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There are two basic kinds of undesirable failovers: ping-pong failovers and runaway failovers. Both can be prevented by a good FMS. A ping-pong failover can occur if there is, for instance, a massive shared disk failure. System crate cannot access the disks, and so it shuts down, initiates a failover, and reboots. Barrel takes over and also cannot reach them. So once crate reboots, barrel fails back to it. This process continues until a human intervenes. A good FMS will support some sort of state locking, where if crate fails to barrel, barrel will hold the critical resources until a human intervenes, fixes the problem, and unlocks the state. In some cases, ping-pong failovers can cause data corruption. Ping-pong failures can also be prevented by disabling automatic reboot. If crate crashes, it is best if it does not automatically reboot, but rather awaits some human intervention. State locking will also help prevent runaway failovers. In a runaway failover, samson crashes and delilah takes over. In an effort to diagnose the problem with samson, the system administrator reboots samson. Immediately upon completion of the reboot, delilah sees that samson is back, gives up the critical processes, and fails back to samson before the system administrator has even begun trying to identify the cause of the original failure. If, however, delilah can lock control of the cluster s critical resources after it takes over, then nothing that happens on samson should cause delilah to fail back to samson. Once the system administrator is satisfied that the problem is fixed, then, if he chooses, he can manually induce delilah to switch back to samson. (Availability is increased, though, if delilah is allowed to keep running the critical resources even after samson comes back up.)



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Designing a highly available system will lead to several sessions where you re sitting in a room, huddled with developers, managers, businesspeople, and the system administration staff, trying to decide what to do when all of your networks fail or when an application refuses to restart on a server. Performing some thought experiments during this part of the design phase will prevent you from ending up in an unknown or unmanageable state later on; it s time well spent on verifying your decisions and implementation ideas.

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Conference on Measurement and Modeling of Computer Systems, pp 160 169, May 1996 M Crovella and L Lipsky Long-lasting transient conditions in simulations with heavytailed workloads In Proc 1997 Winter Simulation Conference, 1997 R Dighe, C J May, and G Ramamurthy Congestion avoidance strategies in broadband packet networks In Proc IEEE INFOCOM'91, pp 295 303, 1991 N G Duf eld and N O'Connel Large deviations and over ow probabilities for the general single server queue, with applications Technical Report DIAS-STP-93-30, DIAS Technical Report, 1993 A E Eckberg B-ISDN=ATM traf c and congestion control IEEE Network, 6:28 37, September 1992 K Fendick, M Rodrigues, and A Weiss Analysis of a rate-based control strategy with delayed feedback In Proc ACM SIGCOMM'92, pp 136 148, 1992 S Floyd and V Jacobson The synchronization of periodic routing messages In Proc ACM SIGCOMM'93, pp 33 44, 1993 M Garret and W Willinger.

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A state transition diagram shows you how the system flows from one welldefined operational state to another, during the course of certain events. In the diagram, the states are shown as bubbles, while the transitions between the states are labeled with the events or failures that take you from one bubble to another. A very simple state transition diagram is shown in Figure 16.2, where a system has four operational states: (1) OK, (2) Application Recovery, (3) Primary Network Down, and (4) Manual Recovery. Every arrow is labeled with the event that takes you to another state, such as the application failing, a successful recovery of the application (via the FMS), or the failure of the primary or secondary network. As shown in Figure 16.2, the system is normally in the OK state. If the primary application fails, the system starts recovery (by restarting the application on the same server, for example), and when completed, it goes back to the OK state. If the primary network fails, the system moves to the lower-right-hand state; again, an application fault and recovery loops into the Recovery state and then back to the starting point. But what if something happens during application recovery At that point, or if the second network fails after the system is already in the Primary Network Down state, manual recovery begins. It s clear when the system is automated, moving between states, and also clear when there have been enough failures or complex, multiple-mode failures that require a human being to make decisions. Why would you spend the time drawing one of these There are many motivations to develop and maintain state transitions:

Analysis, modeling and generation of self-similar VBR video traf c In Proc ACM SIGCOMM'94, pp 269 280, 1994 M Gerla and L Kleinrock Flow control: a comparative survey IEEE Trans Commun, 20(2):35 49, 1980 G C Goodwin and K S Sin Adaptive Filtering, Prediction and Control Prentice Hall, Englewood Cliffs, NJ, 1984 M Grossglauser and J-C Bolot On the relevance of long-range dependence in network traf c In Proc ACM SIGCOMM'96, pp 15 24, 1996 Z Haas and J Winters Congestion control by adaptive admission In Proc IEEE INFOCOM'91, pp 560 569, 1991 Z Haas A communication architecture for high-speed networking In Proc IEEE INFOCOM'90, pp 433 441, 1990 D Hong and T Suda Congestion control and prevention in ATM networks IEEE Network Mag 31:10 16, July 1991 K Hornik, M Stinchcombe, and H White Multilayer feedforward networks are universal approximators Neural Networks, 2(23):359 366, 1989 C.

You can get beyond the single-failure mode of most FMS packages. What do you do if you suffer a second failure while recovering from the first What are the kinds of failures you want to worry about handling in succession

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