Sun Cluster Concepts Guide for Solaris OS

Data Services

The term data service describes an application, such as Sun Java System Web Server or Oracle, that has been configured to run on a cluster rather than on a single server. A data service consists of an application, specialized Sun Cluster configuration files, and Sun Cluster management methods that control the following actions of the application.

For information about data service types, see Data Services in Sun Cluster Overview for Solaris OS.

Figure 3–4 compares an application that runs on a single application server (the single-server model) to the same application running on a cluster (the clustered-server model). The only difference between the two configurations is the clustered application might run faster and will be more highly available.

Figure 3–4 Standard Versus Clustered Client-Server Configuration

Illustration: The following context describes the graphic.

In the single-server model, you configure the application to access the server through a particular public network interface (a hostname). The hostname is associated with that physical server.

In the clustered-server model, the public network interface is a logical hostname or a shared address. The term network resources is used to refer to both logical hostnames and shared addresses.

Some data services require you to specify either logical hostnames or shared addresses as the network interfaces. Logical hostnames and shared addresses are not interchangeable. Other data services allow you to specify either logical hostnames or shared addresses. Refer to the installation and configuration for each data service for details about the type of interface you must specify.

A network resource is not associated with a specific physical server. A network resource can migrate between physical servers.

A network resource is initially associated with one node, the primary. If the primary fails, the network resource and the application resource, fail over to a different cluster node (a secondary). When the network resource fails over, after a short delay, the application resource continues to run on the secondary.

Figure 3–5 compares the single-server model with the clustered-server model. Note that in the clustered-server model, a network resource (logical hostname, in this example) can move between two or more of the cluster nodes. The application is configured to use this logical hostname in place of a hostname associated with a particular server.

Figure 3–5 Fixed Hostname Versus Logical Hostname

Illustration: The preceding context describes the graphic.

A shared address is also initially associated with one node. This node is called the global interface node. A shared address (known as the global interface) is used as the single network interface to the cluster.

The difference between the logical hostname model and the scalable service model is that in the latter, each node also has the shared address actively configured on its loopback interface. This configuration enables multiple instances of a data service active on several nodes simultaneously. The term “scalable service” means that you can add more CPU power to the application by adding additional cluster nodes and the performance will scale.

If the global interface node fails, the shared address can be started on another node that is also running an instance of the application (thereby making this other node the new global interface node). Or, the shared address can fail over to another cluster node that was not previously running the application.

Figure 3–6 compares the single-server configuration with the clustered scalable service configuration. Note that in the scalable service configuration, the shared address is present on all nodes. Similar to how a logical hostname is used for a failover data service, the application is configured to use this shared address in place of a hostname associated with a particular server.

Figure 3–6 Fixed Hostname Versus Shared Address

Illustration: The preceding context describes the graphic.

Data Service Methods

The Sun Cluster software supplies a set of service management methods. These methods run under the control of the Resource Group Manager (RGM), which uses them to start, stop, and monitor the application on the cluster nodes. These methods, along with the cluster framework software and multihost devices, enable applications to become failover or scalable data services.

The RGM also manages resources in the cluster, including instances of an application and network resources (logical hostnames and shared addresses).

In addition to Sun Cluster software-supplied methods, the Sun Cluster system also supplies an API and several data service development tools. These tools enable application developers to develop the data service methods needed to make other applications run as highly available data services with the Sun Cluster software.

Failover Data Services

If the node on which the data service is running (the primary node) fails, the service is migrated to another working node without user intervention. Failover services use a failover resource group, which is a container for application instance resources and network resources (logical hostnames). Logical hostnames are IP addresses that can be configured on one node, and later, automatically configured down on the original node and configured on another node.

For failover data services, application instances run only on a single node. If the fault monitor detects an error, it either attempts to restart the instance on the same node, or to start the instance on another node (failover). The outcome depends on how the data service has been configured.

Scalable Data Services

The scalable data service has the potential for active instances on multiple nodes. Scalable services use the following two resource groups:

The scalable resource group can be online on multiple nodes, so multiple instances of the service can be running at once. The failover resource group that hosts the shared address is online on only one node at a time. All nodes that host a scalable service use the same shared address to host the service.

