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messages that generates higher levels of alerts is also wise. Avoid a system where unknown or new messages are routinely overlooked.
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Most likely, whatever system problem you are trying to solve or information you are trying to collect has been previously solved or collected by someone else. Before you spend a lot of time writing a homegrown single-use application, do a web search for something like it. Usually it is much easier to customize an existing application for your purposes than it is to write something from scratch. The customization process is also much less prone to error. The following are some examples of useful public domain software: Perl. A very useful programming language that was designed by and for system administrators. It runs on just about every major operating system. Tripwire. A Unix utility that watches a list of key system files and notifies the administrators if the files are altered. Top and wintop. These utilities return as output a list of the processes running on the local system, arranged and sorted any number of ways. Top is the Unix version; wintop is the Windows version. Ntp. A cross-platform clock-synchronizing utility. All the systems on your network synchronize their clocks with a preconfigured time server, or with an external server such as an atomic clock located out on the Web. If you do find it necessary to create your own utilities, use the commandline interface, rather than a Windows-based one. It is not hard to imagine a scenario where the person who dials into the server to fix it only has access to a slow line on a dumb terminal from very far away. A command line interface makes the repair process much simpler; no specialized hardware is required.
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Time Matters
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Regardless of the type of system or the method you choose, it is imperative that all systems in a cluster be time-synchronized. Applications and operating systems can get confused when a fundamental assumption is violated: that time always flows in the same direction, forward, at the same rate of one second per second. If systems are out of time-sync, it is possible for one system to create a file with a timestamp that a second system regards as being somewhere in the future. Results can be most inconsistent and confusing. The Unix make utility, for example, will not behave properly when a file s timestamp occurs in the future.
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Failover Management and Issues
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The public domain application ntp is the best utility we have seen to synchronize clocks between multiple systems. Unlike Unix s rdate command or a manual clock set, ntp resets clocks slowly and gradually over a period of time, allowing the time to be changed without applications on the server even being aware of the change. The rdate command changes the date of one server to match another, but it does it all at once, often resulting in time seeming to move backward on the server whose date changes. On Windows, there are similar products, such as WinSNTP and Timeserv.
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Other Clustering Topics
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In this section, we look at some other topics related to clustering and availability that may not fit in other places but are certainly worthy of our attention.
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Replicated Data Clusters
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We discussed replicating data between clustered nodes briefly in 15, but we feel that it is worth discussing a little further at this point. In a replicated data cluster (RDC), data is shared between the clustered nodes by replicating it from one node to the other, rather than by sharing disks between the nodes. We ll discuss more about the mechanisms and choices related to data replication in 18, Data Replication. For the purposes of this discussion, you need only understand the differences between shared data (where all systems in a cluster can see and access the very same disks) and replicated data (where each system in the cluster, usually a two-node cluster, has its own independent copy of the data, and updates are sent between the systems across a network). We believe that when there is a choice between replicated data clusters and shared data clusters (SDCs), SDCs are always preferable. The differences and advantages of shared data clusters are quite clear. RDCs require the extra step of keeping the data in sync between the two clusters at all times, and in real time. Keeping real-time synchronization between two systems data sets requires synchronous replication (where the data must be sent to the remote system as part of each write to the local system). Synchronous replication cannot help but introduce I/O overhead, slowing down all the production work. As we ve discussed, performance is an important element of availability. Slow performance decreases availability. The performance impact is generally a bigger problem with hardware-based replication than it is with software-based replication. (We ll defend this statement in 18.) What s more, since RDCs require additional processing steps, additional components, and a functioning LAN or WAN over which the replicated data is sent, RDCs add complexity when compared to an SDC, as well as more elements that can fail, thus violating Key HA Design Principle #1.
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