Amazon AWS Reviews

Customers can use it for the web-based management of the product. We also store and retrieve data for their network connections. Also, we use the AI/ML portion called SageMaker to calibrate the algorithms and basically drive automation into the customer's use case. Typically our use cases are in hotels, public transportation, convention centers - anywhere where you are sharing internet connections. For example, hotels, conventions centers - anything where you might have people jockeying for a shared internet connection with possible oversubscription or network congestion. We also have enterprise Work-From-Home users due to the pandemic and they need to continue to provide access to those remotely into their own data center, corporate network, and public cloud.

Flexible fast way to bring up servers and network infrastructure with variable costs.

We use the AI/ML Sagemaker to help us build models. 

We use several feature services on AWS, including Lambda, S3 database, RDS database, Alexa Voice Services and Cognito Gateway. They are all excellent in terms of offering great functionality.

They're pretty good about taking customer feedback and are generally able to productize the requested feature.

The initial setup is straightforward, especially if using Lightsail to start.

The solution scales very nicely.

The stability is good with a large number of Availability Zones WW.

Technical support is helpful and responsive but you must pay for a tiered support plan to ensure response.

The pricing is something you have to watch. You really have to constantly optimize your costs for instance, storage, IP's and things like that. That can become a job in itself to manage just from a budgeting standpoint if you are a moderate to heavy user. However, that's true for Azure or GCP as well. 

If they did more automation on alerting you to cheaper pricing or automated volume pricing based on time/use or even porting you on to on-demand instances automatically, that would be kind of cool. That's something that I haven't seen yet. They could just automatically optimize for your workflow and put you onto a lower-priced instance to save you money.  you Maybe allow you to pick an economy setting, or a performance setting, by time of day etc. something like that. That would be great. Then you don't have to think about it as much as you do in the current iteration.

It would be interesting to have a cost optimized accounting service so that they would come in and help remediate and give suggestions on how to cut costs. I know it's probably antithetical to their bottom line, but that said, obviously, if you take the high road there, you're going to probably keep people, and keep people from switching for lower costs. A lot of times, they can architect a better solution or a similar solution for lower cost and that would lead to customer retention--or maybe a longer term retention discount if youve stayed with them for awhile. That would be helpful if they had that. They have solutions architects, to consult however, they're usually just trying to design the best technical solution as opposed to the most cost-optimized solution. 

We've been using the solution for about four years at this point.

Services are pretty good stability-wise. They've got great redundancy. The one thing I would tweak them is when you're within the region or zone, they make it more difficult for you to do redundant zones, without carrying the IP addresses over seamlessly. That is a little bit of a sticking point, so you could have remote redundancy with the addressing there with it even outside of the AZ's. That would be a lot easier than having to go through the programming of it. 

The scalability is great. You can go from one small instance to GPU, very powerful instances, clusters. There is not any problem with scaling if you can afford it. If you've got the volume, you certainly can scale.

We have maybe a dozen or so customers that will use the product and then access the UI and the management system through the cloud. Then, of course, as developers, we have about 10 to 25 employees that have to use it to varying degrees to support the customers and do development.

I like the tech support. It varies by level in that you've got to pay more to get the immediate response time. Generally, I'd say it's pretty good. Literally phone rings minutes after you log a trouble ticket. They're usually pretty good about escalations and helping. Out of AWS, Azure, and GCP, I'd give them the number two ranking. Azure has good support, however, it's expensive. GCP probably is number three I'd say, of the top three.

We also occasionally use the Google Cloud Platform and Azure, although we tend to use AWS the most. GCP is a little bit cheaper overall, however, then you've got the cost of management that is typically a person so you do need to invest in that. 

We started with Amazon and we've pretty much stayed with them. We've switched to Google and done some work on Azure that was customer driven, however, pretty much our prime public cloud has been AWS.

The initial setup is not overly complex. It's pretty straightforward. 

