Category Archives : Database

03

Dec

Modernize your Java Spring Boot application with Azure Database for MySQL

This blog post is co-authored by Parikshit Savjani, Senior Program Manager, Azure OSS Database service.

Spring is a well-known Java-based framework for building web and enterprise applications addressing the modern business needs. One of the advantages of using the Spring Boot framework is that it simplifies the data access from relational and NoSQL data stores. Spring Boot framework with MySQL Database backend is one of the established patterns to meet the online transactional processing needs of business applications. The modern business applications are built and deployed on cloud native microservice platforms like Azure Kubernetes service (AKS) moving away from traditional monolithic design to meet the elastic scale and portability needs. The databases on the other hand have more stateful requirements with atomicity, consistency, durability, resiliency, and zero data loss across failures. It is therefore more suited to run databases outside of Kubernetes environment on managed database services like Azure Database for MySQL service which meets these requirements.

Developers and customers can easily build and deploy their Java Spring Boot microservices application in Azure platform thereby improving developer productivity and enabling businesses to achieve more with the following solutions.

Azure DevOps, a developer platform to build automated and robust CI/CD pipelines. Azure

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27

Nov

Azure Cosmos DB and multi-tenant systems
Azure Cosmos DB and multi-tenant systems

In this blog post, we will discuss how to build a multi-tenant system on Azure Cosmos DB. Azure Cosmos DB itself is a multi-tenant PaaS offering on Microsoft Azure. Building a multi-tenant system on another multi-tenant system can be challenging, but Azure provides us all the tools to make our task easy. An example of a multi-tenant system would be a company providing background check services that any other company can use in their HR system. For the purposes of this blog post we are going to use this example and continue from the point of view of company providing background checks as a service. We will refer to this company as “publisher.”

Let’s begin to discuss how you can build a multi-tenant system that will store sensitive user data. Data isolation and security is the most important aspect of any system. We must design the system so that each tenant’s data is isolated from one another. The data stored in any given tenant should be divided into compartments so one tenant breach cannot flow into another tenant. This would be similar to compartmentalizing the hull of a ship to reduce floodability.

To increase the isolation and protection of customer

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21

Nov

How to develop secure applications using Azure Cosmos DB
How to develop secure applications using Azure Cosmos DB

Before we begin to discuss how to develop secure applications using Azure Cosmos DB, we should also highlight some of the different layers of security that Azure Cosmos DB offers. The following image illustrates these various layers of security:

Azure Cosmos DB is a ring zero Azure service, this means it will be available in any new Azure data center as soon as it goes online and must keep all its compliance certificates current. Azure Cosmos DB has a plethora of certifications that you can read more about in the blog post “Azure #CosmosDB: Secure, private, compliant”.

The first layer of Azure provides physical safety of data centers and continuous protections from DDoS attacks. Azure has dedicated teams to continuously monitor the security issues. All Azure services run a common security agent to collect anomalous activity. Production resources are patched regularly and all the secrets, certificates, or passwords have a defined lifetime. These certificates or secrets should be rotated after they expire. All the production ports in Azure Cosmos DB are scanned and penetration tested regularly. The source code is scanned for security issues and they require two approvers before integrating into the product. For additional information, read more

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21

Nov

Visualize your Cosmos DB Gremlin API graph data with Linkurious enterprise

Data visualization is one of the most critical components for any kind of solution, and graph databases are no different. For Azure Cosmos DB, a highly-scalable and enterprise-ready visualization solution has been a common ask from customers. The need to visualize connected data is particularly present for both technical and non-technical users who face growing volumes of increasingly complex data. Extracting actionable insights from large and complex datasets is often difficult and time-consuming.

Interactive visualization tools allow for a faster understanding of complex data, and help users achieve a better understanding of problems. As result, users have a higher chance of discovering insights.

“Thanks to Azure Cosmos DB’s integrated Gremlin API, teams of analysts can now use Linkurious’ turnkey graph intelligence platform in combination with Azure Cosmos DB to detect and investigate threats hidden in complex connected data.” 

David Rapin, CTO and co-founder of Linkurious.

Today, we’re announcing that the popular graph visualization platform Linkurious enterprise is now available for Azure Cosmos DB Gremlin API databases. On this platform you can create reports and visualizations from graph data while still leveraging full create, read, update, and delete functionality. In addition to that, the product highlights enterprise-ready features including secured

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19

Nov

Real-time event processing with Azure Database for PostgreSQL and Event Grid integration

Most modern applications are built using events whether it is reacting to changes coming from IoT devices, responding to a new listing in a marketplace solution, or initiating business processes from customer requests. PostgreSQL is a popular open source database with rich extensibility to meet the event-based notification and distributed design needs of the modern application. PostgreSQL’s Notify functionality allows for sending a notification event as change feed to the listener channel specified in the database. With serverless platforms in Azure such as, Azure Event Grid a fully managed serverless event routing service, Azure Functions a serverless compute engine, and Azure Logic Apps a serverless workflow orchestration engine, it is easy to perform event-based processing and workflows responding to the events in real-time.

