Tuesday, February 21, 2012

Cluster Tutorial

A cluster is two or more computers (called nodes or members) that work together to perform a task.

There are four major types of clusters:

• Storage
• High availability
• Load balancing
• High performance

Storage clusters provide a consistent file system image across servers in a cluster, allowing the servers to simultaneously read and write to a single shared file system. A storage cluster simplifies storage administration by limiting the installation and patching of applications to one file system. Also, with a cluster-wide file system, a storage cluster eliminates the need for redundant copies of application data and simplifies backup and disaster recovery. Red Hat Cluster Suite provides storage clustering through Red Hat GFS.

High-availability clusters provide continuous availability of services by eliminating single points of failure and by failing over services from one cluster node to another in case a node becomes inoperative. Typically, services in a high-availability cluster read and write data (via read-write mounted file systems). Therefore, a high-availability cluster must maintain data integrity as one cluster node takes over control of a service from another cluster node. Node failures in a high-availability cluster are not visible from clients outside the cluster. (High-availability clusters are sometimes referred to as failover clusters.) Red Hat Cluster Suite provides high-availability clustering through its High-availability Service Management component.

Load-balancing clusters dispatch network service requests to multiple cluster nodes to balance the request load among the cluster nodes. Load balancing provides cost-effective scalability because you can match the number of nodes according to load requirements. If a node in a load-balancing cluster becomes inoperative, the load-balancing software detects the failure and redirects requests to other cluster nodes. Node failures in a load-balancing cluster are not visible from clients outside the cluster. Red Hat Cluster Suite provides load-balancing through LVS (Linux Virtual Server).

High-performance clusters use cluster nodes to perform concurrent calculations. A high-performance cluster allows applications to work in parallel, therefore enhancing the performance of the applications. (High performance clusters are also referred to as computational clusters or grid computing.)

Red Hat Cluster Suite Introduction
Red Hat Cluster Suite (RHCS) is an integrated set of software components that can be deployed in a variety of configurations to suit your needs for performance, high-availability, load balancing, scalability, file sharing, and economy.

Cluster Management (CMAN)
Cluster management manages cluster quorum and cluster membership. CMAN  performs cluster management in Red Hat Cluster Suite for Red Hat Enterprise Linux 5. CMAN is a distributed cluster manager and runs in each cluster node.

CMAN keeps track of cluster quorum by monitoring the count of cluster nodes. If more than half the nodes are active, the cluster has quorum. If half the nodes (or fewer) are active, the cluster does not have quorum, and all cluster activity is stopped. Cluster quorum prevents the occurrence of a "split-brain" condition — a condition where two instances of the same cluster are running. A split-brain condition would allow each cluster instance to access cluster resources without knowledge of the other cluster instance, resulting in corrupted cluster integrity.

Quorum is determined by communication of messages among cluster nodes via Ethernet. Optionally, quorum can be determined by a combination of communicating messages via Ethernet and through a quorum disk. For quorum via Ethernet, quorum consists of 50 percent of the node votes plus 1. For quorum via quorum disk, quorum consists of user-specified conditions. By default, each node has one quorum vote. Optionally, you can configure each node to have more than one vote.

CMAN keeps track of membership by monitoring messages from other cluster nodes. When cluster membership changes, the cluster manager notifies the other infrastructure components, which then take appropriate action. For example, if node A joins a cluster and mounts a GFS file system that nodes B and C have already mounted, then an additional journal and lock management is required for node A to use that GFS file system. If a cluster node does not transmit a message within a prescribed amount of time, the cluster manager removes the node from the cluster and communicates to other cluster infrastructure components that the node is not a member. Again, other cluster infrastructure components determine what actions to take upon notification that node is no longer a cluster member. For example, Fencing would fence the node that is no longer a member.

Lock Management
Lock management is a common cluster-infrastructure service that provides a mechanism for other cluster infrastructure components to synchronize their access to shared resources. In a Red Hat cluster, DLM (Distributed Lock Manager) is the lock manager. As implied in its name, DLM is a distributed lock manager and runs in each cluster node; lock management is distributed across all nodes in the cluster GFS and CLVM use locks from the lock manager. GFS uses locks from the lock manager to synchronize access to file system metadata (on shared storage). CLVM uses locks from the lock manager to synchronize updates to LVM volumes and volume groups (also on shared storage).

Fencing is the disconnection of a node from the cluster's shared storage. Fencing cuts off I/O from shared storage, thus ensuring data integrity. The cluster infrastructure performs fencing through the fence daemon, fenced. When CMAN determines that a node has failed, it communicates to other cluster-infrastructure components that the node has failed. fenced, when notified of the failure, fences the failed node. Other cluster-infrastructure components determine what actions to take — that is, they perform any recovery that needs to done. For example, DLM and GFS, when notified of a node failure, suspend activity until they detect that fenced has completed fencing the failed node. Upon confirmation that the failed node is fenced, DLM and GFS perform recovery. DLM releases locks of the failed node; GFS recovers the journal of the failed node.

The fencing program determines from the cluster configuration file which fencing method to use. Two key elements in the cluster configuration file define a fencing method: fencing agent and fencing device. The fencing program makes a call to a fencing agent specified in the cluster configuration file. The fencing agent, in turn, fences the node via a fencing device. When fencing is complete, the fencing program notifies the cluster manager.

Cluster Configuration System
The Cluster Configuration System (CCS) manages the cluster configuration and provides configuration information to other cluster components in a Red Hat cluster. CCS runs in each cluster node and makes sure that the cluster configuration file in each cluster node is up to date.

