Database Automation Guide
What is Database Automation?
Database automation means leveraging processes and tools to make admin tasks for a database simpler and safer. By using database automation for your database management, you not only have fewer deployment errors but also higher reliability and speed on changes implementations. Additionally, your DBAs will use less time on manually checking and updated code and have more time for patching, scaling, provisioning and other tasks.
The Empty Seat in DevOps
DevOps is changing the culture of IT. This movement is bringing application development and operations teams to the same table. Together, they are working to overcome all of the challenges facing the entire application delivery process.
However, while speed to market is important, businesses can’t forget about the internal implications of accelerated release cycles. With that in mind, there is one empty seat within the “DevOps Inner Circle”: the database administrator (DBA).
DBAs hold the keys to the database and the data within it, a business’s most important asset. But DB change innovation has not kept pace with agile development methodologies and database DevOps tooling that enable continuous delivery of software updates and changes. Many enterprises are still updating databases the same way they always have:
- Manual script review
- Manual validation
- Manual execution
- Individual specialized initiatives
As a result, application release cycles always slow down at the database release process and businesses struggle to keep up with customer demand. Because of this, it’s time databases and DBAs become part of DevOps and start leveraging database continuous delivery to meet demands and deliver more features. Including DBAs and database automation in DevOps can create better, more efficient teams and save time and money. DBAs can even help companies create better solutions for their customers’ needs or their own. And, by augmenting processes with database automation, DBAs and development teams can work better (and faster) than ever before.
Bringing DBAs into DevOps
Before database automation, developers needed to bring their database scripts to DBAs for review and validation to ensure compliance with technical, business, and regulatory standards. DBAs were buried in change requests necessitated by accelerated application release cycles. Inviting DBAs into the DevOps inner circle allows teams to consider the implications of new application changes and updates across the entire technology stack.
One of the founding principles behind DevOps is the breakdown of silos between development and operations teams. Product managers can easily translate customer needs. They can then give feedback to developers in a way they understand—using epics and themes, for example. This puts everyone on the same page so that application updates or changes can be quickly coded, tested, and delivered.
Before application updates can be released to users, they need to be translated into the changes that will update the database. This is where DevOps breakdowns occur. DBAs have to rely on manually intensive, timeworn, error-prone processes and methods to make sure the right changes are made to the database.
By inviting DBAs into DevOps, database updates that could “break the build” (like inserting a new column with a default value when the row count exceeds a million) can be found and fixed before the change reaches the database.
Having DBAs involved in release cycles sooner can also help ensure developers are coding with corporate compliance in mind. This makes changes to the database smoother while adhering to guidelines that DBAs have typically policed.
Breaking down silos and making teams more aware of bottlenecks in the release process lets them expect and avoid database issues. This means faster releases and fewer headaches for everyone.
Database Automation and DevOps
Faster release cycles are good for business, and not just because they get applications in front of end-users sooner. Continuous delivery cycles are designed to cut down application development costs and man-hours. But, while development timelines get shorter, the workload and time for database deployments get longer.
Enterprises can have many database configurations, so each change needs to be checked for compatibility. As the complexity of data repositories grows, so too does the time it takes to review and approve changes. In a recent IOUG survey on database manageability, 41 percent of respondents said changes took a week or more to approve. With multiple change requests coming to DBAs each day, it’s clear that sheer manpower can’t keep up with continuous delivery forever. Relief for DBAs is nonexistent without database automation.
Database automation software can protect against any unwanted outcomes. DB automation can help forecast the impact application changes will have on the database. With this information, DBAs can use those forecast reports to quickly discover issues instead of taking days to find them.
As part of a DevOps team, the DBA equipped with reasons for database automation can do more than save time and headaches for themselves. Protecting against errors that could break the build saves teams from spending time to find and fix the source of a breakdown, and saves a business from losing revenue while the fix is made. Plus, automating tasks for DBAs in the DevOps inner circle gives them more time and space for innovation.
Database Automation Best Practices
The most time-consuming tasks a DBA must deal with include reviewing and testing changes to the database. Database automation can take care of many of these tasks. However, DBAs need to follow database automation and testing best practices. Some of these best practices include:
Decide what processes to automate
Determine which processes should be automated first. Ask yourself which tests require a lot of data to perform the same task and take a lot of time.
Test early and often
Start testing as early in the cycle as you can. The earlier and more often you can test, the more bugs you can find early on. This can also help you identify more candidates for automation.
Select the database automation tool that best suits your needs
There are a lot of tools for database automation in the market. You need to consider which ones will work with your platform and existing technologies as well as provide flexibility for your testers.
Logging and error tracking
While not exciting work, logging, and error tracking can help you track and analyze errors as your database automation system grows.
Manage dependencies for your automated processes
As your database automation system develops, it will have more moving parts. By setting up and managing dependencies for processes to complete, you can ensure the safety of your system.
DevOps teams and DBAs have more tasks to handle across different functions. Database automation makes it easier for both to handle database changes while also ensuring continuous delivery with full visibility into structure, code, and data. Are you ready to automate your database?
More on database release automation:
To learn more about the DBA and their role in DevOps check out our white paper: The DBA’s Role in DevOps.