Consider a marketplace e-commerce solution where buyers meet sellers. A typical marketplace solution is a collection of microservices providing a seamless buying and selling experience to the end users. The modern microservices design leverages purpose-built app platforms and data stores, which are optimized for scenarios while working in tandem to achieve a unified experience for end users. For example, graph store is better suited for recommendation engine, while a relational datastore like PostgreSQL is suited for relational

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12

Nov

https://azure.microsoft.com/blog/microsoft-azure-tutorial-how-to-integrate-azure-functions-with-mongodb/Special thanks to Graham Neray and the MongoDB team for their contribution to this blog post.  We’re excited to share that teams can now use the global cloud database MongoDB Atlas for free on Microsoft Azure. The newly available free READ MORE

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08

Nov

Static Data Masking for Azure SQL Database and SQL Server
Static Data Masking for Azure SQL Database and SQL Server

The SQL Security team is pleased to share the public preview release of Static Data Masking. Static Data Masking is a data protection feature that helps users sanitize sensitive data in a copy of their SQL databases.  

Use cases

Static Data Masking is designed to help organizations create a sanitized copy of their databases where all sensitive information has been altered in a way that makes the copy sharable with non-production users. Static Data Masking can be used for:

  Development and testing Analytics and business reporting Troubleshooting Sharing the database with a consultant, a research team, or any third-party  

Static Data Masking facilitates compliance with security requirements such as the separation between production and dev/test environments. For organizations subject to GDPR, the feature is a convenient tool to remove all personal information while preserving the structure of the database for further processing.

How Static Data Masking works

With Static Data Masking, the user configures how masking operates for each column selected inside the database. Static Data Masking will then replace data in the database copy with new, masked data generated according to that configuration. Original data cannot be unmasked

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06

Nov

Run your LOB applications with PostgreSQL powered by the plv8 extension

We are extremely excited to share that the plv8 extension for PostgreSQL is now enabled in all generally available regions of Microsoft Azure Database for PostgreSQL. The plv8 extension was one of the highly requested UserVoice asks from our growing customer base and the PostgreSQL community. It is a popular community extension that unlocks new scenarios and possibilities, it also enables developers to write their functions in JavaScript which can be called from SQL.

PostgreSQL is an established open source database with strong native JSON capabilities, and the plv8 extension further enhances it by integrating the JavaScript v8 engine with SQL. Marten library is one such library that uses the plv8 extension to allow developers to leverage PostgreSQL as a NoSQL document store or event store. Using PostgreSQL as a document database opens new possibilities for designing and developing retail cart applications, marketplace solutions, IoT event processing, and LOB applications.

Enterprises, small and medium businesses, as well as ISVs can now accelerate the development and deployments of their LOB applications on the managed Azure Database for PostgreSQL service. This helps shorten the time to market.

Let us see an example of how one can use the plv8 extension with Azure

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05

Nov

Best practices for alerting on metrics with Azure Database for PostgreSQL monitoring

Whether you are a developer, database administrator, site reliability engineer, or a DevOps professional, monitoring databases is an important part of maintaining the reliability, availability, and performance of your PostgreSQL server. There are various metrics available for you in Microsoft Azure Database for PostgreSQL to get insights on the behavior of the server. You can also set alerts on these metrics using the Azure portal or Azure CLI.

With modern applications evolving from a traditional on-premises approach to becoming more hybrid or cloud-native, there is also a need to adopt some best practices for a successful monitoring strategy on a hybrid and public cloud. Here are some example best practices for using monitoring data on your PostgreSQL server, and areas you can consider improving based on these various metrics.

Active connections

Sample threshold (percentage or value): 80 percent of total connection limit for greater than or equal to 30 minutes, checked every five minutes.

Things to check: If you notice that active connections are at 80 percent of the total limit for the past half hour, verify if this is expected based on the workload. If you think the load is expected, active connections limit can be increased by

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05

Nov

Best practices for alerting on metrics with Azure Database for MySQL monitoring

Whether you are a developer, database administrator, site reliability engineer, or a DevOps professional, monitoring databases is an important part of maintaining the reliability, availability, and performance of your PostgreSQL server. There are various metrics available for you in Microsoft Azure Database for MySQL to get insights on the behavior of the server. You can also set alerts on these metrics using the Azure portal or Azure CLI.

With modern applications evolving from a traditional on-premises approach to becoming more hybrid or cloud-native, there is also a need to adopt some best practices for a successful monitoring strategy on a hybrid and public cloud. Here are some example best practices on how you can use monitoring data on your MySQL server, and areas you can consider improving based on these various metrics.

Active connections

Sample threshold (percentage or value): 80 percent of total connection limit for greater than or equal to 30 minutes, checked every five minutes.

Things to check: If you notice that active connections are at 80 percent of the total limit for the past half hour, verify if this is expected based on the workload. If you think the load is expected, active connections limit can

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