Amazon AWS Reviews

You can design and customize solutions with AWS. It has so many options, including storage, computing, database, notification, and messaging solutions. It depends on what the application team designs. 

I like AWS for its scalability, reliability, and availability, and it's much more mature and user-friendly compared to some other cloud providers. The learning curve and time for deployment are also shorter.

Amazon needs to develop better tools for troubleshooting network traffic, application insights, performance, and even some aspects of integration mapping. I'm hoping AWS implements something like Azure's Network Watcher and a log analytics solution where a can pull logs from various services and present them in a single dashboard. I want to summarize the performance and usage of every service and application.

All cloud solutions are scalable. It depends on the design, but most of them scale well. There are tens of thousands of users working on the solution.

Amazon technical support is great.

Deploying AWS could be straightforward or complicated depending on the use case. If it's a simple application, you can deploy it within a day. If it's very complex and your team isn't experienced, it can take months.

The amount of maintenance needed depends on your application and how you define support and maintenance. Some staff will handle things internally and others will be responsible for the cloud applications. 

I would say AWS is balanced. Cloud solutions are not cheap, and the ROI could vary widely according to your usage.

The cost depends on the usage and applications. If you're hosting thousands of applications, you'll be paying tens of thousands of dollars. In addition to usage fees, you have to factor in the costs of development teams and the staff you need to support the applications. These are the three costs you need to kind of calculate to decide on the budget.

I would rate AWS 7.5 out of 10. There are a lot of options in this space, and Microsoft is also good. We are evaluating the data on each. We would rate Azure close to eight, so they're both great solutions. 

This solution has many use cases. Amazon AWS offers a lot of services, all of which are useful. How useful this solution will be for you depends on how it fits your business. 

Amazon AWS is easy to use and in the past two years, I've never had any issues with scalability or stability. 

This solution could be improved by a better licensing model, especially for third-party software. Amazon AWS could also potentially be improved by more free storage, but I think that it's okay when compared to competitors' products. 

I have been using Amazon AWS for more than two or three years. 

This solution is stable. I haven't had any problems with stability in the past two years. 

This solution is cloud-based, so it's scalable. It is elastic, so as soon as you want to increase storage, you do so without any issues. There are about four thousand to five thousand people using AWS in my organization. 

I have contacted Amazon's technical support and it was quite an easy process. You will have a solution within 24 hours. 

I didn't use another fast cloud solution before Amazon AWS. 

The initial setup is easy and you don't really need to install anything. If you understand cloud solutions, you can easily do it yourself. 

I implemented myself, with an in-house team. 

We need to pay for everything. If someone is a personal user, they get one year free. But if you are using this as a professional or enterprise solution, then your company has to pay. The license pricing is comparable to that of competitors'. 

I rate Amazon AWS a nine out of ten, primarily because I have a background in Java. Someone else with more experience in Microsoft technologies would probably prefer Azure. I recommend AWS to anyone considering implementing it because it's easy to use. 

I am using it for enterprise warehousing. I am using it for web development, data warehousing, and also for building apps.

I am using its latest version. In terms of deployment, it is a platform as a service.

Macie is great. It is a service that makes recommendations on a data layer for cybersecurity. It is a great service.

Its elasticity is good, and I haven't come across any problems with it. So far, everything has been good.

One thing that Azure offers that I think is good is Migrate appliance. So, Azure has a migrate appliance that allows you to run against workloads to determine the cost, preparedness, and scalability. I haven't found a similar feature in AWS. That kind of service would be great on AWS too if you could point it to the data center.

I have been using this solution for well over five years.

I have not had any performance issues.

It's very easy to scale. Its elasticity is good. If you want to scale up or down, you can. You can scale out. There is no problem at all. That's one of the features that I like about it.

We have less than 50 people who are using this solution.

I've not used their tech support yet.

We didn't use a different solution previously. They're the first.

You need to know what you're doing. I know they're trying to make it easy. Some things are easy. Some things you have to know what you're doing.

It seems to be reasonable. It's the first one that I've used as a cloud platform, so they've set the benchmark for me, and now, I'm comparing everything else to them.

I would advise others to just plan out what they are looking for in terms of use cases. 

I would rate Amazon AWS an eight out of 10.

My primary use case is to set up an end-to-end application to deliver a business case involving data ingestion, processing, transformation, and checking, followed by outputs to other functions and processes in AWS and also to external systems.

We are using Step Functions as a core automation tool and it offers great power through its simplicity. It is quite easy to use, although there is a learning curve when using the Step Function scripts. Once mastered, after a week or so, the flows can be built quickly and effectively, allowing us to link a custom business process to multiple other AWS service automatically. 

That done, most business cases can be delivered easily and quickly, all in a serverless and cost-effective way. 

