Flyway VS Docker Compose

The session logs show that the application loads configurations and establishes a connection with a PostgreSQL database. This involves initializing a HikariCP connection pool and Flyway for database migrations. The logs confirm that the database schema validation and migration checks were successful. The startup of the Jetty HTTP server follows, and the server becomes operational and ready to accept requests on the specified port.

Also RedGate, but Flyway has some reasons to recommend it over RedGate Deploy depending on your DBAs/workflows: https://flywaydb.org/

(Though I don't think it is "complete" or "perfect", either.)

EF Migrations are in a really good place now if you like/don't mind C# as a language (and you can easily embed SQL inside the C#, too, but there are benefits to being able to also run high level C# code). With today's tooling you can package your migration "runner application" as a single deployable executable for most platforms. You can build the executable once and run it in all your environments. (The same tool that updates your QA and Staging updates your Prod, testably running the same migrations.) Given the single executable deployable I might even consider using it for projects not themselves written in C#.

There is a bit of tooling needed but is already around. For Java for example I had very good experience with a combination of flyway [1] for migrations, testcontainers [2] for making integration tests as easy as unit tests and querydsl [3] for a query and mapping layer.

[1] https://github.com/flyway/flyway

[2] https://java.testcontainers.org/modules/databases/postgres/

[3] https://github.com/querydsl/querydsl

When software starts using a database, it's advisable to have version control, just as we have Github to control our source code. This is all to be sure about what was executed for that specific version. For Java and Spring boot, we have the Flyway framework that aims to resolve this situation, free of charge.

If you're looking for tools, like https://www.liquibase.com/ or https://flywaydb.org/, which are database-state-based schema migration toolkits - it might be relatively straightforward to build similar ones using Databricks SQL drivers.

Honestly I kind of wish there was a Lukas Eder database migration library. Call it whatever jooq-migration. At least I would have more insight of what is going on (<-- seriously look at the commit history).

This is a 4th option, which should play nice with ArgoCD. The following example runs flyway as a k8s job. The desired migration changes are recorded as files within the chart. This helm chart can be integrated with your application (Using hooks to determine when the migration job is run) or run manually.

By using an opinionated framework within the app/service (like Flyway, Migrate, Diesel, etc). Schema migrations happen on app/service start-up.

Depending on the language or platform there are libraries you can use to manage this, such as Prisma on node and Flyway for Java/JVM.

It's probably overkill but I've used github plus flyway at a couple places in the past which is pretty nice tool for tracking changes to a variety of db's, it's also very helpful if you ever need to replicate a db in a new region/environment.

sudo curl -L https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m) -o /usr/local/bin/docker-compose sudo chmod +x /usr/local/bin/docker-compose

Solutions are many, and could include Docker Compose, VS Code dev containers, Telepresence, Localstack or setting up temporary AWS accounts as a development environment for serverless applications.

Using Docker Compose to run Postgres and any third-party services locally provides a streamlined and consistent development environment. Developers can define services in a docker-compose.yml file, which enables them to configure and launch an entire stack with a single command. In this case, Postgres is encapsulated within a container with predefined configurations. Docker Compose also facilitates easy scaling, updates, and isolation of services, enhancing development efficiency and reducing the setup time for new team members or transitioning between projects. It encapsulates complex configurations, such as Postgres' performance monitoring and logging settings, in a manageable, version-controlled file, simplifying and replicating the service setup across different environments.

“Compose simplifies the control of your entire application stack, making it easy to manage services, networks, and volumes in a single, comprehensible YAML configuration file. Then, with a single command, you create and start all the services from your configuration file.” - Docker documentation

curl -fsSL https://get.docker.com -o get-docker.sh sudo sh get-docker.sh # Install docker compose sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose # Apply executable permissions to the binary sudo chmod +x /usr/local/bin/docker-compose # Run Project docker-compose up -d

Docker,

This foundation now opens the door to even more powerful concepts. You can explore more advanced concepts such as container networking, streamlining the management of complex applications with Docker Compose, and how to make your application data persistent using volumes.

In many projects that are containerized, especially in cases where development is also done locally with docker-compose, teams often have two Dockerfiles, 1 for Development, the other for Production. If you happen to have multiple environments like pre-prod, staging and so on, some teams could have different Dockerfiles for these environments.