AI is reshaping programming as we know it, creating an intersection of the old and the new. As a programmer, this creates new challenges but with a familiar ring to them. Here are four ways that I’ve found to help me stay on top of these demands.

#1 Containers matter—and debugging needn’t be hell

Containers are being used in key ways for AI to construct a unified and simplified platform to collect, organize, and analyze data. But when something goes wrong and we need to debug an application that’s running within the container, we’ve been lacking in tools. Have you experienced the “hell” of finding that using containers meant giving up on using the best analysis tools? Well, that has changed. In general, tools are finding a way to offer strong support inside containers—as long as we use the latest versions. Intel has extended profiling tools to help with enterprise applications inside Docker and Mesos containers, those using Python, and those running Java services and daemons. For instance, the Intel® VTune™ Amplifier 2019 (the latest version) supports profiling code within containers—see the latest user’s guide for more information.

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