It's pretty easy to get started. However, you do have to make an investment and learn the different cloud platform's nomenclature. Most of our guys now are cloud practitioners and architects now that they've taken the training. We had to bite the bullet even though we've been users for four years. There is an investment that you have to make on the OPEX side. That's the case for any of the public clouds. Although once you know one, you can pretty much pick up the other ones pretty quickly.

In-house

Have to watch price/billing creep, but there are tools to watch and monitor your usage and billing.  

Azure. GCP

We're a software development group building specialty LAN/WAN optimization solutions, so we don't use a lot of canned products per se.

We do tend to sue reasonably new software versions of the OS...whatever is the latest LTS selections.

If you already have your workload ready, that's helpful, as you can actually trial it under a free tier and then see what the cost is, and extrapolate what the ongoing cost is. In the end, that's what gets you. Being able to do some benchmark testing on how much it's going to cost for your particular workflow across the three public clouds is definitely something you probably want to do. Especially if you're going to scale, as, obviously, it can suddenly creep up to not just tens or hundreds of dollars a month, but thousands a month, depending upon what you're doing. I definitely would recommend doing some reference testing of your workflows before deciding on a solution.

I'd rate the solution at an eight out of ten. They're pretty solid. You've got all the services that you can imagine, and then some. There's a very broad breadth of products and services. We haven't had too many SLA issues for recovery or downtime. Maybe we've just been lucky or good so far...

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.

General use cases of AWS are for those needing a managed cloud instance without the bulk costs for a legacy server. We are customers of Amazon and I'm the technology manager. 

The benefit to the company is immense financial savings and the fact that you're able to see your monthly costs before buying anything. The AWS monthly calculator enables you to select your database, servers, volumes, and see how much everything will cost on a monthly basis. You can figure out what you'll be paying, so it enables a comparison; it's usually a third to half the cost of using an on-prem system.

Amazon is easy to upgrade, easy to expand storage and change your EC2 types. Each of those things usually takes at most five minutes to do, whereas on a legacy system you have to actually buy a new system or new hardware and have downtime for installation. Even then it may not be configured the same way and you might end up with a widespread outage. The advantage of using AWS is that all the testing's been done so you have proof that it works. We still do a cursory check, but they don't put anything out there that hasn't been vetted. Plus all the Atlassian tools are on AWS as well. The cloud instances they provide have a very robust network because there are over 160,000 companies that use the tools. Backups are really easy to access as are the automated backups of the VMs and the volumes. We're able to create a new volume from a backup in about two minutes, attach it to the server and view the data side by side to compare the old to the new. It takes 10 minutes total to get all the access needed.

I've had very positive experiences with AWS and it's gotten a lot better over time with their improved interfaces. Everything's all interconnected now and within its own framework. We pull in other tools to the OS such as Docker but AWS provides tools like Yum that enable quick installation of things. It's typically part of the OS. 

While the IAM security key is very secure, they only give you one chance to capture your key. If I'm already logged in and have an email address online, it would be better if it were sent in an encrypted manner to email so that you don't lose the key. I might create the IAM and then perhaps forget to capture it off the screen and then when I do need it, I realize I don't have it and have to create another profile.

I've been using this solution for about 12 years. 

I haven't had any problem with stability. We do multiple zone backups and multiple zone data and we haven't had any problems or slowdowns. We've had dealings with countries like India, where things are generally slower but with AWS there haven't been any issues. There's no wait time.  

Scalability is good. I like the EFS expandable storage because it expands and contracts, you don't have to do anything with it and it's really inexpensive. Somebody may use it for temporary storage where they drop a terabyte of data that they need to give to a customer and then it shrinks back down when they're done with it. It expands and contracts as needed and that's also reflected in the cost.

The technical support is very fast, very efficient and very knowledgeable. Even when I've asked questions and they didn't know the answers, they were able to find someone within 15 minutes that was able to help.

