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Guidelines for OpenVMS Cluster Configurations

Guidelines for OpenVMS Cluster Configurations


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10.7.8 Extended LAN Configuration Guidelines

You can use bridges and switches between LAN segments to form an extended LAN. This can increase availability, distance, and aggregate bandwidth as compared with a single LAN. However, an extended LAN can increase delay and can reduce bandwidth on some paths. Factors such as packet loss, queuing delays, and packet size can also affect network performance. Table 10-3 provides guidelines for ensuring adequate LAN performance when dealing with such factors.

Table 10-3 Extended LAN Configuration Guidelines
Factor Guidelines
Propagation delay The amount of time it takes a packet to traverse the LAN depends on the distance it travels and the number of times it is relayed from one link to another through a switch or bridge. If responsiveness is critical, then you must control these factors.

When an FDDI is used for OpenVMS Cluster communications, the ring latency when the FDDI ring is idle should not exceed 400 ms. FDDI packets travel at 5.085 microseconds/km and each station causes an approximate 1-ms delay between receiving and transmitting. You can calculate FDDI latency by using the following algorithm:

Latency = (distance in km) * (5.085 ms/km) + (number of stations) * (1 ms/station)

For high-performance applications, limit the number of switches between nodes to two. For situations in which high performance is not required, you can use up to seven switches or bridges between nodes.

Queuing delay Queuing occurs when the instantaneous arrival rate at switches or bridges and host adapters exceeds the service rate. You can control queuing by:
  • Reducing the number of switches or bridges between nodes that communicate frequently.
  • Using only high-performance switches or bridges and adapters.
  • Reducing traffic bursts in the LAN. In some cases, for example, you can tune applications by combining small I/Os so that a single packet is produced rather than a burst of small ones.
  • Reducing LAN segment and host processor utilization levels by using faster processors and faster LANs, and by using switches or bridges for traffic isolation.
Packet loss Packets that are not delivered by the LAN require retransmission, which wastes network resources, increases delay, and reduces bandwidth. Bridges and adapters discard packets when they become congested. You can reduce packet loss by controlling queuing, as previously described.

Packets are also discarded when they become damaged in transit. You can control this problem by observing LAN hardware configuration rules, removing sources of electrical interference, and ensuring that all hardware is operating correctly.

Packet loss can also be reduced by using VMS Version 5.5--2 or later, which has PEDRIVER congestion control.

The retransmission timeout rate, which is a symptom of packet loss, must be less than 1 timeout in 1000 transmissions for OpenVMS Cluster traffic from one node to another. LAN paths that are used for high-performance applications should have a significantly lower rate. Monitor the occurrence of retransmission timeouts in the OpenVMS Cluster.

Reference: For information about monitoring the occurrence of retransmission timeouts, see HP OpenVMS Cluster Systems.

Switch or bridge recovery delay Choose switches or bridges with fast self-test time and adjust them for fast automatic reconfiguration. This includes adjusting spanning tree parameters to match network requirements.

Reference: Refer to HP OpenVMS Cluster Systems for more information about LAN bridge failover.

Bandwidth All LAN paths used for OpenVMS Cluster communication must operate with a nominal bandwidth of at least 10 Mb/s. The average LAN segment utilization should not exceed 60% for any 10-second interval.

For FDDI configurations, use FDDI exclusively on the communication paths that have the highest performance requirements. Do not put an Ethernet LAN segment between two FDDI segments. FDDI bandwidth is significantly greater, and the Ethernet LAN will become a bottleneck. This strategy is especially ineffective if a server on one FDDI must serve clients on another FDDI with an Ethernet LAN between them. A more appropriate strategy is to put a server on an FDDI and put clients on an Ethernet LAN, as Figure 10-21 shows.

For Gigabit Ethernet configurations, enable jumbo frames where possible.

Traffic isolation Use switches or bridges to isolate and localize the traffic between nodes that communicate with each other frequently. For example, use switches or bridges to separate the OpenVMS Cluster from the rest of the LAN and to separate nodes within an OpenVMS Cluster that communicate frequently from the rest of the OpenVMS Cluster.

Provide independent paths through the LAN between critical systems that have multiple adapters.

