Nutanix Calm Primary Use Case
We evaluated Calm primarily as an automation platform because that's what it is. I work for a service provider and we represent a lot of customers.
Our journey with Calm started because we wanted to decentralize our platform of services to customers, because agility is one of the biggest concerns. As a service provider, we have very rigid practices because we follow ITIL processes. If we're managing a customer's environment, we need to have controls. The unfortunate reality of controls is that they add rigidity, and that works in contrast to the agility of cloud where customers want to be able to adopt and migrate and move quickly, based on their businesses needs.
We're developing Calm in a way where we give customers choice and flexibility, so that we don't have to consume workloads for them. We give them Marketplace, and part of Marketplace is that we publish open source applications, as well as managed applications and unmanaged applications. These applications could be as simple as a stack of load balancers, middleware, and database. Or it could just be an operating system. It's really the customer's choice. We've given them a platform, similar to the way public cloud providers do, a marketplace where they can go consume, but in our marketplace, that consumption can be on their platform. We provide a shared platform like a public cloud, and the hyperscalers, so they can consume it in Amazon and Microsoft Azure as well.
Part of our journey with Calm was that we wanted to speed the process up, but at the same time, have a standard catalog in that process, and let that catalog evolve with our customer feedback.
In our organization, we are both a partner, a service provider, and reseller of Nutanix. We have a very strong relationship with them. We have adopted Nutanix as a standard for our service provider cloud, which is located in five data centers in the central United States. In these environments, we have deployed Nutanix for our own services and shared services, and we are also selling private cloud, based on the Nutanix platform, to our customers. With these deployments, we are standardizing on Calm as a centralized management marketplace. So it's doing a couple of things. It's letting customers consume against their own platform, and it's allowing customers the access to be able to consume hyperscale and/or our shared platform if they choose to do so.
Our journey, right now, is balancing between managing operating systems and our managed service practice for our customers. We're trying to automate that managed service practice with Calm and their blueprints and the openness of scripting that they support, so that we can automate adding an application, an operating system, from our catalog. It goes through an ITIL process of creating a customer asset in our service library. It grabs values of that asset—naming conventions, components of the infrastructure, et cetera—and puts them into the customer's asset library.
These are all bits of underlying automation that you normally wouldn't necessarily have to do, but as a managed product we do so on behalf of the customer for inventory purposes. And that's just one aspect, what a managed platform does. The other aspect is an unmanaged platform. A customer can say, "I want to do 10 things and I'm managing them myself, and I'm going to probably destroy them when I'm done." We wanted that ubiquitousness, so a customer can choose whether they want something managed by us or managed by them, but where we keep the experience for doing so the same. It's a standard journey instead of their having to open a ticket and request something and then wait for a period of time for it to be executed. We're trying to remove ourselves as friction.
Our use case for Calm has been wrapped around giving customers a marketplace to standardize their experience and to determine what the components of that standardization are, which includes workloads that we manage, workloads that the customer manages, and those two scenarios can be on their private cloud, our shared platform, or the hyperscalers.
One goal was to automate things. We had a lot of tools, but we needed a centralized tool. Calm helps us to centralize the deployments of our VMs.
We have a subsystem installed on Nutanix and we have blueprints for setting up this subsystem very easily. Also, for Kubernetes clusters, we use now CaaS from SUSE and we also create Kubernetes clusters with Calm. Our strategy is to make blueprints for all the virtual machines environments. It's an ongoing process.
We are currently using Calm to automate our infrastructure and platform provisioning, including going into infrastructure-as-code, standing up environments, and triggering deployment processes.
We aren't looking for it to automate application management to a single platform because we are spread across Azure Pipelines and Octopus Deploy and multiple methods of automating our application deployments. In the last year, we have standardized what we are doing with Calm in terms of infrastructure automation. We haven't stepped into application life cycle management with Calm. We are mostly focusing on leveraging Calm as our platform and infrastructure provisioning orchestrator.
It is based on-premises on our Nutanix cluster.View full review »
We wanted to find a way to start getting our academics used to paying for compute without having to actually pay, but still to do it for real in the cloud. We use the self-service portal within Nutanix for them to deposit some funds, which is a cost charge, not a credit card, and then we say, "Okay, based on that, you have bought X amount of CPUs, Y amount of memory, and Z amount of storage." They can then go in and say, "Okay, well, I know I've got a pool of 10 BCPs for a month. I want to spin up three of them to process this data, which I'll then tear down afterwards."
We use it for our neurological psychology department where they do a lot of brain scans. They want to upload them to a place where they can compute the output of those scans and then they want to tear down their compute afterwards, because they don't need to be running all the time.
Another area uses it for looking at weather data, which is typically quite a large amount of data. They only need to process once and then they can destroy it because they don't need to look at it again, once they've done analytics on it.
Those are our typical use cases: to allow our research areas to spin up their resources against a pricing model that they've secured funding for, and not have to engage the IT teams to provide the resources for them. It also allows them not to go beyond their budgets and stay within predefined lanes.
We have it on-premise. We built our own private cloud and we host it on there for our academics to consume and spin up their own resources. We know that we could burst up to Azure, AWS, and GCP, but we don't. We keep it all within our private cloud at the moment.View full review »
We provide Test-VMs to users. Currently, we deploy only Windows-VMs from Windows 10 1803 up to 20H2 and Server 2012 R2 to Server 2019. The blueprints consist of a base Windows Image (which is used as a template for the VM to be) and several tasks you can define and use remote PowerShell to get whatever you need to get done, like install additional software, set registry keys - you name it. Each task is then executed in the defined order and results can be reviewed even during execution time. Hardware specs can be made configurable, so users can adjust the amount of RAM or CPU core count but can also be set to static.
We recently set the machines up to configure customary passwords and give users an email notification when the machine is ready to use. Also we differentiate machine networks based on the users department to separate machines.
We use Calm as an automation engine for deployment of the cluster software over our network. We are also using it to deploy standardized workloads on the Nutanix clusters.
We also use it to create a "self-service shop," where we can select to deploy standardized workloads and choose a certain profile for a particular server, and the Calm engine will integrate with other solutions like our IP database and CDB. Everything is fully automated.
In addition to standardized workloads, we also can say, "Give us a generic virtual machine."
System Engineer at a non-tech company with 10,001+ employees
We are using Calm to deploy a new server. We have four blueprints: the first one is to bring the network; the second one is to configure the elements; the third and the fourth ones are for deploying new servers.View full review »