Sinking Events from MQTT to Timescale with Dapr and Rust
Learn how to forward events from MQTT to TimescaleDB (Postgres) at high-speed and low latencies with Dapr and Rust
Dapr
17 posts
Sinking events from Event Hub to CosmosDB with Dapr
Learn how to quickly store events from Event Hub into CosmosDB with Dapr
Using Pino as logging service in the Dapr JS SDK
Dapr JS SDK enables custom logging service for Pino apps through simple initiation and implementation of custom interface. Learn how you can do so in this article!
Integrating Dapr JS SDK logging into NestJS
Learn how to integrate Dapr JS SDK logging into your NestJS application for improved tracking and debugging. Our easy-to-follow tutorial shows you how to use Dapr's logging capabilities within your NestJS app for efficient, scalable server-side development.
Dapr JS SDK - Getting Started with PubSub Event Processing
Subscribe to Events from your PubSub system in just 3 lines of code with the Dapr JS SDK!
Create an Azure IoT Hub Stream Processor with Dapr
💡Check Out all Dapr Posts Creating a stream processor is always an interesting task, you want to be able to take incoming message and process them one by one, executing some actions along the way. Typically, we would use Apache Spark or Apache Flink to process these incoming streams, but...
Integrate Dapr with Nest.js and the Dapr JS SDK
As the official maintainer of the Dapr JS SDK, I am always looking on how we can improve our documentation, tooling and API to integrate Dapr through Javascript. Recently, I started working on Tinx.ai where I am using Dapr to host the Backend and send events to my event...
Enabling Serverless AI with Azure Container Apps and Dapr
In my previous post I explained how you can get started with Container Apps. The one missing piece of that puzzle is how you can utilize a queue behind to dynamically scale your workload based on items in a queue! This has been one my most difficult blog items so...
Running your AI Workload through Azure Container Apps
For a new project I am working on, I am utilizing a Queuing architecture where jobs come in and a cluster of containers is processing work on this queue. Each job takes an item from a queue, runs the item through its AI pipeline and spits out a JSON response....