The promise of consumption pricing is lower cost which really means free ingestion—send everything now and pay for what you use later, but there are disadvantages. What about the cost of storage, analytics, extra users, real-time SLAs? Pay for it later.
Consumption pricing is nothing more than shifting costs downstream, then guessing about future costs. It relies on the elastic scalability of the resources used as-a-Service on the cloud with no theoretical upper limit on that amount.
Does anyone remember mainframes when you shared the resource based on the time utilized…also known as consumption pricing? A former colleague, early in his career, submitted a program with an infinite ‘do’ loop. Over the weekend. Those were hard dollars to be paid by our employer, so elastic scalability worked until it didn’t. The fundamental disadvantage of consumption pricing is that as data usage continues to unexpectedly rise, the cost will be much higher than estimated or budgeted.
Few companies will expect to use less data next year either, and since consumption models are not directly connected with resource usage, performance SLAs will vary, and that will cost more.
What is your tolerance for some performance variability? If you need real-time, you should have access to real-time otherwise the architecture of the solution is inferior.
Gartner recently wrote that customers, “Perform proof of concept tests on all considered platforms to verify actual cost comparisons and continue to monitor ongoing costs to reduce budgetary uncertainty.”
Bottom line: Consumption pricing is a deception. Welcome back to filtering.
Stop Being Deceived
LogZilla NEO’s Unlimited Pricing Plan achieves 10 TB/day on a single 1U server and ensures that you can send all your machine data, not just the data you can afford.
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