[#]: subject: (Refactor your applications to Kubernetes) [#]: via: (https://opensource.com/article/21/6/tackle-diva-kubernetes) [#]: author: (Yasu Katsuno https://opensource.com/users/yasu-katsuno) [#]: collector: (lujun9972) [#]: translator: ( ) [#]: reviewer: ( ) [#]: publisher: ( ) [#]: url: ( ) Refactor your applications to Kubernetes ====== Tackle-DiVA helps developers understand database operations and transaction processes inside applications. ![Tips and gears turning][1] Application modernization developers must be able to understand database operations and transaction processes inside applications precisely. [Tackle-DiVA][2] (Data-intensive Validity Analyzer) is an open source data-centric Java application analysis tool in the [Konveyor Tackle project][3] that aims at refactoring applications to Kubernetes. This article gives an overview of Tackle-DiVA and presents example instructions and analysis results. ### What is Tackle-DiVA? Tackle-DiVA is built using Java and Python and operated using a command-line interface. It imports target Java application source files and provides analysis results as files. ![Tackle-DiVA operation][4] (Yasuharu Katsuno, [CC BY-SA 4.0][5]) Breaking down this diagram: * **Service entry inventory** analysis extracts a list of Java classes for implementing public APIs. * **Database inventory** analysis exports a list of database tables operated by an application. * **Transaction inventory** extracts a set of transaction processes. * **Code-to-database dependency** analyzes which Java class operates which database table. * The **database-to-database** and **transaction-to-transaction dependency** analyses find clues for transforming parallel executions. * Finally, **transaction refactoring recommendation** analysis shows parallel executable transactions from original sequential executions. ### Try it out! It is easy to get started with Tackle-DiVA. It makes full use of [Docker][6] containers, and the only prerequisite is a Docker-runnable environment, such as RedHat Enterprise Linux, Ubuntu, or macOS. Once you have Docker available on your machine, run: ``` $ cd /tmp $ git clone && tackle-diva $ docker build . -t diva ``` This builds Tackle-DiVA and packs it as a Docker image. Tackle-DiVA is now ready to use on your machine. The next step is to prepare source codes of your target Java applications. I'll use the [DayTrader][7] application as an example: ``` $ cd /tmp $ git clone ``` The final step is to execute the `diva_docker` command by attaching the full directory path: ``` $ cd /tmp/tackle-diva/distrib/bin/ $ ./diva_docker /tmp/sample.daytrader7/ ``` This creates the `tackle-diva/distrib/output` directory and stores the analysis result files: ``` $ ls /tmp/tackle-diva/distrib/output contexts.yml            transaction.json        transaction_summary.dot database.json           transaction.yml         transaction_summary.pdf ``` ### Explore the analysis results Take a look at some analysis results for the DayTrader application. The **service entry inventory** result is stored in the `contexts.yml` file. It finds that the `TradeAppServlet.init class/method` plays a key role in service entries for the `login` and `register` actions: ``` \- entry:    methods:   - "com.ibm.websphere.samples.daytrader.web.TradeAppServlet.init"  http-param:    action:   - "login" \- entry:    methods:   - "com.ibm.websphere.samples.daytrader.web.TradeAppServlet.init"  http-param:    action:   - "register" ``` The **database inventory** analysis exports six database tables in the `database.json` file. These tables are used in the DayTrader application: ``` {  "/app": [    "orderejb",    "holdingejb",    "quoteejb",    "accountejb",    "keygenejb",    "accountprofileejb"  ] } ``` The **transaction inventory** analysis result is dumped into the `transaction.json` and `.yml` files, but it's better to check the `transaction_summary.pdf` file when looking through transactions. The following transaction consists of six SQL operations to two database tables: `holdingejb` and `orderejb`: ![Tackle-DiVA transaction inventory][8] (Yasuharu Katsuno, [CC BY-SA 4.0][5]) The `transaction.json` and `.yml` files also contain **code-to-database dependency** analysis results. The following shows how the TradeDirect class invokes query operations to two database tables, `accountprofileejb` and `accountejb`: ``` "stacktrace" : [   ...   {   "method" : "<src-method: < Source,               Lcom/ibm/websphere/samples/daytrader/direct/TradeDirect,               getStatement(Ljava/sql/Connection;Ljava/lang/String;)               Ljava/sql/PreparedStatement; >>",   "file" : "/app/daytrader-ee7-ejb/src/             main/java/com/ibm/websphere/             samples/daytrader/direct/TradeDirect.java",   "position" : "TradeDirect.java [1935:15] -> [1935:41]"   } ], "sql" : "select * from accountprofileejb ap where ap.userid = (             select profile_userid from accountejb a where a.profile_userid=?)" ``` The **database-to-database dependency** analysis result is located in the `transaction_summary.dot `and `.pdf` files. The `accoutprofileejb` and `accoutejb` database tables have a mutual-query relationship: ![Tackle-DiVA database-to-database dependency][9] (Yasuharu Katsuno, [CC BY-SA 4.0][5]) The **transaction-to-transaction dependency** analysis results are found in the `transaction_summary.dot` and `.pdf` files. Two transactions have a dependency on the `orderejb` database table. The upper transaction updates the table, and the lower transaction queries it: ![Tackle-DiVA transaction-to-transaction dependency][10] (Yasuharu Katsuno, [CC BY-SA 4.0][5]) Finally, parallel executable transactions are shown in the `transaction_summary.dot` and `.pdf` files, resulting from the **transaction refactoring recommendation** analysis. In this example, two transactions in the lower part can be executed in parallel after the upper transaction processing completes, which helps keep data consistency due to no transaction dependencies: ![Tackle-DiVA transaction refactoring recommendation][11] (Yasuharu Katsuno, [CC BY-SA 4.0][5]) ### Learn more To learn more about application refactoring, check out the [Konveyor Tackle site][12], join the community, and access the source code on [GitHub][2]. -------------------------------------------------------------------------------- via: https://opensource.com/article/21/6/tackle-diva-kubernetes 作者：[Yasu Katsuno][a] 选题：[lujun9972][b] 译者：[译者ID](https://github.com/译者ID) 校对：[校对者ID](https://github.com/校对者ID) 本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出 [a]: https://opensource.com/users/yasu-katsuno [b]: https://github.com/lujun9972 [1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/gears_devops_learn_troubleshooting_lightbulb_tips_520.png?itok=HcN38NOk (Tips and gears turning) [2]: https://github.com/konveyor/tackle-diva [3]: https://www.konveyor.io/tackle [4]: https://opensource.com/sites/default/files/uploads/tackle-diva_operation.png (Tackle-DiVA operation) [5]: https://creativecommons.org/licenses/by-sa/4.0/ [6]: https://opensource.com/resources/what-docker [7]: https://github.com/WASdev/sample.daytrader7 [8]: https://opensource.com/sites/default/files/uploads/tackle-diva_transaction-inventory.png (Tackle-DiVA transaction inventory) [9]: https://opensource.com/sites/default/files/uploads/tackle-diva_dbtodb.png (Tackle-DiVA database-to-database dependency) [10]: https://opensource.com/sites/default/files/uploads/tackle-diva_ttot.png (Tackle-DiVA transaction-to-transaction dependency) [11]: https://opensource.com/sites/default/files/uploads/tackle-diva_transaction-refactoring.png (Tackle-DiVA transaction refactoring recommendation) [12]: https://github.com/konveyor/tackle