DevOps for Databases

 

Dev Ops  does not means mean breaking the silos in between the developers and the operations. We need to evaluate each “manual operation” in the delivery pipeline if we think of automation. And database changes certainly require an extensive process, and hence it deserves “deep analysis” for DevOps implementation. And if you want to learn DevOps, you can contact Nearlearn. We provide complete DevOps Online Training for all  DevOps certifications . Nearlearn  also is the number one computer training institute and among the top five computer training institutes in India.

A solution depends upon the complexity and “coupled behavior” of the architecture. And it also depends upon the rigidity which effects the change process.

Our objective is to provide a perspective for automating the database changes. And it is not merely through the explanation of why these database changes are difficult. Though it also through a real-world example that explains how the DevOps simplifies the processes.

Optimization of the code and trouble shooting is now easy through the integrated errors, performance insights at the code level, and logs.

DevOps for Database

The changes in the “Database” begin with the developers committing the changes. They make use of it to create the SQL format. And the changes are reviewed by a database administrator who looks after the databases. He has the best knowledge of the “Database.” And, it can ensure correct changes. And it’s not merely in performance, but in the data integration as well.

And it does look like an essential process? However, the issue arises that the DBA generally gets involved slightly before the deployment to the production, and by then, it’s too late and expensive the proper changes.

It does not mean that the developers require someone other reviewing what they do. However, this is a typical process for some big companies.

The DevOps for the databases is “simply” related to shifting the process to the left, and through automation, you can make the process run more smoothly. However, it’s not just automation.

“Automation is merely a part.”

There are situations when we require something very “Complex,” not better performed through automation. Suppose you have described the “Database” that you use. And you don’t need to the re-architecting. And that certifies that you don’t need any complex changes quite often, and the automation caters to you the implementation of the future alteration in a predictable and repeatable way. And this is the same all the time.

And to be truthful, the automation of the table alteration by adding a new column is easy. And the main problem is the state of which the “database” needs to “take care of.” In case the “Database” has “huge data,” making changes take “huge-time,” and it blocks all the changes like the CRUD operations.

The automation is “however,” is one out of a lot many required in  DevOps  implementation. And in fact, it’s the simple part. Hence always go for automation and avoid the manual changes frequently.

 

No standard among the database Engine

The database alteration requires an all the time standard as each “Engine” comes with different standard management. And its impact varies from one Engine to the other. The “SQL Server” indexes not get affected like the “Oracle,” or the MySQL indexes are alike.

The SQL is not just one database engine that is in common. Though even then, the statements cater to us varied results.

In the coming times, this industry will have an easy time as there is “standardization” of how we deal with the databases. However, meanwhile, ensure you are up with the plan of changing the database engine. Make use of the object-relational framework and various tools for making the job easy. You find some examples in the upcoming section of this blog.

Tightly-coupled designs

Majority of the instances, the system architecture creates the problem in the “Database.” However, there are issues other than database changes in the  Devops  implementation. Nowadays, the norm is the distributed system, and we have architectural patterns such as the microservices, which has solved database coupling through the “database” for each microservices.

Through “Microservices,” we can decouple the “database.” The only way is the microservices interact with the data through the exposed methods from the service. And it’s as such rather than moving directly towards the “database.” And this is even if it’s easy and possible to go that way.

When the “database” is used for storage purposes only, it’s easy to make the changes. And you store the data for analysis. And that is why we shift the data to the “Data Warehouse,” where there is very little chance for the data to change.

The transactional data has the “data” that is needed. And this is known as the CQRS architecture pattern. And in some situations, we have the data for a week and sometimes for a month.

No culture and processes that are well established

Another essential feature of the “database” is the alteration in the culture and the needed processes.

Leaving the database changes till the end of the workflows hints towards “poor” configuration among the teams. It can be that the teams do have the same goals in their brain. Or there can be an ego problem when some feel that they need to require help, and the process happens to be merely the blocker.

You need not wait for the DBAs to review the changes till the final stage. They should be a part of asap in this process. And with time, the developers, operations, and the DBAs agreement on how the database changes need doing. And more experienced the team becomes on review processes, the smoother the processes execute.

When there is an anticipated collaboration among the teams, the best thing can come up, and you need to make one main goal that everyone recognizes.

The Databases Technical practices

We are through how the “database” originates a specific issue in the Data Ops and how the environment becomes apt. However, others, rather than just “technical practice,” boost the DevOps implementation with the changes in the “Database.”

Migrations to the rescue

The Migrations happens to be the script covering the database changes, which ideally are idempotent, which means that it does not matter, times in the number you run the script, the changes apply only once. It’s nice to have the “script” in the version control such that you keep in mind the changes and move “easily” back and forward with the changes.

In different words, migrations happen to be the database changes as the code. You can execute the same migration in various environments. And it should lead to the same result, which stands with the local environment, the developer machine.

