quickstarts | Dapr quickstart code samples and tutorials showcasing core | Microservice library

There are 3 contexts that you need to be aware.

1. Your local station, with your own docker.
2. The cloud based Google Container Registry: https://console.cloud.google.com/gcr/
3. Cloud Run product from GCP

So the steps would be:

1. Build your container either locally or using Cloud Build

2. Push the container to the GCR registry, if you built locally

   docker tag busybox gcr.io/my-project/busybox docker push gcr.io/my-project/busybox

3. Deploy to Cloud Run a container from Google Cloud Repository.

Everything in the classpath is searched for the path specified in the property, e.g. resources dir.

The documentation already gives a hunch: "The class or ...", so at very least the classpath must be searched.

In the linked example project, in the maven pom the resources are extended to also include config, therefore it works there.

At the moment, you get a Uni>. The Mutiny way would be to transform this into a Multi and process each item:

According to dataproc batches docs, the subnetwork URI needs to be specified using argument --subnet.

Try:

Azure Communication Services have multiple types of Teams interop, which are in different phases of development by today (1/31/2022). Your combination of interop and programming language is currently not supported. Interop scenarios:

1. Ability of ACS users to join Teams meeting is generally available for all JS, .net, iOS, Android.
2. Ability of Teams user manage Teams VoIP calls, Teams PSTN calls, and Teams meetings via ACS JavaScript calling SDK is in public preview. Android, iOS, and .net calling SDKs do not support Teams identities.

You can learn more about the support in the following documentation: https://docs.microsoft.com/en-us/azure/communication-services/concepts/interop/teams-user-calling

It is a bit confusing, but the versions of the @azure/ai-form-recognizer package on NPM are one major version ahead of the Form Recognizer API versions. The preview API version "2021-09-30-preview" (REST API "v3") can be used with Form Recognizer SDK version 4.0.0-beta.2. REST API version v2.1 (GA) is used with SDK version 3.2.0. On the README for @azure/ai-form-recognizer 3.2.0, it explains this:

Note: This package targets Azure Form Recognizer service API version 2.x.

I'm guessing based on what you've said that you are using the latest stable version 3.2.0 of the SDK. When extracting data using a prebuilt or custom model in this version, tables are attached to pages, and pages are attached to Forms, so you can access a table by looking through the forms:

If a table is truncated while the streaming pipeline is still going on or performing a streaming insertion on a recently truncated table, you could receive some errors like mentioned in the question (Table is truncated), that's expected behavior. The metadata consistency mode for the InsertAll (very high QPS API) is eventually consistent, this means that when using the InsertAll API, it may get delayed table metadata and returns the failure like table truncated. The typical way to resolve this issue is to back-off and retry.

Currently, there is no option in the BigQuery API to check if the table is in truncated state or not.

You need to change your RestService to accept an instance of the following class instead of Booking:

Make sure that you are using a Live key and not the Test key, as the Test environment does not store any of your requests.

If you are looking for a sample response to work with, here is one I just got back: