If the opening keynotes for the Linux Foundation’s Open Source Summit NA had a theme, it was one of open source adapting to artificial intelligence. View in browser »
The New Stack Update

ISSUE 181: A Data-Smart Open Source

Talk Talk Talk

"Object-oriented Programming 'fails at the only task it was intended to address … In most cases, OOP programs turn out to be one big blob of global state, [which] can be mutated by anyone and anything without restrictions.'"

Developer Ilya Suzdalnitski.
Add It Up
Level of DataOps Maturity

Almost every trend regarding how IT operations are handled gets an “Ops” monikerDevOpsDevSecOpsAIOps, MLOps, GitOps, NoOps, FinOps, etc. We wholeheartedly believe that many of these terms explain real phenomenon. However, as is the case with DataOps, the rush to rebrand existing products obfuscates the degree to which these trends are getting traction.

Although there are differences, at its core DataOps is DevOps processes applied to data operations. Automation of data pipelines and collaboration between teams are two of the key characteristics of “modern” DataOps. Yet, managing databases and other data platforms have been a core component of IT’s responsibilities for years. Without consensus about what DataOps means, market confusion will abound. Here are just a few studies that may be used to overstate the trend’s prominence.

We were shocked to read that 90% of enterprises are using DataOps, so we took a deeper look at that 451 Research survey that touted these results — the survey was sponsored by Delphix. The study actually says that 89% of the respondents expected to increase spending, investment, or development on DataOps technologies. Yet, the study provides a process-oriented definition of DataOps that allows any company to say its product or service is a DataOps technology. The report surveyed 150 representatives of North American organizations with more than 1,000 employees and a minimum of 2PBs of data under management who had a solid understanding of their organization’s data management strategy.

Based on that sample, 71% are already well along on with their DataOps maturity. Just like with DevOps several years ago, it seems that most large enterprises believe they are doing DataOps, but the level of maturity is probably being overstated dramatically.

What's Happening

Priyanka Sharma, director of technical evangelism at GitLab, recently surprised many with a recent The New Stack blog post describing how GitLab began its journey to continuous delivery (CD) without first completely shifting its underlying IT infrastructure to Kubernetes first.

In this episode of The New Stack Makers podcast, Sharma, who also serves on the board of the Cloud Native Computing Foundation (CNCF), further discussed how GitLab has sought to not necessarily opt for necessarily the latest-and-greatest toolsets in its move to CD. Instead, the focus has been on finding the most direct path to CD, while maintaining the investments in and support of GitLab’s legacy systems.

GitLab’s CD Journey Without Kubernetes

A Data-Smart Open Source

If the opening keynotes for The Linux Foundation’s Open Source Summit North America — held in San Diego this week — had a theme, it was one of open source adapting to artificial intelligence. “It was a whole morning of AI,” said Todd Moore, vice president open technology and developer advocacy at IBM, in an interview after his keynote. 

At the event, The Linux Foundation launched a new project called the Confidential Computing Consortium to foster the protection of data in use. IBM revealed that it is open sourcing the instruction sets for its OpenPower CPUs, highlighting the rise of more open architectures such as RISC-V, as well as the demand to accelerate data-intensive workloads for domain-specific uses. 

Moore also talked about IBM’s work on what it calls “Trusted AI,” through its AI Fairness 360 toolkit, a Python package with “metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models,” according to the effort’s GitHub page. IBM has joined The Linux Foundation’s AI Foundation. The concepts for trusted AI follows the Partnership in AI, an effort IBM is helping lead with Microsoft, Google, OpenAI and others to foster the ethical use of AI. 

People need tools in addition to education, Moore said. AI can result in bias. How can you add trust to AI? From Moore’s point of view, the result is in helping developers report and mitigate discrimination and bias in machine learning models throughout the AI application life cycle.

How AI Solves the Kubernetes Complexity Conundrum

Kubernetes offers enterprises a valuable new tool for kicking digital transformations and time-to-market timetables into a new gear. But to take full advantage of it, IT and DevOps need to drive a culture shift toward AI and automation; most other existing IT approaches simply do not adequately work or scale in this new world. Read how artificial intelligence could help with this complexity.

A Step-by-Step Guide to Continuous Deployment on Kubernetes

Here’s a detailed step by step account on how to deploy an app to Kubernetes, from Semaphore’s Tomas Fernandez. By the end of this article, you’ll have a working Kubernetes deployment and continuous delivery workflow, using Semaphore, a fast, powerful and easy-to-use Continuous Integration and Delivery (CI/CD) platform

What We Mean by ‘Feature Flags’

In this contributed post, Split Software developer evangelist Dave Karow defines a widely-used but probably not fully-understood concept in software testing: feature flags. Feature Flags allow the developer to make dynamic decisions about their code. “I’m deciding which way I’m going to send a user, without having to push new code and without having to change a config file. It’s a user-by-user, session-by-session decision,” he writes.

Party On

Cloud on the front end, business on the back — that’s IBM LinuxOne. It also can run 2 million docker containers. Whoah! Thanks to Elizabeth Joseph and Leon Kirliuk of IBM for the demo at The Linux Foundation's Open Source Summit.

On the road again — Anadelia Fadeev and Katy Farmer of InfluxData had all the stars come by the booth at the Open Source Summit in San Diego this week.

On The Road


GitLab Commit

GitLab Commit, GitLab’s inaugural community event, brings together the GitLab community to connect, learn, and inspire. Speakers will showcase the power of DevOps in action through strategy and technology discussions, lessons learned, behind-the-scenes looks at the development life cycle, and more. Learn how to innovate the future of software development by registering today! 35% off with code COMMITTNS.

The New Stack Makers podcast is available on: — Pocket CastsStitcher — Apple PodcastsOvercastSpotifyTuneIn

Technologists building and managing new stack architectures join us for short conversations at conferences out on the tech conference circuit. These are the people defining how applications are developed and managed at scale.
Free Guide to Cloud Native DevOps Ebook

Cloud native technologies — containers, microservices and serverless functions that run in multicloud environments and are managed through automated CI/CD pipelines — are built on DevOps principles. You cannot have one without the other. However, the interdepencies between DevOps culture and practices and cloud native software architectures are not always clearly defined.

This ebook helps practitioners, architects and business managers identify these emerging patterns and implement them within an organization. It informs organizational thinking around cloud native architectures by providing original research, context and insight around the evolution of DevOps as a profession, as a culture, and as an ecosystem of supporting tools and services. 

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