# Rate limiting an application A common scenario in distributed computing is to only allow for a given number of requests to execute concurrently. Using Dapr, you can control how many requests and events will invoke your application simultaneously. *Note that this rate limiting is guaranteed for every event that's coming from Dapr, meaning Pub/Sub events, direct invocation from other services, bindings events etc. Dapr can't enforce the concurrency policy on requests that are coming to your app externally.* ## Setting max-concurrency Without using Dapr, a developer would need to create some sort of a semaphore in the application and take care of acquiring and releasing it. Using Dapr, there are no code changes needed to an app. ### Setting max-concurrency in Kubernetes To set max-concurrency in Kubernetes, add the following annotation to your pod:
apiVersion: apps/v1
kind: Deployment
metadata:
name: nodesubscriber
labels:
app: nodesubscriber
spec:
replicas: 1
selector:
matchLabels:
app: nodesubscriber
template:
metadata:
labels:
app: nodesubscriber
annotations:
dapr.io/enabled: "true"
dapr.io/id: "nodesubscriber"
dapr.io/port: "3000"
dapr.io/max-concurrency: "1"
...
### Setting max-concurrency using the Dapr CLI
To set max-concurrency with the Dapr CLI for running on your local dev machine, add the `max-concurrency` flag:
```bash
dapr run --max-concurrency 1 --app-port 5000 python ./app.py
```
The above examples will effectively turn your app into a single concurrent service.