Open-source software now runs most of the internet, from the Linux servers behind websites to the tools that build and deploy modern applications. In 2018 we published a ten-part series on open-source technology trends. This guide brings that series together and updates it for 2026, focusing on what each technology does and when it makes sense for your business.
OpenStack
OpenStack is an open-source platform for building and running your own cloud: the same kind of on-demand compute, storage and networking you get from a public cloud, but on hardware you control. It is made up of services that work together, including:
- Nova for compute (virtual machines)
- Neutron for networking
- Cinder and Swift for block and object storage
- Keystone for identity and access
- Horizon, a web dashboard for managing it all
OpenStack suits hosting providers, telecom companies and organisations that need a private cloud for cost, control or data-residency reasons. It is powerful but complex to operate, so most teams need experienced engineers to keep it upgraded, monitored and secure.
Containers and Kubernetes
A container packages an application together with everything it needs to run (code, libraries and settings) so it behaves the same on a laptop, a test server or in production. Docker made containers mainstream, and they are now the standard way to ship modern software.
Once you run many containers, you need something to schedule, scale and heal them. That is Kubernetes, the open-source orchestration platform that has become the industry standard and is offered as a managed service by all the major clouds (EKS, AKS, GKE). Containers and Kubernetes make deployments faster and more consistent, but they add moving parts that need monitoring, security policies and careful upgrades.
Progressive Web Apps (PWAs)
A progressive web app is a website built to behave like a mobile app. Using modern browser features such as service workers, a PWA can load instantly, work offline or on poor connections, send notifications and be “installed” on a phone’s home screen, all from a single web codebase.
PWAs are a cost-effective option when you need an app-like experience without building and maintaining separate iOS and Android apps. They are particularly useful for e-commerce, booking systems and internal business tools.
Rust
Rust is an open-source systems programming language designed for speed and safety. Its key feature is that it prevents whole classes of memory bugs, which are a common source of security vulnerabilities in languages like C and C++, without the overhead of a garbage collector.
Rust has moved well beyond being a niche language: it is now used in parts of the Linux kernel, in cloud infrastructure, and in performance-critical tools. For businesses, Rust is worth considering for components where both performance and security matter.
R
R is an open-source language and environment built for statistics and data analysis. It has a huge library of packages for statistical modelling, data visualisation and reporting, and is widely used in research, finance, healthcare and analytics teams.
Today R often sits alongside Python in data teams: R for statistical analysis and visual reporting, Python for broader machine-learning and engineering work. Both run comfortably on cloud servers and containers.
XaaS: “Anything as a Service”
XaaS is the umbrella term for delivering technology over the internet as a subscription instead of installing and running it yourself. It started with the three classic cloud models:
- IaaS (Infrastructure as a Service): virtual servers, storage and networks.
- PaaS (Platform as a Service): managed platforms for running applications and databases.
- SaaS (Software as a Service): complete applications delivered through the browser.
It has since grown to include databases, security, backup, disaster recovery and even AI models delivered “as a service”. The benefit is speed and flexibility; the challenge is keeping costs, security settings and integrations under control as services multiply.
Open-Source AI and Machine Learning
Much of today’s AI is built on open-source foundations. Frameworks such as PyTorch, TensorFlow and scikit-learn are the standard tools for training machine-learning models, and a growing number of open-weight language models can be run on your own infrastructure rather than through a third-party service.
Running AI in-house can improve data privacy and control costs at scale, but it requires suitable compute (often GPUs), secure deployment and ongoing monitoring, the same disciplines that apply to any production system. The idea behind “cognitive cloud”, which we covered in 2018, has largely become reality through AI services offered by the major cloud providers.
Blockchain
Blockchain, a shared and tamper-resistant digital ledger, also has strong open-source roots, from Bitcoin and Ethereum to enterprise frameworks such as Hyperledger. We cover how it works, and the difference between public and private blockchains, in our IT Buzzwords Explained guide.
Choosing the Right Open-Source Stack
Open-source tools give you flexibility and avoid vendor lock-in, but someone has to install, patch, monitor and secure them. A few questions help decide where to start:
- Do you need full control over infrastructure and data (private cloud with OpenStack), or speed and convenience (managed public cloud)?
- Are your releases slowed down by manual steps that containers and CI/CD could automate?
- Do you have the in-house skills to run these platforms around the clock, or would a dedicated team be more cost-effective?
How VIPoint Can Help
VIPoint’s engineers have worked with open-source infrastructure since 2012 and manage more than 10,000 servers for clients in the US, UK and APAC:
- OpenStack management: deployment, upgrades and 24/7 operations for private clouds.
- DevOps services: containers, Kubernetes and CI/CD pipelines.
- Software development: web applications, PWAs and data-driven tools.
Planning a move to open-source or container-based infrastructure? Talk to our team or request a free server security audit.