The Cursor AI code editor raises $60 million, RedMonkâs Rachel Stephens tries to determine if rug pulls are worth it, Caleb Porzio details how he made $1 million on GitHub Sponsors, Elastic founder Shay Banon announces that Elasticsearch is open source (again) & Tomas Stropus writes about the art of finishing.
Dendron founder, Kevin Lin:
PMF is not just your only job but it is the job that only you, the startup founder, can do. Your investors can help introduce you to relevant people, successful founders can tell you how they found PMF, but ultimately, you are the only person that can determine PMF for your company.
And donât forget to talk your users along the way!
Philip Walton:
While most teams I talk to would love to be able to run A/B tests to accurately assess the performance impact of certain changes, the problem is pretty much every popular A/B testing tool on the market has such a negative impact on load performance that theyâre essentially unusable for this purpose.
If youâre just trying to determine which of two marketing headlines converts better, then perhaps this performance difference isnât so bad. But if youâre wanting to run an A/B test to determine whether inlining your CSS in the
<head>of your pages will improve your FCP, well, those popular A/B testing tools are just not going to cut it.
He goes on to describe his process for running performant A/B tests on his static site using Cloudflare workers to swap in/out his experiments.
Check your site against this to determine your accessibility compliance with the WCAG.
Hot off the press from our friend Ben Johnson:
Postlite is a network proxy to allow access to remote SQLite databases over the Postgres wire protocol. This allows GUI tools to be used on remote SQLite databases which can make administration easier.
The proxy works by translating Postgres frontend wire messages into SQLite transactions and converting results back into Postgres response wire messages. Many Postgres clients also inspect the
pg_catalogto determine system information so Postlite mirrors this catalog by using an attached in-memory database with virtual tables. The proxy also performs minor rewriting on these system queries to convert them to usable SQLite syntax.
It appears that Ben is taking code contributions this time around, but only for bug & documentation fixes.
Curl maintainer Daniel Stenberg:
We canât know for sure which products are on the top list of the most widely deployed software components. Thereâs no method for us to count or estimate these numbers with a decent degree of certainty. We can only guess and make rough estimates â and it also depends on exactly what we count. And quite probably also depending on whoâs doing the counting.
He goes through his process of trying to determine contenders, and ends up with zlib, qlite, and libcurl. Other have added OpenSSL, expat and the Linux kernel to that list.
Angie Rojas shared some insights into what Deno brings to the TypeScript ecosystem and whether or not it will ârender Node.js obsolete.â
During the last 10 years, Node.js has become a big player in the backend framework market, powering several large scale applications across the globe. Meanwhile, JavaScript has also evolved greatly, not only because of the efforts of its development team, but also based on community feedback. However, integrating some of these new language features into a 10-year-old framework is not really straightforward, and has a high level of complexity.
Therefore we could say that Node.jsâ architecture hasnât evolved as fast as the language. As a basic example, Node.js is still based on callbacks, while there are far better ways to deal with asynchronicity in modern JavaScript. This is something that its creator, Ryan Dahl, has acknowledged in the past few years, and it has moved him to work on a new framework that addresses some of these issues. It is called Deno, and in the following article, we would like to explore some of its concepts to determine if it will render Node.js obsolete.
Daniel Moch shared his thoughts on semantic versioning and how he treats external libraries that violate its inherent contract with developers.
So as not to bury the lede, Iâll get to my point: Semantic Versioning is a meta-API, and maintainers who are cavalier about violating it canât be trusted to created stable contracts. Iâve lost patience for breaking changes making their way to my code bases without the maintainers incrementing the major version of their projects, especially in language ecosystems where Semantic Versioning is expected, and in such cases Iâm going to begin exploring alternative options so I can ban such libraries from my projectsâpersonal and professionalâaltogether.
âŚ
If you work in a language ecosystem where Semantic Versioning is the de facto norm, where violating it can wreak havoc downstream, then please play nice and follow its dictates. Instead of viewing it as a straight jacket, try to see it as an algorithm to determine what your next release number should be. We should all like algorithms!
