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To many managers, that means separate boxes with increased footprint, increased physical management woes, and more cost Combining environments in the same physical server, using partitions to slice it into production, QA, and development environments, gives you a lifecycle in a box They re isolated, as if they were on separate servers, but with the advantage of running inside a single box Bad When the big box fails, so do all of the partitions As we observed way back in 2, What to Measure, hardware is a relatively rare cause of system downtime; system problems are usually software related But when the partitioned box fails, all of its partitions fail with it unless the failure can be constrained to a single domain of resources that is logically isolated from other domains Neutral You can failover from one domain to another one.



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Since the collection and analysis of the Bellcore Ethernet LAN data [41], follow-up works [1, 15, 27, 57] have shown the robustness of self-similar burstiness in network traf c This has led to the heuristic description: Poisson connection arrivals with heavy-tailed connection duration times lead to self-similar burstiness in multiplexed network traf c This is a rough, `` rst-order'' description of the empirical facts for example, TCP connection arrivals exhibit self-similarity (see 15 on TCP workload modeling) which serves to point toward the principal causal attribute of self-similarity: heavy-tailed activity durations Recent analysis of WAN IP traf c [23, 24] has revealed multifractal structure in the form of nonuniform scaling across short and long time scales (see 20 for a comprehensive discussion).





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By failing over from one virtual machine to another inside the same physical computer, you can recover from non-hardware system failures without having to incur the expense of additional hardware..

That is, on top of the monofractal picture captured by the heuristic statement above, there exists further variability within each connection in particular, heavy-tailed TCP connection lifetimes that fall outside the scope of monofractal self-similarity, which principally concerns large time scale structure in network traf c The re ned, short time scale structure can be described by cascade constructions also used in the generation of deterministic fractals such as two-dimensional grey-scale fractal images [5] where variability (within a connection) is obtained by recursive application of ``measure redistribution'' according to some xed rule (cf 1, Fig 12 (middle)) Several problems remain unsolved.

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Multiplicative Scaling and Causality What causes multiplicative scaling observed for short-range correlation structure Is it related to fragmentation in the TCP=IP protocol stack (including the MAC layer) TCP's feedback control (ARQ and window-based congestion control) ACK compression Topological considerations If a combination, are there dominant factors Cascades although suggestive of certain physical causes are ultimately a data modeling construct and fall short of establishing a mechanistic description of the underlying workload From a workload generation or synthesis perspective, given the possible dependence of multiplicative scaling in short time scale traf c structure on feedback control, an open-loop generation of traf c may be unsatisfactory for closed-loop traf c control and its performance evaluation purposes.

Good. Those different environments might be at different revisions of the operating system or at different patch levels, or contain different product releases of your application. Think of partitions as offering a sort of double buffering for change management and release management. Bad, at times. Let s say you re running a large database application in one partition. You want to drain memory and CPU resources out of this domain for another slice of the server that has become too slow. However, the full-blown database is using 500MB of shared memory, which can t be drained, and it requires another 500MB of memory for process images. You may not be able to resize domains as small as you want if they re running resource intense applications. Below the abstraction level of an entire server, we can virtualize at the operating system level.

Impact of Re ned Short Time Scale Modeling Is multiplicative scaling a robust, invariant phenomenon as self-similarity is for large time scale structure Can modeling of short time scale structure lead to a better understanding of dynamic properties of network protocols Does a re ned model of short-range structure lead to a more accurate prediction of network performance In other words, is re ned modeling of short time scale structure in network traf c a ``relevant'' research activity It is clear that in some contexts (see, eg, 12 for a discussion of.

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