Skip to main content
  1. Blog
  2. Article

Canonical
on 17 May 2011

Steel Storm: Burning Retribution in Ubuntu


Looking for some arcade fun and action? Well then head over to the Ubuntu Software Center and grab a copy of Steel Storm: Burning Retribution?

It’s a fantastic top-down arcade shooter where you battle against numerous invading aliens in a hovercraft. The Kot-in-action team just released the new episode called Burning Retribution, and it’s available in the Software Center now for 9.99 USD – that’s 10% off the normal price.

The new episode has 25 campaign missions as you fight to defend your planet against alien invaders. With more destructive weapons, more bosses, a new sound track and more things to blow up – in other words a whole pile of carnage and fun! If that’s not enough there’s an online mode and you can also create your own missions with a collaborative mission editor.

Here’s the teaser video:

http://www.youtube.com/watch?v=DmFLEHE5Mn8&feature=player_embedded

There’s a hands-on review on OMG Ubuntu and don’t forget to add your own review in the Software Center for every Ubuntu user to see. So, hurry on over to the Software Center where you can buy it for 10% off the normal price for the next week!

Related posts


Canonical
23 April 2026

Canonical releases Ubuntu 26.04 LTS Resolute Raccoon

Cloud and server Article

The 11th long-term supported release of Ubuntu delivers deep silicon optimization and state-of-the-art security for enterprise workloads. ...


Samir Kamerkar
22 April 2026

From Jammy to Resolute: how Ubuntu’s toolchains have evolved

Ubuntu Article

We cover new toolchain versions, devpacks and workflows that improve the developer experience. The evolution of Ubuntu’s toolchains story goes beyond just providing up-to-date GCC, LLVM, and Python. It is also about opinionated openJDK variants, task-focused devpacks, FIPS compliant toolchains, and snaps, like the new .NET snap and Snapcr ...


Rob Gibbon
20 April 2026

Hybrid search and reranking: a deeper look at RAG

AI Article

Many of us are familiar with the retrieval augmented generative AI (RAG) pattern for building agentic AI applications – like digital concierges, frontline support chatbots and agents that can help with basic self-service troubleshooting.  At a high level, the flow for RAG is fairly clear – the user’s prompt is augmented with some relevant ...