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Why kubelet runs as a system service in Kubernetes cluster and not as pod/daemonsets?
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How is Kubernetes Leading the Game in Enabling...
Read this article to know about how NFV core is driven by cloud-native projects, lead by Kubernetes to the orchestration of most of the projects plus managing containerized network functions.
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Analysis of Kubernetes and OpenStack Combination for Modern...
How do Kubernetes and OpenStack integrate and what are the benefits? Sagar Nangare has the answers.
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Powering Edge With Kubernetes: A Primer
Adoption of Kubernetes into data centers or cloud has been remarkable since it was released in 2014. As an orchestrator of lightweight application containers, Kubernetes has emerged to handle and schedule diverse IT workloads, from virtualized network functions to AI/ML and GPU hardware resources.
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Simplify Storage for Kubernetes with Rook and Ceph
Kubernetes has enabled applications to be cloud native, but application storage has not been enabled with cloud native features from the start. Rook bridges that big gap by making storage cloud native in conjunction with Ceph and other storage systems.
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Anomaly Detection in Machine Learning: Classification Algorithms vs...
Anomaly simply means something unusual or abnormal. We often encounter anomalies in our daily life. It can be suspicious activities of an end-user on a network or malfunctioning of equipment. Sometimes it is vital to detect such anomalies to prevent a disaster.
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Let’s go beyond QA and look at QE
By integrating quality at every step of the software development lifecycle, companies can create products that set new standards of quality in the market. It’s clear that Quality Engineering is now a strategic function with the potential to deliver a competitive advantage.
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[Infoblog] Kubernetes and Microservices
Kubernetes supports a microservices architecture through the service construct. It allows developers to abstract away the functionality of a set of Pods and expose it to other developers through a well-defined API.
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[Infoblog] Top 10 Worldwide IT Predictions 2019
Based on IDC analysis, business agility and/or the need for speed from IT and improved security are the top most important trigger factors for considering cloud, in contrast to cost. The market is in need for more consistent and standardized automated cloud resources to enable developers and line-of-business to execute at speed and in a more cost-effective manner.
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Understanding Supervised Machine Learning
Machine learning is about using data to build intelligent artefacts that learn over time. It involves collecting and analysing large amounts of data to extract information using various computational structures and algorithms.
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Is the Public Cloud in decline?
When Public Cloud was first introduced, it took the world by storm. The fact that organizations could access resources based on their need and pay only for what they consumed made Public Cloud a great business enabler
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Analyzing Business Impact of Cloud Modernization
Cloud Modernization may be used in varied sense of its meanings. However for businesses, it means, transforming your infrastructure and applications so that cloud provides best ROI on an ongoing basis. Using cloud modernization to unlock the value of your applications and data, by synergizing them with modern tools of analytics and AI.
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[Infoblog] The Anatomy of 5G
View our infographic on 5G technology overview and use cases.
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[Infoblog] Container Attached Storage
At a high-level Container Attached Storage is software that includes microservice based storage controllers that are orchestrated by Kubernetes. These storage controllers can run anywhere that Kubernetes can run which means any cloud or even bare metal servers or on top of a traditional shared storage system.
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Will Blockchain disrupt the world of data storage...
Blockchain-enabled data storage seems to provide the advantages described above. The question is, in the context of the Enterprise how long will it be before business leaders consider it proven enough to dive in?
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Storage Analytics is becoming more complex – can...
Physical servers and storage equipment are a data center reality. How can we ensure that the workloads are distributed correctly across this infrastructure?AI and Machine Learning can come to the rescue here as well. With these technologies, data centers can distribute workloads equally and efficiently across these servers.
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Distributed Application Architecture for Edge-Based Service Delivery
Now, as the focus of many enterprises and technology vendors started to shift to edge, a new architecture may evolve as distributed applications have a different environment with a different type of latency requirement.
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