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There has always been a fine line between when an emerging IT platform creates enough demand for managed services and when it essentially becomes a commodity that most internal IT teams can manage on their own. Timing that transition is critical for managed service providers (MSPs) because an imbalance between the demand for expertise and the available pool of talent for any given platform is what creates opportunity.

According to a recent global survey of 135 contributors to open-source projects conducted by Cloud Native Computing Foundation (CNCF), roughly half of organizations don’t pay for training (53 percent), with slightly less also noting their organization doesn’t give them the time to pursue certifications and training (52 percent).

About 81 percent of respondents said cost prevented them from completing certifications in the past two years, while 43 percent cited time as a limiting factor. The top two constraints for training were Cost (62 percent) and time (36 percent) as well.

Of course, MSPs struggle with the same issue. Acquiring new skills always comes at a cost. Therefore, if an MSP decides to invest in acquiring them, it is crucial to estimate the time required to achieve a return on investment (ROI). A platform like Kubernetes has been around for years, but only recently has its demand for managed services reached a level strong enough to justify one.

Pace of change leads to declining costs for MSPs

The length of that opportunity, however, is anybody’s guess. Over time layers of abstraction that make a technology simpler to manage are always created. Today it’s still challenging for an internal IT team to manage a cloud-native computing environment based on Kubernetes clusters. The challenge is that the pace at which abstractions for managing complex IT environments are being created is thanks to advances in automation and artificial intelligence (AI), accelerating.

MSPs will naturally benefit from those advances because the total cost of managing these environments will start to decline. The issue is that as these abstractions become more available, it becomes simpler for internal IT teams also to manage these platforms, which tends to adversely impact demand for external expertise.

Timing, as is always the case, is everything when it comes to managed services. As more abstractions become available, the price that MSPs can realistically charge for a service starts to decline. It wasn’t all that long ago that managing virtual machines was a highly profitable service. Today virtual machines are spun up by developers in a few seconds with little to no regard for cost in the age of the cloud. There are still opportunities for MSPs higher up the stack from virtual machines, but acquiring those skills requires an investment.

Essentially, any investment an MSP makes in training is a wager that needs to be carefully calculated. There is only so much training an IT team can be provided with while also being tasked to manage an existing service. Too many training bets placed on the wrong platforms can easily cripple an MSP that often finds itself needing to pivot quickly to another platform that they will again need to invest in training to service.

Photo: SFIO CRACHO / Shutterstock

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Mike Vizard

Posted by Mike Vizard

Mike Vizard has covered IT for more than 25 years, and has edited or contributed to a number of tech publications including InfoWorld, eWeek, CRN, Baseline, ComputerWorld, TMCNet, and Digital Review. He currently blogs for IT Business Edge and contributes to CIOinsight, The Channel Insider, Programmableweb and Slashdot. Mike blogs about emerging cloud technology for Smarter MSP.

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