AWS Lambda vs. Azure Kubernetes Service (AKS)

Scenarios where AWS Lambda is well suited: 1. When we need to run a periodic task few times in a day or every hour, we may deploy it on AWS Lambda so it would not increase load on our server which is handling client requests and at the same time we don't have to pay for AWS Lambda when it is not running. So, overall we only pay for few function invocations. 2. When some compute intensive processing is to be done but the number of requests per unit of time fluctuates. For example, we had deployed an AWS Lambda for processing images into different sizes and storing them on AWS S3 once user uploads them. Now, this is something that may happen few times every hour on a particular day or may not happen even once on other days. To handle this kind of tasks AWS Lambda is a better choice as we don't have to pay for the idle time of the server and also we don't have to worry about scaling when the load is high. Scenarios where AWS Lambda is not appropriate to use: 1. When we expect a large request volume continuously on the server. 2. When we don't want latency even in case of concurrent requests.

Incentivized

[Azure Kubernetes Service (AKS)] is great when you need to be able to deploy a large number of services in a highly repeatable way. Once you know how to use it, it is a very fast to stand up a new environment. However there is a lot you need to know to get to that point and it is a specialized area. This is not suitable for small teams who are supporting multiple product stacks.

Incentivized

• AWS Lambda is a welcoming platform, supporting several languages, including Java, Go, PowerShell, Node.js, C#, Python, and Ruby. And if you need to deploy a Lambda function in another language, AWS offers a Runtime API for integration.
• We really appreciate how AWS Lambda is always-on for our functions, with only a brief "cold-start" waiting period the first time a function is called after being dormant.
• In addition to only generating costs when it's actually being used, AWS Lambda really puts the "serverless" in serverless architecture, offering turnkey scaleability and high availability for our code with zero effort on our part.

Incentivized

• To scale the microservices very easily.
• Easy to set up in CI/CD pipeline.
• It has a good pricing option as well in Azure. Basic works fine.
• Accelerates containerized application development for the developers.

Incentivized

• The UI and Developer experience is not so great. IF you use an abstraction like Serverless Application Model (SAM), things get pretty easy, but it's still AWS UI/DX you're working with after that (which is to say, not their strength).
• Documentation is always a mixed bag. Sometimes it's just easier to google your specific problem and see how others have solved it. This can be much faster than trying to find an example that may or may not be there in the documentation (which oftentimes has multiple versions and revisions).

Incentivized

• GUI on azure portal need to enhanced.
• The feature set should be matching with Openshift which is also kubernetes based
• Troubleshooting errors

Incentivized

It is very easy to get started with AWS Lambda and create your first function. The user interface makes it easy to add AWS services to be inputs or outputs to the function, meaning it can be configured in many different ways for different needs. This makes it ideal for various scenarios in AWS.

Incentivized

Barring certain missing features such as operator management , open cluster management, it does gives lot of options to host containerized applications. The GUI may be improved and can give user more insights to the cluster rather than using command line tools. The integration with standard azure monitoring tools is a big plus to use Azure Kubernetes Service (AKS)

Incentivized

As this is a product where a great part of errors can be at the source code level, AWS support team doesn't dive that further. I mean they don't evaluate problems more complex related to your code, [which] is totally understandable, but this make[s] debug process more tough and painful.

Incentivized

Microsoft support was really good, whenever we raise any ticket they come back to us within a couple of hours.

Incentivized

It's fine, it works as the others would have, except EC2. We are migrating back to EC2 for dedicated compute because we have scaled to a point where we have consistent traffic. The tradeoff of maintaining infrastructure in-house outweighs the benefits of moving quickly through our roadmap.

Incentivized

Worked with very similar in-house-built Kubernetes/container management system. We are leveraging AKS as it's more robust and stable being in the technical space for quite some time. Also, it has got a vast number of management and security features which makes it more attractive. They even have a model where the cost can be reduced by up to 90% if the application can afford to handle a quick downtime once in a while.

Incentivized

• We have simplified log fiie ingestion using Lambda functions. The return has been less time worrying about getting logs from source to ingestion; one the process is in place the team is nearly 100% hands off.
• We have begun taking a more API focused approach by using API Gateway as the interface to business processes and Lambda as the back end compute. Moving away from server based back ends places us on a path to reducing overall spend in compute costs.
• Lambda functions allow us to easily interface with third party services through APIs. This simplifies access management since the function can be granted permissions and access to the function can be gated with API keys and other authentication methods.

Incentivized

• The ability to scale has reduced the need for headcount in IT
• The authentication process has kept us compliant with regulatory bodies
• The ability to replicate environments is great.

Incentivized