Database DevOps

Fast-changing markets demand better products, launched quickly. But it can be hard for development teams to keep pace with the demands of the business whilst satisfying the need for data integrity and database performance.

How Database DevOps drives innovation

• By integrating the work of development and operations teams, Database DevOps helps them work together to get better results, faster.
• The DevOps approach promotes collaboration throughout your organisation, not just technical teams. With increased business knowledge in the development phase, you get the solution your organisation needs.
• With Database DevOps, you can advance development on multiple tracks at once. Even code that affects the database can be deployed safely hundreds or even thousands of times per day via continuous integration and deployment (CI/CD) techniques, enabling your organisation to react to changing markets and customer needs faster than the competition.

Delivering quickly is no good if the end product is faulty, slow or does not meet the needs of the customer or business requirements. But manual quality checks and traditional working practices add time and can cause friction between teams.

How DevOps for Data improves quality

• By moving to an iterative development process, product owners, developers and operators can regularly review each feature’s progress to ensure the result matches the vision. These small, frequent reviews promote agile co-operation between the teams.
• With more frequent and granular reviews, bugs can be found sooner and the impact to resolve them is minimised with less dependent code changes and retesting required. The technical debt accumulated with each release can be substantially reduced.
• With the use of both open source and proprietary tools, code can automatically be reviewed not just for functional defects, but security, performance and stylistic problems can be detected, measured and reported. Existing tools used for code quality such as code linting and static code analysis can be extended to support the database artifacts and integrated as part of the overall build process.
• Subject to the appropriate checks and controls, database code can be promoted across all environments up to production using reliable tooling to remove the risk of human error. Often this can be done by automating existing tooling, enabling proven tools to offer further value.

With a faster pace of development comes a requirement for more resources to develop and test with, but the business pressure to ‘do more with less’ has never been greater.

How Database DevOps reduces costs

• With expert knowledge of data systems, the Database DevOps service enables the same standard software tools used for orchestrating application development to be securely and reliably used to control the database components – reducing setup, support and maintenance costs. Open source toolsets such as Git, Jenkins and Ansible are now a possibility.
• Automating the mundane tasks of deployment and code review allows skilled staff to concentrate on adding value to enhance system design and performance, increasing their productivity, engagement and job satisfaction.
• By integrating systems based on traditional technologies such as UNIX or mainframes that might otherwise be considered ‘legacy’ into the DevOps process, they can continue serving the business and enhance return on investment.

For many businesses, integrating the database is the last piece of the DevOps puzzle.  As the cornerstone of any application, the mix of art and science required to produce a performant, secure, reliable database can seem impossible to master with modern DevOps techniques.

How Database DevOps facilitates platform integration

• With the capability and experience to integrate all types of databases into the DevOps pipeline, systems as disparate as mainframes and cloud platform-as-a-services can work together as integral parts of the enterprise.
• With the database a part of the DevOps CI/CD pipeline, new architectural styles can be more easily supported – microservices, event-based processing, hybrid cloud developments all become a realistic prospect, enabling existing data systems to provide services to more applications.
• In addition to enabling agile development, Database DevOps makes the platform itself agile using modern tools such as Ansible to build even mainframe environments. And it need not stop with the database itself, other related components such as transaction managers can be included to provide a complete technology stack.

Introducing modern, cross platform graphical and command line tools for creation and maintenance of database objects and jobs provides a familiar and easy to learn environment for the next generation of staff.