We recently released the stable 1.0.0 release of our prometheus_client package — a way to expose Prometheus metrics in your Dart application. It’s inspired by similar packages like the official client_java for Java or the community package prom_client for Node.js. We have several Microservices written in Dart where we use the package to provide observability. I want to share the experience we had while developing the package.
I recently wrote about my indicators that I use while choosing dependencies in the NPM ecosystem. After writing the post I thought, can you automate these steps to provide a quick view on package health? One tool that does that is the Snyk Advisor. I tried the advisor and want to summarize my experience.
In my previous post, I wrote about choosing dependencies wisely. The NPM ecosystem is known for its small packages with a lot of dependencies. You can quickly lose track about your dependency usage. Do you have all dependencies configured correctly? Are all of your dependencies still in use? I want to present you depcheck, a small utility to keep track of your dependency usage.
Open-Source software brings great opportunities through a huge ecosystem of reusable packages. The NPM ecosystem grows by millions of packages each year. With so many packages, there is one for everything! There are central server packages like express, famous UI frameworks like react, widely used build tools like @babel/core, or helpful utilities like lodash. But there are also very specific packages solving niche problems, like a video container format writer based on JSX or an xkcd API client. But not every package is a good pick, often they turn out as a bad choice later on. To avoid regrets when choosing Open-Source dependencies, here are some points to consider.
If you are using react and test your components (you should!), then you are probably using the Testing Library. Testing helps to be confident that your components work as expected — especially in corner cases that are harder to test manually. The learning curve for a library can be steep, but doesn’t have to!
Even with fast internet speeds, one key metric for improving initial page load times for websites or web apps is reducing the data transmitted over the wire. While you can optimize all kinds of assets, like styles and images, I want to focus on the size of the JavaScript bundles. Code size has an impact on download duration, but also on parsing and JavaScript execution. This can be measured as Total Blocking Time (TBT) or First Input Delay (FID), a metric suggested by Google to measure page performances as part of the Web Vitals.
Welcome to the Blog of Tentacle Labs! Recently we got inspired by a post on the StackOverflow blog. It highlights how developers benefit from expanding their skill of writing text, not just source code. One point got us hooked in particular: “if you can’t teach it, then you don’t really know it.”
