etcd VS PostgreSQL

sudo dnf -y install curl wget vim ETCD_RELEASE=$(curl -s https://api.github.com/repos/etcd-io/etcd/releases/latest|grep tag_name | cut -d '"' -f 4) echo $ETCD_RELEASE wget https://github.com/etcd-io/etcd/releases/download/${ETCD_RELEASE}/etcd-${ETCD_RELEASE}-linux-amd64.tar.gz tar xvf etcd-${ETCD_RELEASE}-linux-amd64.tar.gz cd etcd-${ETCD_RELEASE}-linux-amd64 sudo mv etcd* /usr/local/bin ls /usr/local/bin /usr/local/bin/etcd --version

Reading the standard library will give you ideas/insight about various Go idiomatic patterns/approaches, and you can see a full website/API implementation in the pkg.go.dev repository (https://github.com/golang/pkgsite). Projects like https://github.com/etcd-io/etcd may be interesting too.

Failure Detection and Recovery It’s not enough to have backup systems. It’s also crucial to detect failures quickly. Modern systems employ monitoring tools and rely on distributed coordination systems such as Zookeeper or etcd to identify faults in real-time: once detected, recovery mechanisms are triggered to restore the service.

Service Discovery: Microservices need to discover and communicate with each other dynamically. Service discovery tools like etcd, Consul, or Kubernetes built-in service discovery mechanisms help locate and connect to microservices running on different nodes within the infrastructure.

APISIX uses etcd to store and synchronize configurations.

etcd is an excellent key-value distributed database used internally by Kubernetes and managed by the CNCF. It's a great option, and that's the reason why Apache APISIX uses it too. Yet, it's not devoid of issues.

Someone on HN (https://news.ycombinator.com/item?id=36682595) suggested etcd (https://etcd.io)

In traditional mode, APISIX stores its configuration in etcd. APISIX offers a rich API to access and update the configuration, the Admin API. In standalone mode, the configuration is just plain YAML. It's the approach for GitOps practitioners: you'd store your configuration in a Git repo, watch it via your favorite tool (e.g., Argo CD or Tekton), and the latter would propagate the changes to APISIX nodes upon changes. APISIX reloads its configuration every second or so.

I am not sure neither. But this might overcome the etcd's soft storage limit of 8GB? [1]

[1] https://github.com/etcd-io/etcd/issues/9771

Data Handling: Utilizes Windmill for data pipelines, with a primary database powered by PostgreSQL. Auxiliary data storage is handled by MongoDB, with Redis for caching to optimize performance

PostgreSQL

The LMS Moodle Operator serves as a meta-operator, orchestrating the deployment and management of Moodle instances in Kubernetes. It handles the entire stack required to run Moodle, including components like Postgres, Keydb, NFS-Ganesha, and Moodle itself. Each of these components has its own Kubernetes Operator, ensuring seamless integration and management.

Another key feature of txtai is being able to quickly move from prototyping to production. This article will demonstrate how txtai can integrate with Postgres, a powerful, production-ready and open source object-relational database system. After txtai persists content to Postgres, we'll show it can be directly queried with SQL from any Postgres client

SQL (Structured Query Language) databases are relational databases. They organize data into tables with rows and columns, and they use SQL for querying and managing data. Examples include MySQL, PostgreSQL, and SQLite.

Node.js, MySQL and PostgreSQL servers installed on your machine

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

I've used MySQL for years. But recently, I found myself working PostgreSQL and simple things like dumping and restoring a database are different enough that I decided to document the process. It's straightforward enough once I knew how.