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5G network rollout using DevOps: Myth or reality?

IBM Journey to AI blog

This requires a careful, segregated network deployment process into various “functional layers” of DevOps functionality that, when executed in the correct order, provides a complete automated deployment that aligns closely with the IT DevOps capabilities. appeared first on IBM Blog.

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Mainframe and the cloud? It’s easy with open source

IBM Journey to AI blog

DevOps, open source and the mainframe Open-source software and DevOps share a common philosophy and technical underpinnings. DevOps is a mindset, a culture and a set of technical practices that foster better communication and collaboration across the software lifecycle. The key to this deep relationship? Open-source software.

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DevOps Use Cases for AI-Assisted Kubernetes

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As indicated in my prior blogs Optimizing Cloud Costs for DevOps With AI-Assisted Kubernetes and Optimizing Cloud Costs for DevOps With AI-Assisted Orchestration, an AI-assisted Kubernetes orchestrator is needed to optimize cloud costs for DevOps, DevSecOps and SRE.

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Achieve DevOps maturity with BMC AMI zAdviser Enterprise and Amazon Bedrock

AWS Machine Learning Blog

Although much of the focus around analysis of DevOps is on distributed and cloud technologies, the mainframe still maintains a unique and powerful position, and it can use the DORA 4 metrics to further its reputation as the engine of commerce. Using a Git-based SCM pulls these insight together seamlessly.

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Top 6 Kubernetes use cases

IBM Journey to AI blog

Overview of Kubernetes Containers —lightweight units of software that package code and all its dependencies to run in any environment—form the foundation of Kubernetes and are mission-critical for modern microservices, cloud-native software and DevOps workflows.

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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

MLOps is a set of practices that combines machine learning (ML) with traditional data engineering and DevOps to create an assembly line for building and running reliable, scalable, efficient ML models. AIOPs enables ITOPs personnel to implement predictive alert handling, strengthen data security and support DevOps processes.

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Shift from proactive to predictive monitoring: Predicting the future through observability

IBM Journey to AI blog

DevOps culture and collaboration Instana’s focus on fostering a Dev Ops culture and collaboration is another distinguishing factor. Learn more about IBM Instana The post Shift from proactive to predictive monitoring: Predicting the future through observability appeared first on IBM Blog.

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