@fluidframework/azure-client
The azure-client package provides a simple and powerful way to consume collaborative Fluid data with the Azure Fluid Relay service (FRS).
Using azure-client
The azure-client package has a AzureClient
class that allows you to interact with Fluid.
import { AzureClient } from "@fluidframework/azure-client";
Instantiating AzureClient
Fluid requires a backing service to enable collaborative communication. The AzureClient
supports both instantiating against a deployed Azure Fluid Relay service instance for production scenarios, as well as against a local, in-memory service instance, known as Tinylicious, for development purposes.
NOTE: You can use one instance of the AzureClient
to create/fetch multiple containers from the same Azure Fluid Relay service instance.
In the example below we will walk through both connecting to a a live Azure Fluid Relay service instance by providing the tenant ID and key that is uniquely generated for us when onboarding to the service, as well as using a tenant ID of "local" for development purposes to run our application against Tinylicious. We make use of AzureFunctionTokenProvider
for token generation while running against a live Azure Fluid Relay instance and InsecureTokenProvider
, from the @fluidframework/test-client-utils
package, to authenticate a given user for access to the service locally. The AzureFunctionTokenProvider
is an implementation that fulfills the ITokenProvider
interface without exposing the tenant key secret in client-side code.
Backed Locally
To run Tinylicious on the default values of localhost:7070
, please enter the following into a terminal window:
npx tinylicious
Now, with our local service running in the background, we need to connect the application to it. For this, we first need to create our ITokenProvider
instance to authenticate the current user to the service. For this, we can use the InsecureTokenProvider
where we can pass anything into the key (since we are running locally) and an object identifying the current user. Both our orderer and storage URLs will point to the domain and port that our Tinylicous instance is running at.
import { AzureClient, AzureConnectionConfig } from "@fluidframework/azure-client";
import { InsecureTokenProvider } from "@fluidframework/test-client-utils";
const clientProps = {
connection: {
tenantId: "local",
tokenProvider: new InsecureTokenProvider("fooBar", { id: "123", name: "Test User" }),
orderer: "http://localhost:7070",
storage: "http://localhost:7070",
},
};
const azureClient = new AzureClient(clientProps);
Backed by a Live Azure Fluid Relay Instance
When running against a live Azure Fluid Relay instance, we can use the same interface as we do locally but instead using the tenant ID, orderer, and storage URLs that were provided as part of the Azure Fluid Relay onboarding process. To ensure that the secret doesn't get exposed, it is passed to a secure, backend Azure function from which the token is fetched. We pass the Azure Function URL appended by /api/GetAzureToken
along with the current user object to AzureFunctionTokenProvider
. Later on, in AzureFunctionTokenProvider
we make an axios GET
request call to the Azure function by passing in the tenantID, documentId and userID/userName as optional parameters. Azure function is responsible for mapping between the tenant ID to a tenant key secret to generate and sign the token such that the service will accept it.
import { AzureClient, AzureConnectionConfig } from "@fluidframework/azure-client";
const lientProps = {
connection: {
tenantId: "YOUR-TENANT-ID-HERE",
tokenProvider: new AzureFunctionTokenProvider(
"AZURE-FUNCTION-URL"+"/api/GetAzureToken",
{ userId: "test-user",userName: "Test User" }
),
orderer: "ENTER-ORDERER-URL-HERE",
storage: "ENTER-STORAGE-URL-HERE",
},
};
const azureClient = new AzureClient(clientProps);
Fluid Containers
A Container instance is a organizational unit within Fluid. Each Container instance has a connection to the defined Fluid Service and contains a collection of collaborative objects.
Containers are created and identified by unique IDs. Management and storage of these IDs are the responsibility of the developer.
Defining Fluid Containers
Fluid Containers are defined by a schema. The schema includes initial properties of the Container as well as what collaborative objects can be dynamically created.
See ContainerSchema
in ./src/types/ts
for details about the specific properties.
const schema = {
initialObjects: {
},
dynamicObjectTypes: [ ],
}
const azureClient = new AzureClient(props);
const { container, services } = await azureClient.createContainer(schema);
const id = await container.attach();
Using Fluid Containers
Using the AzureClient
object the developer can create and get Fluid containers. Because Fluid needs to be connected to a server, containers need to be created and retrieved asynchronously.
import { AzureClient } from "@fluidframework/azure-client";
const azureClient = new AzureClient(props);
const { container, services } = await azureClient.getContainer("_unique-id_", schema);
NOTE: When using the AzureClient
with tenant ID as "local", all containers that have been created will be deleted when the instance of the Tinylicious service (not client) that was run from the terminal window is closed. However, any containers created when running against the Azure Fluid Relay service itself will be persisted. Container IDs can NOT be reused between Tinylicious and Azure Fluid Relay to fetch back the same container.
Using initial objects
The most common way to use Fluid is through initial collaborative objects that are created when the Container is created.DistributedDataStructures and DataObjects are both supported types of collaborative objects.
initialObjects
are loaded into memory when the Container is loaded and the developer can access them via the Container's initialObjects
property. The initialObjects
property has the same signature as the Container schema.
const schema = {
initialObjects: {
map1: SharedMap,
text1: SharedString,
}
}
const { container, services } = await azureClient.getContainer("_unique-id_", schema);
const initialObjects = container.initialObjects;
const map1 = initialObjects.map1;
const text1 = initialObjects["text1"];
Using dynamic objects
LoadableObjects can also be created dynamically during runtime. Dynamic object types need to be defined in the dynamicObjectTypes
property of the ContainerSchema.
The Container has a create
method that will create a new instance of the provided type. This instance will be local to the user until attached to another LoadableObject. Dynamic objects created this way should be stored in initialObjects, which are attached when the Container is created. When storing a LoadableObject you must store a reference to the object and not the object itself. To do this use the handle
property on the LoadableObject.
Dynamic objects are loaded on-demand to optimize for data virtualization. To get the LoadableObject, first get the stored handle then resolve that handle.
const schema = {
initialObjects: {
map1: SharedMap,
},
dynamicObjectTypes: [ SharedString ],
}
const { container, services } = await azureClient.getContainer("_unique-id_", schema);
const map1 = container.initialObjects.map1;
const text1 = await container.create(SharedString);
map1.set("text1-unique-id", text1.handle);
const text1Handle = map1.get("text1-unique-id");
const text1 = await map1.get();
const text1 = await map1.get("text1-unique-id").get();
See GitHub for more details on the Fluid Framework and packages within.