Amazon AWS Reviews

We are mostly using it for DevOps. 

We are using its latest version. They do auto-updates and update it at their own will.

It is easy to spin up resources.

There is no control of downtime.

I have probably been using this solution for eight months.

Over the past couple of days, we've had some outages. It seems they had some network issues, but overall, it has been pretty dependable and stable.

It is easy to scale. We probably have about 50 users who use this solution.

They're decent. Sometimes, they take a while to get back to you. It depends on the severity.

We were using another solution. We switched to it because of its ease of use, ease of deployment, and cost.

Its setup is of medium complexity. It depends on what you're setting up. Some of the things are easy, and some of the things are difficult. For example, setting up infrastructure as code with Terraform is difficult.

It is comparable if you add in the price structure to an on-prem solution.

On the DevOps side, make sure you know what you're doing for security before you implement it. Make sure it is secure.

I would rate it an eight out of 10.

AWS is deployed into a public cloud. We have five lines and everything is autotomized. We are using several AWS solutions, including Containers, Pierre, Stargate, and Lambda. We have several projects in production, but I can't disclose more details because it's confidential. 

AWS is easier to implement than other solutions, and it's more reliable. 

It would be helpful for us if we could easily integrate Oracle RDS with AWS. That would work well with the solutions we have in place.

AWS is stable.

We can quickly add resources with AWS when necessary. Our company currently has 200 users working with AWS.

Amazon support could be better.

Deploying AWS is easy. The amount of time it takes depends on the application. I couldn't give a precise estimate of the number of minutes. We have four engineers to manage and maintain the solution.

We pay about $20,000 per month, and the license is all-inclusive. 

We are compared AWS with Azure and IBM Cloud, but in the end, we decided to work with AWS.

I rate Amazon AWS 10 out of 10. For me, it's perfect. AWS is effortless to configure and has high availability. 

The scalability and security of Amazon AWS are the most valuable features.

There are multiple operational and administrative services on AWS, I am expecting to see an integrated single platform of all the services so that it will be easier for the administrators to monitor and manage.

We are resellers of the production services of AWS. I have been working with Amazon AWS for almost 8 years.

The AWS products are stable.

The environment is stable. Every time a new feature is introduced, it advances the capabilities. Once the product is deployed, you can scale up easily.

Technical support has been very good.

The initial set up of AWS is easy and not complex.

The pricing is reasonable and comparable to similar services when run on-premise.

All the services and features provided by AWS are good. They are always improving their features.

I recommend implementing the products on Amazon Web Services. It is a stable environment and mature cloud platform. I would rate the product an 8 out of 10.

While I cannot say for certain, I believe that we are using the latest version. 

We primarily use the solution to rent servers for storing certain commercial applications.

I especially like the flexibility and scalability of the solution. It is totally scalable. 

While feasible, custom configuration will be more time consuming than standard, although we have not encountered many instances which required us to seek support or advice.

I believe we have been using Amazon AWS for more than 10 years.

The solution is absolutely stable. This is one of its best features. 

The solution is absolutely scalable. 

Amazon allows us to scale up and then down, something important to one of our customers who was in need of temporary increases in the throughput provided to the servers. This allowed us to meet the client's needs for the days or weeks that they required more dynamically located servers, after which we were able to scale down. This we were able to do through Amazon. This was difficult to accomplish beforehand, as the client had private servers for which he was forced to buy machines which he would subsequently keep. 

I cannot comment on Amazon's technical support, as we have not made use of it. 

We did use other solutions prior to Amazon AWS. We made use of local service and dealt with projects involving Google and Microsoft. We also used Microsoft Azure. 

Not long ago  we used Microsoft Azure, though this is necessary with some of our projects. We have different projects which vary with the customer's specifications. Some utilize Azure, although most require the use of Amazon. 

When comparing Microsoft Azure with Amazon AWS, I do not see much disparity. It really comes down to a business choice. If the customer is familiar with Microsoft, then the testing team maintaining the product will need to be acquainted with it as well and its ongoing use is required. Similarly, Amazon will continue to be employed if this is already the case. As such, the difference betwen the solutions does not come down to considerations of a technical nature as they are largely similar. The primary consideration is one of business, the use of one solution and provider over another. 

When it comes to standard configuration, the installation is quick, usually taking one or two days to complete. Custom configuration, while feasible, takes somewhat longer. So far, we have not had many instances in which we required support or advice concerning custom configurations. 

The technical team would be in a better position than I to address any technical issues involved in the setup. From my perspective as a project manager, I feel what we have to be sufficiently good. There is much advertising, information on the advantages of the product and guides available. 

Installation was carried out by our own internal integration team, not externally outsourced. I did not handle it myself. It was done by a team specialist. 

The technical team responsible for the deployment consists primarily of engineers. 

I cannot comment on whether we have seen an ROI, return on investment, as I do not possess this information.

The licensing cost varies with the project involved. Certain projects run around $6,000 per month, some less and others more. We handled many projects, each with its own complexities and specifications. The price ranges of the licenses varies with the complexity of the project. 

Broadly speaking, there is a need to rely on specialists for properly setting up one's accounts and addressing his needs. This is not specific to Amazon, however, but is something prevalent with all providers.

I have assumed the role of both customer and integrator. In the past, I worked as a project manager with different projects employing Amazon products, services and software. 

For the most part, the solutions I used have been public, not private, such as AWS cloud. 

The number of users of the solution varies with the individual project. This can range from 20 to 200 to 500 users. 

Our teams have undertaken every role, be them architecture, development, design or testing. They are all internally integrated. 

I am a fan of Amazon products and generally recommend them to others. Of course, we employ Azure and Google products when the customer specifically requests these. 

Since all products have room for improvement, even when this is not apparent to me, I rate Amazon AWS as a nine out of ten.

Our primary use case of AWS, for most projects, is for hosting on AWS and developing locally, as well as testing some AWS environments. We are mostly using this platform from a developer point of view. AWS is our cloud platform by choice. 

One of the most valuable things about it, besides the stability, is that you can forget about infrastructure because you're just doing it on AWS. I remember the times before AWS and other cloud solutions existed, and it was a huge pain to get real hardware, put it inside, configure everything, report everything, and do a scale. It was very, very difficult compared to how it is now. Not even just AWS, but what all these cloud providers are doing, I would say, is a huge advancement in technology. 

AWS could be improved with more integration, but I can see that they're developing these features and working very hard on their platform. 

I have been working with AWS for a few years. 

Amazon AWS is very stable. 

One of the major points for AWS is the scalability that comes with it. You can monitor it really well, and you can even adjust down, or sometimes up. What this technology allows is very nice. 

AWS is predominantly used in most of the projects that we have. In my organization, there are thousands of users who are using AWS. 

I have never personally contacted tech support. 

There isn't really an installation for AWS, but you will need certain certificates to download the interface. I generated some certificates, put them on my machine, and then used them to connect to AWS services. 

It depends on the project, but there is usually only one guy needed for deployment. For bigger, more complex platforms, you may need two or three guys to deploy AWS. 

I implemented AWS myself. 

You pay for a license, and that's how you get your own account. These are usually not individual licenses, but rather for a group of people. I think these licenses come at some volume, but I don't know many details about the licensing. 

I rate AWS a five out of ten, but it's mainly because I don't feel very experienced in AWS. I have gone to the console many times and seen many features that I have never used. I'm sure I can learn quickly, though, because there is a lot of information shared on the internet about how to use it—there are a lot of resources that you can use to learn, and there are a lot of features available on AWS. They're working very hard on their platform, and I can only see their usage growing in the future. 

I would certainly recommend AWS to others. 

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.