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🚀 Introducing Stack Decisions - Read More About It
Noah Zoschke
Engineering Manager at Segment · 21 hours ago
Datadog
TypeScript
Envoy
GRPC
Go
#Framework
#REST
#Json
#Security
#Reliability
#Observability

We just launched the Segment Config API (try it out for yourself here) — a set of public REST APIs that enable you to manage your Segment configuration. Behind the scenes the Config API is built with Go , GRPC and Envoy.

At Segment, we build new services in Go by default. The language is simple so new team members quickly ramp up on a codebase. The tool chain is fast so developers get immediate feedback when they break code, tests or integrations with other systems. The runtime is fast so it performs great at scale.

For the newest round of APIs we adopted the GRPC service #framework.

The Protocol Buffer service definition language makes it easy to design type-safe and consistent APIs, thanks to ecosystem tools like the Google API Design Guide for API standards, uber/prototool for formatting and linting .protos and lyft/protoc-gen-validate for defining field validations, and grpc-gateway for defining REST mapping.

With a well designed .proto, its easy to generate a Go server interface and a TypeScript client, providing type-safe RPC between languages.

For the API gateway and RPC we adopted the Envoy service proxy.

The internet-facing segmentapis.com endpoint is an Envoy front proxy that rate-limits and authenticates every request. It then transcodes a #REST / #JSON request to an upstream GRPC request. The upstream GRPC servers are running an Envoy sidecar configured for Datadog stats.

The result is API #security , #reliability and consistent #observability through Envoy configuration, not code.

We experimented with Swagger service definitions, but the spec is sprawling and the generated clients and server stubs leave a lot to be desired. GRPC and .proto and the Go implementation feels better designed and implemented. Thanks to the GRPC tooling and ecosystem you can generate Swagger from .protos, but it’s effectively impossible to go the other way.

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14 upvotes·724 views
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1695 points
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Using dice to recreate a picture
5 days ago · 
v.redd.it
news about the dynamic, interpreted, interactive, object-oriented, extensible programming language Python.
723 points
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Free Hotel Wifi with Python and Selenium
5 hours ago · 
gkbrk.com
Recently I took my annual leave and decided to visit my friend during the holidays. I stayed at a hotel for a few days but to my surprise, the hotel charged money to use their wifi. In $DEITY‘s year 2000 + 18, can you imagine?
203 points
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I'm making a library to do 🎵 audio classification (in just 3 simple calls). Thoughts/criticism appreciated
2 days ago · 
v.redd.it
r/Python: news about the dynamic, interpreted, interactive, object-oriented, extensible programming language Python
236 points
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Adam Neary
Engineer at Airbnb · 2 days ago
GraphQL Playground
Apollo
GraphQL
#Prisma
#BackendDrivenUI

At Airbnb we use GraphQL Unions for a "Backend-Driven UI." We have built a system where a very dynamic page is constructed based on a query that will return an array of some set of possible “sections.” These sections are responsive and define the UI completely.

The central file that manages this would be a generated file. Since the list of possible sections is quite large (~50 sections today for Search), it also presumes we have a sane mechanism for lazy-loading components with server rendering, which is a topic for another post. Suffice it to say, we do not need to package all possible sections in a massive bundle to account for everything up front.

Each section component defines its own query fragment, colocated with the section’s component code. This is the general idea of Backend-Driven UI at Airbnb. It’s used in a number of places, including Search, Trip Planner, Host tools, and various landing pages. We use this as our starting point, and then in the demo show how to (1) make and update to an existing section, and (2) add a new section.

While building your product, you want to be able to explore your schema, discovering field names and testing out potential queries on live development data. We achieve that today with GraphQL Playground, the work of our friends at #Prisma. The tools come standard with Apollo Server.

#BackendDrivenUI

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14 upvotes·1.7K views
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Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · 9 days ago
Nagios
Grafana
Graphite
Prometheus

Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:

By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.

To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...

https://eng.uber.com/m3/

(GitHub : https://github.com/m3db/m3)

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5 upvotes·17.6K views
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Ankit Sobti
CTO at Postman Inc · 9 days ago
dbt
Amazon Redshift
Stitch
Looker

Looker , Stitch , Amazon Redshift , dbt

We recently moved our Data Analytics and Business Intelligence tooling to Looker . It's already helping us create a solid process for reusable SQL-based data modeling, with consistent definitions across the entire organizations. Looker allows us to collaboratively build these version-controlled models and push the limits of what we've traditionally been able to accomplish with analytics with a lean team.

For Data Engineering, we're in the process of moving from maintaining our own ETL pipelines on AWS to a managed ELT system on Stitch. We're also evaluating the command line tool, dbt to manage data transformations. Our hope is that Stitch + dbt will streamline the ELT bit, allowing us to focus our energies on analyzing data, rather than managing it.

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6 upvotes·16.5K views
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Eli Hooten
CTO at Codecov · 14 days ago
Visual Studio Code
Vue.js
CoffeeScript
JavaScript
TypeScript

We chose TypeScript at Codecov when undergoing a recent rewrite of a legacy front end. Our previous front end was a mishmash of vanilla JavaScript and CoffeeScript , and was expanded upon haphazardly as the need arose. Without a unifying set of paradigms and patterns, the CoffeeScript and JavaScript setup was proving hard to maintain and expand upon by an engineering team. During a move to Vue.js , we decided to also make the move to TypeScript. Integrating TypeScript and Vue.js is fairly well understood at this point, so the setup wasn't all that difficult, and we felt that the benefits of incorporating TypeScript would outweigh the required time to set it up and get our engineering team up to speed.

