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This commit is contained in:
Aaron Crawfis 2021-04-14 16:25:43 -07:00
parent 31fe5f6205
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daprdocs/content/en/developing-applications/integrations/autoscale-keda.md
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---
type: docs
title: "Autoscaling a Dapr app with KEDA"
linkTitle: "Autoscale"
linkTitle: "Autoscale with KEDA"
description: "How to configure your Dapr application to autoscale using KEDA"
weight: 2000
---
@ -9,7 +10,7 @@ Dapr, with its modular building-block approach, along with the 10+ different [pu
For Kubernetes, Dapr integrates with [KEDA](https://github.com/kedacore/keda), an event driven autoscaler for Kubernetes. Many of Dapr's pub/sub components overlap with the scalers provided by [KEDA](https://github.com/kedacore/keda) so it's easy to configure your Dapr deployment on Kubernetes to autoscale based on the back pressure using KEDA.
This how-to walks through the configuration of a scalable Dapr application along with the back pressure on Kafka topic, however you can apply this approach to [pub/sub components]({{< ref pubsub >}}) offered by Dapr.
This how-to walks through the configuration of a scalable Dapr application along with the back pressure on Kafka topic, however you can apply this approach to any [pub/sub components]({{< ref pubsub >}}) offered by Dapr.
## Install KEDA
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Now, that the `ScaledObject` KEDA object is configured, your deployment will scale based on the lag of the Kafka topic. More information on configuring KEDA for Kafka topics is available [here](https://keda.sh/docs/2.0/scalers/apache-kafka/).
You can now start publishing messages to your Kafka topic `demo-topic` and watch the pods autoscale when the lag threshold is higher than `5` topics, as we have defined in the KEDA scaler manifest. You can publish messages to the Kafka Dapr component by using the Dapr [Publish](https://github.com/dapr/CLI#publishsubscribe) CLI command
You can now start publishing messages to your Kafka topic `demo-topic` and watch the pods autoscale when the lag threshold is higher than `5` topics, as we have defined in the KEDA scaler manifest. You can publish messages to the Kafka Dapr component by using the Dapr [Publish]({{< ref dapr-publish >}}) CLI command

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daprdocs/content/en/developing-applications/integrations/azure-functions.md Normal file
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---
type: docs
title: "Dapr extension for Azure Functions runtime"
linkTitle: "Azure Functions"
description: "Access Dapr capabilities from your Functions runtime application"
weight: 3000
---
Dapr integrates with the Azure Functions runtime via an extension that lets a function seamlessly interact with Dapr. Azure Functions provides an event-driven programming model and Dapr provides cloud-native building blocks. With this extension, you can bring both together for serverless and event-driven apps. For more information read
[Azure Functions extension for Dapr](https://cloudblogs.microsoft.com/opensource/2020/07/01/announcing-azure-functions-extension-for-dapr/) and visit the [Azure Functions extension](https://github.com/dapr/azure-functions-extension) repo to try out the samples.

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daprdocs/content/en/developing-applications/integrations/gRPC-integration.md
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---
type: docs
title: "Dapr's gRPC Interface"
linkTitle: "gRPC"
linkTitle: "gRPC interface"
weight: 1000
description: "Use the Dapr gRPC API in your application"
type: docs

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daprdocs/content/en/developing-applications/integrations/workflows.md Normal file
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---
type: docs
title: "Build workflows with Logic Apps"
linkTitle: "Workflows"
description: "Learn how to build workflows using Dapr Workflows and Logic Apps"
weight: 4000
---
To enable developers to easily build workflow applications that use Dapr’s capabilities including diagnostics and multi-language support, you can use Dapr workflows. Dapr integrates with workflow engines such as Logic Apps. For more information read [cloud-native workflows using Dapr and Logic Apps](https://cloudblogs.microsoft.com/opensource/2020/05/26/announcing-cloud-native-workflows-dapr-logic-apps/) and visit the [Dapr workflow](https://github.com/dapr/workflows) repo to try out the samples.