The initial setup is pretty straightforward. The main thing is getting the security protocols set up in the proper order, otherwise it won't work. You have to go in and set up the main group and make sure to share it to your database. They've improved their documentation and it's a lot better but still lacks a little in some areas. If you've deployed before, setup takes a couple of hours, otherwise it might take up to a day. It's a lot faster on cloud; if you're working on-prem you have to jump through a lot of hoops because each team has its own security. 

They have scripting tools on AWS which allow you to set up your framework and you can use it as a template. We use an AWS architect for implementation and to make sure all the security is set up. And then we have a DevOps team that manages the OS updates. That's a team of three handling over 100 servers, VMs basically. Once a month they do the non-production patching with the production patching the following week. 

Licensing fees are only applicable if you're using Red Hat or an Oracle database. You have to pay for both of those. If you're using Postgres or MySQL, there are no costs for the actual database application. There are no fees for individuals using Oracle Java, but businesses pay a license. We use an OpenJDK that is vetted by Atlassian so if you don't want to buy Java you can use the OpenJDK.

My advice would be to do some homework, read as much as you can about the setup before you dive in. If you take an hour to review the setup and then put together your own process so you know all the steps required and you use a checklist, it simplifies things. Have some kind of system, whether it's a spreadsheet or a Confluence page where you're documenting the steps and keeping track of where you're at. 

Whenever I'm asked to do something, I can find a tool on AWS that I can vet for our customers, and for that reason, I rate Amazon AWS 10 out of 10. 

I work on the AWS - the AWS Lambda portions of the Amazon cloud.

It's a good cloud for beginners.

There is no downtime. The solution is reliable. 

Deploying resources on AWS is fairly easy and more secure than any other cloud. That's what our initial impressions are.

Amazon AWS is very lame in the sense that it's into some sort of beginner stage stuff. Most of our customers prefer Azure Cloud over AWS. Azure has lots of features, especially on the identity side. It has integration with the social media built-in plugins. It has integration with a plethora of applications. It has that sort of an ecosystem. Amazon, on the other hand, on most of the integration side, there are applications in Java or there are customer-specific applications and therefore we have to do the development. This is in contrast to Microsoft Azure, where we get the ready-made plugins.

Our experience is AWS should be preferred for the financial sector where there are not very many changes. It's more minimal changes that come into play on the implementation side. We recommend Microsoft Cloud to most of our customers, especially when they want quick implementation and there are a plethora of things to integrate the cloud with. 

With AWS, we feel it has a lot of improvement areas. It's a good cloud, however, if I compare it with Azure, Azure is more of a feature-rich cloud. 

The initial setup can be a bit difficult. 

I expect AWS to come up with more identity features. They should have a very robust identity federation system, like what Azure and maybe Google Cloud are offering. Identity has some sub-verticals, like single sign-on and multifactor authentication and federation with some on-premise systems like ADFS servers or LDAP directories. Those things are very difficult to configure in AWS. AWS should come up with more connectors and more robust and user-friendly IdAM systems so that we can reduce time. We should be able to implement our projects faster.

I've been using the solution for two to two and a half years at this point. 

In terms of stability, the first impression is whatever services we have provisioned in the AWS cloud, we've never caught any issues where we needed to reach out to the Amazon support team. There is no downtime, for example. There are no application crashes. We don't need to plan any high availability or disaster recovery for any of our servers. In regards to that, Amazon is doing a very good job of offering good performance and reliability.

We've never needed to solicit the help of Amazon technical support, In contrast, in the case of Microsoft, we definitely needed their help.

Right now we are working on three clouds actually, Azure, AWS, and Google and we have SAP Cloud in the pipeline as well.

The initial setup is kind of difficult. It's not just users going to Amazon and buying it from an Amazon account. You have to do a lot of configurations.

On a scale of one to five, one being easy and five being hard, I'd rate the implementation process at a four. 

We don't buy the clouds. We give them to the customers and our customers buy the tenants, the subscriptions. They are aware of the license documents with Amazon and the other cloud vendors. Once we have the subscription of a customer, we do the technical implementation.

