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选题[tech]: 20210617 Refactor your applications to Kubernetes
sources/tech/20210617 Refactor your applications to Kubernetes.md
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[#]: subject: (Refactor your applications to Kubernetes)
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[#]: via: (https://opensource.com/article/21/6/tackle-diva-kubernetes)
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[#]: author: (Yasu Katsuno https://opensource.com/users/yasu-katsuno)
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[#]: collector: (lujun9972)
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[#]: translator: ( )
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[#]: reviewer: ( )
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[#]: publisher: ( )
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[#]: url: ( )
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Refactor your applications to Kubernetes
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======
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Tackle-DiVA helps developers understand database operations and
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transaction processes inside applications.
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![Tips and gears turning][1]
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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.
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This article gives an overview of Tackle-DiVA and presents example instructions and analysis results.
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### What is Tackle-DiVA?
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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.
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![Tackle-DiVA operation][4]
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(Yasuharu Katsuno, [CC BY-SA 4.0][5])
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Breaking down this diagram:
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* **Service entry inventory** analysis extracts a list of Java classes for implementing public APIs.
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* **Database inventory** analysis exports a list of database tables operated by an application.
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* **Transaction inventory** extracts a set of transaction processes.
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* **Code-to-database dependency** analyzes which Java class operates which database table.
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* The **database-to-database** and **transaction-to-transaction dependency** analyses find clues for transforming parallel executions.
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* Finally, **transaction refactoring recommendation** analysis shows parallel executable transactions from original sequential executions.
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### Try it out!
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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.
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Once you have Docker available on your machine, run:
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```
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$ cd /tmp
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$ git clone <https://github.com/konveyor/tackle-diva.git> && tackle-diva
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$ docker build . -t diva
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```
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This builds Tackle-DiVA and packs it as a Docker image. Tackle-DiVA is now ready to use on your machine.
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The next step is to prepare source codes of your target Java applications. I'll use the [DayTrader][7] application as an example:
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```
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$ cd /tmp
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$ git clone <https://github.com/WASdev/sample.daytrader7.git>
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```
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The final step is to execute the `diva_docker` command by attaching the full directory path:
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```
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$ cd /tmp/tackle-diva/distrib/bin/
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$ ./diva_docker /tmp/sample.daytrader7/
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```
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This creates the `tackle-diva/distrib/output` directory and stores the analysis result files:
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```
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$ ls /tmp/tackle-diva/distrib/output
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contexts.yml transaction.json transaction_summary.dot
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database.json transaction.yml transaction_summary.pdf
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```
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### Explore the analysis results
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Take a look at some analysis results for the DayTrader application.
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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:
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```
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\- entry:
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methods:
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- "com.ibm.websphere.samples.daytrader.web.TradeAppServlet.init"
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http-param:
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action:
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- "login"
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\- entry:
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methods:
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- "com.ibm.websphere.samples.daytrader.web.TradeAppServlet.init"
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http-param:
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action:
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- "register"
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```
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The **database inventory** analysis exports six database tables in the `database.json` file. These tables are used in the DayTrader application:
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```
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{
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"/app": [
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"orderejb",
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"holdingejb",
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"quoteejb",
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"accountejb",
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"keygenejb",
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"accountprofileejb"
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]
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}
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```
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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`:
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![Tackle-DiVA transaction inventory][8]
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(Yasuharu Katsuno, [CC BY-SA 4.0][5])
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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`:
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```
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"stacktrace" : [
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...
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{
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"method" : "<src-method: < Source,
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Lcom/ibm/websphere/samples/daytrader/direct/TradeDirect,
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getStatement(Ljava/sql/Connection;Ljava/lang/String;)
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Ljava/sql/PreparedStatement; >>",
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"file" : "/app/daytrader-ee7-ejb/src/
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main/java/com/ibm/websphere/
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samples/daytrader/direct/TradeDirect.java",
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"position" : "TradeDirect.java [1935:15] -> [1935:41]"
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}
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],
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"sql" : "select * from accountprofileejb ap where ap.userid = (
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select profile_userid from accountejb a where a.profile_userid=?)"
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```
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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:
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![Tackle-DiVA database-to-database dependency][9]
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(Yasuharu Katsuno, [CC BY-SA 4.0][5])
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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:
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![Tackle-DiVA transaction-to-transaction dependency][10]
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(Yasuharu Katsuno, [CC BY-SA 4.0][5])
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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:
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![Tackle-DiVA transaction refactoring recommendation][11]
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(Yasuharu Katsuno, [CC BY-SA 4.0][5])
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### Learn more
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To learn more about application refactoring, check out the [Konveyor Tackle site][12], join the community, and access the source code on [GitHub][2].
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/21/6/tackle-diva-kubernetes
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作者：[Yasu Katsuno][a]
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选题：[lujun9972][b]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://opensource.com/users/yasu-katsuno
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[b]: https://github.com/lujun9972
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[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)
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[2]: https://github.com/konveyor/tackle-diva
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[3]: https://www.konveyor.io/tackle
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[4]: https://opensource.com/sites/default/files/uploads/tackle-diva_operation.png (Tackle-DiVA operation)
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[5]: https://creativecommons.org/licenses/by-sa/4.0/
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[6]: https://opensource.com/resources/what-docker
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[7]: https://github.com/WASdev/sample.daytrader7
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[8]: https://opensource.com/sites/default/files/uploads/tackle-diva_transaction-inventory.png (Tackle-DiVA transaction inventory)
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[9]: https://opensource.com/sites/default/files/uploads/tackle-diva_dbtodb.png (Tackle-DiVA database-to-database dependency)
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[10]: https://opensource.com/sites/default/files/uploads/tackle-diva_ttot.png (Tackle-DiVA transaction-to-transaction dependency)
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[11]: https://opensource.com/sites/default/files/uploads/tackle-diva_transaction-refactoring.png (Tackle-DiVA transaction refactoring recommendation)
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[12]: https://github.com/konveyor/tackle
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