Amazon AWS Reviews

We advise our clients on using AWS services. It has many applications; in health care with regard to patient medical history. Some use it for hosting, SAP and V-ware. Those are the most common uses for our clients. We are resellers and I'm the operations director.

I think machine learning is one of the most used and most valuable services, especially in scientific research. The solution is evolving all the time. 

Some of the services are hard to use so I think a more user-friendly interface would be helpful.

The solution is stable. 

The solution is very scalable. 

Amazon offers different support plans. We have enterprise support and they generally get back to us within half an hour. The escalation process is very fast, because they know that there is a critical platform involved. They generally offer a high level of support. 

The initial setup is not too complex but it's not straightforward either, somewhere in the middle. In terms of deployment time, it can be anywhere between a few minutes and a week, depending on what you need. 

Training is critical before implementing the solution. There are very good AWS certifications like the certified practitioner, and there's a lot of free training on the AWS webpage that customers can use. Most of the training is hands-on so you can experience how things would be done in a work environment. AWS recently deployed 100 free courses on amazon.com to help people better understand their products. I would recommend looking at those.

I rate this solution nine out of 10. 

We're using AWS for limited purposes right now. The university has its storage, servers, and large amounts of data center equipment, and the cloud fills a niche. We put things in the cloud so that others have access. But from a storage standpoint, 95 percent of the usage is entirely on-premises. We might use it more in the future, but we're trying to build up a storage ecosystem right now. We'll likely build that around some open-source solution, like Ceph or MEAN.io, or something from a popular vendor. 

RedHat has Ceph storage too, and IBM has object storage. I'm not sure what the university will go with, but those are the ones we are looking at. We're using AWS S3 for general storage and storing images. We also use AWS as a platform for building some web services and things like that. 

We've built several AI ML solutions and done lots of work on the GPUs available on Amazon servers. We did a lot of work around web spidering, natural language processing, and machine learning or deep learning workloads. 

I think Amazon could improve some of the security or fine-grained access for metadata and many other things. From a cloud standpoint, Amazon provides more ways to restrict access or provide fine-grained access to different services. For the time being, I think the ecosystem is relatively secure, but there is room for improvement. 

AWS is scalable. It's serving about 150 users at my company right now. All of the users are researchers who do their own thing. Each research team manages its own partition and has fine-grained access to all the services. Small groups of around 10 to 15 people manage their own respective groups as to all the requirements associated with AWS.

We customized our Amazon AWS deployment. The process takes about three to five hours, depending on the ecosystems we are building. It depends on whether it is related to web services or the call configuration. Some configurations take no more than half an hour. If you're doing something involving the server, you need to personally install some servers and some of the other database-related stuff.

I'm one of the AWS architects, but we have administrators who take care of the maintenance. I'm looking at some of the SNIA content, and it seems pretty good for object storage or some of the other storage-related options. I'm still trying to see which solutions are potentially more suitable for us. 

I'm not sure about the licensing. I don't know what kind of subscription the university bought. I imagine it's similar to Cognizant, which had a usage-based mechanism. We bought yearly subscriptions for specific servers while pre-booking some of the server-based storage or computing infrastructure.

We've used Azure also. They are all fairly good. 

I rate AWS eight out of 10. I used to work in Cognizant and TCS before that, and we used different cloud services, such as Amazon and Azure. If you want some kind of public cloud infrastructure, I would go with one of these or maybe Google Cloud. The university is in the process of setting up its own storage or server ecosystem. We plan to store massive amounts of video, images, and other objects, like our AI/ML workloads. 

We use Amazon AWS for many applications as well as Amazon's native services. We have a mix of content-based workloads and traditional legacy type of applications. 

Amazon AWS contains a lot of helpful services. 

Amazon AWS would be improved if it were more stable and if customer support's responses were faster. 

I have been using this solution for many years, somewhere between seven and ten. 

This solution has been relatively stable. We had one issue sometime back, so the infrastructure could be more resilient. 

This solution is scalable. 

I have contacted customer support and their response time could be faster. 

We migrated to Amazon AWS from the Data Centers. 

The installation was straightforward. The installation time varies depending on workloads. 

I implemented through an in-house team. We have multiple teams for deployment and maintenance. 

There is no licensing cost. 

I would rate Amazon AWS an eight out of ten. I recommend this solution to anyone who wants to start using it. 

We are essentially using a couple of virtual machines. We also use Amazon's transcoding services that convert video formats. We use it for internal purposes, especially for specific applications that it has. 

One of the most valuable features is that Amazon AWS has a lot of data centers and regions where we can position our virtual machines for leverage. Amazon AWS is also easy to use. You can quickly spin up something, use Explorer, building proofs of concept, things like that. Once the proof of concept is built once and we know how things are going to look from a production perspective, we try to move everything to the data centers. These features and the ease of use are the main reasons why we use AWS. 

There are no additional features I would like to see. All the features we require are already provided and we aren't looking for anything else beyond that. 

In general, the only feedback I have is about the startup programs they used to have. Startups would get a particular amount of credits so that people who are just starting their own business could export. This is no longer the case, but it was very good because it helped a lot of people start their businesses. Amazon should consider this again. 

I have been using this solution for three years. 

This solution is scalable. 

I have never needed to contact technical support. 

I previously used Azure. I was working for a company that used Azure CSP, but I prefer AWS. 