We don't get into procurement or subscription renewals or product updates or anything like that. We are more on the technical side.

We were doing some research on Oracle Cloud. Whether we are going to build the practice on Oracle Cloud or not, that's the call that has to be taken by my leadership. 

My job role is as a Cloud Security Architect. I prepare solutions and I sell them to the customers. My work primarily involves working on identity systems. I primarily work on the identity federation side. You have identities and disparate sources, and we prefer to have a single identity source using federations and then we prepare solutions around it and sell them to our customers. Those kinds of solutions are the ones I work in.

My advice for first-time users is, if you wish to migrate your private data center to a private cloud where you have servers like VPN servers, radio servers, you have servers for your own applications, whether it's Windows, Linux, Unix, or ADFS, it's better to go for an AWS cloud. However, if you are looking for identity Federation or identity provisioning, then you need to go for a Microsoft Cloud. 

I'll rate AWS  at a seven out of ten due to the fact that it's very secure. It has very good migration categories for the on-premises servers and applications to the AWS private cloud. I can't rate it ten out of ten due to the lack of IdAM features I've seen, and AWS has less of a user base as it's not very user-friendly. This is where Azure scores a lot higher for me. It's very user-friendly and it's feature-rich, actually. If AWS can develop a more feature-rich offering, it will be on par with Azure.

We build business applications for our customers using Amazon AWS in 15 different industries.

Many of my customers use many cloud services together.

The most valuable features of Amazon AWS are the high level of capabilities, cloud-native environment, developer-friendly, intuitive interface, and automation. The solution overall is easy to learn from the resources available.

The customization could improve. However, it depends on the customization needed. 

To enhance its capabilities, Amazon AWS should improve its integration with other digital security platforms and solutions, especially those used by companies in domains, such as banking, financial services, and insurance. While Amazon AWS has its own solution, there are many other initial vendor companies that perform exceptionally well. Therefore, it is crucial for Amazon AWS to have better integration with those platforms and solutions, including how to host and integrate them with the rest of the Amazon AWS services. Although Amazon AWS has its strengths, it doesn't always work seamlessly for customers, making it a significant obstacle to migrating applications to Amazon AWS. Rather than focusing on developing new features, Amazon AWS could better serve its customers by supporting these existing solutions in the digital security space.

There are many excellent encryption solutions available, along with many other solutions. By supporting these solutions and offering easy integration, Amazon AWS can create a win-win situation for its customers.

I have been using Amazon AWS for approximately seven years.

When you have complex deployments, such as with more than two availability zones, there are reliability, and resiliency options that are complex to implement and expensive. Providing stability or more complex deployments is possible, but very expensive.

I rate the stability of Amazon AWS a nine out of ten.

We have more than 50,000 users using this solution in my organization. Everyone in our company is using the solution.

The solution is highly scalable.

I rate the scalability of Amazon AWS a ten out of ten.

The support provided by Amazon AWS is highly responsive. We have a strong alliance with Amazon AWS, and we regularly interact with their teams. They conduct knowledge-sharing sessions for us and keep us informed about new features. They are always available to support us. They have helped us from the inception phase of any large engagement up to providing help in troubleshooting some problems. They are extremely helpful.

I rate the support of Amazon AWS a ten out of ten.

Positive

I have worked with Google Cloud Services and Microsoft Azure.

Amazon AWS is known for building many industry platforms, and companies often look to all three hyper scalers to help them build such platforms on Amazon AWS. Large consortia of companies collaborate on such initiatives. However, Google and Azure are more interested in partnering with and supporting industry-level consortiums and technology initiatives, while Amazon AMS sees it more as an engineering capability and expects developers to build everything from the ground up. Therefore, Amazon AMS may need to adjust its approach slightly in comparison to its competitors.

The simplicity of Amazon AWS depends on the engineering processes implemented by the client's organization. Setting up these processes may take some time, but the AWS SDK provided by Amazon is helpful. Moreover, integration with other tooling is also necessary.

