlassFish cluster is created, the JMS service automatically configures a Message Queue broker cluster to provide JMS messaging services, with one clustered broker assigned to each cluster instance. This automatically created broker cluster is configurable to take advantage of the two types of broker clusters, conventional and enhanced, supported by Message Queue.

Additionally, Message Queue broker clusters created and managed using Message Queue itself can be used as external, or remote, JMS hosts. Using external broker clusters provides additional deployment options, such as deploying Message Queue brokers on different hosts from the GlassFish instances they service, or deploying different numbers of Message Queue brokers and GlassFish instances.

For more information about Message Queue clustering, see Using Message Queue Broker Clusters With GlassFish Server.

Connection Failover

The use of Message Queue broker clusters allows connection failover in the event of a broker failure. If the primary JMS host (Message Queue broker) in use by a GlassFish instance fails, connections to the failed JMS host will automatically fail over to another host in the JMS host list, allowing messaging operations to continue and maintaining JMS messaging semantics.

For more information about JMS connection failover, see Connection Failover.

RMI-IIOP Load Balancing and Failover

With RMI-IIOP load balancing, IIOP client requests are distributed to different server instances or name servers, which spreads the load evenly across the cluster, providing scalability. IIOP load balancing combined with EJB clustering and availability also provides EJB failover.

When a client performs a JNDI lookup for an object, the Naming Service essentially binds the request to a particular server instance. From then on, all lookup requests made from that client are sent to the same server instance, and thus all EJBHome objects will be hosted on the same target server. Any bean references obtained henceforth are also created on the same target host. This effectively provides load balancing, since all clients randomize the list of target servers when performing JNDI lookups. If the target server instance goes down, the lookup or EJB method invocation will failover to another server instance.

IIOP Load balancing and failover happens transparently. No special steps are needed during application deployment. If the GlassFish Server instance on which the application client is deployed participates in a cluster, the GlassFish Server finds all currently active IIOP endpoints in the cluster automatically. However, a client should have at least two endpoints specified for bootstrapping purposes, in case one of the endpoints has failed.

For more information on RMI-IIOP load balancing and failover, see Chapter 12, RMI-IIOP Load Balancing and Failover.