Concurrency

New, asynchronous "shared-nothing" platforms and APIs like Vert.x and Play / Akka and Qbit have emerged. These platforms use a different concurrency model than the standard Java / JEE concurrency model of threading, shared memory and locking. New non-blocking concurrency algorithms have been published, and new non-blocking tools like the LMax Disrupter have been added to our toolkits. New functional programming parallelism has been introduced with the Fork and Join framework in Java 7, and the collection streams API in Java 8.

More complex design: Though some parts of a multithreaded applications is simpler than a singlethreaded application, other parts are more complex. Code executed by multiple threads accessing shared data need special attention. Thread interaction is far from always simple. Errors arising from incorrect thread synchronization can be very hard to detect, reproduce and fix.
Context Switching Overhead: When a CPU switches from executing one thread to executing another, the CPU needs to save the local data, program pointer etc. of the current thread, and load the local data, program pointer etc. of the next thread to execute. This switch is called a "context switch". The CPU switches from executing in the context of one thread to executing in the context of another. Context switching isn't cheap. You don't want to switch between threads more than necessary.
Increased Resource Consumption: A thread needs some resources from the computer in order to run. Besides CPU time a thread needs some memory to keep its local stack. It may also take up some resources inside the operating system needed to manage the thread.

Difference between Callable and Runnable interface.

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