8 IT Predictions for the New Year

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Everyone has their predictions for the new year but do they often prognosticate using an animated video? The folks over at created a clever animation depicting their reasonable and humorous predictions for 2010. rPath might be best known for its . You can also . They're also known for release automation, cloud computing, virtualization, self-service IT and much .

If you'd like to see their cool webinar, hosted by your own DaniWeb Linux Guy, click on over to Linux Magazine and check it out.

I've built several appliances using their online wizard and have done so for a few years now. I only recently got to know them on a more personal basis from the webinar. But the 8 predictions for IT in 2010 is a must catch.

What do you think of their predictions? Did they leave out anything?

Dani AI

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Nice find, . Predictions are useful as conversation starters, but the work is turning them into repeatable, low-risk projects. Below are practical, hands-on points that help turn trend-talk into something you can test, measure and ship.

  • Define success up front. Pick 2–3 concrete KPIs for a pilot (deployment frequency, mean time to recover, cost per instance, or feature lead time). If you cannot measure it, you cannot prove it.
  • Run small, end-to-end pilots. Limit scope, automate the build and deploy pipeline, and exercise rollback and upgrade paths at least once in the lab.
  • Treat artifacts as code. Version every build artifact, pin dependencies, produce reproducible images, and keep an immutable-artifact registry so you can trace exactly what was deployed.
  • Automate testing early. Include quick smoke tests and upgrade-path tests in the pipeline so regressions surface before production.
  • Build ops and security into the design. Plan secrets management, least-privilege access, automated patching and basic monitoring from day one.

Common blind spots worth calling out:

  • Culture and process: tooling alone rarely delivers; change the process, incentives and roles too.
  • Orchestration and lifecycle: packing an image is easy; operating, scaling and updating it at scale is harder.
  • Data and migration complexity: moving services is one thing; moving state and data often eats the schedule.
  • Cost governance and lock-in: early wins can hide long-term operational or vendor-cost risks.

If you build appliances or images (as mentions), focus on reproducibility and upgrade safety: keep minimal base images, document build scripts, store checksums/signatures, and always validate a restore/rollback procedure. Treat each prediction as a hypothesis: test it quickly, measure results, and iterate.

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