71–80 of 93 posts
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Will any sort of scheduled execution be possible with DO Functions? I've been looking for a way to add scheduled tasks (e.g. session cleanup) to DOAP apps.
yep - it's coming.
AWS x86 Price $0.0000166667 for every GB-second $0.20 per 1M requests Arm Price $0.0000133334 for every GB-second $0.20 per 1M requests DO $0.0000185/GB-second So basically a little higher price for each GB/s but no cost pr request. AWS free tier provides 400,000 GB-s and 1 million free requests per month DO free tier 90,000GB-seconds of usage for free per month So cheaper in some respects compared to AWS. Google and…
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so this means that DO users have been moving to AWS Lambda?
As serverless has been gaining traction a lot of users have moved from traditional vps deployments to serverless offerings because it is more affordable for sporadic workloads.
Waiting for a standardized approach to serverless that lets us just write the code once and deploy to _any_ cloud provider. Right now, all of these products (aws, azure, do, etc) seem to have, at least, slight differences that would make it not possible to switch to another provider without some code changes.
It’s been around for years https://www.serverless.com/framework/docs/providers
AWS x86 Price $0.0000166667 for every GB-second $0.20 per 1M requests Arm Price $0.0000133334 for every GB-second $0.20 per 1M requests DO $0.0000185/GB-second So basically a little higher price for each GB/s but no cost pr request. AWS free tier provides 400,000 GB-s and 1 million free requests per month DO free tier 90,000GB-seconds of usage for free per month So cheaper in some respects compared to AWS. Google and…
Thanks this was the information I was looking for and glad I won't be moving off AWS Lambda anytime soon. Really puzzling why DO would announce a new product and make it more expensive than incumbents. Typically, you would want to undercut existing competitors right out of the gate because your competitors will do it for you....by making the first move to reduce their prices, diminishing your own market. Perhaps ther…
They don't want to be like most of the other cloud infrastructure companies like Cloudflare that are burning a lot of cash to look cheap. Eventually they will have to increase prices too.
AWS, Azure, GCP get the advantage of having contracts with big technology companies that they can oversell their products too to help make up for the loses they have from basic users. It a lot easier to sell junk to big corporations to increase revenue than it is for DigitalOcean to do the same for SMB and start ups.
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up to 10ms CPU time per request Not much of a room here it seems. AWS still offers more generous CPU time. In fact any price move by new entrants can be countered by AWS going forward. So AWS users benefit from not moving. Simply wait for others to reduce their prices and expect AWS to do the same.
The key difference is that unlike lambda where you are charged for network waiting time, Cloudflare from what I can tell, doesn't count time the CPU is suspended for networking operations. I use a cloudflare worker for DDNS updates, and it runs on the free tier. If the 10ms included network time, my worker would consistently timeout, but it hasn't timed out yet so I must conclude that it doesn't count network time.
Last I checked I think our median is 6ms (against a limit of 50 IIRC) on Workers Bundled.
I recently learn about this term, so can someone be kind enough to explain to me ELI5 serverless usage[0], advantages over "traditional" servers and why I should/could care? [0] by usage I mean, I still deploy my monolithic app, or just one function per route?
We deploy our full monolithic app to lambda (as a docker image) and then just have a wrapper entrypoint script that dispatches the request to the appropriate module and function.
There are benefits to keeping each lambda function small but we like the benefit of deploying one lambda and being able to call any function within the monolith.
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What is the underlying software used for DO functions? OpenFaas? Firecracker? gvisor? something custom to DO?
The foundation is Apache OpenWhisk https://github.com/apache/openwhisk with DO specific customization to work with App Platform, managed databases, trusted sources, log shipping, and other DO specific capabilities. The closest programming model is AWS Lambda in terms of the semantics and execution model.
The only time I've used "cloud functions" in the past has been for executing complex jobs that may take up to several minutes. For this, cloud functions has been very useful and easy to scale.
I hope DO can consider increasing this limit.