A better world is possible.

When you work with Blue Herring the easy things become easy, and that makes the hard things possible. It’s a collaborative process that exposes the dependencies and data chains in your enterprise applications so you can simplify and streamline them.

The system is effective because it reduces the number of interaction points. Component interactions are bounded by O(n2), so halving the number of measurement points can potentially cut your workload by ¾.

That’s it. That’s the magic. It’s just math. Fewer moving parts means fewer interactions means fewer conflicts.

As a result, you will be able to integrate, deploy, and deliver with greater consistency and way less drama.

What it’s based on

Business Value First

Devops itself is about business performance.

The newest and shiniest toys are great. But to be meaningful, they need to be improving the outcome of business processes.

Your internal and external customers will continue to invest in your operations as long as they are yielding outstanding business value.

Deployment is the deliverable

“But it works on Dev!” has become the cliché for production-level failures. Operations people have long understood that apps that don’t work in production don’t work; the rest of the culture is finally catching up now.

Working with the Blue Herring system has to be outcome-based and deployment-centric.

Machines do the work

As a principle, all the work is scripted so all the work is repeatable.

Realistically you may have to make an occasional exception in the interest of expediency, and then documentation is your friend.

We apply human ingenuity to simplifying the systems and structures first; then we set the machines to monitoring and processing.

Consistency and reliability are what matter.

As a technology leader, you’re always asking “What could possibly go wrong?” The Blue Herring system defines a simplified “happy path,” catalogs exceptions to that path, and documents any unavoidable loose ends. The process lets you know what could go wrong, and our tools let you know when it does go wrong.

The results are noteworthy.

Find out more about the process.
Next: how we do it