Amazon AWS Reviews

The use cases of the solution depend on your project. The project I am working on right now is using Amazon Rekognition heavily, along with S3 and EC2. There are a lot of instances involving EC2. The last one involved using a text-to-speech, of which I don't remember the name, but that was the project's main goal. The use cases depend on the circumstance of your project, so it is not the same for all.

The most valuable feature of the solution is that they offer everything around in just one platform. They have almost everything. For example, a couple of weeks ago, I was trying to build a server with RabbitMQ for some kind of real-time communication in an environment where I was working. Amazon already has a service named Amazon MQ, because of which you don't need to configure your server by yourself since you already have it integrated into the ecosystem. It's easy to ensure that the server is there for your system without any issues and allows you to run it in seconds instead of three or four days.

Price is an area with a shortcoming in the solution that has a scope for improvement. Amazon can improve in some areas related to its pricing. Amazon selected the pricing plans, and I had to choose one. In general, it is an expensive tool.

It is cheap when you are starting with the tool since they have this free tier. However, that is not the reality when you really start working with Amazon since you will end up paying a lot at the end of every month.

I have been using Amazon AWS with different clients for six to seven years. I am a customer of the solution.

I believe that it's a stable product. I never had any issues with Amazon. I'm trying to remember, but I think that I have never faced any stability issues. It was working twenty-four hours and seven days a week all the time.

I have contacted Amazon's customer support. It was just a couple of calls when I was working in Iceland on a project, and the servers were not reachable. There was some kind of issue at the country level, not an issue of Amazon specifically. There was some issue with the solution in Iceland.

The initial setup is a thing that you need to learn. The setup part is not easy at all. Usually, in some companies, you have a person that works only with Amazon. You have one profile in your company just to work with the infrastructure services inside Amazon. You need a kind of specialized profile for that work.

The solution's pricing depends on your traffic since they charge you based on the traffic, not the servers. The price can go into many, many thousands depending on the traffic.

The price also depends on your services since, if you are using Amazon Rekognition or S3 with a low tier price.

Well, for a small company, normally, my advice would be that Amazon AWS is not the best option. If you are trying to use Amazon for the first time, it means you need a big project on your hands, and you already have an MVP running. If you are going to use Amazon for the first time, then you already know what you are going to deal with, so such people don't need my advice in that case.

The price is my concern, so I am searching for some other options to leave Amazon. It is not for quality-related reasons.

I rate the overall solution a seven out of ten.

I generally EC2 workloads. We use it to host our applications and provide our software service on the cloud. We integrate with EKS (Elastic Kubernetes Service) to manage containerized applications.

EKS helps us manage our containerized applications on AWS. We use various AWS services for different functionalities, such as computing services, database storage, content delivery, etc.

AWS's security model, including IAM or security groups, has contributed to our organization's compliance. It manages authentication, permissions, and overall security posture, which helps us maintain compliance.

AWS has made our lives much easier. It simplifies workload management and operations.  

The cloud-based nature of AWS is crucial for scaling our resources effortlessly. It's a key reason we chose AWS.

We find EKS particularly helpful for its ease of use and management of containerized applications.

Faster API response times and an improved console experience would be better. Enhanced performance across APIs and the console would streamline our workflows.

In future releases, improved compatibility and minimal downtime during upgrades would be significant enhancements.  

I have been using it for seven years. 

I would rate the stability a nine out of ten. It's generally very reliable.

I would rate the scalability a ten out of ten. No problem with scaling this product.

There are around 300 end users in my company using this solution. 

AWS technical support is good in general.  

Positive

The features, quality, and support are likely comparable to other products.

The initial setup is simple. 

Pricing definitely isn't high; I would rate the pricing a five out of ten, with ten being expensive. 

AWS pricing is quite competitive. AWS is cost-effective because it saves time. Faster deployments and testing make it very valuable. Pricing isn't the main thing; it's more about getting things done efficiently. Then, engineers can discover additional savings within AWS itself.

So, it's more flexible. We save a lot of time thanks to AWS

Overall, I would rate the solution an eight out of ten. 

I build infrastructure from the ground up. VPCs, in-depth virtual machines, new websites, migrations from on-prem to AWS, or even between cloud providers. 

