Amazon AWS Reviews

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.  

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. 

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.

The use cases depend on the projects. The project that I am currently working on uses Rekognition heavily. It also uses S3 and EC2. My previous project was using it for the text-to-speech feature.

The ecosystem offered by the product has almost everything. A couple of weeks ago, I was trying to build a server with RabbitMQ for real-time communication in an environment. Amazon already has a service called Amazon MQ. We don’t need to configure the server ourselves because we already have one integrated into the ecosystem. It’s easy to install the server in our system. We can run it in ten minutes instead of waiting three to four days.

The initial setup is not easy at all.

I have been using the solution for six to seven years.

The solution is stable. I never had any issues with Amazon. It works all the time, 24/7.

I have contacted support. It was just a couple of calls. We weren’t able to reach the server. There was some issue at the country level in Iceland. The problem was not with Amazon specifically.

We will have to learn to setup the tool. Someone with no experience would not be able to do it. In some companies, there is a person that works only with Amazon. The person will be profiling the company to work with the service center infrastructure inside Amazon.

The solution should improve the pricing. The area that I work for is expensive. The product is cheap when we start using it. It provides AWS Free Tier. However, it is not the same when you work continuously with Amazon. We end up paying a lot at the end of every month. 

The pricing depends on the traffic because they charge by the traffic. They do not charge us based on servers. The price also depends on the services we use. It would be different if we used S3.

The product is not the best option for a small company. If someone is trying to use Amazon for the first time and already has an NPP running, they can use it. If someone has used Amazon, they would already know what they are going to deal with. The cost is a concern for me. Some people are trying to leave Amazon and are searching for other options. Overall, I rate the solution a seven out of ten.

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 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. 

We are primarily using the solution as real-time streaming to our data-lake. We also have microservices publishing to APIs. It's a customer 360 application. 

We also used the product for migration from on-prem Hadoop to AWS EMR.

We used to spend about $57,000 on-perm with another solution. Then we lifted and shifted to AWS. It came down in cost to about $33,000 while maintaining the same inner software with Apache Kafka. However, we then got into ECS Fargate, and that brought costs down further to about $22,000. When we removed ECS, we moved into a serverless Lambda for 45 million, and our billing is now $8000 per month. It's an amazing amount of savings.

The solution's API Gateway is very good.

The storage on offer is excellent. 

Recently they improved a lot in the analytics that they have on the backend. 

It's great that the product is completely serverless. 

The implementation for end-to-end, for Lambda serverless implementation, is excellent. I do run about 16 million messages per day with their Lambdas, for my API microservices.

The initial setup is not difficult.

We get a lot of exception errors, and we're working with AWS to figure out how to fix that. when we lift and shift . We get a lot of alerts. 

As our serverless Lambda is maintained by AWS, in a certain aspect,  we need to gain some more visibility into what is going on when problem happens with AWS serverless 

Their metadata management in AWS needs improvement. They need a centralized metadata management tool, where it can be integrated with  outside metadata tools  with the API. We really need a central metadata framework.

I've been using the solution for four years. It's been a while at this point.

The stability of the solution is very good. there are no bugs or glitches. it doesn't crash or freeze. It's reliable. That said, initially, we did have a few problems, however, everything has ironed out. It's great now.

Scalability-wise, the product is very good. The Lambdas and the serverless architecture are very good on AWS. If a company needs to expand, it can do so with ease.

We have a lot of APIs, and we'll run them on my customer 360. There are six departments that use the product. We have about 1,000 users currently.

We've dealt with technical support in the past and have not been satisfied for the most part. Azure's technical support is much better. AWS often can't help us resolve our issues. But they brought some good consultants basing on our request and helped us . The account Manager always there when he took over this account .  

 i recommend IAAS AWS , for IPAAS ( integration as platform service) and Hybrid cloud Azure

We've also planed for  Azure. We've found Azure to be much more helpful when dealing with issues than AWS has been. I prefer them over AWS in support , application development  and integration as platform. But AWS has great products like S3 , API gateway , transit gateways , route 53 . AWS has  more OS options than AZURE and database offerings. their EMR is good with spark and python but not well supported for Scala and HBase. AWS serverless offerings are very good with out any major problems which includes ECS with fargate and EKS . But we got a good support from account manager

The initial setup is not complex. When we lifted and shifted faced lot of problems on EMR. Moved to ECS, as well as serverless Lambda, it's was that difficult then. That said, we had to think about how we run our Lambdas, and what problems we are facing or might face.