Choosing a database is hard. They each have their pros and cons, and without much experience it is hard to determine which is the best fit for your project. In this episode Johan Brandhorst joins us to talk about Postgres. When is it a good fit? How well does it scale? What libraries exist in Go for using Postgres?
critic.shexposes high level functions for testing consistent with other frameworks and a set of built in assertions. One of my most important goals was to be able to pass in any shell expression to the_testand_assertmethods, so that one is not limited to the built-ins.The coverage reporting is currently rudimentary, but it does indicate which lines havenât been covered. It works by running the tests with extended debugging, redirecting the trace output to a log file, and then parsing it to determine which functions/lines have been executed. It can definitely be improved!
See a demo of critic.sh in action on asciinema đ˝ď¸
Phoenix 1.3 introduced the idea of Contexts, which Iâm generally very much in favor of. However, I wish there was a little bit more structure to the idea. Itâs so open ended that Iâve found deciding where best to put a function kind of tricky, and then I frequently end up with duplicate behavior across contexts or have a hard time finding functions later on because the module theyâre in made sense at the time, but it doesnât make as much sense now.
So, Iâm proposing the idea of a Primary Context and a Secondary Context.
Iâve also struggled to determine just how to use Contexts to my benefit. It seems that Devon is trying an add more structure approach whereas I have (so far) gone with a YAGNI approach.
Well, it depends. But the good news is Jason Etcovitch (Engineer at GitHub) examines the pros and cons of each and where they fit. He even shared a comparison table to help determine which to choose.
Should your next automation tool be built in GitHub Actions or as a separate service with Probot? Since GitHub announced the beta release of GitHub Actions in October 2018, thereâs been a new excitement around building automation - and thatâs awesome! But I wanted to take a look at the various pros and cons of GitHub Actions and Probot, where each excels and where each might not be the best tool for the job.
Click through and scroll to the bottom of the post if all you care about is the comparison.
Hold on to your seat! This is a deep dive on improving time-to-interactive for Netflix.com on the desktop. Addy Osmani writes on the Dev Channel for the Chromium dev team regarding performance tuning of Netflix.com. They were trying to determine if React was truly necessary for the logged-out homepage to function.
Even though Reactâs initial footprint was just 45kB, removing React, several libraries and the corresponding app code from the client-side reduced the total amount of JavaScript by over 200kB, causing an over-50% reduction in Netflixâs time-to-interactivity for the logged-out homepage.
Thereâs more to this story, so dig in. Or, share your comments on their approach to reducing time-to-interactivity and if you might have done things differently.
How do you develop an idea for a talk, determine the conferences to pitch, actually deliver the talk, and whether or not itâs even worth doing? Joshua Comeau writes on Medium:
Iâm still very much at the beginning of my career. Iâm only ~5 years into what will likely be a 40-year career, so Iâm only about 1/8th through! That thought is simultaneously liberating and dizzying; it means I donât have to feel rushed when it comes to making the most of every available opportunity, but it also means I have no clue whatâs ahead.
Conference-speaking is a worthwhile endeavor, but itâs one heck of a bumpy ride, and not always worth it. Iâll continue to prepare talks â as long as folks still want to hear what I have to sayâŚ
Joshua ends with an invitation ⌠đ
I encourage you to give it a shot. Feel free to reach out to me, Iâm always happy to give your proposal a quick read :)
You know how it goes: you set up your app to auto-crop uploaded images and it blindly follows your orders, cropping out the most interesting part of your usersâ images.
Not anymore, baby! Caire uses an energy map to perform edge detection and determine the least important parts of to crop out. Itâs more complicatd than that, but the whole process is described in the README so click through for the nitty, gritty.
The results are pretty impressive!
Despite the recent announcement to fix AMPâs URLs, a large community of web workers (the people, not the feature) are âdeeply concernedâ about Googleâs Accelerated Mobile Pages:
AMP keeps users within Googleâs domain and diverts traffic away from other websites for the benefit of Google. At a scale of billions of users, this has the effect of further reinforcing Googleâs dominance of the Web.
The whole letter is brief and worth reading to determine if youâre for or against its message. The key statement:
The Web is not Google, and should not be just Google.
