talk-transcripts
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talk-transcripts
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Teach Yourself Programming in Ten Years (1998)
Thank you for this recommendation. I've never heard of it before and now I'm reading: https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
It's giving me energy this Monday holiday(USA)!
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Can't Be Fucked: Underrated Cause of Tech Debt
race?
> [Audience reply: Sprinter]
> Right, only somebody who runs really short races, okay?
> [Audience laughter]
> But of course, we are programmers, and we are smarter than runners, apparently, because we know how to fix that problem, right? We just fire the starting pistol every hundred yards and call it a new sprint.
https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
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Strong typing, a hill I'm willing to die on
>So this is 10x, a full order of magnitude reduction in (?) severity before we get to the set of problems I think are more in the domain of what programming languages can help with, right? And because you can read these they'll all going to come up in a second as I go through each one on some slide so I'm not going to read them all out right now. But importantly there's another break where we get to trivialisms of problems in programming. Like typos and just being inconsistent, like, you thought you're going to have a list of strings and you put a number in there. That happens, you know, people make those kinds of mistakes, they're pretty inexpensive.
[0] Video: https://www.youtube.com/watch?v=2V1FtfBDsLU
[1] Slides and transcript: https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
[2] Video https://www.youtube.com/watch?v=YR5WdGrpoug
[3] Slides and transcript https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
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Puzzle Languages
This is tangentially related to Puzzles-vs-Problems in Rich Hickey's Effective Programs
> Eventually I got back to scheduling and again wrote a new kind of scheduling system in Common Lisp, which again they did not want to run in production. And then I rewrote it in C++. Now at this point I was an expert C++ user and really loved C++, for some value of love. But as we'll see later I love the puzzle of C++. So I had to rewrite it in C++ and it took, you know, four times as long to rewrite it as it took to write it in the first place, it yielded five times as much code and it was no faster. And that's when I knew I was doing it wrong.
[...]
> So I mean for young programmers, if everybody's tired and old, this doesn't matter any more. But when I was young, when I was young, I really, you know, when you're young you've got lots of free space. I used to say "an empty head", but that's not right. You've got a lot of free space available and you can fill it with whatever you like. And these type systems they're quite fun, because from an endorphin standpoint solving puzzles and solving problems is the same, it gives you the same rush. Puzzle solving is really cool. But that's not what it should be about.
Talk: https://www.youtube.com/watch?v=2V1FtfBDsLU
Slides and transcript: https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
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All the ways to capture changes in Postgres
Using triggers + history tables (aka audit tables) is the right answer 98% of the time. Just do it. If you're not already doing it, start today. It is a proven technique, in use for _over 30 years_.
Here's a quick rundown of how to do it generically https://gist.github.com/slotrans/353952c4f383596e6fe8777db5d... (trades off space efficiency for "being easy").
It's great if you can store immutable data. Really, really great. But you _probably_ have a ton of mutable data in your database and you are _probably_ forgetting a ton of it every day. Stop forgetting things! Use history tables.
cf. https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
Do not use Papertrail or similar application-space history tracking libraries/techniques. They are slow, error-prone, and incapable of capturing any DB changes that bypass your app stack (which you probably have, and should). Worth remembering that _any_ attempt to capture an "updated" timestamp from your app is fundamentally incorrect, because each of your webheads has its own clock. Use the database clock! It's the only one that's correct!
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G. Polya, How to Solve It
Rich Hickey (creator of Clojure) references Polya several times in his classic talk "Hammock Driven Development". Here's a transcript:
https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
I've long been impressed by Hickey's problem solving skills, so I took much of this talk to heart, and even bought a copy of HTSI. Can't say it really helped me any more than Rich's talk (as a programmer) but I'm thinking I'll give it another look.
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Interfaces All the Way Down
>Great product designs require no manual, and similarly, great interfaces need no documentation. Imagine having to read a manual on how to use a coffee mug.
This could not be more wrong.
Not everything is easy. If a library is addressing a complicated domain, solving by definition a complicated problem, it is fine if it requires some learning.
