Fluentd VS go-sqlmock

Get Started with Fluentd

Currently, there is no cluster-wide logging. Fluentd can be used to have a unified logging layer for the cluster.

Fluentd hasn't been touched for 8 years? Looking at the repo it looks like it's alive and well. https://github.com/fluent/fluentd

Fluentd is an open-source log management and data collection tool. Just like Logstash, Fluentd uses a pipeline-based architecture. This allows it to collect data from various sources and network traffic and forward it to various destinations.

Fluentd is a powerful log management tool that offers organizations the flexibility and scalability required to handle large volumes of log data from a variety of sources and transport it to various destinations. Utilizing a flexible and modular architecture, Fluentd allows users to easily add new input and output plugins to integrate with a wide range of systems and applications. It supports a wide range of data sources and destinations, including databases, message queues, and data stores.

Substation is an affordable alternative to products like Cribl (~10x cost savings) and is easier to manage than similar open-source projects such as Logstash and fluentd. It's been used in production by the security team at Brex for 2+ years and is ready for any scale, even beyond 100,000 events per second!

There are probably too many to chose from. Logstash, Promtail, Vector, Filebeat, FluentD, Logagent and probably many more

To alleviate some of the pain, it’s a good idea to use industry standards and tooling like OpenTelemetry (https://opentelemetry.io). For data collection specific to logs, open-source tools like LogStash and Fluentd are also popular.

Created and maintained by the creators of fluentd, fluentbit is a lightweight, fast, and scalable logging and metrics processor and forwarder. Built specifically for the cloud and containerized environments, it allows users to collect data from any source, enrich it with filters and forward it to the tool of their choice.

For that, I used the lib go-sqlmock. So, for example, the following snippet is part of the person/service_test.go file:

It's not the right call IMO to skip mocking the database connection to achieve 100% test coverage. How your app will behave in failure scenarios that are impossible to imitate during integration tests is part of the software contract. If your choice is to panic, or return an error, document that by testing that behavior. If another dev, or future you inadvertently breaks the contract, the test suite will fail. That's what you want. For unit tests against your database you should be using either go-sqlmock if testing against database/sql or pgxmock if testing against pgx. That being said, the points raised elsewhere in this thread regarding unit tests potentially hiding edge cases in terms of how an actual database will interact with your application that are not reflective of your understanding when writing mocks are 100% valid. You should do both. Unit test your app and write integration tests as well. On my team, we run integration tests using docker-compose.

I use Sqlmock for that purpose

There is a good lib for db tests https://github.com/DATA-DOG/go-sqlmock