You can sign the letter with a pull request, but youâll have to wait in line.
Eduardo Cuducos joined the show to talk about Operação Serenata de Amor an Artificial Intelligence and Data Science project that aims to inform the general public about government corruption and spending. We talked about how this artificial intelligence project analyzes claims for reimbursement from congresspeople to determine illegal probability, how it monitors government spending, the technology behind it, and how other governments might be able to follow this model.
Nadia Eghbal joined the show to discuss a HUGE topic thatâs near and dear to our heart â funding open source! We discussed what it takes to fund open source software development, Nadiaâs current investigative journalism efforts around funding open source (funded by the Ford Foundation), venture-backed open source projects, what it means for an open source project to be in good shape, some potential solutions to provide better long-term support for open source, and we tried to determine how much the open source of the world might be worth.
parallax.js is a lightweight parallax engine that responds to the movements from your smartphoneâs gyroscope and motion detection. The tool lets you specify depths and directions that determine how your webscape responds to physical movement.
Creating layers is super simple, as documented:
Simply create a list of elements giving each item that you want to move within your parallax scene a class oflayerand adata-depthattribute specifying its depth within the scene. A depth of 0 will cause the layer to remain stationary, and a depth of 1 will cause the layer to move by the total effect of the calculated motion.
Parallax.js is useable in jQuery and Zepto as a plugin, too.
MIT Licensed. Browse the source code on Github.
From John Egan, Growth Hacker at Shopkick, Flawless is a Python framework that catches exceptions and uses git-blame to notify only the developer that wrote the buggy code.
How Flawless works:
The Flawless client wraps your code with a try/except block. When an exception is caught it then sends the entire traceback to the Flawless server. The Flawless server then aggregates exception reports from clients and figures out which line of code caused the exception. Once the line that caused the exception is identified, Flawless runs "git blame" to determine the email address of the developer that last touched that line of code. Flawless then sends the developer an email with the traceback.
Check out the GitHub page for Flawless for more details and setup instructions.
The Rails 3 Asset Pipeline is super powerful, but it has one thing about it thatâs truly annoying: tons of logger output in development mode. Hereâs a simple Rails appâs log output when hitting an index page:
Started GET "/" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Processing by ArticlesController#index as HTML
Article Load (0.2ms) SELECT "articles".* FROM "articles"
Rendered articles/index.html.erb within layouts/application (2.3ms)
Completed 200 OK in 11ms (Views: 9.5ms | ActiveRecord: 0.2ms)
Started GET "/assets/authors.css?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /authors.css - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Started GET "/assets/tags.css?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /tags.css - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Started GET "/assets/jquery.js?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /jquery.js - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Started GET "/assets/comments.js?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /comments.js - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Started GET "/assets/tags.js?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /tags.js - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Started GET "/assets/application.js?body=1" for 127.0.0.1 at 2012-04-16 13:48:27 -0400
Served asset /application.js - 304 Not Modified (0ms)
[2012-04-16 13:48:27] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Seriously, I chopped about half of that out. Really, really annoying.
Enter quiet_assets. This little gem makes all of this junk go away. To install it, just add
gem 'quiet_assets', :group => :development
to your Gemfile, bundle, and breathe. Now, it just looks like this:
Started GET "/" for 127.0.0.1 at 2012-04-16 13:51:54 -0400
Processing by ArticlesController#index as HTML
Article Load (0.1ms) SELECT "articles".* FROM "articles"
Rendered articles/index.html.erb within layouts/application (2.7ms)
Completed 200 OK in 115ms (Views: 65.2ms | ActiveRecord: 1.8ms)
[2012-04-16 13:51:54] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
[2012-04-16 13:51:54] WARN Could not determine content-length of response body. Set content-length of the response or set Response#chunked = true
Much nicer. I can actually tell whatâs going on!
