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DevOps and Developer Trends to Consider in 2020

Dzone - DevOps

Here's what the new year will bring in DevOps. In 2019, our industry has seen great steps forward in the world of DevOps and engineering technology. New research from more than 30 million workflows revealed the importance of continuous integration for high performing teams.

DevOps 88
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Continuous Security

Mentormate

Continuous integration (CI) and continuous delivery (CD) are together the most powerful hidden impact that Agile can have on a product development or engineering organization. However, investments in CI/CD can be leveraged to provide continuous security as well. Why is it hidden? Prioritizing and Managing Alerts.

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Our book “Software Architecture Metrics: Case Studies to Improve the Quality of Your Architecture” is published!

Apiumhub

He is a former practitioner of Agile methodologies, particularly extreme programming, with experience in practices like TDD, continuous integration, build pipelines, and evolutionary design. His main technical interests are software architecture, DevOps, software security, and software energy efficiency.

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The Good and the Bad of Python Programming Language

Altexsoft

machine learning , DevOps and system administration, automated-testing, software prototyping, and. Particularly, it facilitates the work of researchers, data scientists, data engineers , QA engineers , and DevOps specialists. Many DevOps tools are Python-based, including. Buildbot for continuous integration (CI).

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Knowing your cloud is knowing what’s normal…and what’s not

Lacework

Learning the ins and outs of a single cloud provider takes time, energy, and effort. With the rise of cloud, many organizations have adopted DevOps to rapidly deploy new services and capabilities to their customers. But what about Continuous Context? Are there vulnerabilities in dependencies or in the code?

Cloud 52
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Kubernetes and Artificial Intelligence/Machine Learning (AI/ML) — Four Things to Understand Today

Blue Sentry

consumer goods, energy, healthcare, logistics, automotive, etc.) When we look at ML deployments, there are a ton of different platform and resource considerations to manage, and CI/CD (Continuous Integration & Continuous Delivery) teams are often managing all of these resources across a variety of different microservices (i.e.,