Amazon AWS Reviews

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 use Amazon AWS as an IaaS Cloud for our e-commerce sites.

Because of the stability and scalability AWS provides, our team can now focus on how to engage and delight our customers instead of constantly being fixing production issues.

We have not had any problems at all. 

In the 4 years that we have been using  IaaS services from Amazon, we have not had any issues.

It's a great IaaS cloud. They are the leaders. No cloud provider can match Amazon right now.

Other providers are improving year over year, but Amazon is still ahead at least two years.

Working with AWS requieres your organization to invest in training your team to better use and take advantaje of all that AWS has to offer.

We have been using this solution for 4 years.

AWS provides without a doubt the most mature and stable IaaS cloud in the market.

We have thousands of customers who are going to our websites to purchase goods and it takes a matter of minutes to scale the infrastructure both horizontally or vertically.

Great services, assistance and response time from the AWS team

It depends on how complex is the architecture of the solution to be deployed, in our case because Magento is sort of "native" for AWS it has been straightforward.

We implement through a vendor team specialized implementing and managing Magento on AWS

I would rate Amazon AWS a ten out of ten.

I am an AWS Certified Solution Architect Associate as well as a Certified Cloud Practitioner, and I am currently pursuing the development specialty. I mainly use AWS to develop cloud solutions for clients.

As a Solution Architect Associate with focus on development, my clients typically ask me to help them personalize AWS services as they pertain to the client's business. For example, I will often work with AWS SQS queues, ETL jobs, APIs and storage, and other services offered by AWS in the cloud.

Generally, my work has more to do with development rather than architecture, and other AWS services that I use include EC2, S3, Lambda, API Gateway, Amazon Connect, Alexa, DynamoDB, ECS, and EKS.

My daily activities are essentially focused around implementing AWS services for clients who want to migrate their existing computing infrastructure to the cloud. For example, if a data center is on-premise, our solution is to bring that data center to the cloud. This kind of migration includes moving all the applications that a company uses to the cloud in progressive steps. We also work to enhance their applications with extra code and the advanced features that the AWS cloud offers, like Lambda for instance. 

The clients that I work with — which include large organizations like universities — also use cloud providers other than AWS, including 3Cloud, Google Cloud Platform, and Microsoft Azure. I, however, specialize only in AWS and Azure.

Here is an example of how AWS has helped one of our clients: With Amazon Connect, we can track all activity in the past and in real-time, so we can know how many calls are in progress and if there are any problems. With a student payment system, for example, if a student has a problem because their credit card was rejected, we're able to trigger an SMS notification to somebody so they can contact the student to make a payment with a different form.

The university is thus able to offer a streamlined payment service with automatic fallback options (e.g. receiving payments with a card reader in person) and all of this is automated thanks to AWS Lambda, which lets us handle customized metrics automatically and in real time.

The AWS feature that I most enjoy is Lambda functions. I primarily use serverless components because they allow you to process things without having to compromise on resources like when running EC2 instances or virtual machines. With minimal effort, you can scale up an unlimited number of processes, even concurrently, to process things. I frequently work with web APIs, so I use Lambda a lot in this area.

Recently we had a long conversation about functionality that is missing in Alexa — in Mexico, specifically. Alexa for Business is a service and platform that Americans can use to make a call to an Amazon Echo device or a telephone via the app. But in Mexico, we are not allowed to use that technology. This is a significant disadvantage of AWS for those living in Mexico.

I also think that Amazon Rekognition could be improved. For example, I have used Rekognition to label things like trucks, buses, etc. Then we put a camera in front of a bus, so that we can send notifications if the bus driver overtakes another car on the wrong side of the road. However, it seems that Rekognition's machine learning doesn't yet have the capabilities needed to make this kind of labeling and recognition system work properly. Thus, we've had to resort to alternative solutions.

And in terms of how easy it is to learn, Amazon doesn't have the most friendly educational platform. It is very obtuse, in fact. I have wasted a lot of time and effort studying through the official channels, so now I mostly use Udemy courses instead. They are very practical and much simpler, but I would still prefer to learn from the official educational platform if it were improved.

I have been using AWS for about five years now. 

The stability of AWS is very good. 

I work with AWS Lambda all the time and I never have any problems with scaling. Recently, Lambda launched a new billing system, which is cost per millisecond. Before, we would get cost per hundred milliseconds, as the minimum, and now if we use only 10 milliseconds, then the cost for 10 milliseconds is exactly how much we have to pay. So that's great, because now I can scale my functions with a precise cost calculation.

I currently have several issues with Amazon Connect because we can only obtain two telephone numbers by default. With this scenario, there was a very difficult process to let Amazon know that we are not working for ourselves in our console, and that we offer our services as a third party, in terms of SaaS and IaaS, to our customers.

