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Re: [LUG] Nginx vs. Apache
- To: "list@xxxxxxxxxxxxx" <list@xxxxxxxxxxxxx>
- Subject: Re: [LUG] Nginx vs. Apache
- From: Matt Stevenson <mrmstevenson@xxxxxxxxx>
- Date: Mon, 11 May 2015 21:53:16 +0100
- Delivered-to: dclug@xxxxxxxxxxxxxxxxxxxxx
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Thanks Simon Iâll check out the free versions specs. We had Apache crash on us this week although I fixed the issue, hence the sudden interest. Still working up an appetite for Docker and a http2 strategy.
On Monday, May 11, 2015, Matt Stevenson <mrmstevenson@xxxxxxxxx> wrote:
> Theres a thought Tom so we are back to Single servers and failover oh no my head hurts, thanks for the warning though!
>
> On Monday, May 11, 2015, Tom <madtom1999@xxxxxxxxxxxxxx> wrote:
>> On 11/05/15 21:17, Joseph Bennie wrote:
>>>
>>>> On 11 May 2015, at 20:53, Simon Waters <simon@xxxxxxxxxxxxxx
>>>> <mailto:simon@xxxxxxxxxxxxxx>> wrote:
>>>>
>>>> I'm skeptical of load balancing for databases.
>>>>
>>>> It makes sense if the goal is robustness, although some big services
>>>> use other means, like a master/slave model, or just use highly
>>>> available hardware configurations, with a single simple MySQL instance.
>>>>
>>>> But the gain from multiple servers is low. With master/master all the
>>>> transactions may be effectively being applied to both servers anyway,
>>>> so the performance can go down.
>>>>
>>>> In contrast even modest database optimisations can reduce effort by
>>>> orders of magnitude. Not done this sort of stuff so much with MySQL,
>>>> but I imagine the principles are similar to other relational databases.
>>>>
>>>> Modern servers can handle thousands or tens of thousands transactions
>>>> per second.
>>>>
>>>> What sort of stats do you have for the database. Table sizes, index
>>>> sizes, transaction mix, cache hit rates etc. if you haven't looked at
>>>> this you probably need a DBA not hardware.
>>>>
>>>>
>>>
>>> I mostly second this, My personal experience of running a pair of
>>> parallel Master-slaves = never a day when it worked right! (v5.0, its
>>> improved apparently), just beef up a server to be the master and have
>>> slave replication for read/redundancy, if you can scale the read
>>> operations then you can get some perf
--
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