This morning on Continuous Discussions (#c9d9) podcast, we discussed DevOps for Big Data applications.
With Machine Learning, AI, BI, Real-time stream processing — we see big HUGE Data applications all around us – and these will continue to grow, along with the commoditization of data and business insights.
How do DevOps and Big-Data interact?
Are there unique challenges for practicing DevOps for Big Data applications?
What are some best practices and proven patterns for rapidly combining, deploying and maintaining data analysis algorithms and backend?
Watch the replay of the episode:
This episode features:
On the next episode of #c9d9:
Join us on July 11 when we discuss challenges and best practices for building, testing, and deploying database changes, to increase the speed and quality of releasing DB changes as part of your CD pipeline.
This episode will feature:
Continuous Discussions (#c9d9) podcasts air every other Tuesday. See all episodes here.
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