The cluster configuration file (/etc/cluster/cluster.conf) is an XML file

High-availability Service Management
High-availability service management provides the ability to create and manage high-availability cluster services in a Red Hat cluster. In a RedHat cluster, an application is configured with other cluster resources to form a high-availability cluster service. A high-availability cluster service can fail over from one cluster node to another with no apparent interruption to cluster clients.

To create a high-availability service, you must configure it in the cluster configuration file. A cluster service comprises cluster resources. Cluster resources are building blocks that you create and manage in the cluster configuration file — for example, an IP address, an application initialization script, or a Red Hat GFS shared partition.

You can associate a cluster service with a failover domain. A failover domain is a subset of cluster nodes that are eligible to run a particular cluster service

Red Hat GFS

Two GFS file systems are available with Red Hat Cluster Suite: GFS and GFS2. GFS/GFS2 is a native file system that interfaces directly with the Linux kernel file system interface (VFS layer). A GFS/GFS2 file system can be implemented in a standalone system or as part of a cluster configuration. When implemented as a cluster file system, GFS/GFS2 employs distributed metadata and multiple journals.

GFS/GFS2 is based on a 64-bit architecture, which can theoretically accommodate an 8 EB file system. However, the current supported maximum size of a GFS/GFS2 file system is 25 TBThe maximum number of nodes supported in a Red Hat Cluster deployment of GFS/GFS2 is 16.

Cluster Logical Volume Manager
The Cluster Logical Volume Manager (CLVM) provides a cluster-wide version of LVM2. CLVM provides the same capabilities as LVM2 on a single node, but makes the volumes available to all nodes in a Red Hat cluster. The logical volumes created with CLVM make logical volumes available to all nodes in a cluster.

The key component in CLVM is clvmd. clvmd is a daemon that provides clustering extensions to the standard LVM2 tool set and allows LVM2 commands to manage shared storage. clvmd runs in each cluster node and distributes LVM metadata updates in a cluster, thereby presenting each cluster node with the same view of the logical volumes (refer to Figure 1.11, “CLVM Overview”). Logical volumes created with CLVM on shared storage are visible to all nodes that have access to the shared storage.

CLVM allows a user to configure logical volumes on shared storage by locking access to physical storage while a logical volume is being configured. CLVM uses the lock-management service provided by the cluster infrastructure

Global Network Block Device
Global Network Block Device (GNBD) provides block-device access to Red Hat GFS over TCP/IP.GNBD is similar in concept to NBD; however, GNBD is GFS-specific and tuned solely for use with GFS. GNBD is useful when the need for more robust technologies — Fibre Channel or single-initiator SCSI — are not necessary or are cost-prohibitive.

GNBD consists of two major components: a GNBD client and a GNBD server. A GNBD client runs in a node with GFS and imports a block device exported by a GNBD server. A GNBD server runs in another node and exports block-level storage from its local storage (either directly attached storage or SAN storage).

Linux Virtual Server (LVS) is a set of integrated software components for balancing the IP load across a set of real servers. LVS runs on a pair of equally configured computers: one that is an active LVS router and one that is a backup LVS router. The active LVS router serves two roles:

• To balance the load across the real servers.
• To check the integrity of the services on each real server.

The backup LVS router monitors the active LVS router and takes over from it in case the active LVS router fails.

Components of a Running LVS Cluster
The pulse daemon runs on both the active and passive LVS routers. On the backup LVS router,pulse sends a heartbeat to the public interface of the active router to make sure the active LVS router is properly functioning. On the active LVS router, pulse starts the lvs daemon and responds to heartbeat queries from the backup LVS router.

Once started, the lvs daemon calls the ipvsadm utility to configure and maintain the IPVS (IP Virtual Server) routing table in the kernel and starts a nanny process for each configured virtual server on each real server. Each nanny process checks the state of one configured service on one real server, and tells the lvs daemon if the service on that real server is malfunctioning. If a malfunction is detected, the lvs daemon instructs ipvsadm to remove that real server from the IPVS routing table.

If the backup LVS router does not receive a response from the active LVS router, it initiates failover by calling send_arp to reassign all virtual IP addresses to the NIC hardware addresses (MAC address) of the backup LVS router, sends a command to the active LVS router via both the public and private network interfaces to shut down the lvs daemon on the active LVS router, and starts the lvs daemon on the backup LVS router to accept requests for the configured virtual servers.

To an outside user accessing a hosted service (such as a website or database application), LVS appears as one server. However, the user is actually accessing real servers behind the LVS routers.Because there is no built-in component in LVS to share the data among real servers, you have have two basic options:

• Synchronize the data across the real servers.
• Add a third layer to the topology for shared data access.

The first option is preferred for servers that do not allow large numbers of users to upload or change data on the real servers. If the real servers allow large numbers of users to modify data, such as an e-commerce website, adding a third layer is preferable.

Note that this document comes without warranty of any kind. But every effort has been made to provide the information as accurate as possible. I welcome emails from any readers with comments, suggestions, and corrections at webmaster_at admin@linuxhowto.in

Copyright © 2012 LINUXHOWTO.IN


  1. Pankaj - I have a doubt regarding cluster.conf. Is there any process to change the location of this conf file for security reason. Is there any thing in ricci to do this ?? Please suggest me

    If yes, then how the node will interact to eachother and how luci update to conf file..


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