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Tag Archives: azure

Tips and Trick for Azure Functions

These are my favourite tips and tricks. These are only those who me and my colleguages have tried out.

Architecture tips

Keep it slim

Functions should do one thing and they should do it well. When you develop it in C# and Visual Studio, it is so tempting to develop a “microservice” in a good way, you add interfaces, implement good patterns, and all of a sudden you get a monolith packaged in a microservice. If your function grows, stop, rethink. Better to see how it input and output bindings can be used. Also orchestration with Logic Apps or Durable Functions can help.

Automated Deployment

It might be an obvious one, but it is super easy to setup CI/CD for Azure Functions in Azure DevOps. Set it up as early as possible. Don’t rely on publishing from Visual Studio.

Environments

Different environments like Production and Staging (Test, UAT, QAT, verification), and DEV are not straight forward anymore, when everything is reactive and micro. But it is good to have at least two setups: one for Production and one for Staging. Especially separating the storage accounts has been proven to be a success story. You can have the same queue name, but different connections. Deploying to Staging and Production will be easier. The functions in different “environments” will write/read a queue with the same name but in different storage accounts.

I also find it convenient to have postfix in the azure function names, like collect-shipments-staging and collect-shipments-production.

If it is possible, use separate resource groups for the “environments”.

Tips for performance

One instance at a time

Use host.json to prevent parallelization

{
  "queues": {
      "batchSize": 1,
      "newBatchThreshold": 0
    }
}

Add messages to a queue as output

Instead of adding queue messages in code, define it as an output. You can even add multiple messages. This saves you instantiating of CloudStorageAccount which is a good thing for performance.

Take Last Run into account

Just check the timer parameter: timer.Schedule.Last for the time when your Azure Function ran last.

Reuse HttpClient

This tip is from CloudBurst in Malmö in September 2019. Eventhough your function runs on a consumption plan, the chance is big that your code will run on the same server, which means that you can reuse some resources, like HttpClient.

Simple Build for dotnet new react

I created a sample ASP.NET Core app with React. 

dotnet new react

 

 

Then it took a couple of hours to get the build to work. Here is my working azure-pipelines.yml:

 

Resources:

S01E01 IoT: Posting Temperature from Raspberry Pi to Azure

Recently I have looked more at IoT, Raspberry Pi in my spare time. In my blog post I want to share my experience in a series of posts. This post is about measuring temperature, humidity and pressure with Raspberry Pi 2 Model B and Sense Hat and posting this data to Azure Table Storage.

I followed this tutorial for connecting to azure with python and these instructions for reading data from Sense Hat.

The python script is on github. Along the way I learned that only python 2.x can be used with azure and table names cannot contain underscore (I got Bad Request error when I tried to create a table with the name “climate_data”). But overall, the process was straightforward. The temperature is not correct, maybe because the sensor is inbetween Raspberry Pi and Sense Hat where it gets warm. But it is just a Proof-of-Concept.

I have used Visual Studio 2015 to see the data in Azure Table Storage. For that I needed to install Azure SDK 2.7. There are many other “explorers” for Azure Storage.

sense-001

Other resources

Accessing Azure from Linux and Mac

Improvement #1 Corrected Temperature

I found a formula for calculating more correct temperature on the raspberry pi forum.

Ta = 0.0071*Tm*Tm+0.86*Tm-10.0
Tm = measured with the temp+humidity sensor
Ta = ambient temperature

I also added a notifcation when data is sent by showing an “S” on the Sense Hat.

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