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The following are the application failure modes we dissect in detail in this chapter: Improper handling of a server restart Networked applications must be able to detect the corner cases when data management services restart or failover, such as a long break in service or an aborted transaction Many of these conditions are the same for server reboot and failover, so ensuring proper restart behavior is a good idea even without high availability or other server management software in place Nonfatal system or external failures How does your user application react if it can t find a remote server What if a disk quota is exceeded and a write operation fails None of these conditions is strong enough to cause a failover immediately, but they may have adverse affects on applications.



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When a disk fills up, failover isn t going to help, as the overflowing disk is going to be imported on the other side of the HA pair Persistent failures, such as a network segment that fails and requires redundant routing, or a disk that presents media failures, may be handled automatically, but you want to be sure your application will tolerate the intermediate failures well There s little point in having automated recovery if the user-level application has already failed Internal memory and state management In the vernacular, this category is filed under bugs We restrict our discussion to memory-corruption problems and their detection Memory-related problems are probably one of the most common sources of application-level failures Developer difficulty with memory management was one of the key drivers behind the memory access constraints in Sun s Java environment..

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Logical faults. Examples of these include looping or hung code, deadlock conditions, improper handling of unexpected input, or merely wrong answers. We ll include some boundary condition handling in this category (these are also known as bugs). Many of the topics in this chapter may seem like commonsense items, but even obvious application safety mechanisms fall by the wayside when customer deadlines, urgency of bug fixes, or upcoming trade shows in Las Vegas demand swift development. Damn the torpedoes, full speed ahead works in the movies, but not in the real world when you ve got a beeper attached to your waist. It pays to invest time with the developers up front to be sure the applications under development fit your models for cost, complexity, and time to recover, and that the development and operational camps are aligned in terms of priorities. This often means crossing political boundaries and offering some value in return for a series of meetings. Set your sights on the level of continuous application uptime that you need to achieve, and you can generally coax all of the teams into the same goals. Our goal in this chapter is to show you where the torpedoes are and what you can do to avoid them.

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Investing in application recovery is akin to the message sent out by health management organizations: If you do a good job of early detection and prevention, you won t get too sick. Given that software failures account for a large portion of system failures, your applications need to be sensitive to the different types of faults they ll hit. That s another reason why investments in applications come before investments in clustering software. Why make a bad application failover between hosts, instead of fixing the application Job one is to decide how you ll react to each type of failure. These are cost-time-benefit evaluations, balancing the time required to implement a recovery technique against the cost of having or not having that recovery, with the possible benefit of the automated recovery considered. There s no sense in adding checkpoint features to a database application if it can be easily restarted and the database handles transactional integrity. On the other hand, if an application crash runs the risk of corrupting data or propagating wrong answers, you ll want to invest in taking the necessary steps to keep your data flows clean. We ve broken down recovery techniques into five major categories. We ll provide an overview of these categories here, and then dive into detail on how the most appropriate ones apply to each type of data management service crash, nonfatal system error, and internal logic problem. Detect and retry. Images of Abort, Retry, Fail haunt DOS-literate users. This is the simplest approach, and while it seems obvious, you need to be sure your application tries enough to achieve reconnection to a data service or recovery. In the event of memory exhaustion or

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