Maestro Blog

Maestro billing engine allows transforming virtual and hardware capacities utilization into bills , based on the events within their timeline, and states they get as a result of such events However, the modern world, with its dynamic changes in situations and requests, needs flexibility – and in billing, as well. The hourly cost of your datacenter maintenance may depend on external factors, like varying electricity costs (for example, cheaper night hours), which can let you make nightly hours of your infrastructure usage be also more affordable. You may also want to re-distribute the load between data centers or data center sections during peak hours by offering lower prices in underutilized zones, and higher prices – in those that are overloaded.  Season discounts, special offerings, and other pricing alterations are also on the list. You even may want to apply extra charges for your users access to public clouds, by adding a respective coefficient to the native provider’s bill. S...

Typically, for on-premises infrastructures, the enterprises use capacity quotas to regulate the amount of resources each team can use (in CPUs, Memory GBs, storage GBs, etc.). This approach is effective and convenient when all your resources are exclusively in your own data centers. However, the things get more complicated when a public cloud is added. In such case, using both the resource-based approach in your private DC, and public clouds’ pay-as-you-go, you need to make an extra effort to properly arrange your financial procedures and planning, as, in fact, you need to deal with two completely different calculation approaches. A pay-as-you-go approach for private data centers is a right decision if you aim to unify and simplify financial governance, planning, resource allocation and utilization accountability. An effective, powerful, and flexible billing engine is a keystone for such solution. Maestro has one, and further in this post, we will uncover the approaches it uses, and th...