- Runs fast, unless your function was frozen for not enough usage or the like
- Easy to deploy and/or "misuse"
- Debugging doesn't really work
All in all, probably the least painful thing I've used on AWS. But that doesn't necessarily mean much.
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- Runs fast, unless your function was frozen for not enough usage or the like
- Easy to deploy and/or "misuse"
- Debugging doesn't really work
All in all, probably the least painful thing I've used on AWS. But that doesn't necessarily mean much.
- There is a surprisingly high amount of API gateway latency - The CPU power available seems to be really weak. Simple loops running in NodeJS run way way slower on Lambda compared to a 1.1 GHz Macbook by a significant magnitude. This is despite scaling the memory up to near 512mb. - Certain elements, such as DNS lookups, take a very long time. - The CloudWatch logging is a bit frustrating. If you have a cron job it…
I have heard that go will be supported in the next three months and theres a lot of improvements coming. Cant wait to ditch those js and python wrappers.
- Use environment variables
- Use step functions to create to create state machines
- Deploy using cloudformation templates and serverless framework
Development can be tricky, there are a lot of of all in one solutions like the serverless framework, we use Apex CLI tool for deploying and Terraform for infra. These tools offer a nice workflow for most developers.
Logging is annoying, its all cloudwatch, but we use a lambda to send all our cloudwatch logs to sumologic. We use cloudwatch for metrics, however we have a grafana dashboard for actually looking at those metrics. For exceptions we use Sentry.
Resources have bitten us the most, not enough memory suddenly because the payload from a download. I wish lambda allowed for scaling on a second attempt so that you could bump its resources, this is something to consider carefully.
Encryption of environment variables is still not a solved issue, if everyone has access to the AWS console, everyone can view your env vars, so if you want to store a DB password somewhere, it will have to be KMS, which is not a bad thing, this is usually pretty quick, but does add overhead to the execution time.
Works terribly. It's basically a thin wrapper around a shoddy jar framework. All the languages supported are basically shit-farmed from the original Java one. The Java one is the only one that works half decently.
I use both NodeJS and C# lambda's without issue. The support is really good.
Debugging experience isn't great but aside from that it's fast and easy to use.
C# lambda's can call RDS and respond back in ~5ms...
(before anyone calls me out on the 5ms...)
http://www.philliphaydon.com/2017/05/10/part5-configuring-th...
Last image, I state 2-3 second startup and then 4ms response on a call to the database.
We have a number of different use cases at FundApps, some obvious like automated tasks, automatic DNS, cleanup AMI's etc, to the more focused importing and parsing of data from data sources. This is generally a several times a day operation, so lambda was the right choice for us. We also use API gateway with lambdas, its a small API, about 2 requests per second on average, but very peaky during business hours, its re…
We use Node.JS lambda functions for real time image thumbnail generation and scraping needs. As well as mirroring our S3 buckets to another blob storage provider and a couple of periodic background jobs. It works beautifully. It's a little hard to debug at first but when it's set up, both pricing and reliability is really good for our use cases. I think a lot of people try to use the "serverless" stuff for unsuitable…