I am a technology journalist with three decades of press experience. Primarily I work as a news analysis writer dedicated to a software application development ‘beat’. I have spent much of the last twenty years focusing on open source, analytics & data science, cloud computing, mobile devices & data management.
Software is diverse. Because enterprise software systems are built using a wide variety of code libraries, internal architectural structures, development methodologies and of course different software languages, software diversity enables programmers to dip into a vast toolkit of tools. From this diversity comes breadth, adaptability and flexibility, but - equally perhaps - from this breadth also comes complexity, confusion and a lack of standardization.
“I believe the reason we have grown so much is the scalability and extensibility of Kubernetes i.e. give us an edge device, give us a traditional server or any other computing entity and we can see how cloud-native Kubernetes is fit for purpose, at scale,” said Sharma.
Some of the proprietary cloud solutions that are less than open source might let developers only make a certain number of ‘calls’ . But Sharma advises that there is a place for everything – propriety technology also, so what matters is standardization and that tends to happen more organically in open models.
In terms of what kinds of tools the software industry should be using in this space, the overwhelming consensus of opinion in this space pushes towards the use of open source software, open data models, open governance and open everything. This is perhaps because none of these AI models should be running in a vacuum i.e. monitoring, observability, event logging, security scanning and a whole selection of infrastructure requirements needs to be shared.
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