From the smallest startups to the largest enterprises alike, organisations are using Artificial Intelligence and Machine Learning to make the best, fastest, most informed decisions to overcome their biggest business challenges. But with AI/ML complexity spanning infrastructure, operations, resources, modelling and compliance and security, while constantly innovating, many organizations are left unsure how to capture their data and get started on delivering AI technologies and methodologies.

Traditional development methods do not scale into the IoT sphere. Strong inter-dependencies and blurred boundaries among components in the edge device stack result in fragmentation, slow updates, security issues, increased cost, and reduced reliability of platforms. This reality places a major strain on IoT players who need to contend with varying cycles and priorities in the development stack, limiting their flexibility to innovate and introduce changes into their products, both on the hardware and software sides.

Private cloud, public cloud, hybrid cloud, multi-cloud... the variety of locations, platforms and physical substrate you can start a cloud instance on is vast. Yet once you have selected an operating system which best supports your application stack, you should be able to use that operating system as an abstraction layer between different clouds.

Container technology has brought about a step-change in virtualisation technology. Organisations implementing containers see considerable opportunities to improve agility, efficiency, speed, and manageability within their IT environments. Containers promise to improve datacenter efficiency and performance without having to make additional investments in hardware or infrastructure. Traditional hypervisors provide the most common form of virtualisation, and virtual machines running on such hypervisors are pervasive in nearly every datacenter.

Big Software, IoT and Big Data are changing how organisations are architecting, deploying, and managing their infrastructure. Traditional models are being challenged and replaced by software solutions that are deployed across many environments and many servers. However, no matter what infrastructure you have, there are bare metal servers under it, somewhere.