Service requests enter the cluster through a single network interface (the global interface). These requests are distributed to the nodes, based on one of several predefined algorithms that are set by the load-balancing policy. The cluster can use the load-balancing policy to balance the service load between several nodes. Multiple global interfaces can exist on different nodes that host other shared addresses.

For scalable services, application instances run on several nodes simultaneously. If the node that hosts the global interface fails, the global interface fails over to another node. If an application instance that is running fails, the instance attempts to restart on the same node.

If an application instance cannot be restarted on the same node, and another unused node is configured to run the service, the service fails over to the unused node. Otherwise, the service continues to run on the remaining nodes, possibly causing a degradation of service throughput.

Note –

TCP state for each application instance is kept on the node with the instance, not on the global interface node. Therefore, failure of the global interface node does not affect the connection.

Figure 3–7 shows an example of failover and a scalable resource group and the dependencies that exist between them for scalable services. This example shows three resource groups. The failover resource group contains application resources for highly available DNS, and network resources used by both highly available DNS and highly available Apache Web Server (used in SPARC-based clusters only). The scalable resource groups contain only application instances of the Apache Web Server. Note that resource group dependencies exist between the scalable and failover resource groups (solid lines). Additionally, all the Apache application resources depend on the network resource schost-2, which is a shared address (dashed lines).

Figure 3–7 SPARC: Failover and Scalable Resource Group Example

Illustration: The preceding context describes the graphic.

Load-Balancing Policies

Load balancing improves performance of the scalable service, both in response time and in throughput. There are two classes of scalable data services.

A pure service is capable of having any of its instances respond to client requests. A sticky service is capable of having a client send requests to the same instance. Those requests are not redirected to other instances.

A pure service uses a weighted load-balancing policy. Under this load-balancing policy, client requests are by default uniformly distributed over the server instances in the cluster. For example, in a three-node cluster, suppose that each node has the weight of 1. Each node will service 1/3 of the requests from any client on behalf of that service. The administrator can change weights at any time through the scrgadm(1M) command interface or through the SunPlex Manager GUI.

A sticky service has two flavors, ordinary sticky and wildcard sticky. Sticky services enable concurrent application-level sessions over multiple TCP connections to share in-state memory (application session state).

Ordinary sticky services enable a client to share state between multiple concurrent TCP connections. The client is said to be “sticky” toward that server instance listening on a single port. The client is guaranteed that all requests go to the same server instance, provided that instance remains up and accessible and the load-balancing policy is not changed while the service is online.

For example, a web browser on the client connects to a shared IP address on port 80 using three different TCP connections. However, the connections exchange cached session information between them at the service.

A generalization of a sticky policy extends to multiple scalable services that exchange session information in the background and at the same instance. When these services exchange session information in the background and at the same instance, the client is said to be “sticky” toward multiple server instances on the same node listening on different ports .

For example, a customer on an e-commerce site fills the shopping cart with items by using HTTP on port 80. The customer then switches to SSL on port 443 to send secure data to pay by credit card for the items in the cart.

Wildcard sticky services use dynamically assigned port numbers, but still expect client requests to go to the same node. The client is “sticky wildcard” over pots that have the same IP address.

A good example of this policy is passive mode FTP. For example, a client connects to an FTP server on port 21. The server then instructs the client to connect back to a listener port server in the dynamic port range. All requests for this IP address are forwarded to the same node that the server informed the client through the control information .

For each of these sticky policies, the weighted load-balancing policy is in effect by default. Therefore, a client's initial request is directed to the instance that the load balancer dictates. After the client establishes an affinity for the node where the instance is running, future requests are conditionally directed to that instance. The node must be accessible and the load-balancing policy must not have changed.

Additional details of the specific load-balancing policies are as follows.

Failback Settings

Resource groups fail over from one node to another. When this failover occurs, the original secondary becomes the new primary. The failback settings specify the actions that will occur when the original primary comes back online. The options are to have the original primary become the primary again (failback) or to allow the current primary to remain. You specify the option you want by using the Failback resource group property setting.

If the original node that hosts the resource group fails and reboots repeatedly, setting failback might result in reduced availability for the resource group.

Data Services Fault Monitors

Each Sun Cluster data service supplies a fault monitor that periodically probes the data service to determine its health. A fault monitor verifies that the application daemon(s) are running and that clients are being served. Based on the information that probes return, predefined actions such as restarting daemons or causing a failover can be initiated.