AWS has improved my organization by:

- saving us time, cost, and difficulty by allowing us to use serverless services

- enabling us to assemble complex applications with the minimum of boilerplate and plumbing

- allowing us to pay-as-we-go, so we can rapidly prototype, test, and then deploy to a production application setup

We can run advanced demos with our own data very quickly, showing potential clients the value of our services when we assemble apps for them.

We can show customers clear cost benefits and clearly effective solutions when assembling AWS services together. 

The security has great IAM, roles, and carefully partitioned permissions that allow us to fine-tune control across our applications. External intrusion attempts will never get past application boundaries, which increases trust.

The composition of apps has everything wrapped according to function and applications. We can assemble services as we go. This speeds delivery times by orders of magnitude.

The price forecasting and billing dashboard by service, with billing budgets and alerts, have helped us shut down resources that were accruing costs that we no longer needed, saving us money.

The service's power lies in its simplicity. It is great in that respect. 

The UI is constantly being improved and the billing dashboard has been improved.

Previously, we asked for more end-to-end workshops, examples, and tutorials and these have been added and improved. 

Recently, AWS has been adding improvements across services, documentation, tutorials and we have now got workshops with real-world scenarios which are tremendously useful It makes me a very happy user. 

AWS and the cloud is a space for constant learning and AWS has increased their output in that respect. 

I have been using AWS since 2014.

The solution is very stable. The only errors I encountered were my own. Some services took a few minutes to refresh and propagate across my environments, and once these had propagated, the solutions were rock solid.

The scalability is excellent. At no point have I hit scalability limits with AWS services and features. 

Customer service and tech support were excellent a few years ago when I needed them.

My general process is to explore and check options and run from a tutorial or AWS workshop. If this doesn't get me results, I then do a web search, and I generally find either further AWS docs or a specific example I can use to solve my issue. Within the last few years, my colleagues and I have been able to deliver as required. 

We did previously use a different solution when building AWS Lambda cloud functions. I could compare them directly with Azure Functions and Google Cloud and have found that the AWS Lambda solution is simpler, clearer, deploys quicker, and is generally much more simple and effective to use.

In terms of documentation, AWS is the clear leader. Their end-to-end examples and workshops are much more effective.

AWS services in many cases are deployed to AWS after being validated in Amazon.com's operations. This is evident in the ease-of-use and simplicity of many of the service features, and also in the excellent options offered for more complex services like AWS Forecast, where, for example, a checkbox and drop-down allows the user to add holidays for the country they work in when doing forecasts.

AWS has a stronger focus on business solutions than either GCP or Azure, and in many of the solutions, I have used. This is why in many cases I have switched from using other clouds, to AWS. 

The setup in AWS is a whole service in and of itself. To set up AWS applications, AWS offers a full service, CloudFormation, with some added features that allow us to automate the deployment of the full solution stack.

This makes setup complex, in that one must modify the CloudFormation template one requires and validate it. An external resource was required to check the templates. 

Once this is done, the full solution stacks are automatically deployed. 

I handled the initial setup in-house and by myself.

A recently deployed Step Function automation fulfilled all the needs of a workflow automation engine while remaining below the free operation per month, so we were able to deliver a fully automated application approval process without paying for any workflow automation engine license fees or any server hardware or infrastructure costs.

I would advise others to work from an architecture overview. 

Be aware of the very powerful schema-less data services in the cloud. They can help remove the need for data warehouses - e.g. multi-TB datasets - can be read, joined, queried and made to output daily reports within minutes, on temporary clusters, and that cost less than USD1000 per month. This is compared to the hundreds of thousands of USD for data warehouse licensing costs, plus the schema design time and ongoing DevOps they require.

Moving to serverless operations in the cloud frees up your people to deliver business services rather than spend days and days on administering data centers and the associated concerns that come with them.

I also looked at Azure and it was deemed less reliable than AWS as AWS has not had as many outages and uptime concerns as Azure has had of late. Azure Function Apps, Data Factory, Managed SQL.

Besides Azure, I looked at GCP and VMs, Cloud Functions, Speech-to-Text transcription, BigTable, and BigQuery.

Empower your in-house people to start building and running their workloads in AWS. 

Let them learn as they go. There are multiple online courses for a few dollars that can assist with specific, individual AWS services, as well as running through the AWS workshops. 

Incentivize AWS certifications. Involve your tech people with business solution prototyping. 

Tag your resources, name them well, and set budget thresholds. Assign people to tune the resources being used. Incentivize communications and publish the AWS services and features being used to deliver your business capabilities.

We use Amazon AWS to deploy our architecture.

The most valuable features are CodePipeline, CodeDeploy, CodeBuild, and CodeCommit. We use them to deliver our solution.

The services that we are using have frequent updates, at least twice a year. They provide a new version that has more capabilities or features that fit our process and procedures.

I am an integration specialist and Amazon AWS always seems to be a step ahead of the competition when it comes to the solutions integration abilities with its services.

