DevOps: Database Change Management with Snowflake
A series of articles about DevOps: Database Change Management with Snowflake
- DevOps: Database Change Management with Snowflake (this one)
- DevOps: Database Change Management with Snowflake and GitHub
This tutorial will guide you step-by-step to set up database change management for Snowflake in Bytebase. With Bytebase, a team can have a formalized review and rollout process to make Snowflake schema change and data change.
Here we have to mention the informative blog post Embracing Agile Software Delivery and DevOps with Snowflake, which provided valuable insights and inspired us to implement similar processes in our product.
You’ll have a GUI and the full migration history. You can use Bytebase Free Plan to finish the tutorial. There is also a bonus section about schema drift detection for those advanced users if needed.
Before you start this tutorial, make sure:
- You have a Snowflake account with the role
- You have Docker installed locally.
Step 1 - Start Bytebase in Docker
- Make sure your docker daemon is running, and start the Bytebase docker container by typing the following command in the terminal.
Bytebase is running successfully in Docker, and you can visit it via
localhost:5678in your browser. Register the first admin account which will be granted
Step 2 - Add Snowflake account in Bytebase
In Bytebase, an Instance could be your on-premises MySQL instance, an AWS RDS instance etc, in this tutorial, a Snowflake account.
localhost:5678and login as Workspace Owner.
Click Add Instance.
Add a Snowflake instance. You need to pay attention to some fields: Environment: choose
Test, if you choose
Prod, you will need approval for all future change requests. In this tutorial, let's try to keep it simple. (However, it’s all configurable later.)
Account name: Go to your Snowflake account, you can find it in the URL, or from the locator field (but lower case).
Username and password: The ones you use to log into your Snowflake account.
Regarding the Connection info, make sure your account has
DEFAULT_WAREHOUSE set in Snowflake, as shown below.
Step 3 - Create a Project with Snowflake instance
In Bytebase, Project is the container to group logically related Databases, Issues and Users together, which is similar to the project concept in other dev tools such as Jira, GitLab. So before you deal with the database, a project must be created.
After the instance is created, click Projects on the top bar.
Click New Project to create a new project
TestSnowflake, key is
TS, mode is
standard. Click Create.
Step 4 - Create a database in Snowflake via Bytebase
In Bytebase, a Database is the one created by
CREATE DATABASE xxx. A database always belongs to a single Project. Issue represents a specific collaboration activity between Developer and DBA such as creating a database, altering a schema. It's similar to the issue concept in other issue management tools.
After the project is created, go to the project and click New DB.
Fill the form with Name -
DB_DEMO_BB(BB is short for Bytebase), Environment -
Test, and Instance -
Snowflake instance. Click Create.
Bytebase will create an issue “CREATE DATABASE ….” automatically. Because it’s for the
Testenvironment, the issue will run without waiting for your approval by default. Click Resolve, and the issue is Done. The database is created.
Go back to the home page by clicking Home on the left sidebar. If it’s the first time you use Bytebase, it’ll show a celebration. On the home page, you can see the project, the database, and the issue you just resolved.
Step 5 - Create a table in Snowflake via Bytebase
In Step 4, you actually created an issue in UI workflow and then executed it. Let’s make it more explicit.
Go to project
TestSnowflake, and click Alter Schema.
DB_DEMO_BBand click Next. It could generate a pipeline if you have different databases for different environments.
Input title, SQL, and Assignee, and click Create.
Bytebase will do some basic checks and then execute the SQL. Since it’s for
Testenvironment, the issue is automatically approved by default. Click Resolve issue.
The issue status will become Done.
On the issue page, click view migration. You will see diff for each migration.
You can also go to Migration History under the project to view the full history. Or go into a specific database to view its history.
Bonus Section - Schema Drift Detection
To follow this section, you need to have Team Plan or Enterprise Plan (you can start 14 days trial directly in the product without credit card).
Now you can see the full migration history of
DB_DEMO_BB. However, what is Establish new baseline? When should it be used?
By adopting Bytebase, we expect teams to use Bytebase exclusively for all schema changes. Meanwhile, if someone has made Snowflake schema change outside of Bytebase, obviously Bytebase won’t know it. And because Bytebase has recorded its own copy of schema, when Bytebase compares that with the live schema having that out-of-band schema change, it will notice a discrepancy and surface a schema drift anomaly. If that change is intended, then you should use baseline to reconcile the schema state again.
In this section, you’ll be guided through this process.
Go to Snowflake, and add a COLUMN there. Make sure the new column is added.
Wait for 10 mins (as Bytebase does the check roughly every 10 mins). Go back to Bytebase, and you can find the Schema Drift on database DB_DEMO_BB
The Anomaly Center also surfaces the drift
Click View diff, you will see the exact drift.
Use baseline to reconcile the schema state from the live database schema. Go to DB_DEMO_BB > Migration History and click Establish new baseline.
It will create an issue. Click Resolve to make it done.
Go back to DB_DEMO_BB or Anomaly Center, and you will find the Drift is gone.
Summary and Next
Now you have connected Snowflake with Bytebase, and tried out the UI workflow to do schema change. Bytebase will record the full migration history for you. With Team or Enterprise Plan, you can even have schema drift detection.
In the next article, you’ll try out GitOps workflow, which will store your Snowflake schema in GitHub and trigger the change upon committing the change to the repository, to bring your Snowflake change workflow to the next level of Database DevOps - Database as Code.