Author: anil

Vmware

Supporting Digitisation in India: VMware’s Perspective on Opportunity and People-Centred Technology

VMware’s Senior Director for End User Computing shares how the company is supporting India’s digital transformation, why cloud adoption has lagged other Asia-Pacific markets, and why people must remain at the centre of digitisation efforts.

JIRA

How the Jenkins to Jira Cloud Integration Was Built (and What You Can Do With It)

A deep dive into the architecture, security model, and pipeline steps behind the official Jira Software Cloud plugin for Jenkins — including how a new OAuth credential type enables secure, one-way data flow from behind-the-firewall CI/CD tools to Jira Cloud.

Ansible

Cloud Infrastructure Automation Software: Key Players, Market Segments, and Growth Drivers

An overview of the cloud infrastructure automation software landscape, covering key vendors including AWS, Google, Ansible, Microsoft, HashiCorp Terraform, and Puppet Enterprise, along with market segments and growth drivers for DevOps teams.

Global market

Datacenter Automation Software Market Overview: Key Vendors, Segments, and Regional Trends (2019–2026)

An overview of the global datacenter automation software market landscape, covering key vendors such as VMware, BMC, Cisco, IBM, Microsoft, Puppet, Chef, and ServiceNow, along with market segments, regional trends, and growth drivers.

DevOps ToolsGlobal market

Cloud Container as a Service (CaaS): Market Overview, Segmentation, and Key Players

Container as a Service (CaaS) sits between IaaS and PaaS, letting developers deploy isolated, reproducible container environments without managing the underlying cluster infrastructure. This article explains how CaaS works, who the major players are, and which industries and regions are driving adoption.

AWS

AWS SageMaker Studio: A Critical Look at the ‘IDE for ML’ and What It Means for Data Scientists

AWS SageMaker Studio launched with bold promises as an integrated IDE for machine learning. We examine its key features—Notebooks, Debugger, Model Monitor, AutoPilot, and Experiments—and where the implementation falls short for data scientists.