I think given the languages you have selected you are coming more from a quant background? These languages are great for heuristics and analysis but you would really want all 'static' components such as connectivity built in assembly/C/C++. For 'algo' components I like Java as you can still pull microsecond order latencies when crunching numbers but more importantly it gives you a huge time to market advantage than the C/C++ for almost the same speeds. I'm also not clear on if you are connecting directly to the market for market data or using aggregation (like reuters). The latter would be too slow. I'm also not clear on what middleware you are using which is probably the biggest decision you will have to make. Most either use inhouse tech or 29west LBM (everyone still calls it that even though they were bought out).
An overlooked part of HFT in my experience OS optimisation and even things like TCP bypass (for some components) which can lead to huge speed advantages and end to end latency reductions. I agree with those about FPGA.. in my experience they really don't come into the equation except for components that rarely change.
Anyway a few guys including Martin Thompson have felt similarly to you and initiated the lodestone project (http://lodestonefoundation.wordpress.com/). If you are keen to learn more their architectures for low latency, distributed and componentisation then I feel that you could join forces and contribute to that initiative. FYI: Martin built most of the technology behind the disruptor (http://lmax-exchange.github.io/disruptor/).
Great to see interest in making this knowledge more widely available :)