Hi Antonio,
As I mentioned in one of my previous posts, and will emphasise again:
large scale cannot happen magically just through the addition of a
few small elements.
From your description of your environment, it sounds like the systems
and features being used are primarily "host-wise" - e.g. tied to the
runtime state/environment of a single instance of Asterisk on a single
host. This is a limitation upon its scalability.
To provide services on a large scale, the system has to be composed of
non-hostwise components; the architecture must be distributed. This
is a defining property and an organising principle of its design from
the very bottom, not a setting you can simply enable when your user
base grows large enough. Building distributed VoIP service delivery
platforms is a very different science than building non-distributed
ones.
Once again, let me make a more general cluster analogy; if you have a
single instance of an application on a different server, you cannot
just add more some more servers, run the application in parallel on
them, and expect it to work. Instead, either the whole application
must be written in a way that anticipates its being deployed in
parallel on multiple nodes, or single instances of it must be placed
into some sort of harness that can implement a distributed/parallel
abstraction layer for it while preserving for the application the
illusion of single-instance runtime. Either way, multiple nodes
executing the program must have a way of keeping shared logical state
across the entire execution continuum (in a centralised or distributed
way), passing messages amongst nodes asynchronously, synchronising
storage access to prevent race conditions / mutual exclusion
violations, avoid deadlocks, etc.
An application or service designed to run on multiple nodes to begin
with will have these facilities baked into its architecture, while an
application or service not designed to do that would probably have to
be rewritten or, at least, very extensively modified in order to suit
the new requirement. In more generic computation this probably means
the use of something like the LAM/MPI libraries, or perhaps some sort
of concept aspiring to Google's MapReduce and/or BigTable.
It's the same thing with VoIP and Asterisk. Much of what you've got
now relies on particular Asterisk nodes performing particular
functions, which just isn't how a distributed system works unless you
are willing to settle for some sort of compromise involving node
specialisation -- which might be okay: a dedicated conferencing
server, dedicated ACD/queue server, etc. But this ultimately has
scalability barriers too and represents an inefficiency.
I have mentioned one possible and common distributed Asterisk
architecture before: a central FastAGI controller in which all
application logic is implemented - and, in the case of things which
already exist in Asterisk such as queues, often RE-implemented in a
way compatible with distributed architecture - to which all calls are
dispatched via N Asterisk servers. Such a backend could implement the
necessary shared state for logical abstractions extended across N
servers. The example I often give is one of Asterisk queues (in the
sense of Queue()): a queue exists only in one Asterisk server, but
you can reimplement the "user experience" aspect of a queue in FastAGI
(estimated time to wait announcement, music, etc.), which would then
allow you to extend one logical queue over multiple Asterisk servers
and potentially support thousands of callers in "one" queue.
Even if you do not use such an architecture, you're going to have to
think along these lines. Kamailio alone cannot make anything scale;
the service delivery backend has to be built with a distributed
architecture in mind.
-- Alex
--
Alex Balashov - Principal
Evariste Systems
Web :
http://www.evaristesys.com/
Tel : (+1) (678) 954-0670
Direct : (+1) (678) 954-0671