Azure

Eliminate Cold Starts by Predicting Invocations of Serverless Functions

Azure Functions introduce a data-driven strategy to pre-warm serverless applications right before the next request comes in

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Serverless in the Wild: Azure Functions Production Usage Statistics

Insightful statistics about the actual production usage of Azure Functions, based on the data from Microsoft's paper

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When Does Cold Start Happen on Azure Functions?

The first cold start happens when the very first request comes in after deployment. After that request is processed, the instance stays alive for the time being to be reused for subsequent requests.

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Comparison of Cold Starts in Serverless Functions across AWS, Azure, and GCP

AWS Lambda, Azure Functions, and Google Cloud Functions compared in terms of cold starts across all supported languages

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Cold Starts in Azure Functions

Influence of dependecies, language, runtime selection on Consumption Plan

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Azure Functions: Cold Start Duration per Language

The following chart shows the typical range of cold starts in Azure Functions, broken down per language. The darker ranges are the most common 67% of durations, and lighter ranges include 95%.

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Hosting Azure Functions in Google Cloud Run

Running Azure Functions Docker container inside Google Cloud Run managed service

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Santa Brings Cloud to Every Developer

How Santa Cloud uses F# and Pulumi to bring cloud resources to the homes of software engineers.

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Choosing the Best Deployment Tool for Your Serverless Applications

Factors to consider while deploying cloud infrastructure for serverless apps.

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AWS Lambda vs. Azure Functions: 10 Major Differences

A comparison AWS Lambda with Azure Functions, focusing on their unique features and limitations.

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How To Deploy a Function App with KEDA (Kubernetes-based Event-Driven Autoscaling)

Hosting Azure Functions in Kubernetes: how it works and the simplest way to get started.

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How To Build Globally Distributed Applications with Azure Cosmos DB and Pulumi

A reusable component to build highly-available, low-latency applications on Azure

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Ten Pearls With Azure Functions in Pulumi

Ten bite-sized code snippets that use Pulumi to build serverless applications with Azure Functions and infrastructure as code.

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How to Measure the Cost of Azure Functions

Azure pricing can be complicated—to get the most value out of your cloud platform, you need to know how to track spend and measure the costs incurred by Azure Functions.

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7 Ways to Deal with Application Secrets in Azure

From config files to Key Vault and role-based access, learn how infrastructure as code helps manage application secrets in Azure.

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Load-Testing Azure Functions with Loader.io

Verifying your Function App as a valid target for the cloud load testing.

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How Azure CLI Manages Your Access Tokens

Azure CLI is a powerful tool to manage your cloud resources. Where does it store the sensitive information and why might you want to care?

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Globally-distributed Serverless Application in 100 Lines of Code. Infrastructure Included!

Building a serverless application on Azure with both the data store and the HTTP endpoint located close to end users for fast response time.

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Hosting a Static Website on Azure with Pulumi

Static websites are back in the mainstream these days. Setting up the infrastructure to serve a static website in Azure is a task where Pulumi shines.

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Serverless as Simple Callbacks with Pulumi and Azure Functions

The simplest way to take a Node.js function and deploy it to Azure cloud as an HTTP endpoint using Pulumi.

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Level up your Azure Platform as a Service applications with Pulumi

Leverage Pulumi for continuous delivery of code and infrastructure to Azure PaaS. An ASP.NET Core application running on App Service and DevOps pipelines.

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Reducing Cold Start Duration in Azure Functions

The influence of the deployment method, application insights, and more on Azure Functions cold starts.

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Concurrency and Isolation in Serverless Functions

Exploring approaches to sharing or isolating resources between multiple executions of the same cloud function and the associated trade-offs.

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Visualizing Cold Starts

Serverless cold starts illustrated with animated GIFs.

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Serverless at Scale: Serving StackOverflow-like Traffic

Scalability test for HTTP-triggered serverless functions across AWS, Azure and GCP

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A Fairy Tale of F# and Durable Functions

How F# and Azure Durable Functions make children happy (most developers are still kids at heart)

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Making Sense of Azure Durable Functions

Why and How of Stateful Workflows on top of serverless functions

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From 0 to 1000 Instances: How Serverless Providers Scale Queue Processing

Comparison of queue processing scalability for FaaS across AWS, Azure and GCP

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Azure Functions V2 Is Released, How Performant Is It?

