This talk will focus on understanding the DevOps movement from the perspective of the database professional. We will discuss the Values, Principles, Methods, Practices, and Tools applied and provide an example of how these will affect the database teams. This talk will discuss techniques such as version control of the database, continuously integrating database changes, deploying databases changes in an automated way, automated database sandbox creation, automated database comparison, using tools such as dbdeploy, dbmaintain, liquibase, flyway, and many others. Practices for setting up development work areas and how to include the dba as a ops role into the dev team

To get full benefits of continuous Delivery, all components of the software being developed need to be delivered at the same pace. Components of the software development like databases need different techniques to be managed . Techniques that that would have to cater to changes being deployed to the database along with code and at the same time be enable the database to handle multiple versions of the application software.

The world of data is changing and becoming yet more important as data has become a significant competitive advantage. We are collecting increasing amounts of data, but wanting to process it in decreasing time. This demands new techniques in data storage, enabling the raise of NoSQL technologies. In this talk Pramod will talk about NoSQL in two phases.

In the first phase, the talk will focus on core concepts needed to understand NoSQL databases, NoSQL data models, in particular the role of aggregates and the consequences of schema-less models, options for distribution and the consequences of maintaining consistency.

In the second phase the talk will focus on implementation details and look at some representative databases so you can get a feel for how real NoSQL databases work using Riak, MongoDB, Cassandra, and Neo4J and also look at how to implement evolutionary design with schema migration -- an essential requirement even with schema-less databases. Pramod will also help you to understand how to pick the right database for the requirements.

To get full benefits of continuous Delivery, all components of the software being developed need to be delivered at the same pace. Components of the software development like databases need different techniques to be managed . Techniques that that would have to cater to changes being deployed to the database along with code and at the same time be enable the database to handle multiple versions of the application software.

Polyglot Programming as a technique is not new and as a paradigm was coined in 2006 by Neal Ford. In today's world, we often architect solutions which need to be highly scalable, secure, efficient, have an engaging GUI, be extensible with low technical debt in parts or whole. To work with a single tech stack promotes a sense of mono culture which is detrimental and limiting the way a solution can be designed. Moreover, with multi-core machines available, processing now can leverage parallel processing and it maybe make more sense to use a language which takes away the overhead of the intricacies of multi-thread programming.

In other words, in many cases, engaging in Polyglot Programming helps you focus more on the domain and adds to developer productivity.

On the flip side, increasing the moving parts also means that if not designed well, Polyglot Programming could be a double edged sword and produce more mess in the way different pieces interact with each other.

In this talk, we will showcase an ecosystem we built, involving a desktop device configuration backed, an OS-agnostic desktop GUI, a cloud service, a cloud cluster configuration tool and how we used the Agile principles, namely TDD, Continuous Integration and the works to be able to keep the polyglot ecosystem sane.

Name wise, the languages/tools/etc which we used in our Polyglot case – Google Go, Node-Webkit, JS (Knockout/RequireJS), Ruby, Cucumber, RIAK, Chef, Lisp, Jenkins

Over the life of an application as requirements change, application usage patterns alter, load and performance changes the need to change database and database architecture is inevitable. There are patterns of these changes such as

1. 1. Encapsulate Table with View
2. 2. Migrate method from database
3. 3. Replace method with views
4. 4. Introduce Read only table
5. 5. Split table
6. 6. Make column non-nullable
7. 7. Drop column
8. 8. Add foreign key constaint
9. 9. Merge columns
10. 10. Replace columns

In this talk we will discuss the above database refactoring patterns and different implementation techniques to enable blue, green deployments, allow for legacy applications to work with fast changing database and enable the teams to effectively refactor the database to fulfill the changing needs of the organization.