Sharing Data Between Workers and Configuring Caching

To view an example policy project that uses caching, see Data Caching Policy Example.

Envoy spawns many workers to increase the policy’s capability of handling requests. A single worker handles all the stages of a specific request, including outgoing connections and the response flow. This enables you to track internal status for a specific request, and to create a sequential execution flow despite the underlying event-driven implementation.

Each worker processes a single request at a given time. To share a global state in a specific worker, use a RefCell without any risk of concurrent modification.

Use the provided Cache mechanism to create a shared global state for all workers.

After injecting the cache builder, provide an ID for the cache and the maximum number of elements the cache can support.

The following example configures a cache that can hold ten elements:

#[entrypoint]
async fn configure(
    launcher: Launcher,
    cache_builder: CacheBuilder,
) -> Result<()> {
    let cache = cache_builder.new(String::from("caching")).max_entries(10);
    ...

The cache has the following interface:

pub trait Cache {
    fn save(&self, key: &str, value: Vec<u8>) -> Result<(), CacheError>;
    fn get(&self, key: &str) -> Option<Vec<u8>>;
    fn delete(&self, key: &str) -> Option<Vec<u8>>;
    fn purge(&self);
}

Because different workers write to the cache concurrently, there is no guarantee that the value overwritten when saving the cache is the same as when it was retrieved.

Sharing Data Between Workers and Configuring Caching

See Also