Sentiment analysis with machine learning

When developing a new technology, it really helps if you are also a user of that new tech. This has been an approach of Red Hat around artificial intelligence and machine learning — develop openly on one hand, exchanging knowledge across the organization to use the same tools in the other hand to work on interesting business problems. All while keeping a two-way exchange to and from the open source commons.

This is the sort of left-hand/right-hand move that data scientist Oindrilla Chatterjee began using as part of a project she originally started during an internship, then later in a full-time role at Red Hat. Chatterjee and her team are looking at how to do sentiment analysis using machine learning on a dataset consisting of customer and partner surveys regarding a service offering.

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Anomaly Detection on OpenStack Logs Using Machine Learning

(There’s a great  new conference in the U.S., DevConf.US, returning in 2019 to Boston University (15 to 17 Aug). This highly-technical conference is interested in drawing a diverse group of speakers and attendees, with a specific emphasis on people who are new to speaking and tech conferences in general. Only in its second year, DevConf.US builds on the successful decade-spanning run of DevConf.CZ in Brno, CZ.

This is a session from DevConf.US 2018. The call for proposals to present at DevConf.US 2019 is now open.)

In this session from the CentOS Dojo held as part of DevConf.US, OpenStack technical support engineers Madhur Gupta and Shatadru Bandyopadhyay talk about how to use machine learning for anomaly detection on OpenStack logs. Once an anomaly is detected in the logs, it can be used to automate further action, while helping in root cause analysis.

The challenge with anomaly detection in OpenStack in the first place is that it generates a significant quantity of logs, even in relatively simple production setups. How do you ingest and detect anomalies in all that data?

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Red Hat’s Open Source AI Vision

Analytics, Machine Learning, and AI represent a fundamental transformation that over the coming decade will affect every aspect of society, business, and industry. It will fundamentally change, how we interact with computers – and how we develop, maintain, and operate systems. It’s impact will be visible in our part of the universe much sooner than for the analog world. This deeply affects both open source in general, as well as Red Hat, its ecosystem, and customer base.

In this video from the inaugural DevConf.US 2018, Daniel Riek who leads the AI Center of Excellence in Red Hat Office of the CTO, talks about this coming change.

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Getting Strategic About Security

In this video from the Red Hat Summit 2018, Chief Security Architect Mike Bursell takes an enthusiastic look at three open source security technologies: DevSecOps, serverless computing, and Trusted Execution Environments.

These technologies are examples of where Red Hat’s longview is aimed for the security realm.

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Next Generation Tools for Container Technology

In this video from the 2018 Red Hat Summit, Dan Walsh and Mrunal Patel lead a journey through a set of next generation tools for creating, deploying, and maintaining containers.

This journey covers tools such as CRI-O, Buildah, and Skopeo, which are being developed with other tools by Red Hat and the community into a complete toolchain for developing, operating, and maintaining Open Container Initiative (OCI)-compliant containers.

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Kubernetes and the Platform of the Future

In another installment from the Red Hat Summit track from the Office of the CTO, this video is an informal discussion between Brandon Philips (previously CTO of CoreOS, acquired by Red Hat) and Clayton Coleman (Chief Engineer for OpenShift), interviewed by Steve Watt. They focus on Kubernetes as a platform of the future, identifying interesting trends in the open source ecosystem.

This discussion is a good example of the type of technologists that comprise the modern open source ecosystem, and epitomized by these three from Red Hat. Their backgrounds in real world development and operations combines with a genuine desire to help people that fuels their work in open source communities and product creation.

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Clouds Today, Serverless Tomorrow: Your Future Apps and Platforms

When we look to the future of applications and platforms, we need to keep an eye on the solutions of the past.

That is one of the main theses of Stephanos Bacon, Sr. Director of Portfolio Strategy at Red Hat, in this video from Red Hat Summit 2018, “Clouds Today, Serverless Tomorrow: Your Future Apps and Platforms”:

In order to understand the present situation around the many choices of languages and platforms a developer faces, Stephanos briefly walks through a 25 year year journey of enterprise software development. This journey is one of a “continuous-though-forward-moving cycle”.

This cycle looks back at itself to learn and adapt from the past while moving forward in response to changing market imperatives.  While we may need new solutions, we also reach back in time to find seemingly old solutions that address new classes of problems.

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10 Trends Reshaping the Developer Experience

In this video, Director of Product Management for Developer Tools Brad Micklea talks through ten trends Red Hat is investing in that are already reshaping the developer experience.

The idea of software development as a major creative source for innovation has emerged in recent decades.  During most of that time for the people writing code and running it in production, instead of being deep in the act of painting a masterpiece, they have had to spend too much time building and cleaning brushes.

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