Azure Data Factory and Virtual Networks – Choosing the right integration runtime
Azure Data Factory is Microsoft’s cloud service for creating integration pipelines between different data sources and orchestrating these pipelines to create fully automated integration solutions. Data Factory provides capabilities for simply copying data from one place to another, performing transformations on the data and even employing custom functionality from a wide array of different separate … More Azure Data Factory and Virtual Networks – Choosing the right integration runtime
How to: Using managed identities to access Cosmos DB data via RBAC and disabling authentication via keys
Historically, authenticating against Microsoft’s Cosmos DB service has only been possible in one of two ways: Either by using keys – long passwords that grant you either full read or read-write access to all data in the Cosmos DB account – or by building a custom user management solution that generates short-lived tokens to specific … More How to: Using managed identities to access Cosmos DB data via RBAC and disabling authentication via keys
How to: Easily deploying Azure Machine Learning models to Azure App Service
In this How to I assume you to have some prior knowledge and experience with Azure and Azure Machine Learning. If the latter is completely new you, I whole-heartedly recommend the quite excellent and free “Create no-code predictive models with Azure Machine Learning” learning path by Microsoft to get started! Azure Machine Learning is a … More How to: Easily deploying Azure Machine Learning models to Azure App Service
Life cycle of a machine learning software project
Whenever you are starting on a new project of any kind, it’s good to be aware of how that project is likely to pan out and what kind of milestones and challenges you should expect to meet. In the field of software engineering, we have lots of different process models and methodologies already to give … More Life cycle of a machine learning software project
How to: Automating Automated Machine Learning in Azure Part 2 – Deploying models and preparing training data
This post is the second part in a two-piece series on automating Automated Machine Learning. If you have not yet read the first part, I recommend checking it out first since the solution shown here will be built on top of where we left off last time. Previously I showed you how you can automate … More How to: Automating Automated Machine Learning in Azure Part 2 – Deploying models and preparing training data
Ignite 2021 – My top three things to look out for
This year we had the pleasure of enjoying Microsoft Ignite’s plethora of release already in March, only six months after the previous event in September 2020. For me the best part of these Microsoft conferences is always getting my hands on the book of news and going through it, looking for new upcoming things that … More Ignite 2021 – My top three things to look out for
How to: Automating Automated Machine Learning in Azure Part 1 – Scheduling AutoML runs
A key concern with machine learning projects is being able to adapt to changes in the real world. This is especially true when the problem you are trying to solve evolves constantly, as any model training is always done using historical data and as such after a while it may no longer represent the problem … More How to: Automating Automated Machine Learning in Azure Part 1 – Scheduling AutoML runs
Getting the most out of serverless Azure SQL
Microsoft released the serverless compute tier for Azure SQL databases to General Availability a little over a year ago, back in November 2019. Despite the fact that it’s been a while already, based on my personal experiences people are still a bit unfamiliar with serverless Azure SQL – what it is, how it works and, … More Getting the most out of serverless Azure SQL
Joonas Äijälä 