Marcin Kulik has released vim-pasta, a plugin for Vim that looks at the destination context to determine the indentation level for pasted text. Consider a paste with the cursor on line 1 of the following code block:
if i_were_president
<paste would land here>
<when you really wanted it here>
...
end
Vim-pasta drops the text at the correct indentation level, in this case nested inside the if. Also, vim-pasta preserves indentation within the pasted code, preserving the format of blocks like this example:
obj = {
a: 1,
b: 2,
foo: 3,
barbaz: 4
}
Pasta is disabled by default for Python, CoffeeScript, and Markdown since the destination indentation level canât easily be guessed for these languages. You can configure how vim-pasta handles other languages via its black and white lists:
let g:pasta_disabled_filetypes = ['python', 'coffee', 'yaml']
let g:pasta_enabled_filetypes = ['ruby', 'javascript', 'css', 'sh']
See the README for advanced usage.
For developers, application logs are critical to figuring out whatâs going on inside the apps we create. We tail them. We search them. We analyze and graph them. Graylog2 a slick log management, monitoring, and alerting tool powered by Java, Ruby, and MongoDB, performs these well. Graylog consists of a Java server that collects your logging data and stuffs it into MongoDB and a Ruby on Rails web interface for searching, filtering, and graphing that data.
Graylogâs server component requires Mongo version 1.6 or later and a Java environment.
Check out the projectâs wiki for installation and startup instructions. Graylog also supports AMQP as an alternate transport for messages, just configure appropriately in your config file.
Graylog supports writing custom rules to determine what messages find their way to MongoDB and in what form, using Drools Expert, as in this example:
import org.graylog2.messagehandlers.gelf.GELFMessage
rule "Rewrite localhost host"
when
m : GELFMessage( host == "localhost" && version == "1.0" )
then
m.setHost( "localhost.example.com" );
System.out.println( "[Overwrite localhost rule fired] : " + m.toString() );
end
rule "Drop UDP and ICMP Traffic from firewall"
when
m : GELFMessage( fullMessage matches "(?i).*(ICMP|UDP) Packet(.|n|r)*" && host == "firewall" )
then
m.setFilterOut(true);
System.out.println("[Drop all syslog ICMP and UDP traffic] : " + m.toString() );
end
In addition to syslog format, Graylog also supports GELF, or the Graylog Extended Log Format, which offers
Hereâs a quick example of a GELF message:
{
"version": "1.0",
"host": "www1",
"short_message": "Short message",
"full_message": "Backtrace herennmore stuff",
"timestamp": 1291899928,
"level": 1,
"facility": "payment-backend",
"file": "/var/www/somefile.rb",
"line": 356,
"_user_id": 42,
"_something_else": "foo"
}
A GELF message is just a GZIPâd or ZLIBâd JSON string. Check the GELF Spec for a list of required fields.
Graylog also ships with a rather slick web interface for searching and viewing Graylog messages. Filters can be applied and saved into logical âstreamsâ, allowing you to look at a slice of your data.
Graylog can even alert you when certain thresholds are exceeded for a given stream, as in this example email alert:
From: graylog2@example.org
To: lennart@socketfeed.com
Subject: [graylog2] Stream alarm! (Stream: Finance)
# Stream >Finance< has 23 new messages in the last 15 minutes. Limit: 15
# Description: Just a dummy stream with a not-so-random name but random data.
From: graylog2@example.org
To: lennart@socketfeed.com
Subject: [graylog2] Subscription (Stream: Finance)
# Stream >Finance< has 24 new messages since 2011-01-08 20:31:13 +0100
2011-01-08 21:12:38 +0100 from >localhost.localdomain<
sundaysister kernel: [92837.097110] CPU0: Core temperature/speed normal
2011-01-08 21:12:38 +0100 from >localhost.localdomain<
sundaysister kernel: [92837.096461] CPU0: Core temperature above threshold, cpu clock throttled (total events = 1485916)
For Ruby web applications, there is a bonus Rack application that allows you to send all application exceptions to Graylog in the spirit of Hoptoad.
The great thing about open source is that youâre likely to find a project that is as âfull-featuredâ or âlightweightâ as your tastes. Happy.js from Henrik Joreteg at &yet aims to be a lightweight form validation plugin for jQuery or Zepto.js that also supports the HTML5 required input attribute.
