Assessing database migration complexities with migVisor Part 2

This is in continuation to my first blog on database migration assessment using migVisor. In case you have missed my previous blogs please have a look at my previous medium posts on Comprehensive approach to Enterprise DB Migration and Assessing database migration complexities with migVisor(Part 1).

Very often we talk about database migrations without the context of applications accessing the databases. This would be tricky if application landscapes have evolved over time with no awareness of production applications impacting the databases. Let me simplify a bit. What if we have prehand knowledge of applications getting impacted by database migrations then it would be a blessing in disguise. migVisor as a tool gives you the ability not only to do database migration assessments but also it highlights applications associated with sources which were uploaded or declared under the current migVisor account.

To get started Login into the migVisor console @ https://console.migvisor.com/. The “Portfolio” section is the landing page for migVisor. It’s split into 2 sections on the left hand side you see “Database Feature Breakdown” and on the right hand side you see “Application Complexity Breakdown”. Our focus this time is on the “Application Complexity Breakdown” Screenshot below for your reference. This capability was recently introduced in migVisor.

Application Complexity Breakdown reflects total complexity per application. This section is broadly classified into 3 sections i.e. High complexity, Medium complexity and Low complexity.

Hovering over the slice shows the application name and color of the slice highlights the overall complexity level for that particular application.

Lets click on the pie slice to get further details. As you can see in the screenshot below it displays the application name, associated database i.e. in my case its Oracle, language in which applications is written i.e. in my case Java and Overall complexity breakdown with details on features of applications contributing to complexity i.e.

Red — High complexity,

Orange — Medium complexity,

Green — Low complexity

Let’s dive into the Application section. You will find the following details i.e. Total number of applications i.e. in my case its 5. You may apply filters to narrow your search by Language, DB Engine and Creation Mode. “Creation Mode” can be “Analyzed” which means application code was analyzed with migVisor code analyzer and uploaded to the migVisor whereas “Declared” application means which user has declared application using questionnaires to provide migVisor basic information.

Filters affect both sections on the Application page i.e. Summary and Catalog section. You can see in my case all application languages are based on JAVA. Overall complexity can be further broken down into high,low and medium. One interesting find out is on the right hand side applications i.e. “Modern versus Legacy classification”. Modern states that how ready is for modernization or cloud native. In my case 60% is Modern and the rest 40 % is legacy. If the Modern versus Legacy section shows “Unknown” then it means there are not enough details about the applications to classify them.

Clicking on the “Catalog” Section one of the applications in my case beam you will find out that although Overall complexity is Medium but its based of 2 factors i.e. Modernization Complexity and Migration Complexity. This section is the summary title section on Applications.

Modernization Complexity — Refers to application complexity and is not dependent on the database migration layer. It refers to cloud ready and modern status.

Migration Complexity — Refers to database complexity which basically depends on migration from source database engine to the target database engine.

Screenshot below

You can see application features which contribute to the complexity. Coming back to database migration from Oracle to cloud native database on GCP like Spanner, features on Oracle i.e. XML and stored procedures need to be reworked for Cloud Spanner on GCP.

Let’s deepdive to analyze the same beam application. You can find out “Findings per impact level” with high,medium and low. This is the overview section. There are other critical sections like Details, Features and Associated databases.

Lets click on the Details you will details including Language platform used i.e. Java in my case, Lines of code, DB Interface count, Microservices status, Containerization status, source control with git, date of collection etc. These are a few insights which can definitely help to plan the migration better.

Lets Click on “Features” section you will find high, medium and low migration impact split into Modernization impact i.e. cloud icon and database migration impact with database/cylinder icon while moving from Oracle to Spanner. Each of the sections you can expand to find out further details. Lets analyze one such feature Stored Procedures call on oracle with database icon. You can find details i.e. Info section as highlighted below in the screenshot with suggestion steps to mitigate them on target Spanner. Location Section highlights the section where stored procedures on source databases i.e. Oracle PLSQL are located. Pretty useful insights.

Similarly lets click on one of the cloud icons, Screenshot below with similar details on Modernization impact with potential mitigation steps.

Lets click on the last section i.e. “Associated Databases”. This section highlights the associated database Engines,drivers, version detected on source code analysis.

Above was the application page which highlights deepdive analysis per application wise. This capability of Applications extends migVisor capability beyond database features on source databases to be migrated to the target database. This will help in detecting application level insights which are missing on tools which highlight just database complexity assessment.

Hope you enjoyed this reading on migVisor. Stay tuned for more such blogs on DB Migrations !!!!!!