Once the processes and platforms are configured, the execution becomes automatic. This has been successfully accomplished in many engagements where pipelines are run for tasks, such as provisioning new infrastructure and making multiple releases.

For a business with a small deployment and with minor features needed the process of implementation can take 30 minutes and in some instances less than 15 minutes. However, if it's a large release with multiple features, including verifications, it can take up to one and a half hours maximum. The more features added the longer the implementation will take.

In comparison to Google Cloud Platform and Microsoft Azure, the database offered by Amazon AWS is relatively expensive. However, the database also offers rich features.

I rate the price of Amazon AWS a six out of ten.

If you compare Amazon AWS with other hyper scalers, such as Microsoft Azure and Google Cloud Platform, Amazon AWS is the most sophisticated cloud development platform.

The amount of people for the maintenance of the solution depends on the engagement we have with our customers. Some of our customers are sophisticated with modern infrastructure and can handle most of the maintenance themself.

The engineering team responsible for development also handles maintenance, upgrades, and support without any differentiation. However, some customers still follow an older mindset, where a separate ops team is responsible for platform maintenance and operations.

One approach is to have a centralized model where a team of 20-30 members manages all the applications, including operations and maintenance. Alternatively, a distributed model may be used, where four or five different teams manage different aspects. However, on average, the team size for the entire IT organization is typically around 20-30 people.

I strongly recommend this solution to others.

I rate Amazon AWS an eight out of ten.

I gave my rating of eight because the price of the feature is more expensive than the competitors.

I use Amazon AWS to host services for my clients, as well as creating SMTP services for them. These are the main two use cases. AWS offers a wide range of services, but I do not use them all.

AWS has a lot of flexibility, which is great.

Recently tried the boot on the desktop, which is where you create a virtual desktop, on a laptop for example. You provide this, and you can use a laptop on the cloud and have everything safe, without having to purchase an expensive laptop.

When I tried with another company, from Azure, which uses the same thing, that with the boot as desktop they had some work needed to make some changes to the AWS desktop. They are not as flexible or powerful as a platform as Azure on this subject.

Previously, they had great VoIP software that they used in AWS, and when I created an account, they didn't have the option to assign too many numbers, local numbers, that could be used for hosting.

In terms of improvement, they should try to give more emphasis to the VoIP system.

I have been working with Amazon AWS for the last two years.

You can deploy and create any number of virtual machines to meet your needs.

Amazon AWS is very stable.

When I'm setting up SMTP servers for clients. They use SMTP as the main platform, but for example, on their CRM, and to be honest, I never go back to that to check for any issues from the day one that I finish the task and provide everything to the CRM developers to proceed with the integration.

We have over 60 companies in our portfolio, and I would estimate that half of them use AWS services.

Going through the chats has left me a little disappointed. It's taking far too long, and I have to come back with questions. The reason could be that they have too many departments internally, so they assign a ticket from one department to another, and it takes a long time to complete the task and provide an accurate solution.

I'm using both Microsoft Azure and AWS at the same time.

I am a Microsoft Azure certified technician, and some of my clients have asked me about some potential within the product. Based on my research, I discovered that this project can be easily designed using AWS rather than Microsoft Azure. This is why I'm learning more about AWS. It is similar to that of Microsoft Azure, and I'm using it, that we can, say, shut down Microsoft Azure completely and then send all of my clients to AWS.

Half of them are AWS, half are Microsoft Azure, and sometimes there are internal IT departments, which need to follow this path, to create the architecture on Microsoft Azure or AWS based on their architecture.

They are difficult to set up. Before you can start using AWS, you must first read the documentation and learn a lot about it.

I would rate the initial setup a three out of five.

It is not very easy, and difficult to complete some of the tasks.

