integresql VS testcontainers-go

For the case of PostgreSQL I've found IntegreSQL and its Javascript client really helpful because it can create a copy of the database per test case, which it helps to write integration tests with real DB calls.

Mocking has some advantages, but so does using a real database, at work we use https://github.com/allaboutapps/integresql and I quite like the approach that integresql has, since it makes possible to have a fresh database with your dummy data for every test without impacting the execution speed (compared to dropping an re-creating the database).

Happy to hear that! When it comes to testing services that depend on PostgreSQL, this is still my preferred solution.

https://github.com/allaboutapps/integresql

disclaimer: author

I haven't had a change to try it yet, but IntegreSQL[0] looks like this on steroids. It allows you to create a template (runs migrations and seed dates), and then uses Postgres's built in cloning functionality to maintain a pool of fresh databases. They claim 500ms to clone a database without the pool, and that the pool pretty much hides the latency entirely.

[0]: https://github.com/allaboutapps/integresql

Let's first look at the original version of the test, in this case, an end-to-end, using testcontainers.

It supports multiple languages (including Go!) and databases (also messaging infrastructure etc.) - All you need is Docker. Testcontainers for Go makes it simple to programmatically create and clean up container-based dependencies for automated integration/smoke tests. You can define test dependencies as code, run tests and delete the containers once done.

Testcontainers Go Documentation

Some of the features: - ✅ Using Vertical Slice Architecture as a high level architecture - ✅ Using Event Driven Architecture on top of RabbitMQ Message Broker with a custom [Event Bus](pkg/messaging/bus/) - ✅ Using Event Sourcing in Audit Based services like [Orders Service](services/orders/) - ✅ Using CQRS Pattern and Mediator Patternon top of Go-MediatR library - ✅ Using Dependency Injection and Inversion of Controlon top of uber-go/fx library - ✅ Using RESTFul api with Echo framework and using swagger with swaggo/swag library - ✅ Using Postgres and EventStoreDB to write databases with fully supports transactions(ACID) - ✅ Using MongoDB and Elastic Search for read databases (NOSQL) - ✅ Using OpenTelemetry for collection Distributed Tracing with using Jaeger and Zipkin - ✅ Using OpenTelemetry for collection Metrics with using Prometheus and Grafana - ✅ Using Unit Test for testing small units with mocking dependent classes and using Mockery for mocking dependencies - ✅ Using End2End Test and Integration Test for testing features with all of their real dependeinces using docker containers (cleanup tests) and testcontainers-go library

For example, you could take a look at this open-source project that helps you spawn docker containers as part of your test setup enabling you to execute queries to a local database.

Using something like TestContainers to spin up a DB for testing has been my best experience. Any mocks leave too much room for error imo

I highly recommend testcontainers for this.

The next block in .gitlab-ci.yml is the services block. Since our tests use testcontainers package and we're pushing a docker container onto Dockerhub, we will need to specify a services block next. Services will enable our pipeline to leverage Docker-in-Docker DinD.