Spectro Cloud announced Palette EdgeAI to simplify how organizations deploy and manage AI workloads at scale across simple to complex edge locations, such as retail, healthcare, industrial automation, oil and gas, automotive/connected cars, and more.
DevOps discussions typically center around process, culture, and technology. But if you work for a global financial institution or a high-end game developer, you probably wish someone would talk about scale.
In fact, the differences between DevOps and "Big DevOps" are non-trivial. Two scale-related attributes in particular make Big DevOps susceptible to bottlenecks that organizations working at smaller scale are far less likely to encounter:
1. The massive size of the application codebases
2. The need to distribute those massive codebases across multiple globally dispersed dev and test teams
Together, these two attributes can result in some pretty serious process bottlenecks that impede their digital agility and seriously undermine their ability to compete in today's fast-moving markets.
That's why anyone leading a Big DevOps enterprise has to solve their Big DevOps codebase distribution problem.
Unfavorable Code-to-WAN Ratios
The primary cause of Big DevOps code distribution bottlenecks is the network. Enterprise WAN connections are just too narrow to accommodate massive codebases. Even if you spend lots of money on additional bandwidth and network acceleration, the ratio between your bits of code and your bits-per-second of network will invariably result in unacceptably slow transfers. The result is software delivery that keeps getting delayed with every distribution of every large code artifact.
Of course, code distribution bottlenecks aren't the only cause of DevOps delays. Large, complex software projects can fall behind schedule for many reasons. But the code distribution bottleneck adds a chronic impediment that makes it impossible to ever make up lost time. So, as the saying goes, the hurrier you go, the behinder you get.
By itself, the cloud cannot address this Big DevOps bottleneck. Your teams simply can't work on codebases hosted in the cloud. They have to work locally. So the cloud presents two problems. First, all your teams all over the world have to keep downloading and uploading massive files. Second, you have to make sure everything everybody does everywhere stays in synch.
That's why Big DevOps requires an entirely different approach to codebase distribution.
For Global DevOps, Try Global Dedupe
Big DevOps will ultimately require you to adopt a hybrid hub-and-spoke model that lets you maintain a "gold copy"of your codebase in the cloud — while giving everyone everywhere a local copy that gets continuously updated with any changes to the current build. This model eliminates network-related bottlenecks while allowing your geographically dispersed teams to collaborate without tripping over each other's work.
This hybrid cloud hub-and-spoke model has actually been used for year by CAD/CAM teams for years to address a very similar file distribution problem. And it does more than just eliminate process delays. It can also save you considerable sums of money — because you can spend less on your network and your local storage infrastructure.
Time, however, is the real enemy when it comes digital deliverables. So if you're doing Big DevOps, take a hard look at your codebase distribution bottleneck. The future of your company may depend on it.
Barry Phillips is CMO of Panzura.
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