Recently, I started building chatbots using Amazon Connect, IVRs, and Lambda. Lambda is also used for the contact center's business logic.

Based on what I do, it's not one service; they're interconnected. For example, when migrating a website from one cloud provider to another, I use EC2, a database system, and Route 53 for DNS. They really depend on each other. 

Now, if I had to pick just one... I like EC2. I can spin up applications and shut them down. When I work on security groups, opening and closing ports, EC2 allows it.

There is room for improvement in cost. Everyone complains about AWS being expensive. The initial cost starts small but can skyrocket unexpectedly. That's why some people, like my friend, have moved to Linode. 

Linode tells you upfront: "This instance with this configuration will cost $20/month. That's it." There are no hidden fees.

With AWS, it might start at $20, but then it creeps up to $35, $40, $50, and so on. It's a big concern, and people are even moving back to on-prem infrastructure because of it. 

Cost is crucial, and I see it myself. It gets expensive over time. AWS needs to improve its cost transparency and offer more predictable billing options. 

The cost is what everyone is running away from. It gets expensive over time.

I have been using it since 2014. 

Stability is guaranteed because the stability depends on how you design your solution. 

AWS has what's called the shared responsibility model. It simply means there's the work of you, the customer, and the job of AWS as a cloud provider. They handle the physical infrastructure, but you, the customer, need to be able to set up the application in such a way that if anything breaks, you can stabilize it. 

If you're designing your infrastructure using, for example, there are several factors you need to consider when designing your infrastructure, like scalability, security, etc. There are about six of them. 

So, you need to take all of those factors into consideration when designing your infrastructure. Because if you don't design it well, it could fail. So you have to design it so that it shouldn't fail. 

The onus is not entirely on AWS for you to have a stable infrastructure. You need to design your infrastructure properly, and then AWS manages the physical side of things. But overall, it's a stable cloud provider. That's why they're number one.

It's highly scalable. It's guaranteed 99.99% uptime, and it shows you can scale up or scale out whenever you need more space. 

Scaling up means you can add more memory to your VM at any time or increase the size of your database. Scaling out means you can create multiple VMs in different regions if you want; that's where availability zones come in. 

You can add more VMs if needed, and if one shuts down for any reason, the other one comes up. This is where load balancers come into play. The load balancers automatically create new VMs to manage the load of traffic coming to your website or application. So, it's highly scalable.

I have not personally contacted the support team. 

The first time I used AWS was in 2014 for my first project on the platform. That was the first time I logged in to the console, created a VPC, and deployed a VM. Everything was new to me. I used Udemy to learn to learn about this product in 2014.

I actually learned as I went along on the project. I knew nothing about it before starting, and I figured it out along the way.  

The difficulty level for the setup depends on how inquisitive you are and how deep you want to learn. If you're not patient, you might miss things. 

You need to have that initial interest and drive to start, and that makes it easier. For me, it was very easy because I was on a project, and it had to be successful at all costs. So, there was pressure, and I had no choice but to make it work. So, it depends on the scenario. 

But overall, it should be easy for a new person to use AWS because there are so many resources available. There are tons of white papers, online courses, and documentation on GitHub, and AWS has a lot of documentation online as well. So, it makes it easy. There's a step-by-step guide on how to use the infrastructure. So, it should be easy for a beginner. 

Setting up a VPC takes less than three minutes. Then, for it to start loading in AWS, it may take an additional two minutes. Then, for the VM, after creating the VPC, it depends on what you want. Do you want a Linux VM, Amazon Linux, Windows, or Mac OS? Whichever one you choose, if it's already created with all the dependencies from the marketplace, spinning up a regular Linux server on an Amazon VM should take less than three to four minutes. It is easy and very straightforward.

I would rate the pricing a nine out of ten, with ten being the most expensive. It's pricier than Linode, which has a fixed price and it is still a pay-as-you-go service. While for,  AWS, over time, it gets expensive. 

Linode is much cheaper and good for small businesses. 

It's good for big players like Fortune 500 companies, but smaller companies struggle. My friend's company even left AWS due to costs. So, for smaller companies, it's expensive.

Use the AWS calculator to confirm resources and configuration. That'll give a budget estimate and insight. 