EventBridge is a tool provided by AWS and it enables integration with the API gateway. We are using it as a solution to our projects and with our clients to integrate with external features, such as B2B or B2C. The Amazon API gateway integrates with EventBridge and other messaging layers. It is a highly integrated solution with those platforms.

I have been using this solution for approximately five years.

The solution is stable.

Amazon AWS has a very easy tool to scale in terms of scaling up and down. We have different options to do this operation and they are very useful.

The technical support has been helpful.

The setup of the solution is not so easy, it requires various skills to complete it. The whole implementation can take a month. However, different parts can take more or less time depending on the knowledge of the implementor.

The messaging layer, in general, is easy today than before when you had to create all the data centers around the world and create the steps to connect the data centers to each other. They have improved a lot over the year but they could still improve more.

Amazon AWS has pay-as-you-go options available.

It is important for people who want to use Amazon AWS to have a very good implementation strategy to make the migration. Amazon has provided some framework to help those wanting to start the migration process.

I rate Amazon AWS an eight out of ten.

We use the AWS Cloud service for storing company-related information.

The cloud-based infrastructure has several good products that people normally use.

We have had several issues with the products and services but as of now, there are no good alternatives.

I have been using Amazon AWS for the past seven years.

I use AWS several times each day, and we plan to continue using it.

We have 7,000 users on AWS.

The technical support and customer service are good.

I have also worked with Microsoft Azure and I find the initial setup of AWS to be easier.

The installation and initial setup are easy.

This is a subscription-based product.

This is not an expensive product but it would be an improvement if the price were cheaper. Google Cloud, for example, is cheaper.

This is definitely a product that I recommend.

I would rate this solution a nine out of ten.

We use Amazon AWS together with MuleSoft's CloudHub, because CloudHub is an extension of Amazon VPC. As part of that, when we set up the infrastructure and everything, we will be interacting with Amazon products. And with big customers, we have data in the private cloud and within that private cloud we have the MuleSoft CloudHub which is connected through the organization's private cloud to a specific geographical AWS public cloud. Regarding security, we also have a number of layers there, too.

As an example, we have seen approximately 300 ETFs developed for different areas, e.g. for United Arab Emirates and other customers. And the internal customers are also using AWS. All in all, there are approximately 10,000+ users who are using it, and things are going pretty well.

The reason I like AWS is that they have a large market share and a large presence. When it comes to our use case, a big positive is that MuleSoft and AWS are working together very well. So instead of competing against each other, they're meshing together.

There have been some issues in the past when it comes to file integrations in AWS's cloud products. However, there are now alternative solutions out there that are helping to integrate them all.

One thing is that sometimes it becomes a problem when troubleshooting our tools because when you have some things local and some things remote on a foreign server, it can get complicated. We find that sometimes it's a challenge to gather the necessary information from logs and such because you need the proper agreement to capture those details. 

In the future, I would like to see Amazon move more into local clouds, by capturing more of the small market. Nowadays, spending a lot of money is not on the list of priorities for many companies, especially considering what's going on in the world. We want to leverage whatever amount is available and still get all the benefits of new AWS cloud offerings.

I have been using Amazon AWS for a couple of years now. 

The infrastructure of AWS is very stable.

AWS is very scalable. 

I've never worked with technical support personally because we have a lot of network engineers to handle that. 

When it comes to pricing, not all applications require that much performance. That's the reason why other cloud markets are also catching up, because the two predominantly high-performance platforms, AWS and GCP, are almost the same.

Looking at the primary market for AWS, I see that there's a lot of customers who have only mid-level performance requirements, because you will have all these normal applications such as online auction websites, gaming applications, voice applications, and so on. These are not, for example, large monitoring applications, financial independents, or brick and mortar companies. So AWS caters to about 40% of the market when it comes to general applications.

As it happens, in many cases, you simply don't need the high-performance offerings from AWS, nor the innovative products from Google Cloud Platform, which can come with large price tags.

Overall, AWS is pretty good and I can definitely recommend it because it's a proven product. When you're solving big problems, you want — first and foremost — proven infrastructure, technology, tools, and mechanisms. Then slowly, you'll be able to remove dependencies by moving to others as needed. So for project initiation and everything, you get to rely on something which is rock solid and proven in the industry with a long track record.

I know AWS can be an expensive option, but it doesn't have to be out of budget if you choose the appropriate level of product for your performance requirements. They can provide high-performance computing resources, while at the same time catering to the mid-level market with lower performance offerings. 

Previously, in the initial days of AWS, back in 2005/2006, there were some concerns about security and such things, but nowadays there is not much to worry about because a lot of those concerns have been taken care of. Recently, there has been another shift in attitude towards them, because not everybody is a big fan of public cloud because of what is happening in the world with respect to data privacy and everything.

Regardless, the three big names of Microsoft, Google, and AWS are really grabbing the market, and IBM is also catching up well. Because of the data privacy concerns, however, I do see some customization in European countries who are interested in interacting with the cloud market at a more local level.

I would rate Amazon AWS an eight 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.