With strong organization and design for our development teams, cloud infrastructure and security considerations, we’ll now extract Azure cost information that we can share with our organization. In addition, we will see that we can retain this information if needed to track growth (or reduction) in costs. This step is important as it will allow our teams to have an insight into their development and it will also be another audit we can use on the security side to catch unusual growth (or significant reductions) in resource costs that may be the result of an attacker. Our ultimate goal with tracking these costs and sharing them with teams is to improve our development and possibly re-organize it as needed, giving us the ability to further reduce our spending.Read more »
We’ve looked at both the organization and development side of managing Azure costs. One risk we have is attackers who compromise an account and mis-scale resources (such as scaling up), driving up our costs. Another scenario is attackers scaling resources too low that affects client’s ability to do their work (performance problems) – a separate risk that may result in lower costs on the cloud side, but higher costs against our reputation. A third risk is reconnaissance of our Azure use: this allows the attackers to get information about our design and later make a wide range of attacks that will appear as normal to us – in this case, Azure costs may be only one of the impacts with other impacts being as severe.Read more »
Depending on our design and security, we can create functions or use built-in tools to control our Azure costs. In some contexts, we may look at the overall cost of what tools we’re using, which the Azure portal conveniently shows. Applying what we’ve looked at on the organization and development level, we can organize resources on their design (or ad hoc, as we’ll see) along with creating scripts that control our scale for situations where we may want higher or lower scale. We’ll look at both of these scenarios and how they can help us in both organization and development contexts.Read more »
Azure costs can quickly mount, without careful supervision and management. This article will detail cost mitigation strategies using security and designRead more »
This article will fully cover the code snippet SQL developer productivity feature in Azure Data Studio including a list of available snippets and examples of how to create custom code snippetsRead more »
This guide is all about provisioning SQL Server 2019 using Azure Container Instance (ACI), including the installation and configuration. In this article, we talk about the Azure Container Instance (ACI), the Azure PowerShell module, installation and configuration of SQL Server using the Azure PowerShell module, and automation of installation and deployment using templates.Read more »
In this guide, we’ll discuss more about migrating a SQL Server database to Azure SQL Database using SQL Server Transactional Replication.
As we’ve worked with Azure Cosmos DB, we’ve seen that we can store data within fields and the fields of each document don’t always have to match – though we still want some organization for querying. The fields and values storage becomes useful when working with object-oriented languages as these fields can be keys that we use with values that we extract as properties. For an example, the below PowerShell line creates a JSON document in an object and we can see that we can extract the values of these keys in the JSON object.Read more »
Since we will sometimes require removing documents in Azure Cosmos DB, we’ll want to be able to specify the documents for removal. In some cases, this will be as simple as specifying a field for removal, such as removing one type of workout in our temporary database we’ve created. In other delete situations, we’ll want to remove if the value of the field isn’t what we expect – such as greater than what we want. This applies to updates as well – we may want to drill into a specific value range for an update. In this tip, we’ll look at using operators with strings, numeric types and dates.Read more »
In the first part of this series Getting Started with Azure Cosmos DB, we looked at using Azure Cosmos DB for saving an individual’s fitness routine and why this database structure is better for this data than a SQL database while also showing that we still have to organize our structure like a file system organizes files. In this part of our series, we’ll begin looking at the terminology translation between NoSQL and SQL along with running updates for our documents and queries with filters that return some fields in our document, but not other fields.
In the past two years, we’ve seen an explosion in growth with document-oriented databases like Azure Cosmos DB. MongoDB – one of the major document databases – went live on the Nasdaq and attracted some attention in the past year as well. While more developers are using the document structure for some appropriate data models, less than 10 years ago, some in the industry were predicting that document databases were unnecessary and wouldn’t last because all data could be flattened to fit the SQL model. I took the opposite approach, being an early adopter of MongoDB along with continuing to use SQL databases as I saw opportunities in both SQL and NoSQL for various data structures. While some data do fit the SQL model and SQL will continue to exist, some data are best for document databases, like Azure Cosmos DB. In this series, we’ll be looking at the why and how of document databases.
In this article, we will learn Key Performance Indicators usage in Power BI and solve a business case problem through Power BI.Read more »
Azure Machine Learning (also known as Azure ML) is cloud-based machine learning solution of Microsoft. Microsoft Azure Machine Learning is a fully-managed cloud-based service that provides the ability to create and train predictive analytic solutions. Another advantage of Azure ML is that you can access and easily make changes anywhere in machine learning models with help of Microsoft Azure Machine Learning Studio.Read more »
In the previous article on Azure Cosmos DB, we reviewed NoSQL concepts and how to integrate with the Microsoft Azure platform-as-a-service model using the API. After working as a database engineer for over a decade, I feel that this technology is the future for many organizations for various reasons. I had that in mind as I wrote this article which will provide basic information and help you to get started with MongoDB API integration. The MongoDB API works with BSON documents. BSON is MongoDB’s binary-encoded-version of JSON, and it extends the JSON model with additional language feature support. It’s a great effort from Microsoft to build the enterprise solutions which provide flexibility in manage distributed data along with scalable option.Read more »
This article is part 4 of the series for SQL Server 2019 Enhanced PolyBase. Let quickly recap the previous articles.Read more »
In my previous article, I’ve discussed a lot about the Graph database implementation with SQL Server 2017. In this case, we’ll see a walk-through of Graph API integration with Azure Cosmos DB.
Before we jump into the concepts though, let’s take a high-level overview of NoSQL databases. A NoSQL database is designed in such a way that no extra efforts are needed for the database to be distributed because NoSQL Database designed that way.Read more »
In this article on PolyBase, we will explore more use case scenarios for external tables using T-SQL.Read more »
In the previous article of the series, we took an overview of PolyBase in SQL Server 2017. We also learned about the Azure Data Studio and SQL Server 2019 preview extension to explore SQL Server 2019 features.Read more »
There is a growing trend among professionals and entire companies to move away from email as a primary means of communication and are even adopting alternative technologies. One of the most popular of these is Slack. Slack is a new kind of messaging and communication platform between colleagues, team or community members that allows them to integrate a lot of services including Visual Studio Team Service, Jira and GitHub.Read more »
The real-life requirement
Disclaimer: I assume dear Reader, that you are more than familiar with the general concept of partitioning and star schema modeling. The intended audience is people who used to be called BI developers in the past (with a good amount of experience), but they have all sorts of different titles nowadays that I can’t keep up with… I won’t provide a full Visual Studio solution that you can download and just run without any changes or configuration, but I will give you code can be used after parameterizing according to your own environment.Read more »
SQL Data Sync allows you to synchronize data across multiple Azure SQL databases and on-premises SQL Server databases.
In this article, how to synchronize Azure SQL database with on-premises SQL Server database will be shown.Read more »
SQL Data Sync is a service that allows synchronizing data across multiple Azure SQL databases and on-premises SQL Server databases.
In this article, a base concept of how the SQL Data Sync service works will be explained as well as what the requirements and limitations are when want to create data synchronization by using SQL Data SyncRead more »
The below screenshots and code samples are valid at the time of writing (May 2018) but as things in Azure can change so quickly, please check the latest documentation if a code sample doesn’t work as expected!Read more »
If you noticed a tool we missed, please let us know in the comments below. Read more »