Civo, the cloud native service provider, has announced its new Machine Learning (ML) managed service, “Kubeflow as a Service” aimed at improving the developer experience and reducing the resources and time required to gain insights from ML algorithms.
ionir’s Insight on the Future of Stateful Applications on Kubernetes
March 17, 2022 by Leave a Comment
A new survey by ionir shows that 60% of respondents are running stateful applications on Kubernetes, and of those who aren’t already, 50% plan to do so in the next 12 months. That’s among the findings of The Future of Stateful Applications on Kubernetes report, available on the ionir website: https://info.ionir.com/the-future-of-stateful-applications-on-kubernetes.
Managing and Scaling Applications in Kubernetes
August 13, 2021 by Leave a Comment
In early 2021, Traefik Labs conducted a survey to measure the market adoption of Kubernetes and to understand the challenges organizations face in managing and scaling applications. The results show that while businesses clearly see the need for Kubernetes, they still face difficulties when it comes to
adopting and scaling the technology.
10 Kubernetes Features You Must Know About
November 20, 2019 by Leave a Comment
In this contributed article, technology writer Gilad David Maayan provides some of the more advanced functionalities and features of Kubernetes to help you get more from your configuration. Kubernetes (k8s) has become key to some of the biggest operations in the world, including Google, Shopify, and Slack. K8s has enabled companies to take advantage of cloud computing in a way that was previously not possible, and it might be able to do the same for big data.
Dotscience Enables Simplest Method for Building, Deploying and Monitoring ML Models in Production on Kubernetes Clusters to Accelerate the Delivery of Business Value from AI
November 3, 2019 by Leave a Comment
Dotscience, a pioneer in DevOps for Machine Learning (MLOps), announced new platform advancements that offer the easiest way to deploy and monitor ML models on Kubernetes clusters, making Kubernetes simple and accessible to data scientists.
Kubernetes Driving Google Cloud
October 26, 2019 by 1 Comment
Kubernetes is increasingly being used with big data deployments. This trend is driving more big data apps to move to GCP, which offers homegrown support for Kubernetes. To make these workloads simpler and cheaper, there’s a need for a new solution for managing data workloads on Google Cloud Dataproc. With GCP’s CAGR estimated to grow by 64% CAGR through 2021, the cloud is now clearly a three-horse race.
Lucidworks Fusion 5.0 Features Data Science Toolkit Integration and Microservices Architecture Orchestrated by Kubernetes
September 15, 2019 by Leave a Comment
Lucidworks, a leader in AI-powered search, announced the release of Fusion 5.0, the latest version of the company’s flagship product. Lucidworks Fusion 5.0 lets customers rapidly develop and deploy AI-powered search and data discovery applications in a modern, Kubernetes-based containerized architecture. This update includes features that simplify implementation for data science teams and developers to create both a more personalized experience for digital commerce customers and also improve employee productivity and engagement in the digital workplace.
Tips for Using Kubernetes in Large Enterprises
September 13, 2019 by Leave a Comment
In this contributed article, technology writer Gilad David Maayan provides a clear and concise overview of Kubernetes, the darling of the DevOps community. He then offers a number of useful tips for using Kubernetes on an enterprise scale.
Mesosphere Kubernetes Engine Brings Breakthrough Automation & Efficiency for Data-Driven Apps on Multi-Cloud & Edge
October 28, 2018 by Leave a Comment
Mesosphere, the multi-cloud automation platform company, announced the general availability of Mesosphere Kubernetes Engine (MKE), Mesosphere DC/OS 1.12 and the public beta of Mesosphere Jupyter Service (MJS). Mesosphere Kubernetes Engine is the only software platform that delivers pure Kubernetes-as-a-Service on multi-cloud and edge with high-density resource pooling, yet without the need for virtualization.
