23 releases
0.6.13 | Jan 8, 2023 |
---|---|
0.6.12 | Oct 30, 2022 |
0.6.11 | Sep 25, 2022 |
0.6.8 | Jul 24, 2022 |
0.3.2 | Nov 6, 2021 |
#552 in Network programming
38 downloads per month
52KB
783 lines
lambda-runtime-types
This crate provides types and traits to simplify the creation of lambda functions in rust. It provides Event and Return types and specific Runners for various lambda types.
Basic Lambda with no shared data
Creating a normal lambda is very easy. First create a type which implements Runner
and
then use it either in the exec
or exec_tokio
function:
struct Runner;
#[async_trait::async_trait]
impl<'a> lambda_runtime_types::Runner<'a, (), (), ()> for Runner {
async fn run(shared: &'a (), event: lambda_runtime_types::LambdaEvent<'a, ()>) -> anyhow::Result<()> {
// Run code on every invocation
Ok(())
}
async fn setup(_region: &'a str) -> anyhow::Result<()> {
// Setup logging to make sure that errors are printed
Ok(())
}
}
pub fn main() -> anyhow::Result<()> {
lambda_runtime_types::exec_tokio::<_, _, Runner, _>()
}
Available lambda types
There are various modules which predefined Event and Return types and Runner traits specialised for differnet lambda usages. Check out the modules for examples or their usage.
Custom Event and Return types
If the predefined types are not enough, custom types can be used as long as types for
events implement serde::Deserialize
and return types implement serde::Serialize
.
#[derive(serde::Deserialize, Debug)]
struct Event {
#[serde(flatten)]
attributes: std::collections::HashMap<String, serde_json::Value>,
}
#[derive(serde::Serialize, Debug)]
struct Return {
data: std::borrow::Cow<'static, str>,
}
struct Runner;
#[async_trait::async_trait]
impl<'a> lambda_runtime_types::Runner<'a, (), Event, Return> for Runner {
async fn run(shared: &'a (), event: lambda_runtime_types::LambdaEvent<'a, Event>) -> anyhow::Result<Return> {
println!("{:?}", event);
Ok(Return {
data: event
.event
.attributes
.get("test")
.and_then(|a| a.as_str())
.map(ToOwned::to_owned)
.map(Into::into)
.unwrap_or_else(|| "none".into()),
})
}
async fn setup(_region: &'a str) -> anyhow::Result<()> {
// Setup logging to make sure that errors are printed
Ok(())
}
}
pub fn main() -> anyhow::Result<()> {
lambda_runtime_types::exec_tokio::<_, _, Runner, _>()
}
Shared Data
With AWS Lambda, its possible to share data between invocations, as long as both invocations use the same runtime environment. To use this functinality, its possible to define a shared data type which will persist data by using Interior Mutability:
#[derive(Default)]
struct Shared {
invocations: tokio::sync::Mutex<u64>,
}
struct Runner;
#[async_trait::async_trait]
impl<'a> lambda_runtime_types::Runner<'a, Shared, (), ()> for Runner {
async fn run(shared: &'a Shared, event: lambda_runtime_types::LambdaEvent<'a, ()>) -> anyhow::Result<()> {
let mut invocations = shared.invocations.lock().await;
*invocations += 1;
Ok(())
}
async fn setup(_region: &'a str) -> anyhow::Result<Shared> {
// Setup logging to make sure that errors are printed
Ok(Shared::default())
}
}
pub fn main() -> anyhow::Result<()> {
lambda_runtime_types::exec_tokio::<_, _, Runner, _>()
}
Its important to know, that lambda execution evironments never run multiple invocations simultaneously. Its therefore possible to keep the mutex unlocked for the whole invocation as it will never block other invocations. Instead it is even recommended to do so, to make sure that there are no unnessary things slowing down lambda execution time.
Timeout handling
This crate implements a timeout handling logic. Normally, if a lambda runs into a timeout,
it will not create an error, which then does not get propagated by on_error
destinations.
To fix that, a timeout handler is setup, which will "fail" 100 miliseconds before the lambda would run into a timeout, creating an error which then is propagated. There is, however, no gurantee that this handler will fail in time. It will only work, when there are multiple tokio threads or when the main lambda code is currently awaiting, giving tokio the chance to switch tasks (or run them in parallel) and fail the execution.
Memory exhaustion
Another thing to consider when running lambdas is memory exhaustion. Unfortunatly it is not
possible in rust to check the current memory usage. Therefore it is also not possible to
fail before running into OOF. When running lambdas, it may be necessary to setup checks to
verify that a lambda completed successfully, and did not run into OOF, as these errors also
do not get propagated to on_error
destinations.
License: MIT OR Apache-2.0
Dependencies
~6–21MB
~293K SLoC