In cloud space, it is called TCO (Total Cost of Ownership). Before buying, ask:

1. How many VMs do I need?
2. Why am I moving to the cloud?

Write down those answers and your resource needs. Then, use the calculator to project costs over six months or a year. Remember, it's not perfect - there might be hidden costs. If it says $10,000, expect $12,000. So, add a buffer. Only then commit.  

My advice is to check the calculator first for an estimate, then research GCP and Azure to compare before deciding. Use data to make informed choices and decisions.

Overall, I would rate the solution a nine out of ten. Saving that one point for pricing.

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 it to run our production workload.

I like the auto-scaling functionality and compliance requirements, whichever they are requesting. 

I also appreciate new setup services, which allow customers to easily manage their entire AWS infrastructure through code, and the managed services that handle the heavy lifting for us.

AWS could benefit from being more cloud-agnostic. This means allowing customers to easily migrate their workloads and applications built on AWS services to other hyperscalers if needed. Currently, the architecture feels closed, making it difficult for customers to move to different cloud providers seamlessly.

One of the issues I'm facing is that my RDS SQL Server version 5.8 is reaching its end of life, and I need to upgrade it to a customer-wanted version. I want to do this on Graviton instances, but Graviton only starts with version 8.0 and currently doesn't support the 5.8 series. 

We've raised a Priority Feature Request (PFR) with AWS to have this functionality added for at least three months. This would give us enough time to upgrade our database to the 8.0 version without any issues.

I have been using it for the last two and a half years. 

The product is very stable and robust. I haven't experienced any issues so far.

The scalability and elasticity are key advantages of AWS compared to other providers. This is one of the main reasons why hyperscalers like AWS are preferred.

If we need to add or remove workloads, the performance remains consistent.

More than 70% of our workforce uses this solution. So, there are more than 40 end users. 

In situations beyond my expertise, I've contacted the engineers. They've been helpful in resolving issues, providing support with freezes, and offering guidance whenever needed.

The quality of the customer service and support depends on the engineer I interact with. 

However, in most cases, including my own, around 75% of the time, the engineers I've encountered have been knowledgeable, supportive, and flexible. 

While individual experiences may vary based on specific learning, I would generally rate the support as good.

Positive

The specific reason my company chose this product was that whatever use case we were expecting, everything was readily available on the AWS cloud. We didn't want to reinvent the wheel. 

We just wanted to choose the right services that would be cost-effective, optimized, meet customer requirements, and offer elasticity, scalability, flexibility, and security. 

So, when we compared AWS to other cloud vendors like Azure or Google, AWS performed significantly better. Based on that, our leadership recommended going with AWS, and the business and technical teams supported that decision. So, by taking into account all the inputs from various departments, we decided to go with AWS.

Setting up AWS was easy. I used Infrastructure as Code (IaC) with YAML codes to deploy the infrastructure quickly.

It took me about half an hour to spin up the VPC, security policy, launch instances, attach the Elastic Block Store (EBS) volumes, connect to the S3 VPN endpoint, and configure cloud-native services like CloudWatch and CloudTrail. 

However, it took me almost a week to prepare the IaC code beforehand. This code can be easily reused and modified for future deployments with any minor changes required by the customer's use cases.

The pricing depends on the workload. For example, if your workload involves Windows technologies, AWS may not be the most cost-effective option. In that case, you might be better off with Azure. 

But if you're working with open-source technologies, then AWS can be a good choice. They have their own process called RabbitMQ, which is an on-premises architecture where you can recompile all your applications to run on your own infrastructure. This can significantly reduce your costs compared to other hyperscalers like Google, Oracle, or Azure.

So, it would be worth my money to go with Amazon AWS at the end of the day. However, if it's a Windows-based workload, I wouldn't recommend AWS.

You can just go ahead with AWS with your eyes closed. You won't regret it.

Overall, I would rate the solution an eight out of ten. 

It plays a pivotal role in data processing and application development. In our projects, we've harnessed the power of AWS for a range of applications. One key scenario involves building pipelines to process data collected from devices, such as audio and video footage. AWS services like Amazon Kinesis and Lambda functions were used in conjunction with other services like DynamoDB, SNS (Simple Notification Service), and SQS (Simple Queue Service). Another use case involves handling data from e-commerce websites. We collect and process this data using AWS Lambda functions, SNS, and Elasticsearch. The processed data is then fed into a separate application, which serves various marketing and analytical purposes.