To use Happy.js, youâll need to include three items in your documentâs <head>.
jQuery (or Zepto.js)
<script src="jquery.js"></script>
Happy.js itself
<script src="happy.js"></script>
Your JavaScript validation functions either externally referenced or inline, like this example:
<script type="text/javascript" charset="utf-8">
var happy = {
USPhone: function (val) {
console.log('is phone called');
return /^(?(d{3}))?[- ]?(d{3})[- ]?(d{4})$/.test(val)
},
email: function (val) {
return /^((([a-z]|d|[!#$%&'*+-/=?^_`{|}~]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])+(.([a-z]|d|[!#$%&'*+-/=?^_`{|}~]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])+)*)|((x22)((((x20|x09)*(x0dx0a))?(x20|x09)+)?(([x01-x08x0bx0cx0e-x1fx7f]|x21|[x23-x5b]|[x5d-x7e]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(\([x01-x09x0bx0cx0d-x7f]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))))*(((x20|x09)*(x0dx0a))?(x20|x09)+)?(x22)))@((([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])([a-z]|d|-|.|_|~|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])*([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))).)+(([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])([a-z]|d|-|.|_|~|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])*([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))).?$/i.test(val);
},
minLength: function (val, length) {
return val.length >= length;
},
maxLength: function (val, length) {
return val.length <= length;
},
equal: function (val1, val2) {
console.log('isEqual called', val1, val2);
console.log((val1 == val2));
return (val1 == val2);
}
};
</script>
With the script in place, you can set up your HTML as usual:
<form id="awesomeForm" action="/lights/camera" method="post">
<input id="yourName" type="text" name="name" />
<input id="email" type="text" name="email" />
</form>
⌠and then add your validation rules with .isHappy:
<script>
$(document).ready(function () {
$('#awesomeForm').isHappy({
fields: {
// reference the field you're talking about, probably by `id`
// but you could certainly do $('[name=name]') as well.
'#yourName': {
required: true,
message: 'Might we inquire your name'
},
'#email': {
required: true,
message: 'How are we to reach you sans email??'
test: happy.email // this can be *any* function that returns true or false
}
}
});
});
</script>
Validation options determine if a value is required, a message displayed upon failure, and a test function you supply to validate the field value. This function can be anything that returns true or false. On blur and submit events Happy.js will run validations and set an unhappy class on the field and prepend the field with an error message like this one, which you can style with CSS:
<span id=â"textInput1_unhappy" class=â"unhappyMessage">âPlease enter an emailâ</span>
Happy.js also lends itself to Underscore.js integration, with Underscoreâs mixin feature:
_.mixin({
USPhone: function (val) {
console.log('is phone called');
return /^(?(d{3}))?[- ]?(d{3})[- ]?(d{4})$/.test(val)
},
email: function (val) {
return /^((([a-z]|d|[!#$%&'*+-/=?^_`{|}~]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])+(.([a-z]|d|[!#$%&'*+-/=?^_`{|}~]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])+)*)|((x22)((((x20|x09)*(x0dx0a))?(x20|x09)+)?(([x01-x08x0bx0cx0e-x1fx7f]|x21|[x23-x5b]|[x5d-x7e]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(\([x01-x09x0bx0cx0d-x7f]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))))*(((x20|x09)*(x0dx0a))?(x20|x09)+)?(x22)))@((([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])([a-z]|d|-|.|_|~|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])*([a-z]|d|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))).)+(([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])|(([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])([a-z]|d|-|.|_|~|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF])*([a-z]|[u00A0-uD7FFuF900-uFDCFuFDF0-uFFEF]))).?$/i.test(val);
},
minLength: function (val, length) {
return val.length >= length;
},
maxLength: function (val, length) {
return val.length <= length;
},
equal: function (val1, val2) {
console.log('isEqual called', val1, val2);
console.log((val1 == val2));
return (val1 == val2);
}
});
With this integration option, set up your validation test to _.email instead of happy.email;
Douglas Crockford, author of JavaScript: The Good Parts and creator of JS Lint (featured in Episodes #26 and #46), wants to apply his Chuck Norris-style skills to protect the web from rogue widgets and ads.
