Implementing database change notification using SignalR and Azure Functions
This post is about implementing database change notification using SignalR and Azure Functions. In this post we will using Azure Function with SQL trigger for change identification and Azure SignalR...
Azure SQL triggers for Azure Functions
This post is about Azure SQL trigger for Azure Functions. The Azure SQL trigger uses SQL change tracking functionality to...
Continue readingAzure SQL output binding for Azure Functions
This post is about Azure SQL output binding for Azure Functions - this feature is preview right now. The output...
Continue readingAzure SQL input binding for Azure Functions
This post is about Azure SQL input binding for Azure Functions - this feature is preview right now. The input binding helps us to read data from SQL Server in Azure Functions. To write to SQL Server we need to use the Output binding. Azure function now offers SQL trigger as well, we will be discussing this in a later post.
Configure Auto Scaling in Azure App Service
This post is about configuring automatic scaling in Azure App Service. Automatic scaling is a new feature available in Azure App Service scale out configuration. The feature of automatic scaling is a novel way to expand the capacity of your web applications and App Service Plans without having to make scaling decisions yourself. It differs from the existing Azure autoscale, which allows you to specify scaling rules according to schedules and resources. With automatic scaling, you can modify scaling settings to enhance your application’s performance and prevent delays in starting up. This Automatic scaling feature is in preview. And it is available for Premium Pv2 and Pv3 pricing tiers, and supported for all app types: Windows, Linux, and Windows container.
Getting started with Data API builder for Azure SQL Database or SQL Server
This post is about Data API builder, which is tool helps to provide modern REST and GraphQL endpoints to your Azure Databases. By utilizing the data API builder, you can make your database objects available through REST or GraphQL endpoints, allowing you to access your data using contemporary approaches on any device, language or platform. The integrated policy engine is both adaptable and versatile, supporting conventional functionalities such as pagination, filtering, projection and sorting. Consequently, creating CRUD backend services can be accomplished within a matter of minutes instead of days or hours, significantly boosting developer efficiency to an unprecedented level.
Improve application startup time with EF Core compiled models
This post is about improving EF Core performance with compiled models. EF Core compiled models feature introduced in EF Core 6.0 which will provide both better startup performance, as well as generally better performance when accessing the model. This feature is very useful when you’re using very large models with relationships.
Improving EF Core performance with Compiled Queries
This post is about improving EF Core performance with Compiled queries. From EF Core 2.0 onwards, EF Core supports compiled queries, which helps developers to compile the queries in advance and executed when application executes the query. By default EF Core automatically compiles and caches your queries using a hashed representation of the query expression - when the code runs the previously executed query, EF Core lookup the cache with the hash value and returns the compiled query from the cache. We can explicitly compile the query upfront and invoke the compiled query. To compile the query, EF Core exposes two extension methods in EF class - EF.CompileQuery() and EF.CompileAsyncQuery(). These methods helps us to create compiled queries and call them using a delegate.