HPE Alletra Storage MP B10000 Reviews

My main use cases for HPE Alletra Storage MP B10000 are virtualization and database.

The features of HPE Alletra Storage MP B10000 that I prefer the most are the snapshotting and ease of administration. These features have benefited my organization by providing time and cost savings.

The ability to scale capacity and performance independently impacts operations positively, as increasing capacity is effortless; you just plug it in, and it's bigger. The solution's AI-driven predictive analytics and performance reporting give us a picture of which VMs are being used the most, so we know if we have to adjust how they're set up. These features have helped reduce the time spent on capacity planning.

The solution enables the line of business or DB admins to self-provision storage. The ability to self-provision storage has helped reduce the time required for storage provisioning and management because of the ease of provisioning; it just doesn't take long to do it.

They need to put back in the feature in which you can export volumes by set instead of individually. I mentioned this in a meeting I recently had with them.

Our main use cases for HPE Alletra Storage MP B10000 involve a lot of VOD infrastructure within my company, where we store the content so that we can play it out to the clients. This is where we store most of the content.

The features of HPE Alletra Storage MP B10000 that I appreciate the most include the high RAM, which allows us to extract the data quickly, and the GUI, which is much more intuitive than the competitors. 

These features benefit our organization by enabling us to provide low-latency VOD content to the clients.

We need to ensure that the GUIs are intuitive so that when an issue happens, we can easily navigate through it and fix it. Everything has been smooth so far with the product.

My main use cases for HPE Alletra Storage MP B10000 is the replication.

The data we get and manage is better for the company.

We use the solution for general compute for our VMware infrastructure. We use it for some niche radiology pack solutions.

We're seeing a reduction in the actual amount of data being stored. There's more room to grow. It saves us time and increases efficiency. It is set it and forget it. It frees us up to do other things.

The solution offers primary storage for our VMware environment.

We're still in the process of moving our workload over to it. We're going from an undersized array with SSDs to a brand-new technology with NVMe storage, and it's going to allow us to run our applications without having the kind of latency that was causing performance issues for our end users. Also, we're going to be able to do sandbox replication between our two data centers. 

For the most part, looking at how we consume data and pay for data at the end of the day is the advantage. The pay-as-you-go model is a much easier way to go.

Moving to a consumption model is highly desirable from the client side. everyone seems to be moving in that direction. 

It provides a cloud-like experience on-prem. It simplified it for the most part. When you look at a lot of the storage and historically how it's been done, you're doing a lot of forecasting, a lot of business justification, a lot of purchasing of hardware, and oversizing for growth, et cetera. The pay-as-you-go model is a much more simplified way of doing things. And it offers more flexibility.

The scale capacity improves and simplifies the experience in terms of growth and performance. A lot of clients I work with have performance requirements. I work heavily in financial and healthcare segments and those need 24/7/365 performance with no downtime. 

GreenLake helped to reduce our operational expenses.

We primarily use the solution for storage provisioning and running demos. 

It helps us reducing the complexity in order to manage your storage systems. Simplifying the management of every array from several locations is difficult. One of the most important things for us is to reduce complexity, managing, and operating tasks. Our goal was not to have a lot of different consoles for every device. It unifies everything.

My use case is mainly for virtualization. Most of the workloads are virtualization. They're running virtual machines on there. Now I'm also deploying it for containerized applications. I also have a small Kubernetes stack storing its data.

I am a long-time HPE storage user and what I like the most is that they picked the best of both worlds and merged them together in one platform. 

I can start small. I can scale up. I can scale out. I can scale the capacity independently of the performance. 

The most important feature is that it's easy to manage. It has integrations with my application and with my software stack.

It's so easy. We have the full life cycle management doing updates, and it's just a button, so it makes life easier. 

The ease of management has the biggest impact. That directly impacts my daily life. With easier management with one console, the application team can use the same tool. It's much more efficient. The communication, the enablement, it goes much faster, and we are much more efficient.

The evolution over the last year has been good. They are doing a great job and have a good roadmap. 

We've saved a lot of time. However, how much time saved would depend on the number of actions or how you are measuring.

It improved your storage performance in iOS due to the technology that they're using and the NVMe Storage.

Today I get a better deduplication level compared to the previous generations. That means the price per gigabyte or terabyte is lower for me.