ADSafe locks down guest script access to global variables and other page information and provides safe, indirect access to certain items via an ADSAFE object. ADSafe blocks or modifies access to:
this - If a method is called as a function, this is bound to the global object. Since ADsafe needs to restrict access to the global object, it must prohibit the use of this in guest code.arguments - Access to the arguments pseudo-array is not allowed.eval - The eval function provides access to the global object.with statement - The with statement modifies the scope chain, making static analysis impossible.arguments, callee, caller, constructor, eval, prototype, stack, unwatch, valueOf, and watch - Capability leakage can occur with these names in at least some browsers, so use of these names with . notation is prohibited._ - Some browsers have dangerous properties or methods that have a dangling _.[ ] subscript operator except when the subscript is a positive numeric literal or string literal - Lookup of dynamic properties could provide access to the restricted members. Use the ADSAFE.get and ADSAFE.set methods instead.Date and Math.random - Access to these sources of non-determinism is restricted in order to make it easier to determine how widgets behave.An example ADSafe widget provides a <div> and enclosed <script> tag that uses the ADSAFE proxy object:
<div id="WIDGETNAME_">
html markup required by the widget
<script>
ADSAFE.go("WIDGETNAME_", function (dom) {
"use strict";
// This is where the code for the widget is placed. It can access
// the document through the dom parameter, allowing it indirect
// access to html elements, allowing it to change content, styling,
// and behavior.
});
</script>
</div>
ADSafe also allows loading approved external libraries:
<div id="WIDGETNAME_">
html markup required by the widget
<script>
ADSAFE.id("WIDGETNAME_");
</script>
<script src="ADsafe approved url"></script>
<script>
ADSAFE.go("WIDGETNAME_", function (dom, lib) {
"use strict";
// This is where the code for the widget is placed. It can access
// the document through the dom parameter, allowing it indirect
// access to html elements, allowing it to change content, styling,
// and behavior.
// Each library file can give itself a name. This script can access
// the library file as lib.name.
});
</script>
</div>
The source provides additional templates for creating ADSafe library modules and widgets. Be sure and check out the project web site for documentation on the ADSAFE object and other advanced usage.
When you command many domains or even just a few domains, what tools do you use to understand the various services your domain uses?
Domain profiler is a tool by JoĂŤl Franusic that generates profile reports on âDecisions that cost moneyâ. It leverages information from various sources such as Whois, DNS, SSL, ASN and more to determine what decisions have been made regarding a domain or list of domains.
These decisions fall into two categories:
Take a peek at this example report for Y Combinator domains.
There are two tools that ship with the current version of Domain Profiler. Before you get started youâll need to install Matt Aimonettiâs googlecharts gem.
gem install googlecharts
Next you need to fork it and pull down your copy.
git clone git@github.com:YOURUSERNAME/domain-profiler.git
The first command is a quick gist for a single domain that outputs to the prompt.
./profile [DOMAIN]
Letâs see this in action
$ ./profile thechangelog.com
==========[ thechangelog.com ]==========
Web Hosting:
(Rackspace)
72.32.231.8
DNS Hosting:
(Go Daddy)
ns39.domaincontrol.com.
ns40.domaincontrol.com.
Email Hosting:
(Google)
10 ASPMX.L.GOOGLE.com.
20 ALT1.ASPMX.L.GOOGLE.com.
30 ALT2.ASPMX.L.GOOGLE.com.
40 ASPMX2.GOOGLEMAIL.com.
50 ASPMX3.GOOGLEMAIL.com.
Domain Registrar:
(Go Daddy)
SSL Issuer:
(none)
Common Name: none
The second command reads a file that contains a list of domains and generates an HTML-based report like the Y Combinator report shown above, only this time itâs GitHub.com and a few of their known domains.
./profile-list [DOMAIN-FILE]
Letâs see this in action (assuming the file exists)
$ ./profile-list github-list "GitHub" > github.html
Fetching data for github.com: DNS Whois SSL ...
Fetching data for jobs.github.com: DNS Whois SSL ...
Fetching data for status.github.com: DNS Whois SSL ...
