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.
In 2020, the web is still the most accessible permission-less platform. For the past few months, I have been playing and building side projects to simplify my life. I started with a Calendar Bot for scheduling events, DeckSaver for downloading decks from Docsend, AutoSnoozer for email management, and StayInTouch for maintaining follow-ups.
When I started on this journey, I had the following in my mind.
Docker containers are small OS images in themselves that one can deploy and run without worrying about dependencies or interoperability. All the dependencies are packed in the same container file. And the docker runtime takes care of the interoperability. You are not tied to using a single language or framework. You can write code in Python, Go, Java, Node.js, or any of your favorite languages and pack it in a container.
Consider a simple example of a Go-based webserver
Update: As of April 2020, I have switched over to GitHub Actions. Travis CI has become buggy and flaky over time and I got tired of trying to keep the builds green. My GitHub action scripts can be seen here.
Just like many software engineers, I maintain my config files for GNU/Linux and Mac OS in a git repository. Given that, I wrote a fair bit of them in interpreted code, notably, Bash, it is a bit hard to ensure that it is bug-free. The other problem I face is that packages on homebrew, the Mac OS package manager becomes obsolete and gets deleted from time to time.
I added CI testing on Travis CI to prevent these breakages and to ensure that my dotfiles are always in good shape for installation. The great thing about Travis CI is that it is entirely free for open-source repositories even for testing on Mac OS containers.
Earlier, the Software world was rigidly divided between closed and open-source software. Microsoft Windows is closed-source, GNU/Linux is open-source. Microsoft Office and Lotus Notes are closed-source, LibreOffice is open-source. Turbo C++ is closed-source, and GCC is open-source.
But now, a new class of software products has emerged whose core is open-source, but still, the open-source software is of limited use. One model is to offer some critical and useful functionality in a closed-source layer via a managed service in AWS/GCP/Azure, for example, Redis is open-source, but useful modules on top of it are not. Another model is to use licensing gimmickry, for example, MongoDB is licensed under SSPL which requires that if anyone offers MongoDB as a service, then the source code of the full service must be published under this license. The third approach is to make the core software open-source but make it dependent on closed-source cloud services. For example, the node package manager (npm) is open-source, but a closed source company owns the default npm registry. Android is open-source, but most day-to-day application ranging from Google Maps to Google Music are closed-source. Now onwards, rather than calling such software open-source, we should call them closeum.
Consider this email,
And now consider this one,
Hi Ashish,
You signed up for the Orchard beta not too long ago, and we’re excited to finally send you an invite!
(Just to jog your memory, Orchard helps you make the most of your relationships, keeping you up to date on where you’re spending your time and who you need to catch up with. It’s somewhere between a personal CRM and a todo list for your connections.) [Emphasis mine]
You should receive an invite from Apple’s Testflight service in the next few minutes. It will contain a code or link you need to install the app. You’ll also need to have the TestFlight app installed on your phone. If you need us to send the invite to a different email address, just reply to this message and let us know.
Once you’ve checked out the app, please send us your feedback — this is a beta and we need your help to improve! Be honest, frank, and opinionated: you won’t hurt our feelings. Bugs, ideas, concerns, etc all fair game. You can reply to me or send to team@orchard.ai.
Thank you!
Brian and the entire Orchard team
brian@orchard.ai
Which one do you think your early adopters have a higher likelihood of understanding and responding to?
Don’t forget while you might live and breathe your startup, your early adopters have probably signed up to try several such services, and unless you remind them what your product is about, they might as well delete the email and move on.
When the code runs on your servers, you have much more control over the “context” in which it runs. On the mobile devices, the device OS and the user control the context. This difference leads to some subtle implications.
One significant set of differences comes from the lack of control of the platform. For server-side code, one can choose from a wide array of languages. For the mobile code, however, the best choice would almost always be the one dictated by the platform – Java/Kotlin on Android and Objective-C/Swift on iOS. Further, for the server-side where one can stick to a particular version of the language. In the case of mobile, the platform controls the language version. Same goes regarding the hardware choices – one can choose to use different types of server machines specialized in handling those jobs, eg. GPUs for math-intensive computes. While for the mobile-code, one had to write a good enough fallback to support a wide-enough set the devices. Similarly, the server-side has to rarely worry about the server killing a running process while it is normal for mobile OSes to kill backgrounded processes eventually.
The other set of differences comes from the temporary changes to the platform introduced by the carrier and the user. A network request running on mobile has to be robust enough to deal with intermittent broken connectivity to outright unavailability of a data connection, e.g., due to the user switching to the airplane mode. On mobile, network type matters as well. A network request on cellular would usually cost more than a network request on Wi-Fi to the user and a network request on roaming even more. On mobile, the code has to be aware of not doing unnecessary work when the user is low on battery. Server-side code is rarely subjected to such constraints.
Lastly, it is possible to parallelize and speed up the server-side code by adding more resources like RAM or better CPUs. If a certain number of servers are not enough, you can add more. There isn’t usually a way to offload compute-intensive or memory-intensive work off of the mobile devices without trading it off for network latency and sometimes, user’s privacy as well. While it might be preferable to go with a multi-processing approach in the server code to avoid concurrency issues, on the mobile, however, multi-threading being more straightforward and less resource-intensive is almost always the choice.
While iPhone is recognized as a global name while erstwhile Nexus and now, Pixel has almost no branding outside of the Android fanboys.
Further on Google’s naming snafu:
The bandwidth of different senses
Our brain loves distractions, and multi-tasking gets bored quickly. When we read text or watch a photo, it engages us visually, a video (with audio) engages us even more. The bandwidth of eyes is much larger than the bandwidth of our ears. When we are watching something, it utilizes more bandwidth and hence occupies more of our attention span. Also, given the way our eyes work, we can focus more on the exciting aspect of the visual feed. Compared to that, audio underutilizes our brain’s bandwidth. Further, the unidimensional flow of audio data at a linear speed does not mimic our ability to process it. Contrast forced direct listening with how non-linearly humans read.
How eyes jump forward and backward while reading
And that’s why video games are even more engaging than video. They utilize the bandwidth even further by forcing us to think and act in the game.
Since audio underutilizes our brain’s bandwidth, it leaves spare bandwidth for distractions, including eating food, driving, and exercising. No wonder most audio consumption is passive and happens as a secondary activity as opposed to being a mainstream activity like reading or watching movies.