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+Design Goals
+============
+
+ProxySQL has been built with a few key design choices in mind.
+
+# Maximal uptime
+
+Since ProxySQL is a proxy, it's expected to be up there as close to 100% of
+the time as possible. This means that we should be handling differently the
+usual suspects when it comes to downtime:
+* __configuration changes__. This is usually done by changing the configuration
+file and restarting the daemon. In ProxySQL, by design, the user is able to
+modify most configuration variables through the admin interface, without
+having to restart the server. Example things that can be modified at runtime:
+  * interfaces on which ProxySQL is listening
+  * backend servers to which ProxySQL is connecting
+  * timeouts for the different operations performed by ProxySQL
+* __crashes__. ProxySQL has an extensive suite of integration tests that are
+ran using Docker, to ensure that it does not crash. Also, each major release
+is performance-tested using sysbench, and memory-leak tested using valgrind.
+In addition to this, an angel process has been implemented that monitors and
+restarts ProxySQL when needed, in order to keep downtimes to a minimum, if they
+end up occuring.
+
+# Maximal scalability
+
+There are several key scenarios that we wanted to run as fast as possible when
+interacting with ProxySQL:
+* time to complete a new MySQL connection to it: this is why ProxySQL has a
+pool of threads all waiting via the system call `accept()` to receive a new
+connection. Because of this, the probability of the new TCP connection of being
+established faster is increased
+* time to connect to a MySQL backend: this is why ProxySQL has a backend
+connection pool in which it keeps some idle connections alive to the backend
+servers, according to the configuration. When it needs to send a packet to
+those servers, most of the time the connection is already open
+* multi-core scalability: ProxySQL has a multi-threaded design where all threads
+do the same thing (marshal messages back and forth between the backend servers
+and the MySQL client connections), and our tests show that it scales very well
+with the number of cores. 
+
+# Cascade possibilities
+
+ProxySQL can be cascaded to as many layers as required. For example, one common
+scenario is to have a ProxySQL instance as close to the servers running the
+application as possible, pointing to another middle layer cluster of ProxySQL
+servers that routes all traffic to a farm of backend MySQL servers.
+
+A -> P1 -----> {P2, P3, P4 ..} ------> {B1, B2, B3, ..}
+
+The advantage in this case is that it is completely fault tolerant with respect
+to the MySQL access, given that the app is not a single point of failure. There
+is no modification needed at the application level for the application to
+connect to a cluster of proxies instead of a single one. If any proxy from the
+middle layer fails, the P1 proxy will detect that and will route traffic through
+the other ones. If any of the backends B1, B2, B3, ... fails, then the middle
+layer proxies will take care of the job in a way that is transparent to P1.
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