In today’s software development and deployment world, the use of DevOps methodology is essential. This methodology focuses on fostering collaboration between developers and system administrators within a company, creating a seamless development cycle and accelerating the delivery of software products.
The DevOps trend emerged in 2008 when Patrick Debois attended the Agile conference and founded the Agile Systems Administration Group with Andrew Shafer. Since then, progressive DevOps tools have been widely used in many companies seeking to enhance the efficiency of software development and operations.
Despite the growing prominence of DevOps principles in the software delivery process, there remains a challenge in integrating database development with the DevOps process.
Challenges in Database DevOps and Potential Future Developments
The philosophy of Database DevOps is focused on simplifying and improving database management by automating various aspects of the database lifecycle. While this process is highly effective, it can also present several challenges, including:
In the DevOps environment, continuous deployment of software is facilitated through the use of a CI/CD pipeline. However, this approach does not easily translate to databases. For instance, adding schema changes requires a strategy for migrating old data to a new structure, making the continuous deployment of databases more challenging.
While applications can be highly scalable within a microservice architecture, databases may experience decreased performance as they increase in size.
The database management process does not typically permit reverting back to a previous version of a database, making it difficult to fix any issues that arise in the production environment. This can potentially lead to database breakdowns.
Challenges with Relational Databases in Microservice Architecture:
Another challenge in Database DevOps is the incompatibility between relational databases and the microservice architecture. Microservices have a non-shared architecture to eliminate dependencies on other microservices and protect against failures.
As the field of IT continues to progress at a rapid pace, we can expect to see significant changes in the database development and deployment process in the coming years, addressing current needs. These changes may include:
- Continuous delivery: The integration of a database pipeline into an application pipeline, synchronizing database changes with those of the application, even if multiple applications or microservices use the database.
- Rational cloud-native database solutions: Integration of solutions with DevOps CI/CD pipelines through APIs and cloud-native infrastructure.
- Equal database deployment: The ability to deploy databases to cloud environments, Docker containers, Kubernetes, and all operating systems in the same way.
- Scalability: Dynamic database scaling based on changes in workloads and user demands.
- Source control: Maintenance of database code through version control, allowing for the review of database changes similar to application changes.
The biggest challenge in managing databases from a DevOps perspective is uncertainty regarding the timeframe for overcoming these obstacles. Despite this, there are ways to address these challenges and automate database deployment today. DevOps Automation for SQL Server is a tool that can significantly enhance the Database DevOps practices of your team. This tool is included in both the SQL Tools pack and dbForge Studio for SQL Server.
DevOps Automation for SQL Server, in combination with dbForge Studio for SQL Server, facilitates the database lifecycle through five stages displayed in the image below.
At the Development stage, database developers modify the database schema. The Version Control stage involves committing the changes to the version control system, such as Git. The Build stage then compiles the database from .sql files on the SQL Server, resulting in the desired database.
However, the process does not end there. The Unit Test stage is critical in ensuring that the database functions correctly after changes have been made. Testing is performed using SQL unit tests.
The Publish stage brings the CI process to a conclusion. At this stage, the NuGet package or ZIP is published to enable sharing. Additionally, you may generate database documentation and include it in the package. Finally, the NuGet package or ZIP is published in the NuGet repository or added to a separate folder.
DevOps principles have become a prevalent trend in many companies, with developers seeking to automate manual operations in the software product deployment process. Reducing human intervention in product delivery enables faster release cycles with fewer failures.
However, the deployment of databases presents unique challenges that are not easily overcome. Fortunately, many of these obstacles can be addressed with Devart products. To elevate your database deployment process, consider trying the 30-day trial versions of dbForge Studio for SQL Server and DevOps Automation for SQL Server.