The most valuable is ensuring the integrity of our written code through thorough verification. Also, we've leveraged AWS services like Redshift and Glue. Glue, in particular, is a potent tool that simplifies the ETL (Extract, Transform, Load) process. It streamlines tasks like table creation and data loading into Redshift, making the process more efficient and manageable.

There should be improvement in terms of creating databases of varying sizes which would provide flexibility.

I have been working with it for three years.

It offers good stability capabilities. We haven't encountered any issues or downtimes.

In terms of scalability and data security, AWS excels, which is why it's a prominent player in the market.

We receive data from SAP systems, which we process using Databricks. Within Databricks, our coding approach varies; sometimes we use SQL, and in other cases, particularly in certain projects, we employ PySQL and SpotsSQL. We then process this data, which might involve SQL Server, Oracle, or other databases. For ETL (Extract, Transform, Load) processes, we've worked with Data Factory. When dealing with data originating from SAP systems, which often includes unstructured or semi-structured data like JSON, we make use of a diverse toolset. This enables us to load data into databases such as SQL Server and Snowflake or any other required database.

The initial setup was straightforward.

The setup process was facilitated through CI/CD pipelines. Initially, we used the AWS CI/CD pipeline but later transitioned to GitLab because we encountered limitations with certain AWS CI/CD use cases. In GitLab, we found more flexibility, enabling us to execute specific functions or steps independently. In contrast, AWS CI/CD typically follows a more rigid sequence, where phases are executed sequentially from initialization to build and deployment.

The pricing may vary and is often influenced by marketing strategies.

It's a valuable tool, but working with AWS can be challenging. I would rate it nine out of ten.

I am impressed with the solution's EC2 EKS. 

The product should reduce carbon emissions. 

I have been working with the solution for ten years. 

I would rate the tool's stability an eight out of ten. 

I would rate the solution's scalability a nine out of ten. 

I would rate the solution's setup an eight out of ten. 

I would rate the product a nine out of ten. 

In recent years, we have use AWS primarily for its serverless capabilities. It has the ability to scale up from one to 10,000 vCPUs for a few brief seconds. The vCPUs perform intensive calculations with deep learning (artificial intelligence calculations), which is not possible via traditional computing approaches.

AWS helped us reduce costs from CapEx to OpEx. Some of the introduced one-year and three-year reservations helped us reduce costs early on. With time, we learned how to minimize our at REST capacity, allowing us to scale up and scale down in near seconds. 

Serverless computing: This can be more cost-efficient just regarding computing resources than renting or purchasing a fixed quantity of servers, which involves periods of underutilization or nonuse. It can even be more cost-efficient than provisioning an autoscaling group, because even autoscaling groups are typically designed to have underutilization to allow time for new instances to start up.

Also, a serverless architecture means developers and operations specialists do not need to spend time setting up and tuning autoscaling policies or systems. The cloud provider is responsible for ensuring that the capacity meets the demand.

AWS Marketplace: Somehow Amazon associated their marketplace as a place to find images of various installs (preconfigured software) and was late in the game enabling and promoting SaaS-based solutions. Thus, the AWS marketplace has near zero awareness in the mind of the prospect to find solutions to various problems plaguing them. 

No stability issues.

No scalability issues.

They are mainly generalists without access to the operating system. As such, they can provide container level insights,not necessarily at the application level.

I have used AWS for the last eight years since 2010. Previously, we used various VPS, dedicated servers, and Amazon's solutions, which were crude but a promise for something beyond the traditional infrastructure options. 

It was straightforward.

No vendor team was necessary.

We are reducing costs year-over-year.

Much faster than other solutions at a super low cost.

One of the best-kept ways to reduce costs is to develop it on serverless technologies with AWS Lambda, SNS, DynamoDB, and S3. Business example: By deploying our websites on Amazon S3 instead of the traditional Apache web servers, we eliminated many of the compute costs. Our WordPress site is served by a static S3 bucket. One of the benefits of this is our sites are superfast, especially with CloudFront. CloudFront makes the S3 hosted sites available across the world in milliseconds, reducing network hops and costs similar to that of Akamai. 

Just imagine the headaches associated with Apache web servers, MySQL databases, and Nginx reverse proxies?