If Lambda is able to expand the /tmp disk space from 500MB to a few GB I think that will further make the adopter better on my end. I have a requirement in which Lambda is a perfect solution except the disk space is not enough. Of course I can further divide the work into smaller chunks. If you have use distributed task library like Celery, just think of that no longer tie to your application, and you can run on even…
Appreciate the feedback/suggestions! We'll take a look at expanding the disk space, probably as part of the "power level" adjustment that already affects memory, CPU power, etc.
We're considering using API Gateway and Lambda for our upcoming API service. Would love to hear feedback from anyone who's tried it. From the linked article, I got one gist [1] which wasn't very favorable for the API Gateway + Lambda setup. [1] https://gist.githubusercontent.com/mpdehaan/d979252b9c69cfd1...
Depends on your use case and what language you are currently using. We are using nodejs and have built our own collection of libraries: https://github.com/MitocGroup/deep-framework And here is an example: https://github.com/MitocGroup/deep-microservices-todo-app Based on our experience, currently AWS Lambda is amazing for data / content / asset management use cases. Cold start is a known issue, which I hope AWS will…
Yes, cold start (the delay you experience when your code hasn't been used in a while) is a big issue - it means serious additional latency which makes Lambda difficult to use for end-user facing applications. You can get around this by calling the code periodically .. but that defeats the purpose. There are also restrictions around how long your code can run. BUT, if your use case fits within these constraints, it's pretty cool to just deploy your code and forget about all of the administration hassles associated with running it on a server.
If Lambda is able to expand the /tmp disk space from 500MB to a few GB I think that will further make the adopter better on my end. I have a requirement in which Lambda is a perfect solution except the disk space is not enough. Of course I can further divide the work into smaller chunks. If you have use distributed task library like Celery, just think of that no longer tie to your application, and you can run on even…
I used to work at Iron.io they have a product called IronWorker which gave 10GB temp disk. They allowed you to use your own docker containers also. they have a priority queueing system however and come at a premium over lamdba pricing due due to being more feature rich.
custom docker image use came with the overhead of burning in your instances though which I don't think is publicly available yet on the service.
It's funny we tested lambda + Amazon gateway api this week at work. It's awesome!.. Until you have to deal with the cold start issue. Our first call takes about 1.5 seconds; and then all other calls take about 50-80ms. Your container stays in cache about 5-10 minutes unless it is called back, there are no guarantees. This micro service is not called often and for us 1.5 seconds is never acceptable.
Our issue was price. Boss did the math for our use case, around a million hits/sec 24/7, and it worked out to billions of dollars. We're building a solution (on aws) for a little less than that.
We're considering using API Gateway and Lambda for our upcoming API service. Would love to hear feedback from anyone who's tried it. From the linked article, I got one gist [1] which wasn't very favorable for the API Gateway + Lambda setup. [1] https://gist.githubusercontent.com/mpdehaan/d979252b9c69cfd1...
I'm so glad you asked this! I just built a service on API Gateway + Lambda in the past two weeks. Here's my unstructured thoughts - * I love that I don't have to provision any resources. The fact it will scale to volume automatically is a huge win. * Lambda was a treat to work with. We used it with Python. Both the web console and API interface worked great for us. * I was able to get Lambda development working end-t…
We have encountered consistently HTTP 500 response when creating multiple methods simultaneously. I think they have fixed it by now, but imagine the color of my face when I'm about to present a demo to a pretty large audience and we discover this bug?
If Lambda is able to expand the /tmp disk space from 500MB to a few GB I think that will further make the adopter better on my end. I have a requirement in which Lambda is a perfect solution except the disk space is not enough. Of course I can further divide the work into smaller chunks. If you have use distributed task library like Celery, just think of that no longer tie to your application, and you can run on even…
I used to work at Iron.io they have a product called IronWorker which gave 10GB temp disk. They allowed you to use your own docker containers also. they have a priority queueing system however and come at a premium over lamdba pricing due due to being more feature rich. custom docker image use came with the overhead of burning in your instances though which I don't think is publicly available yet on the service.
We have used a combination of AWS Lambda + Amazon ECS, which is kind of similar what you're describing. We are working now to extend the abstracted library that empowers developers to choose programmatically what service to use: https://www.npmjs.com/package/deep-resource ;)
I just ended up using Heroku for an API instead. I was able to use the latest language version and microframework of my choice and still not worry about servers. Setup was way more intuitive than AWS. Testing locally was a known thing and easy. I found wrapping my head around testing API gateway to lambda to aws services a mess. Also all the IAM rules got confusing. I'll probably have another look after it has matured.
I've never used Heroku before and got a production ready API out the door in no time.
I'm so glad you asked this! I just built a service on API Gateway + Lambda in the past two weeks. Here's my unstructured thoughts - * I love that I don't have to provision any resources. The fact it will scale to volume automatically is a huge win. * Lambda was a treat to work with. We used it with Python. Both the web console and API interface worked great for us. * I was able to get Lambda development working end-t…
Have you reported any of your issues with the API Gateway to us? Please feel free to send them to me via the contact address in my HN profile and I will share them with the team ASAP!
I went through official support channels with my blocking issues. They have since been resolved.
It's funny we tested lambda + Amazon gateway api this week at work. It's awesome!.. Until you have to deal with the cold start issue. Our first call takes about 1.5 seconds; and then all other calls take about 50-80ms. Your container stays in cache about 5-10 minutes unless it is called back, there are no guarantees. This micro service is not called often and for us 1.5 seconds is never acceptable.
There's the performance issue on startup, then there's the cost issue with the typical case. With the "round up to the nearest 100ms" pricing, your example ends up overpaying 20-50% for the _typical_ case. If you have any serious use of your app, you are better off with DIY on EC2 or using Heroku.