Packet size You can adjust the NISCS_MAX_PKTSZ system parameter to use the full FDDI packet size. Ensure that the LAN path supports a data field of at least 4474 bytes end to end.

Some failures cause traffic to switch from an LAN path that supports a large packet size to a path that supports only smaller packets. It is possible to implement automatic detection and recovery from these kinds of failures. This capability requires that the ELAN set the value of the priority field in the FDDI frame-control byte to zero when the packet is delivered on the destination FDDI link. Ethernet-to-FDDI bridges that conform to the IEEE 802.1 bridge specification provide this capability.

10.7.9 System Parameters for OpenVMS Clusters

In an OpenVMS Cluster with satellites and servers, specific system parameters can help you manage your OpenVMS Cluster more efficiently. Table 10-4 gives suggested values for these system parameters.

Table 10-4 OpenVMS Cluster System Parameters
System Parameter Value for
Satellites
Value for
Servers
LOCKDIRWT 0 1-4. The setting of LOCKDIRWT influences a node's willingness to serve as a resource directory node and also may be used to determine mastership of resource trees. In general, a setting greater than 1 is determined after careful examination of a cluster node's specific workload and application mix and is beyond the scope of this document.
SHADOW_MAX_COPY 0 4, where a significantly higher setting may be appropriate for your environment
MSCP_LOAD 0 1
NPAGEDYN Higher than for standalone node Higher than for satellite node
PAGEDYN Higher than for standalone node Higher than for satellite node
VOTES 0 1
EXPECTED_VOTES Sum of OpenVMS Cluster votes Sum of OpenVMS Cluster votes
RECNXINTERVL 1 Equal on all nodes Equal on all nodes


1Correlate with bridge timers and LAN utilization.

Reference: For more information about these parameters, see HP OpenVMS Cluster Systems and HP Volume Shadowing for OpenVMS.

10.8 Scaling for I/Os

The ability to scale I/Os is an important factor in the growth of your OpenVMS Cluster. Adding more components to your OpenVMS Cluster requires high I/O throughput so that additional components do not create bottlenecks and decrease the performance of the entire OpenVMS Cluster. Many factors can affect I/O throughput:

These factors can affect I/O scalability either singly or in combination. The following sections explain these factors and suggest ways to maximize I/O throughput and scalability without having to change in your application.

Additional factors that affect I/O throughput are types of interconnects and types of storage subsystems.

Reference: For more information about interconnects, see Chapter 4. For more information about types of storage subsystems, see Chapter 5. For more information about MSCP_BUFFER and MSCP_CREDITS, see HP OpenVMS Cluster Systems.

10.8.1 MSCP Served Access to Storage

MSCP server capability provides a major benefit to OpenVMS Clusters: it enables communication between nodes and storage that are not directly connected to each other. However, MSCP served I/O does incur overhead. Figure 10-24 is a simplification of how packets require extra handling by the serving system.

Figure 10-24 Comparison of Direct and MSCP Served Access


In Figure 10-24, an MSCP served packet requires an extra "stop" at another system before reaching its destination. When the MSCP served packet reaches the system associated with the target storage, the packet is handled as if for direct access.

In an OpenVMS Cluster that requires a large amount of MSCP serving, I/O performance is not as efficient and scalability is decreased. The total I/O throughput is approximately 20% less when I/O is MSCP served than when it has direct access. Design your configuration so that a few large nodes are serving many satellites rather than satellites serving their local storage to the entire OpenVMS Cluster.

10.8.2 Disk Technologies

In recent years, the ability of CPUs to process information has far outstripped the ability of I/O subsystems to feed processors with data. The result is an increasing percentage of processor time spent waiting for I/O operations to complete.

Solid-state disks (SSDs), DECram, and RAID level 0 bridge this gap between processing speed and magnetic-disk access speed. Performance of magnetic disks is limited by seek and rotational latencies, while SSDs and DECram use memory, which provides nearly instant access.

RAID level 0 is the technique of spreading (or "striping") a single file across several disk volumes. The objective is to reduce or eliminate a bottleneck at a single disk by partitioning heavily accessed files into stripe sets and storing them on multiple devices. This technique increases parallelism across many disks for a single I/O.

