Java? Visual Age? Workspaces? Eclipse? JIT? Scala? Solr/Lucene? Nudge? Hadoop? UIMA? Spark? UML2? M2T & T2M? Open Source? DIY’ers? Git? Github? Cloud? Yum? Containers? SNMP? PDF? XML? Everything is a Service? Distributed protocols? Distributed algorithms? IoT? IoE? Internet2?
Here is the link to this week’s keynote at NA EclipseCon in Reston, VA:
Those stuck in the past obsess over their favorite V words and ontologies. They clearly do understand the linked keynote speakers. They operate like cargo cults focused on mystical pretend words fought over by their high priests spilling information.
Those working in the future will apply federated workspaces containing code and datasets, often residing in clouds, as demonstrated in the linked keynote. Those demos utilize containers first constructed and later run in a federated environment both “within” shared workspaces like devops or users and “across” shared workspaces including devops and users. Users can select just the relevant workspaces for their own tasks, supporting fine grained to commons wide usage. Workspaces could hold testing sets, cross validation sets, and training sets with supporting code. Workspaces can be traded like baseball cards, or workspaces can be shared like commons. JIT compilation provides portability and interoperability across all relevant hardware architectures. A9.com estimates JIT code runs 1.6 times slower than highly optimized C/C++ code (it is good enough). Eclipse Che is beta now. Notice how servers disappear into the background.
There are future software barriers yet to solve, including many cores / many lanes, GPGPUs, FPGAs, cache management, memory management, network management, power management (yes, this is critical at the fine scale of HW functional units; how long can you boost speed of a functional unit before cooling it back down). There will be more PCIe lanes on a chip than between chips, and there will be more PCIe lanes on a circuit board than between boards; hence, many lanes has replaced many cores in architecture discussions.
Here is the link to Werner Vogels’ blog post on AWS lessons learned:
Those left behind will obsess over their favorite V words and ontologies. That is their only agenda. They enjoy pretending to make up never before seen definitions of old, commonly used words to confuse everyone and corrupt discourse. Blocking progress.
Werner and the AWS teams have done the heavy lifting and set today’s high bar for big data success for enterprises. They have defined the metrics and measurement processes for global cloud & interclouds and HTC. They have measured and compared programming languages (e.g., Java good; Python 6 to 8 times slower than C/C++). They have implemented the research of Leslie Valiant and Leslie Lamport (e.g., TLA+) to create AWS. They deeply understand distributed algorithms. They are do-it-yourselfers for hardware and networking and software. They have established very advanced software methodologies and are continually fine tuning their devops process. They listen to the world’s software experts like Stroustrup and Stepanov and Odersky.
Heed Occam’s razor or fail repeatedly,
P.S.: These are two examples of the API ecosystem that Wo has been requesting since 2014. Eclipse has legs and the support of all the big vendors including Microsoft now. AWS is two to five years ahead on the other cloud vendors.