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this silo based methodology almost always results in the use of a number
of different availability / dr technologies from an array of vendors,
with considerably different designs, capabilities and limited/no
integration points. for example, an online web ordering system could use
network load balancing for front end web servers, some form of data
mirroring or clustering for backend database servers, and a 3rd party
availability
alternative for middleware. point of sale solutions, crm tools, and even
blackberry messaging environments follow a similar prescription, using
alternate technologies for every layer in the application stack.
having such an approach to implementing an availability solution for
your business application ecosystem has several drawbacks. initially,
one must consider the cost implications of utilizing assorted
technologies within an availability or dr architecture. the most
apparent cost is the equity outlay for the hardware/software alone. by
choosing to deploy different solutions from different
vendors,
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, there is no option to leverage economies of scale. most
hardware and software companies offer volume based pricing enticements
for larger order sizes, but this option is obviously lost when various
alternatives from different vendors are used.
additionally if each solution leverages different underlying hardware,
disk, or os technologies, an even higher total cost of ownership will be
noticed. of course cost extends beyond just hardware and software to
include implementation, coaching, and ongoing management costs. consider deploying even a relatively basic,
three tier application architecture. in the online web ordering example
explained previously,new era nba 59fifty hats, one would need to deal with the somewhat unnerving
task of mastering not only the intricacies of sql clustering, but also
deployment and management of network load balancing and any middleware
components required. each time a new variation of any of these solutions
is made, theres the additional cost of relearning a different
technology.
then contemplate the complexity of integrating differing availability
technologies from numerous vendors. are they guaranteed to interoperate
with one another? is such interoperability built in or will
some amount of customization and manual scripting be
needed, so that each tier can communicate with the other tiers? if
custom scripting is necessary,
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, what happens when even a single part of
the availability architecture changes? will extra, custom consulting
work be needed to develop and re test existing scripts? last but not
least, if and when something breaks down,cheap red bull hats, whose responsibility is it to
determine the root cause? with an array of solutions from different
vendors,cheap dope snapback hats, one must be wary of the unavoidable finger pointing that may
result when things go bad.
obviously one alternative is to simply not integrate the solutions,
after all, so long as every piece is doing its job, isnt it safe to
suppose that the total system is operational? not really. consider for
example the deployment of a multi tier,cheap nfl football hats, distributed architecture across
physical sites for dr purposes. if the whole, primary production site
fails, will the servers start up in the right order and fashion at the
remote site, or will some level of interaction be necessary from an
administrator?
now imagine the more probabletype of failure, when just one component
rather than an entire site fails. unless youve deployed a combined ha +
dr solution, possibilities are that the single failed component will
resume operations at the dr site. but in most cases, the latency between
sites will be too high for any multi tier application to function
properly. in this scenario, its best to actually fail all of the
components across to the remote site as a single, cohesive unit. but
once again, how does this coordination take place? either we are back to
scripting the failover in some manner, or else some hands on
administrator engagement is required. when that happens,
recovery times inevitably increase; when recovery times increase, so
does the bottom line expense of the outage to the business. |
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