Table 10-5 summarizes disk technologies and their features.

Table 10-5 Disk Technology Summary
Disk Technology Characteristics
Magnetic disk Slowest access time.
Inexpensive.
Available on multiple interconnects.
Solid-state disk Fastest access of any I/O subsystem device.
Highest throughput for write-intensive files.
Available on multiple interconnects.
DECram Highest throughput for small to medium I/O requests.
Volatile storage; appropriate for temporary read-only files.
Available on any Alpha or VAX system.
RAID level 0 Available on HSD, HSJ, and HSG controllers.

Note: Shared, direct access to a solid-state disk or to DECram is the fastest alternative for scaling I/Os.

10.8.3 Read/Write Ratio

The read/write ratio of your applications is a key factor in scaling I/O to shadow sets. MSCP writes to a shadow set are duplicated on the interconnect.

Therefore, an application that has 100% (100/0) read activity may benefit from volume shadowing because shadowing causes multiple paths to be used for the I/O activity. An application with a 50/50 ratio will cause more interconnect utilization because write activity requires that an I/O be sent to each shadow member. Delays may be caused by the time required to complete the slowest I/O.

To determine I/O read/write ratios, use the DCL command MONITOR IO.

10.8.4 I/O Size

Each I/O packet incurs processor and memory overhead, so grouping I/Os together in one packet decreases overhead for all I/O activity. You can achieve higher throughput if your application is designed to use bigger packets. Smaller packets incur greater overhead.

10.8.5 Caches

Caching is the technique of storing recently or frequently used data in an area where it can be accessed more easily---in memory, in a controller, or in a disk. Caching complements solid-state disks, DECram, and RAID. Applications automatically benefit from the advantages of caching without any special coding. Caching reduces current and potential I/O bottlenecks within OpenVMS Cluster systems by reducing the number of I/Os between components.

Table 10-6 describes the three types of caching.

Table 10-6 Types of Caching
Caching Type Description
Host based Cache that is resident in the host system's memory and services I/Os from the host.
Controller based Cache that is resident in the storage controller and services data for all hosts.
Disk Cache that is resident in a disk.

Host-based disk caching provides different benefits from controller-based and disk-based caching. In host-based disk caching, the cache itself is not shareable among nodes. Controller-based and disk-based caching are shareable because they are located in the controller or disk, either of which is shareable.

10.8.6 Managing "Hot" Files

A "hot" file is a file in your system on which the most activity occurs. Hot files exist because, in many environments, approximately 80% of all I/O goes to 20% of data. This means that, of equal regions on a disk drive, 80% of the data being transferred goes to one place on a disk, as shown in Figure 10-25.

Figure 10-25 Hot-File Distribution


To increase the scalability of I/Os, focus on hot files, which can become a bottleneck if you do not manage them well. The activity in this area is expressed in I/Os, megabytes transferred, and queue depth.

RAID level 0 balances hot-file activity by spreading a single file over multiple disks. This reduces the performance impact of hot files.

Use the following DCL commands to analyze hot-file activity:

The MONITOR IO and the MONITOR MSCP commands enable you to find out which disk and which server are hot.

10.8.7 Volume Shadowing

The Volume Shadowing for OpenVMS product ensures that data is available to applications and end users by duplicating data on multiple disks. Although volume shadowing provides data redundancy and high availability, it can affect OpenVMS Cluster I/O on two levels:
Factor Effect
Geographic distance Host-based volume shadowing enables shadowing of any devices in an OpenVMS Cluster system, including those served by MSCP servers. This ability can allow great distances along with MSCP overhead. For example, OpenVMS Cluster systems using FDDI can be located up to 25 miles (40 kilometers) apart. Using Fibre Channel, they can be located up to 62 miles (100 kilometers) apart. Both the distance and the MSCP involvement can slow I/O throughput.
Read/write ratio Because shadowing writes data to multiple volumes, applications that are write intensive may experience reduced throughput. In contrast, read-intensive applications may experience increased throughput because the shadowing software selects one disk member from which it can retrieve the data most efficiently.


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