Fetching data for shop.github.com: DNS Whois SSL ...
Fetching data for develop.github.com: DNS Whois SSL ...
Once the above has completed itâs routine, it dumps the output from the report to github.html. The trailing âGitHubâ on the command adds that as a title to the html output file. Below is an example of what youâll see.
Adam talks with Lance Jones and Joanna Wiebe, Founders of Page99Test.com. People in bookstores often read page 99 of a book to get a taste for the writing - to determine if theyâd buy the book. Lance, Joanna and technical Co-Founder, Steven Luke took that time tested idea and have built a brand new platform for book enthusiasts, authors, agents and publishers to get excited about.
Kaizen 19 has arrived! Gerhard has been laser-focused on making Jerodâs pipe dream a reality by putting all of his efforts into Pipely. Has it been a big waste of time or has this epic side quest morphed into a main quest?!
Matched from the episode's transcript đ
Gerhard Lazu: I think we can talk about that now, just so we go through this. We never had this situation before, by the way, where we have two application instances completely separate, that are pointing to the same database. So the data is always the same, but one is going to become the new production, and itâs configured in a certain way, with a new CDN, and the existing application, the one thatâs behind Changelog.com is still consumed by our production CDN. I mean, we have two CDNs. Thatâs the situation. And we canât change the production application, because if we do that, then we have rolled out the new CDN and we donât know whether we are ready yet. I think thatâs what we need to determine today. What else is left? How do things look so far? And just like assess the readiness of the new CDN.
Anthony Eden, Founder & CEO of DNSimple, joins the show to talk about the world of managed hosting for DNS and more.
Matched from the episode's transcript đ
Anthony Eden: So thatâs good, from my point of view at least. It doesnât mean that I donât pay attention anytime that thereâs an incident. And we have very well-documented incident handling policies. We have one person from the engineering team, and it rotates around the whole engineering team, thatâs always on call. And then that person, if an incident starts occurring, they can basically â we have instructions. We have an incident channel in Slack, fire up a Google Meet, get whoeverâs online right now, triage the incident. If you canât triage it, then let it ping up everybody, and all engineers who are available or who are woken up can come in and try to fix it.
[00:55:59.09] We recently switched everything for deployment over to Nomad, which is HashiCorpâs technology for deploying containers out, essentially, in a well-orchestrated fashion. We also finally bit the bullet last year and the year before and started containerizing everything, so now we have pretty much everything containerized as well.
We deploy using ChatOps. So you can do all that type of stuff directly from within Slack. You can query our â we have tools, for example, to determine if particular domains are being hit harder, or what have you, get stats on things⌠And you can do that from ChatOps as well.
And then for observability, weâve run everything through Datadog for many, many years. And so we have the ability to use Datadog to look at logs, to look at metrics⌠We donât do APM level things, because itâs very expensive. Thereâs a large cost associated with it. So we do a lot of our analysis off of logs and off of just general metrics that we keep to determine â because the failure cases, most of them are fairly well known now, so we can alert based on commonly known failure cases for our systems.
Stephan Ewen, Founder and CEO of Restate.dev joins the show to talk about the coming era of resilient apps, the meaning of and what it takes to achieve idempotency, this world of stateful durable execution functions, and when it makes sense to reach for this tech.
Matched from the episode's transcript đ
Stephan Ewen: The short answer is itâs really, I would say, the state of the art to build backends that are supposed to â backends that do any non-trivial state management and coordination, itâs completely unsustainable, I think, the way weâre building this today. Just to give you an example⌠Or letâs actually start with an example. Letâs stay with LLM, because we just talked about it, right? So letâs say youâre building a chatbot; youâre submitting something, like a message there⌠This thing in the end has to reach the LLM, but it has to look up the context in which that chat happened before, it has to make the call, it has to go back, store the context⌠You donât want it to just lose everything if you lose your connection in the middle of â letâs go with the F5 thing again⌠You donât want it to actually trigger the same request twice, or lose the entire session, make you start over. So youâre probably just putting this as an asynchronous request that runs in the background, that youâre sending from your from your chat session, from your browser, but itâs a separate asynchronous request that runs, that talks to the LLM. You want it to be actually retrying in case something fails, or is overloaded and itâs throttling your [unintelligible 00:15:19.22] And then you want to be able to reconnect to that task or request in case something goes wrong in your browser, or you accidentally hit the Back button, or whatever. Just implementing this is a surprisingly complicated thing, where you start to stitch together probably a queue, a database, and a bunch of tasks to manage that.
