remix VS prometheus

Also, Remix sourcemaps didn't work with Cloudflare Workers, but it seems that it should be working already. I should double-check it!

Then in this Github issue, I found something new and flashy, Paraglide JS.

Relates to https://github.com/remix-run/remix/pull/3104

The main goal of this project was to learn something new in a fun way, so I've decided to use Remix for it, and oh my - it was perfect. I was amazed by how powerful it is by using just standard web features such as cookies, query parameters, and forms. Just remember to be cautious when picking a starter template for your project. I picked the default one, and later found out it wasn't supported by Netlify. As a result, I had to delete the entire repository and start the configuration process again. 🙈

Real time data update: Remix supports Server Sent Events e.g. https://github.com/remix-run/examples/tree/main/_official-realtime-app https://github.com/remix-run/remix/discussions/2622

Sometimes the best way to learn is by looking at examples, so we’re going to walk through this Remix issue from Nick Taylor.

You don't need NextJS for SSR. There are less opinionated alternatives like Remix that was built by the React Router team and is backed by Shopify now, you can use something like Razzle or one of its alternatives for semi-opinionated pure SSR or follow the Vite Docs and just do it yourself with express.

- I've found Remix's configurable routes helps to split very large Remix projects into independent features that scales well, when multiple server output bundles drops this will scale the deployments across serverless functions also. RFC. PR.

WriteRequest::timeseries is a vector (https://github.com/prometheus/prometheus/blob/main/prompb/re...) and

Developers widely use Prometheus as a system for operational monitoring and alerting for their projects. Here is a list of tools for monitoring frontend services with Prometheus.

Just to give an example of the power of Go for CLI builds, you may have already used or at least heard of Docker, Kubernetes, Prometheus, Terraform, but what do they all have in common? They all have a large part of their usability via CLI and are developed in Go 🐿.

Distributed system administrators need mechanisms and tools for monitoring individual nodes in order to analyze the system and promptly detect anomalies. Developers also need effective mechanisms for analyzing, diagnosing issues, and identifying bugs in protocol implementations. Logging, tracing, and collecting metrics are common observability techniques to allow monitoring and obtaining diagnostic information from the system; most of the explored code bases use these techniques. OpenTelemetry and Prometheus are popular open-source monitoring solutions, which are used in many of the explored code bases.

Setting up monitoring for a system, especially one involving GRPC communication, provides crucial visibility into its operations. In this guide, we walked through the steps to instrument both a GRPC server and client with Prometheus metrics, exposed those metrics via an HTTP endpoint, and visualized them using Grafana. The Docker-Compose setup simplified the deployment of both Prometheus and Grafana, ensuring a streamlined process.

Alerting and Notification: Select a tool with flexible alerting mechanisms to proactively detect anomalies or deviations from defined thresholds. Consider asking questions like "Does this tool offer customizable alerting options and support notification channels that suit our team's communication preferences?" A tool like Prometheus provides robust alerting capabilities.

Prometheus

Prometheus is an open-source monitoring and alerting toolkit. It is designed to monitor highly dynamic containerized systems, making it an excellent choice for monitoring Docker containers and Kubernetes clusters.

wget https://github.com/prometheus/prometheus/releases/download/v2.46.0/prometheus-2.46.0.linux-amd64.tar.gz

Prometheus: Open-source monitoring system. Often used together with Grafana.