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This chapter covers two of my favorite topics: SOA and architect roles. I have tried to provide a good overview of how I think we can bridge the gap between the business side and the IT side in an organization. The aim of bridging this gap is to reach the level of success we saw in the Shinsei Bank example. SOA is an architecture framework that can help us implement and automate our business processes in the IT infrastructure. This is what makes it such a great part of an ALM process. SOA is built up of separated services, each encapsulating part(s) of our business logic. These services communicate with each other by sending messages. The architects have a big influence on how our business processes are implemented and automated in the IT infrastructure. Business architects are responsible for the way we work in our companies and how the business processes are defined, and IT architects are responsible for how these business processes will be realized in IT. To implement SOA, we need to make sure that architects from both the business and IT sides focus on this architecture.

classes almost completely independent of Spring (save for the @Repository annotation), we still favor the HibernateTemplate approach. Using HibernateTemplate makes your code framework dependent, but chances are that you will not need to change the framework in the life cycle of the application.

Table 3-1. Continued On Change: Prevent Disallow a change if it does not conform to the policy defined. This is an automated evaluation mode. It uses DDL triggers. Available only if there is transactional support for the DDL statements that change the state of the facet

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The code in the examples in the previous section is perfectly functional Hibernate code. In fact, you can take the code we have written and use it in almost any enterprise application. But it will not work as efficiently as we would like. The first problem is that we have done nothing to prevent updates of stale data. The code we have will simply update the rows in the database without any checks. Next, we do not consider transactional behavior. Without any additional code, the code in the callback supplied to the doInHibernate method does not automatically run in a transaction. Enterprise applications certainly need to support transactions in the traditional sense of the word, conforming to the ACID (atomicity, consistency, independence, and durability) rules. Moreover, enterprise applications often include other resources (a JMS queue, for example) in a transaction. Next, the examples we have given work with LogEntry objects. The LogEntry class does not have any associations; it can be fully constructed using data from a single database row. Enterprise applications usually manipulate complex objects with many associations. Handling these associations efficiently is important; otherwise, you may end up with extremely complex SQL statements. Finally, if the t_log_entry table contained hundreds of thousands of rows, the examples we gave would simply crash with a java.lang.OutOfMemoryException. Real applications need to be able to deal efficiently and elegantly with very large data sets. In this section, we will take a look at how we can solve each of these problems in a way that is as close to real-world application code as possible.

If we are to fulfill the goal of a good ALM process that really gives business value to our organizations, we need to consider more than just the process itself We need to tie the strings together from the business needs to the delivered business value If we do not include both business processes and their implementations and architecture as IT systems in our ALM process, we will never deliver enough business value It is my belief that SOA is a great thing, the best right now for architecting our business systems It gives the flexibility we need to quickly adapt to new business challenges I do realize that this cannot be achieved too quickly You just don t change an organization s IT infrastructure all at once.

Table 11-1 shows a scenario in which our application can overwrite data updated by another user. Table 11-1. Stale Data Updates Scenario

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