I'm not directly involved in the creation of accounts, and I just use them once they are created on the company or client's side. But in Amazon Connect, when we needed to add more users, the time response from Amazon was two or three days. We are subscribed to the developer support plan, and I think two or three days is a lot of time.

Either my company or the clients usually have the console already set up when I start work on it, so there's not much in the way of setup that I can comment on.

With the AWS projects that I lead for clients, it's basically just me that works on deployment, implementation, and maintenance.

When it comes to professional certification in AWS, I implore others to study hard before your exams because $300 is a painful waste of money if you fail.

With AWS products, there is a steep learning curve and I think there are so many aspects because it is really an ecosystem. If you are committed to reducing costs, or increasing performance, or optimizing in any manner, you have to know the solution really well.

I think the best way to achieve this is by experience, but if you don't have any experience, studying hard is the next best thing to do.

The two alternatives I've considered are Microsoft Azure and Google Cloud Platform. However, because I am only certified in AWS, I don't know the difference between, for example, Microsoft functions in Azure and AWS Lambda functions in a commercial sense.

In a technical sense, though, AWS seems to be more comprehensive in the programming languages that it supports. For example, with AWS Lambda functions I can program in Python, PHP, Go, and many others, but with functions in Azure, you are limited to fewer options.

To our client, it's neither here nor there, because they're typically not involved in the actual development, but if you use Azure architecture then you're going to be limited to the programming languages that Microsoft supports.

If you want to take advantage of all the benefits that AWS offers, then it's best to take the time to learn how the entire ecosystem, and each part of it, works. 

I would rate Amazon AWS a nine out of ten.

Our primary use case for this solution is commercial cloud computing, analytics, and storage.

We have seen an improvement in our infrastructure, as the code makes it very easy to deploy quickly to AWS.

The features that we have found most valuable are IAM, KMS, and Security Groups for customizable security. Cloud formation for well-defined blueprints is also useful.

An easier way to determine estimated costs quickly would be helpful.

We do have quite a lot of AWS deployments and clients in certain countries.

We use it for spinning up environments, using infrastructure as code. We use it for disaster recovery and high availability for creating BMs for testing. Mainly on the service side, we use it for setting up environments and spinning up environments.

The monitoring is the most valuable aspect of the product.

Technical support is available if you need it.

The solution is stable.

The scalability is okay. It's similar to what you would get with Azure. 

The interface needs a bit of work. It's not intuitive.

The solution's initial setup can be complex. 

I've been using AWS for about 15 years. It's been a very long time. 

The stability is fine. I haven't had issues with crashing or bugs or glitches. 

The solution's scalability is pretty good. These solutions are pretty well known for not being able to scale well. They behave very differently at scale. I wouldn't say it's any better or worse than Azure is; it's probably on par.

Internally, we have about 500 people using the solution right now. 

I have never used technical support myself, although it's my understanding that our team does from time to time. We do all the first line ourselves. Anything that escalates to the third line, we have contracts in place to help us get assistance.

I found the initial setup to be pretty complex. It's just getting more and more complex, with the infrastructure as CodePipelines and that sort of thing. On a scale of one to five, one being the worst and five being the best in terms of complexity, I'd say it's a three.

I have no idea what the operational side does in terms of maintenance. It's not an aspect that falls under my responsibilities. 

I don't handle the licensing side of things and therefore cannot comment on the price of the solution.

We also looked at Azure DevOps.

I'm a customer and an end-user.

We use various deployments, including on-premises, public, private, and hybrid clouds. The deployment is dependent on the customer, the solution, and the service level agreements that we have. We use all of those models. We make our choice based on the requirement.

I'd advise potential new users to actually do a shootout between the different products based on your use case and choose the right one.

I would rate the solution seven out of ten. I'd rate it higher, however, the UI needs improvement first.

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.

My primary use case was as a place to migrate legacy systems.

AWS has reduced our costs and maintenance requirements. It also allows us to control our load in peak times and automatically increases or decreases your capacity as required. 

The features I have found most valuable are S3 buckets and Lambda services.

An area for improvement would be API creation - a lot of tools are provided, but there can be issues with integrating them. There is also a cost underlay, in that at the end of the day, some costs are not in the picture, so AWS needs to improve its costing toolset.

I have been using this solution for two years.

The stability of AWS has improved over time and can now be well managed.

This solution is scalable to any limit.

I previously used Rackspace Openstack but switched because it required more manpower than AWS, and AWS is more cost-effective and tolerant.

The setup was somewhat complex. It was done in three phases over a year.

This solution reduced our overhead cost by 30-40%.

Technical support is expensive to use.

I evaluated Oracle Cloud, but it was more complex to use and provided a smaller toolset than AWS.

This solution is one of the top tools available for legacy migration. I would rate this solution as eight out of ten.

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.