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microservices patterns

Cloud agnostic apps with DAPR

DAPR is cool, as stated on the website “APIs for building portable and reliable microservices”, it works with many clouds, and external services. As a result you only need to configure the services and then use DAPR APIs. It is true and I’ll show you. You will find the code for this article here. A must have tool when working with micro services.

Applications can use DAPR as a sidecar container or as a separate process. I’ll show you a local version of the app, where DAPR is configured to use Redis running in a container. The repo will have Azure, AWS, and GCP configuration as well.

Before we can start the adventure you have to install DAPR.

Running app locally

Configuration

You have to start off on the right foot. Because of that we have to configure secrets store where you can keep passwords and such. I could skip this step but then there is a risk someone will never find out how to do it properly and will ship passwords in plain text. Here we go.

# save under ./components/secrets.yaml
apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: local-secret-store
  namespace: default
spec:
  type: secretstores.local.file
  version: v1
  metadata:
  - name: secretsFile
    value: ../secrets.json

The file secrets.json should have all your secrets, like connection strings, user and pass pairs, etc. Don’t commit this file.

{
    "redisPass": "just a password"
}

Next file is publish subscribe configuration. Dead simple but I’d recommend going through the docs as there is much more to pub/sub. Here you can reference your secrets as shown.

# save under ./components/pubsub.yaml
apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: order_pub_sub
spec:
  type: pubsub.redis
  version: v1
  metadata:
  - name: redisHost
    value: localhost:6379
  - name: redisPass
    secretKeyRef:
      name: redisPass
      key: redisPass
auth:
  secretStore: local-secret-store

Publisher and subscriber

With config out of the way only thing left are publisher part and subscriber part. As mentioned before the app you write talks to DAPR API. This means you may use http calls or Dapr client. Best part is that no matter what is on the other end, be it Redis or PostgreSQL, your code will not change even when you change your external services.

Here goes publisher that will send events to a topic. Topic can be hosted anywhere, here is a list of supported brokers. The list is long however only 3 are stable. I really like how DAPR is approaching components certification though. There are well defined requirements to pass to advance from Alpha, to Beta, and finally to Stable.

# save under ./publisher/app.py

import logging

from dapr.clients import DaprClient
from fastapi import FastAPI
from pydantic import BaseModel

logging.basicConfig(level=logging.INFO)


app = FastAPI()


class Order(BaseModel):
    product: str


@app.post("/orders")
def orders(order: Order):
    logging.info("Received order")
    with DaprClient() as dapr_client:
        dapr_client.publish_event(
            pubsub_name="order_pub_sub",
            topic_name="orders",
            data=order.json(),
            data_content_type="application/json",
        )
    return order

Here is a consumer.

# save under ./consumer/app.py

from dapr.ext.fastapi import DaprApp
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()
dapr_app = DaprApp(app)


class CloudEvent(BaseModel):
    datacontenttype: str
    source: str
    topic: str
    pubsubname: str
    data: dict
    id: str
    specversion: str
    tracestate: str
    type: str
    traceid: str


@dapr_app.subscribe(pubsub="order_pub_sub", topic="orders")
def orders_subscriber(event: CloudEvent):
    print("Subscriber received : %s" % event.data["product"], flush=True)
    return {"success": True}

Running the apps

Now you can run both apps together in separate terminal windows and see how they talk to each other using configured broker. For this example we are using Redis as a broker. You will see how easy is to run them on different platforms.

In the first terminal run the consumer.

$ dapr run --app-id order-processor --components-path ../components/ --app-port 8000 -- uvicorn app:app

In the other terminal run the producer.

$ dapr run --app-id order-processor --components-path ../components/ --app-port 8001 -- uvicorn app:app --port 8001

After you make a HTTP call to a producer you should see both of them producing log messages as follows.

$ http :8001/orders product=falafel

# producer
== APP == INFO:root:Received order
== APP == INFO:     127.0.0.1:49698 - "POST /orders HTTP/1.1" 200 OK

# subscriber
== APP == Subscriber received : falafel
== APP == INFO:     127.0.0.1:49701 - "POST /events/order_pub_sub/orders HTTP/1.1" 200 OK

Running app in the cloud

It took us a bit to reach the clu of this post. We had to build something, and run it so then we can run it in the cloud. Above example will run on cloud with a simple change of configuration.

Simplest configuration is for Azure. Change your pubsub.yaml so it looks as follows, and update your secrets.json as well.

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
  name: order_pub_sub
  spec:
    type: pubsub.azure.servicebus
    version: v1
    metadata:
    - name: connectionString
      secretKeyRef:
        name: connectionStrings:azure
        key: connectionStrings:azure

Your secrets.json should look like this now

{
  "connectionStrings": {
    "azure": "YOUR CONNECTION STRING"
  }
}

Rerun both commands in terminal and the output will look the same as with local env but the app will run on Azure Service Bus.

Bloody magic if you’d ask me. You can mix and match your dependencies without changing your application. In some cases you may even use features not available to a particular cloud, like message routing based on body in Azure Service Bus. This will be another post though.

Here is the repo for this post, it includes all the providers listed below:

  • Azure
  • Google Cloud
  • AWS

Please remember to update your secrets.json.

Have fun 🙂

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