Comparison of performance benchmarks for Azure Functions V1 and V2

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Serverless: Cold Start War

Comparison of cold start statistics for FaaS across AWS, Azure and GCP

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Programmable Cloud: Provisioning Azure App Service with Pulumi

Exploring Infrastructure-as-Code approach suggested by Pulumi with examples around provisioning Azure App Service

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Cold Starts Beyond First Request in Azure Functions

Can we avoid cold starts by keeping Functions warm, and will cold starts occur on scale out? Let's try!

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Azure Functions: Cold Starts in Numbers

Auto-provisioning and auto-scalability are the killer features of Function-as-a-Service cloud offerings, and Azure Functions in particular. One drawback of such dynamic provisioning is a phenomenon called “Cold Start”.

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Azure Durable Functions in F#

Azure Functions are designed for stateless, fast-to-execute, simple actions. Typically, they are triggered by an HTTP call or a queue message, then they read something from the storage or database and return the result to the caller or send it to another queue.

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Load Testing Azure SQL Database by Copying Traffic from Production SQL Server

Azure SQL Database is a managed service that provides low-maintenance SQL Server instances in the cloud. You don’t have to run and update VMs, or even take backups and setup failover clusters.

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Azure Functions Get More Scalable and Elastic

Back in August this year, I’ve posted Azure Functions: Are They Really Infinitely Scalable and Elastic? with two experiments about Azure Function App auto scaling.

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Precompiled Azure Functions in F#

This post is giving a start to F# Advent Calendar in English 2017. Please follow the calendar for all the great posts to come.

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Azure Function Triggered by Azure Event Grid

Update: I missed the elephant in the room. There actually exists a specialized trigger for Event Grid binding. In the portal, just select Experimental in Scenario drop down while creating the function.

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Wanted: Effectively-Once Processing in Azure

Are there any known patterns / tools / frameworks to provide scalable, stateful, effectively-once, end-to-end processing of messages, to be hosted in Azure?

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Azure Functions: Are They Really Infinitely Scalable and Elastic?

Updated results are available at Azure Functions Get More Scalable and Elastic. Automatic elastic scaling is a built-in feature of Serverless computing paradigm. One doesn’t have to provision servers anymore, they just need to write code that will be provisioned on as many servers as needed based on the actual load.

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Authoring a Custom Binding for Azure Functions

The process of creating a custom binding for Azure Functions.

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Custom Autoscaling with Durable Functions

Leverage Azure Durable Functions to scale-out and scale-in App Service based on a custom metric

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Custom Autoscaling of Azure App Service with a Function App

How to scale-out and scale-in App Service based on a custom metric

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Sending Large Batches to Azure Service Bus

Azure Service Bus client supports sending messages in batches. However, the size of a single batch must stay below 256k bytes, otherwise the whole batch will get rejected.

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Finding Lost Events in Azure Application Insights

One of the ways we use Azure Application Insights is tracking custom application-specific events. For instance, every time a data point from an IoT device comes in, we log an AppInsights event.

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Reliable Consumer of Azure Event Hubs

Azure Event Hubs is a log-based messaging system-as-a-service in Azure cloud. It’s designed to be able to handle huge amount of data, and naturally supports multiple consumers.

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Azure Functions as a Facade for Azure Monitoring

Azure Functions are the Function-as-a-Service offering from Microsoft Azure cloud. Basically, an Azure Function is a piece of code which gets executed by Azure every time an event of some kind happens.

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Azure Service Bus Entity Metrics .NET APIs

Getting advanced metrics out of Azure Service Bus in C# code

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Azure SQL Databases: Backups, Disaster Recovery, Import and Export

Azure SQL Database is a managed cloud database-as-a-service. It provides application developers with SQL Server databases which are hosted in the cloud and fully managed by Microsoft.

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Getting started with Azure Application Insights in Aurelia

Azure Application Insights is an analytics service to monitor live web applications, diagnose performance issues, and understand what users actually do with the app. Aurelia is a modern and slick single-page application framework.

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Fire-and-forget in Service Fabric actors

At the recent Webscale Architecture meetup we discussed two implementations of the Actor model in the .NET ecosystem: Akka.NET and Azure Service Fabric Actors. One important discussion was around Ask vs Tell call model.

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Deploy your SPA to Azure

In this post I want to share a simple tutorial on how to deploy your single page application into the Azure cloud. I have a Single Page Application (SPA) done with HTML/JavaScript in a separate local Git repository. I alsp have a ASP.NET 4.6 Web API service which serves the data for SPA in another local Git repository. Now I want to deploy both to the Azure cloud, and make it easy to deploy changes in the future.

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