The initial setup is straightforward. I'm technically proficient and did it myself. 

I implemented through an in-house team. We're a small, boutique-type company, but we are proficient enough. 

In terms of price, there are less expensive options. 

We are using open source technology, so there is no licensing. 

I looked at Google Cloud also, but I still would prefer AWS. It has automation and scripts that we can leverage. People are familiar with AWS, so it's our top choice for public cloud. 

I absolutely recommend Amazon AWS to anyone who wants to start using it. 

I would rate Amazon AWS a 10 out of 10. That's the main reason why we're using it. 

We use Amazon AWS as a data platform.

The features that I have found most valuable are its cloud storage and compute services.

Amazon AWS could improve on its data warehousing appliance.

Its only cons are on the data warehouse side. AWS' data warehouse Redshift is not as good as it should be.

In terms of what should be in the next release, I would say nothing much other than that AWS has a lot of services doing similar work. If they could consolidate and make sure that the services are defined appropriately, that would be an improvement. Currently, there is a duplicacy of work.

I'm working with AWS for almost five years.

The stability is very good.

You do not need tons of people for maintenance, because a lot of automation will be brought in by AWS, and you can have one or two people to manage the platform.

Amazon AWS' scalability is very good.

There are a lot of features that require scaling - the scale up and scale down aspects of load balancer, Spot Instances, On-Demand Instances, and all those things. You can configure your limits, and based on that, the computer infrastructure can be scaled up.

There are tons of users using it. Whatever the project I work on, there are almost 200 users using it.

There are lot of data engineers, data scientists, and business users using it.

Customer and technical support are very good.

The initial setup is straightforward.

The licensing costs are all similar. All charges are similar in nature, such as storage cost, compute cost, VM cost, or VP costs, and all those things. Two advantages on this point here are whether you take Spot Instances or if you reserve for long term usage, then you'll get a lot of benefit.

If you want to use any third party services you have to pay from the Marketplace, but the other things are all pay-as-you-go kind of a model.

Amazon has a great customer base and lot of success stories. That is one advantage that AWS has, whereas the others are catching up. Recently they have more case studies, but for overall breadth of the industry and breadth of the customer experiences, AWS has more customers. AWS has more services than the other competitors.

My advice to anyone thinking about using Amazon AWS is that they need to set up the foundation well, and they need to choose the right partner to do the implementation. The more experience the partner has, the better the implementation will be.

On a scale of one to ten, I would give Amazon AWS an eight.

We use the solution for many use cases, such as application hosting, virtual desktops, and disaster recovery.

Customers don't need to calculate what their future requirements need to be. They can start using Amazon AWS no matter what the requirements are and if they increase size it can support them. By using the solution they can reduce their infrastructure, which helps them reduce the cost and of their infrastructure.

This solution is used as the basic requirement for any virtual machines use cases, the storage is used for each use case.

I have been using Amazon AWS for a year and a half.

The solution is stable. We have global customers on this platform. If you see the past records of Amazon AWS, there has been rarely any downtime or something happening.

Amazon AWS is scalable., there are different tools that help to maintain the scalability of the solution. Many of the tools are free of cost. There is no restriction on how many people can use this solution.

We have 500 customers in the Mumbai region and we plan to increase usage.

There is vendor technical support but it is not required if they are taking our support. The customers can directly purchase their support. Our small customers, are purchasing AWS support and they are pleased with the support.

The initial setup difficulty depends on the customer's environment. If it's a simple single virtual machine, then it's a simple setup. If it's an SAP-type workload on AWS, then it is somewhat complicated.

If it is a small single-server implementation, it will take one day to deploy. Otherwise, from an application perspective, your team needs to handle everything and it could take beyond 15 days to one month.

We have our own team that does the deployment.

The price of the Virtual Desktop service from Amazon AWS could improve, it is more expensive than competitors. The pricing model we are using is pay-as-you-go. You only pay for what you use.

The technical support from Amazon is extra and there are more than 200 services you can use that has a cost.

My advice for those thinking about the implementation of Amazon AWS is to start using it, do not have fear to use these services. If you know how it works and you receive the right support, it always helps to reduce the cost and headache of IT.

I rate Amazon AWS an eight out of ten.

Amazon AWS is good in terms of deployment and user experience. Their certificate management and load balancer are also good features.

The sorting model in AWS is a little bit complicated. When you are going through any component, you can get some surprising results.

I've been using AWS for more than two years.

Scalability is something that people are looking for when they choose Amazon AWS. I like that it integrates well with IBM Resilient, which is like a serverless map. We have more than 5,000 employees in our organization. 

Amazon support is good.

Setting up AWS was straightforward. It only took around 20 minutes. We used about five to 10 team members for deployment. For maintenance, we have an architect and some RDS specialists. 

Amazon AWS could have more options and transparency in its pricing model. You need in-depth knowledge to adopt AWS. So someone without that knowledge base might not understand all of the costs associated with AWS.

I rate Amazon AWS nine out of 10. I would definitely recommend it to others.

AWS is easy to manage.

Some features may be better in Azure or some other portal. AWS could add some of those features.

I've been using AWS for three to four years.

So far, I've had no issues with stability or scalability.

AWS was already installed when I started working at this company, so I don't know.

I rate Amazon AWS eight out of 10.