PLM companies are switching to the cloud. Software vendors are taking different paths and technical strategies – IaaS, PaaS, private clouds, public clouds with high diversity of options and marketing messages. Navigate to some of my previous posts to get up to speed with the topic – Cloud PLM and IaaS Options, PLM PaaS, PLM cloud strategies.
Public cloud and specifically Amazon Web Services is one of the options to explore the potential of new PLM technologies, delivery and business models. To use elastic infrastructure provided by Amazon is compelling to newcomers in PLM industry as well as for established PLM vendors transforming their PLM portfolios. A potential disadvantage of Amazon is that it can get a little pricey. Many cloud companies discovered "cost issue" especially when they come to the point of scaling customers and data.
Earlier this week, I was reading an interesting article by Heap – “How We Estimated Our AWS Costs Before Shipping Any Code”. Heap is an iOS and Web analytics tool that captures every user interaction. Interesting enough, Heap helps you to estimate their AWS cost to decide if product / project/ website has a sustainable business model. Here are few interesting examples provided by Heap article:
Cost reduction: CPU. Our queries involve a large amount of string processing and data decompression. Much to our surprise, this caused our queries to become CPU-bound. Instead of spending more money on RAM, we could achieve equivalent performance with SSDs (which are far cheaper). Though we also needed to shift our costs towards more CPU cores, the net effect was favorable.
Cost inflation: Data Redundancy. This is a necessary feature of any fault-tolerant, highly-available cluster. Each live data point needs to be duplicated, which increases costs across the board by 2x.
This article made me think about possible trajectories of cloud PLM options. PLM vendors thinking about transforming and adapting their existing PLM products for cloud must be aggressively making assessments about their cloud cost on Amazon or alternative platforms. Startup companies developing new generation of PLM products have a very good opportunity to check their costs and viability of their future business models.
What is my conclusion? The battle about cloud viability has strong cost relation. Software companies are moving from "CD shipments" to "service providing". This process will be painful for many of them and sooner they validate and build their future business models is better. For PLM companies, the best association should be "cost model for manufacturing" – the earlier in the process of product design you can see the cost – the better chance this product become successful. Just my thoughts…