When did expertise and learning become bad things? If software is an engineering discipline, why would people in it ever promulgate the idea that any random cog can step in to any “engineer”s shoes?
Rich Hickey analogizes this mentality to the world of music, where it taken for granted that learning an instrument requires a lot of study:
“ We start with the cello. Should we make cellos that auto tune? Like, no matter where you put your finger, it's just going to play something good, play a good note.
“[Audience laughter]
“Like, you're good. We'll just fix that.
“ Should we have cellos with, like, red and green lights? Like, if you're playing the wrong note, you know, it's red. You slide around, and it's green. You're like, great! I'm good. I'm playing the right song. Right?
“ Or maybe we should have cellos that don't make any sound at all. Until you get it right, there's nothing.
“ [Audience laughter]”
https://github.com/matthiasn/talk-transcripts/blob/master/Hi...
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Slightly off-topic: Whose lectures do you recommend listening to, similar to Rich Hickey?
You might find adjacent talks and speakers here ... https://github.com/matthiasn/talk-transcripts
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Functions vs. Procedures: Keep them separate.
Many languages merge the two concepts, and implement procedures as functions that return void. This may muddle/complect their distinction, causing programmers to call procedures from within functions, thereby making those functions into impure functions (meaning that they affect the world outside of themselves, through side-effects like I/O or mutating state). This should be avoided, especially if you care about debug-ability and Functional Core, Imperative Shell architectures (see Gary Bernhardt's Boundaries talk at 31:56) (which make testing your system easier, without mocking).
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What's the thing you avoided a lot but learned later, and it was really helpful?
A great way to do this in practice is to write design docs. I take an approach inspired by Rich Hickey's "Hammock Driven Development" - identify the problem, state it, write it down - describe what you know about it - try to describe what you know that you don't know about it - list the constraints your solution has to operate within - enumerate some potential solutions and explore their problems - (later) choose a path, and describe why it was chosen over the alternatives
Grafana
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Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana
Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within your Nomad environment.
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Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along.
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Monitoring, Observability, and Telemetry Explained
Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities.
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4 facets of API monitoring you should implement
Prometheus: Open-source monitoring system. Often used together with Grafana.
- Grafana: Open and composable observability and data visualization platform
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The Mechanics of Silicon Valley Pump and Dump Schemes
Grafana
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Reverse engineering the Grafana API to get the data from a dashboard
Yes I'm aware that Grafana is open source but the method I used to find the API endpoints is far quicker than digging through hundreds of files in a codebase I'm not familiar with.
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Building an Observability Stack with Docker
So, you will add one last container to allow us to visualize this data: Grafana, an open-source analytics and visualization platform that allows us to see traces and metrics simply. You can set Grafana to read data from both Tempo and Prometheus by setting them as datastores with the following grafana.datasource.yaml config file:
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How to collect metrics from node.js applications in PM2 with exporting to Prometheus
In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:
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Root Cause Chronicles: Quivering Queue
Robin switched to the Grafana dashboard tab, and sure enough, the 5xx volume on web service was rising. It had not hit the critical alert thresholds yet, but customers had already started noticing.
What are some alternatives?
rich4clojure - Practice Clojure using Interactive Programming in your editor
Thingsboard - Open-source IoT Platform - Device management, data collection, processing and visualization.
etaoin - Pure Clojure Webdriver protocol implementation
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
clj-chrome-devtools - Clojure API for controlling a Chrome DevTools remote
Heimdall - An Application dashboard and launcher
codetour - VS Code extension that allows you to record and play back guided tours of codebases, directly within the editor.
Wazuh - Wazuh - The Open Source Security Platform. Unified XDR and SIEM protection for endpoints and cloud workloads.
base - Unison base libraries
Thingspeak - ThingSpeak is an open source “Internet of Things” application and API to store and retrieve data from things using HTTP over the Internet or via a Local Area Network. With ThingSpeak, you can create sensor logging applications, location tracking applications, and a social network of things with status updates.
lumo - Fast, cross-platform, standalone ClojureScript environment
uptime-kuma - A fancy self-hosted monitoring tool