While trying to install a custom exception handler to catch uncaught exceptions (crashes), I ended up writing
Java made a huge mistake of having no network timeouts. A network request can block a thread forever. Even Python did the same. The language designers should have chosen some conservative appropriate numbers instead.
What’s surprising is that the Go language repeated it! Here’s a simple demo
Rather than pushing the code to a remote branch and then testing via Circle CI servers, it is best to run the tests locally first and make them work. Here’s how you can do that.
On Android catching Java exceptions is easy via UncaughtExceptionHandler. Catching NDK crashes is a bit more convoluted. Since the native stack is probably corrupted, you want the crash handler to run on a separate process. Also, since the system might be in an unstable shape, don’t send the crash report to your web server or do anything fancy. Just write the crash report to a file, and on the next restart of the app, send to your web server and delete it from the disk. I ended up using jndcrash package for this.
After I wrote my previous post, some suggested that I can cut down the image size further by using a “scratch” image. And that’s true, “scratch i”s a reserved 0-sized image with nothing in it. And utilizing a scratch binary image did cut down the size of the final Docker image from 13MB to 7.5MB. Pretty good, right? Except the image cannot do an SSL cert verification because of the missing SSL certs!!!
Failed to reach google.com: Get https://google.com: x509: certificate signed by unknown authority
60 milliseconds is when we notice something isn’t immediate. Any user interaction, that involves sending data over the network or doing heavy computation on it, usually takes way longer than 60 milliseconds. So, we end with a progress bar. There are two broad categories of progress bars, one that shows the absolute/relative progress, a determinate progress bar, and one that does not an indeterminate progress bar.
Recently, this question came up during the discussion. “How many source-code repositories should a startup have?”
There are two extreme answers, a single monorepo for all the code or repository for each library/microservice. Uber, for example, had 8000 git repositories with only 200 engineers! I think both extremes are wrong. Too many repositories make it hard to find code and one single repository makes it harder to do simple things like testing, bisecting (to find buggy commit), deciding repository owners.
We all have to make significant code changes from time to time. Most of these code changes are large. Consider the scenario that you merged one such significant change, and then other team members made a few more changes on top. Then a major bug is detected. You desperately make the fix. It makes it in. You declare a victory, and a few hours later, your colleague notices another bug/crash/performance regression. Your commit cannot be reverted. It isn’t just about you. Many others have built on top of the change you made—the code sloths along in this broken state for a few days before you eventually fix it. Everyone has faced this issue at some point or the other.
To use monorepo or not is an eternal debate. Each has its pros and cons. Let’s say you decide to go with monorepo, one major issue you will face over time is slow testing. Imagine a monorepo, consisting of an Android app, an iOS app, some backend code, some web frontend code. On only very few occasions will someone modify more than one of those simultaneously.