To give you another example - we just talked about Stripe, right? So letâs say youâre sending a request there for a payment, and sometimes they tell you âLook, this is good or bad.â Like, they accepted it or didnât. Sometimes they tell you âI donât really know.â âOur fraud detector is still running.â Or âWe have some weird thing in the background that weâre still asking, and it hasnât told us, so Iâm going to send you a webhook in a moment to tell you whether this went through or not.â
[16:02] And now you have like a synchronous request there, and then somewhere else is an asynchronous request coming up. You just want to make those two reliably meet. Even if this one fails, you want it to sort of like recover somewhere, understand where to reconnect with the webhook that youâre awaiting⌠And this little piece - itâs really just one case handling in the backend, where Stripe says âOkay, Iâm processingâ, instead of yes or no. This is actually many days of work, to make that look reliable, to make that work reliably. And itâs like lots and lots and lots of things like this, that just get in the way, with so many moving pieces, so many⌠Yeah, so many APIs to talk to, so much work. So much more work than originally happening asynchronously, and like in separate requests, than just in the synchronous user interaction. Just gluing this all together has become such a complicated thing that we felt âThis does need a better solution.â
This is like the motivation more from, letâs say, the use case side. I can give you a motivation more from like why we actually ended up doing this. I think this is a motivation that probably lots of folks stumbled across ultimately, and so like âOkay, this needs a better solution.â I think thereâs different projects approaching that problem. Why are we approaching it the way weâre doing? This has to do with where we come from. Before we worked on Restate, we were building Apache Flink. This is a different system. Itâs a stream processing framework. Itâs basically events and analytics. So you have these events coming in, often through a message queue, and you want to aggregate them, join them. A few examples where this is used is like fraud detection in banks. Some payment events go in, you aggregate feature vectors of that through a fraud model, or⌠Things like the TikTok recommender use Flink to actually join information from users and interactions together in real time, and understand how to update the features that will go into the recommendation model. I think companies like Uber use it to determine pricing and traffic models and ETA.
So itâs whenever you have events and you want to analyze them in a way that you aggregate them into some sort of â yeah, typically statistical value, or a materialized view. This is what we were building before. So itâs an analytical framework. What did actually happen then is at some point in time we saw folks were using that thing to solve the distributed transaction processing. The types of things where you would say â letâs assume an order processing service that takes the event, checkout that order, and it has to do a bunch of steps. Letâs say update the inventory, trigger payment, call the service to prepare logistics, maybe call another service to put this in the userâs history⌠Maybe more steps, and so on. And we started to see folks using Flink for that, because it had this interesting property that it had sort of this baked in way of reliable communication and state management. It was all built for analytical use cases. But they found this is such an interesting property that they started to apply this to the transactional use cases as well, like order processing, just because theyâve found that this is otherwise way too complicated to build⌠Way too easy to build it in such a way that it is brittle and not scalable, and it has corner cases for when it violates a lot of these properties that weâve just said.
[19:48] And when this started happening repeatedly, we thought âOkay, but apparently there isnât really a good tool out there yet.â And apparently, this property of like correct, stateful coordination is something people really appreciate. They feel like it makes their life easier to build this type of frameworks. And then we set out to build a solution for that, and that became Restate.
Itâs in many ways, actually, from the way it approaches things, or from its architecture, itâs inspired by our work on Apache FlinkâŚBut itâs almost a complete mirror image implementation of it. It takes almost the opposite design choice in most aspects, because itâs really optimized for low-density transactional processing, rather than high throughput analytical processing, which was Flink. But what we retained from this idea is - yes, stateful orchestration, and event-driven foundation and so on, this is something we should build and we should be working on. And yeah, that became Restate.
