Advantages of Using Rampiva Automate Cloud Native Solution for Nuix

In this short video, we share the advantages of using our Rampiva Automate Cloud Native Solution for Nuix data processing.

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What I want to show you now is some of the advantages that you can get from using a cloud native solution, as opposed to having the users manage those virtual machines in those resources manually.

It's much better and much more efficient to have Rampiva do that part. So we have native support for that management of resources on Amazon AWS and Azure, and the advantage of that is that you can have no idle time. So the machines are shut down before you need to process data, or they might not even exist and then Rampiva will either turn them on if they exist or actually create them and assign local resources to them, assign local storage. And then when the processing is done, depending on the settings that you have, we could shut down those machines or completely destroy them, delete them so you don't pay for any even for temporary storage resources. We can run the jobs on a single note.

Or like I said, if you have a 10-terabyte job, you can split that same job with a 10-terabyte data set on a single load command across multiple machines. So you could have one main server and then ten other servers assisting with that. On AWS, we can use the spot instances, which is a mechanism for AWS to say that you can run machines. It's not guaranteed that they will be up, but when they are up, most of the times, you pay around 1/3 the price, or it can be slightly higher or slightly lower depending on what the demand is on the market at that time.

But most cases it will be much more advantageous from a price perspective to use spot instances for processing. So we will use the main instance that's handling the Nuix case that always has to be up.

There will be a dedicated instance, but all of the others that are assisting and participating with resources will use those a spot instances. And then also we can use the Amazon FSxLustre storage, which is a highly performant, highly distributed system from Amazon, from AWS, where if you have hundreds of terabytes to process, this is probably what you should be looking at. And yet one of the advantages from a pricing perspective with FSxLustre is that you only pay for the data you store. So if you only load 10GB of data and then you increase that to 100 terabytes, and then you decrease it back to 10GB, you don't have to do any resizing of virtual disks or anything like that. Amazon only charges you for the data that you store in there. So the way this works is that we have this. Like I mentioned the main engine that we run on an on-demand instance. We can have these remote workers on spot instances. In this example configuration in here, I choose to stop the main instance when the job is done. But like I said, we could also terminate it and then I chose to store the Nuix case on a local storage in Amazon elastic block. But all of the source data and export data go on FSxLustre and you can use Elasticsearch if you want. You can use Amazon S3. There's a lot of options in there.

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