They have a pay-as-you-go subscription. You pay only for the time you use the service. By service, I mean that they are not frequently used by clients. It's the best idea because they are very expensive to them because if it's a small company and you have the option of pay as you go as a solution, it would be less expensive, and better for the company in terms of saving money.

However, if some large clients, for example, use AWS as a hosting provider and compare their prices with other hosting providers, other hosting providers are more affordable. 

I believe that a pay-as-you-go solution is very inexpensive, but not for monthly or fixed prices.

I am a partner and reseller.

I would advise them, before they use the account before they open an account with Amazon, to do their account around just to learn a bit about that solution and then start using it, because it will take a long time to understand how that platform works, how you're going to create a VM on there, how you can create an SMTP.

It is not a simple procedure that we point to and then follows some steps to complete. You must be familiar with information technology. You must have at least basic IT knowledge of a hosting site. This is a platform, and before they begin using it, they must check a number of things and understand how they will proceed.

I would rate Amazon AWS a seven out of ten.

I am using the solution to create my own virtual servers in the cloud. We use one of the servers to deploy the database for NoSQL database on MongoDB. MongoDB allows all types of databases. 

Here is a more detailed explanation. I needed to deploy a backup API that was not in the project I needed it for. To back up the API is essentially treating data from the MongoDB database. Initially, we implemented it locally and tested all the endpoints, and then we deployed it to the AWS services. We needed this to be online and to communicate with the front end, which is an angular app that says you receive the data from another database which is another NoSQL.

This solution offers a very detailed dashboard that has some metrics, such as performance and budget. You can find all the documentation on how to do almost anything. It supports multiple services where you can use Linux. Depending on your use case, you can also manage the allocations, for example, your hard drive and memory.

Additionally, the solution is user-friendly, has intuitive dashboards, and plenty of graphs and charts available.

We had some problems with bandwidth because of high usage. There were so many queries going to the API and since we were on a budget, we did not provide the needed requirements for our software. At those times the performance was really slow, I needed to log in using a remote session to check whether there is a problem and if there was I had to restart the server. If you have the required budget and you know how to customize it, I think it would be working fine.

In a future release, I would like to see more support for AI because it is the future. 

I have been using the solution for the past year.

The solution is really reliable even when we were using it as a demo to showcase to clients.

The cloud-based environment was secure for everything I used it for. It does not allow you to just log in for the remote sessions. You need to configure it to have a computer log into your accounts properly for user management.

The solution is scalable, whenever you want to scale up the solution and improve it, they really offer you that opportunity. For example, increase the hardware and resources.

The customer support is exceptional. I was having some problems with deploying the server and had to contact support. I began chatting with the chatbot and when it did not help me I was transferred to one of their support attendants. Once the ticket is submitted, they send you another email, in three days to check whether the problem was resolved or not. They are really helpful.

Additionally, at one of the AI summits, Amazon had a room that was filled with many technical professionals. They all had different technical backgrounds willing to give support to those who asked questions. It was really helpful.

The installation for me was straightforward since I have some technical background. However, I did still need to read some documentation. The installation documentation is good and informative. Those who are new to the solution can search the internet for information to guide them and there are courses online to follow too.

When I first started using the solution I used a free trial, and then we upgraded to a pay-as-you-go subscription. We have an allocated budget of $50. I am happy with the pricing because the free trial project helped me progress. In our country, there are limitations for what payment methods we can use, we do not support PayPal, and credit card transactions are delayed. Hopefully, this gets better in the future. However, in other countries, this is not a widespread problem.

The type of deployment of the solution depends on the need of the organization. There are some solutions that we deploy for the clients that we need in a more stable environment. In this case, we use the cloud. For testing purposes for internal projects, we use our own servers within the company. I think by the IP numbers, we can request to create a certain server and they created this for us. There are some clients that require a cloud-based solution, we have this capability but it is still in testing and it is not what we use our servers for.

I would recommend this solution for companies like small companies just starting out. It would be really helpful for them.

I rate Amazon AWS a nine out of ten.

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.