# Go Server Client Connection Tracking This package provides a library for network servers to track how many concurrent connections they have from a given client address. It's designed to be very simple and shared between several HashiCorp products that provide network servers and need this kind of control to impose limits on the resources that can be consumed by a single client. ## Usage ### TCP Server ```go // During server setup: s.limiter = NewLimiter(Config{ MaxConnsPerClientIP: 10, }) ``` ```go // handleConn is called in its own goroutine for each net.Conn accepted by // a net.Listener. func (s *Server) handleConn(conn net.Conn) { defer conn.Close() // Track the connection free, err := s.limiter.Accept(conn) if err != nil { // Not accepted as limit has been reached (or some other error), log error // or warning and close. // The standard err.Error() message when limit is reached is generic so it // doesn't leak information which may potentially be sensitive (e.g. current // limits set or number of connections). This also allows comparison to // ErrPerClientIPLimitReached if it's important to handle it differently // from an internal library or io error (currently not possible but might be // in the future if additional functionality is added). // If you would like to log more information about the current limit that // can be obtained with s.limiter.Config(). return } // Defer a call to free to decrement the counter for this client IP once we // are done with this conn. defer free() // Handle the conn } ``` ### HTTP Server ```go lim := NewLimiter(Config{ MaxConnsPerClientIP: 10, }) s := http.Server{ // Other config here ConnState: lim.HTTPConnStateFunc(), } ``` ### Dynamic Configuration The limiter supports dynamic reconfiguration. At any time, any goroutine may call `limiter.SetConfig(c Config)` which will atomically update the config. All subsequent calls to `Accept` will use the newly configured limits in their decisions and calls to `limiter.Config()` will return the new config. Note that if the limits are reduced that will only prevent further connections beyond the new limit - existing connections are not actively closed to meet the limit. In cases where this is critical it's often preferable to mitigate in a more focussed way e.g. by adding an iptables rule that blocks all connections from one malicious client without affecting the whole server.