We're also facing a few problems due to the fact that we use encryption, HCM. When we initially started loading this data, batch data, a lot of Lambdas came, and our limit in HCM is only about 5,000 a minute, however, it quickly jumped up to 20,000 which made it so that we could not load, and errors came up. We had to turn to AWS to get assistance. We just ask them if we can have space over a few days for 20,000 and then they scale it back to 3,000. they helped us 

In terms of the implementation strategy, ours took about eight months. The lift and shift happened within 3 months. Then, we took another four months as we had a lot of problems with our scale-up programming due to multiple issues - for example, libraries, EMR, AWS doesn't have. We faced some problems when we had to change our code according to AWS, or we have to bring in those libraries on our own. So that's where it took time, maybe four months.

For ECS, it took about 30 days to move everything we needed to. 

We don't have a lot of staff to maintain the product. We have about eight people who are capable of doing so. For example, we have someone on infrastructure, who is an architect and we have an enterprise architecture team. I have four developers, two for API and two for Lambda, and one is a systems admin. 

Initial setup environment helped by AWS free . We were able to handle every aspect of the implementation in-house. We didn't need any consultants or integrators. We used our systems manager so that all of our deployments - including environments and keys - can be stored on our SSM. A lot was automated as well.

excellent in covid -19 situation . 

We saw a lot of cost savings when we switched over to AWS. It can really save a company a lot of money.

Azure and AWS 

I'm a user and  implementer.

The solution is on the cloud; it's always the latest version. It's constantly being updated, and we're always using the latest version.

We use both public and hybrid clouds as deployment models.

I'd rate the solution at a seven out of ten.

We are using it for certain business applications.

The scalability is a valuable feature. 

The improvement should be done as per business needs. 

I have been using Amazon AWS for five years. 

It is a stable solution. 

It is a scalable solution. Presently, 3,000 users are using the solution. 

The initial setup is straightforward. 

The pricing is expensive. 

Overall, I would rate the solution a nine out of ten. 

It is primarily for cloud hosting. If you're developing a solution for a customer who wants it on the cloud, then AWS and Microsoft Azure are two major choices. There are other providers too, but AWS is quite user-friendly.

We use AWS for scalable cloud hosting and computing services. We store all our customer data on Amazon EC2 Instances.

We haven't had any security problems, and Amazon offers automated vulnerability audits. This helps us test our solutions for vulnerabilities and show customers that our systems are secure.

Security, quick deployment, and scalability are the top three features for me.

Like every other customer, I'd suggest pricing is the one feature everyone wants AWS to improve. 

I have been using it for five years. 

It is a stable solution. 

It is a scalable solution. We've worked with about five customers so far. 

We haven't needed technical support.

Sometimes, customers ask for AWS solutions, but we offer choices based on their needs. Price and geographical preferences can influence their decision. Sometimes, the customers can go for a cheaper product.  We don't force them, but we make recommendations.

The quickest way to set it up is the most beneficial feature. We can set up resources quickly and scale them as needed, starting small and growing as requirements increase. That's very helpful. It saves us a lot of time. 

The initial setup is straightforward if you spend some time learning it. They're improving the user interface, which helps.

My team takes care of the implementation. They find it easy to deploy. We haven't faced any issues so far.

It's not very pricey, but it could be cheaper. There are other options like GoDaddy and HostGator.

There are various options, and some can be cheaper than paying a full license.

Read the documentation carefully before starting. Preparation saves time in the long run. For example, the ease of integrating different AWS services depends on your expertise.

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