How to Optimize Cloud Spend with ParkMyCloud - ParkMyCloud

How to Optimize Cloud Spend with ParkMyCloud

The focus on how to optimize cloud spend is now as relentless as the initial surge was to migrate workloads from ‘on-prem’ to public cloud. A lot of this focus, and resultant discussions, were in regards to  options related to the use of Reserved Instances (RI’s), Spot Instances,or other pre-pay options. The pay-up-front discount plan makes sense  when you have some degree of visibility on future needs, and when there is no ‘turn-if-off’ option, which we here at ParkMyCloud call “parking”.

When it comes to the ability to ‘park instances’ we like to divide the world into two halves. There are those Production Systems, which typically need to be running 24/7/365, and then there are Non-Production Systems, which at least in theory have the potential to be parked when not in use. The former are typically  your end-customer or enterprise facing systems, which need to be online and available at all times.In this case, RI’s typically make sense. When it comes to those non-production systems, that’s where a tool such as ParkMyCloud comes into play. Here you have an opportunity to review the usage patterns and needs of your organization and how to optimize cloud spend accordingly. For example, you may well discover that your QA team never works on weekends, so you can turn their EC2 instances off on a Friday night and turn them back on first thing on Monday morning. Elsewhere, you might find other workloads that can be turned off in the small hours or even workloads which can be left off for extended periods.

Our customers typically like to view both their production and non-production systems in our simple dashboard. Here they can view all their public cloud infrastructure and  simply lock those production systems which cannot be touched. Once within the dashboard the different non-production workloads can then be reviewed and either centrally managed by an admin or have their management delegated to individual business units or teams.

Based on our customer usage we track, we see these non-production systems typically accounting for about 50% of what the companies spend on compute (i.e. instances / VMs). We then see those who aggressively manage these non-production instances saving up to 65% of their cost, which then makes a large dent in their overall cloud bill.

So, when you are thinking about how to optimize cloud spend, there’s a lot more opportunities than just committing to purchase in advance, especially for your non-production workloads.


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