Production like Environment practice

Let’s discuss the technical practice, which is simple in implementation. However, there is little requirement for discipline testing.

You should test the changes before you apply them in the production environment. If the table data is large, and suppose as large as its not cheap to replicate in the various environment from the production- you use, that you can simulate at least the changes when the data is significant. That ensures the changes don’t take for always. And you don’t block a table for a lengthy period.

You can make use of the Containers. You will find them “easy” and cheaper, and if something goes wrong, you can delete everything and start afresh.

Database computerization tools

We need to talk about some tools to keep talking about the databases. And you will find numerous tools, and you will find new ones frequently. However, some of them are quite popular, and a few of them mentioned below:

• Liquibase (this is free)
• Datical (this is Liquibase’s paid version)
• Delphix (this is the Microsoft Stack)
• Redgate (this is not merely for the database changes)
• DBmaestro (this is the for the database)

And also, tools for database engines, there are outlines that provision migrations too:

• Entity Framework
• Compose
• GORM
• Hibernate

Let’s at first know about the Entity Framework in the .NET Core.

The practical guide for making use of the Entity Framework

You will find numerous powerful tools for automating the database alteration. Consider one approach, where you easily automate the tools such as Jenkins or the VSTS through the Entity Framework (EF) for the .NET Core applications.

If you look at the entity framework, you will find that the data updating is a repeatable process. Let’s build a project and store the code at  Git  Hub .  And let’s focus on the database changes.

We are going to make a small change, and you will find how EF comes into play. You can consider any EF code first based project for this The process goes like as below.

Set the process locally

You will require the .Net Core installed and then run the application with the IIS Express option. Also, you will require the SQL server instance. We need to see how the changes get applied to the database as you move forward.

Begin with making the changes in the input parameters avoiding the database spinning as the application launches. We can do the database updating manually through the use of the EF migration commands. Now open the project properties by right-clicking the project name, and then vary the debug parameters.

You require a proper configuration for connecting to the “database” and with the database password. You can make the changes to the password through the app settings JSON.

Now, pick the project name and then run it by clicking the “Debug” button. And as the application starts, it’s not going to work, as the database is not existing and we have not run the first migration, which makes the database.

Now initiate the database.

Open the terminal. You can make use of the command line of the visual studio. Now, run the below command from the root folder of the project. It should be such that the EF makes the database schema.

Now you can connect the database and then look at the tables necessary, created.

Alter the application through the addition of the new column. For that, you need to make the changes in Models/stud.cs. And then, you need to append the new column.

Now you need to move to view and then append the column, and you need to add a few HTML lines of codes.

And adding the new column, you need to change the code of the corresponding view in the “Make.cs.” You have an action event in the controller, and for that, we have “view,” and you have to make the changes in the view.

Before the application runs again, let’s make the “migration in the EF,” such that the next time you run the database update, the EF processes any remaining migration. For doing that, you need to run the below command.

For exploring the solution, a little, and you will find the new file created with the details of the migration. And always keep in mind that each of the migration files needs to be versioned.

Now run the application once more. The UI gets updated, though it is not going to work as the database is not updated yet. You now need to run the update command once more for applying any of the migration remaining.

Now refresh the application. It will work fine now.

The next time anybody needs to make any change creates a new migration. For updating, we need to make use of the update EF command again. And as you become habitual, you will be better at database change automation. Now keep in mind, DevOps for the database has a lot more than the above technical practices.

 

What about rollbacks ?

It’s also possible to roll back any changes in the database after “update” in the destination database  with the most current migrations. For doing that, you only need to run the below command:

It removes the most current migration. And that means if you are up with one or more migration, the above command rolls back the newest one. And you require to run again for keeping reverting the database alteration.

What if you still a prerequisite to creating scripts ?

While you again adjust the process, you need to check what the EF does in the database. It should be before you commit any of the changes. You can have a look at the SQL format for reviewing the changes. And the EF comes with the command for generating the SQL format well understood by the DBA.

For generating the migration in the SQL format, you need to run the below command:

Each of the SQL statements appears in the terminal. And then, you can store this output for a future review in the “output.”

And that’s all. Above you have practiced on your local. You now need to automate this new process with the help of the Jenkins or the VSTS. You run the update command, which you set in the deployment pipeline once the application deploys. And, developers make use of the other Commands to generate the migrations. And then keep them within the version control.

Swing database fluctuations to the left

As you saw, you don’t have any magic formula required for implementing the DevOps for the databases. You will find a lot of other things as well. However, the first step is your willingness to get out of the comfort and perform the processes better.

If you want to keep things simpler from the processes over to the architecture, you need to focus on the decoupled architecture, which leverages you in making the changes without any problem. And you teach yourself.

It’s not so difficult to make the changes in the database. The real problem is in the implications of losing and damaging a portion of the data. In automation, the two key things are repetition and consistency. And you need to practice a lot, and not merely do the deployment to the production.

You can make use of the Stackify application performance management tool Replace.

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