Choosing to add TypeScript has given us one more layer to rely on to help enforce code quality, good standards, and best practices within our engineering organization. One of the biggest benefits for us as an engineering team has been how well our IDEs and editors (e.g., Visual Studio Code ) integrate with and understand TypeScript . This allows developers to catch many more errors at development time instead of relying on run time. The end result is safer (from a type perspective) code and a more efficient coding experience that helps to catch and remove errors with less developer effort.

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9 upvotes·19.5K views
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Thonny: The Beginner-Friendly Python Editor – Real Python
21 hours ago · 
realpython.com
In this tutorial, you’ll learn all about Thonny, a free Python Integrated Development Environment (IDE) that was especially designed with the beginner Pythonista in mind. It has a built-in debugger and allows you to do step-through expression evaluation.
301 points
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Auth0

As our most active customers needed to remember five different username-password combinations to use our services, it became painfully clear we needed a single sign on system. We looked at a few different systems, but Auth0 allowed us to use a single system for all our B2C, B2B and B2E requirements, had very reasonable pricing and provided a great deal of flexibility thanks to its use of Rules, Hooks, Extensions and Hosted Pages.

You can use any combination of identity providers, without having to make any changes to your app. You can even enable a different set of providers for different applications. We use passwordless, social and database login and plan to add Active Directory soon too.

Integrating Auth0 is incredibly easy, fast and flexible. With just a few lines of code, you're up and running, no matter if you need OAuth2, OpenID Connect or SAML. It provides great quick starts, clear documentation and quick support, both through the community forum and support desk. We're currently running it with various Node.js, PHP and Ruby applications.

All in all, Auth0 provides us with a common user identity across our applications and allows us to focus on the features of our applications, instead of having to spend hours and hours on creating safe login systems.

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11 upvotes·17.9K views
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Yshay Yaacobi
Software Engineer · 14 days ago
Docker Swarm
Kubernetes
Visual Studio Code
Go
TypeScript
JavaScript
C#
F#
.NET

Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

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17 upvotes·1 comment·24K views
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Popular re:Invent 2018 talk - How AWS builds ultra reliable systems
4 days ago · 
youtu.be
Whether it’s distributing configurations and customer settings, launching instances, or responding to surges in load, having a great control plane is key to ...
140 points
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Steve Schoger's design tips are off the chain - here they are in one big list
2 days ago · 
twitter.com
A collection of design tips that I've been working on with @adamwathan.
262 points
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Nick Rockwell
CTO at NY Times · 3 months ago
Kafka
Node.js
GraphQL
Apollo
React
PHP
MySQL
AngularJS

When I joined NYT there was already broad dissatisfaction with the LAMP (AngularJS MySQL PHP) Stack and the front end framework, in particular. So, I wasn't passing judgment on it. I mean, LAMP's fine, you can do good work in LAMP. It's a little dated at this point, but it's not ... I didn't want to rip it out for its own sake, but everyone else was like, "We don't like this, it's really inflexible." And I remember from being outside the company when that was called MIT FIVE when it had launched. And been observing it from the outside, and I was like, you guys took so long to do that and you did it so carefully, and yet you're not happy with your decisions. Why is that? That was more the impetus. If we're going to do this again, how are we going to do it in a way that we're gonna get a better result?

So we're moving quickly away from LAMP, I would say. So, right now, the new front end is React based and using Apollo. And we've been in a long, protracted, gradual rollout of the core experiences.

React is now talking to GraphQL as a primary API. There's a Node.js back end, to the front end, which is mainly for server-side rendering, as well.

Behind there, the main repository for the GraphQL server is a big table repository, that we call Bodega because it's a convenience store. And that reads off of a Kafka pipeline.

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13 upvotes·1 comment·18.8K views
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James Cunningham
Operations Engineer at Sentry · 3 months ago
Redis
PostgreSQL
Celery
Django
#MessageQueue
#InMemoryDatabases

Sentry started as (and remains) an open-source project, growing out of an error logging tool built in 2008. That original build nine years ago was Django and Celery (Python’s asynchronous task codebase), with PostgreSQL as the database and Redis as the power behind Celery.

We displayed a truly shrewd notion of branding even then, giving the project a catchy name that companies the world over remain jealous of to this day: django-db-log. For the longest time, Sentry’s subtitle on GitHub was “A simple Django app, built with love.” A slightly more accurate description probably would have included Starcraft and Soylent alongside love; regardless, this captured what Sentry was all about.

#MessageQueue #InMemoryDatabases

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19 upvotes·11.6K views
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Facebook retires Nuclide Atom extension
19 hours ago · 
blog.atom.io
At this time, Facebook has decided to retire their open source efforts on Nuclide, the Atom-IDE, and other associated repos.
84 points
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Ronan Levesque
Software engineer at Algolia · 9 days ago
React
Gatsby
Ruby
Middleman

A few months ago we decided to move our whole static website (www.algolia.com) to a new stack. At the time we were using a website generator called Middleman, written in Ruby. As a team of only front-end developers we didn't feel very comfortable with the language itself, and the time it took to build was not satisfying. We decided to move to Gatsby to take advantage of its use of React , as well as its incredibly high performances in terms of build and page rendering.

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8 upvotes·2 comments·19K views
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Cooper Marcus
Director of Ecosystem at Kong Inc. · 9 days ago
Zapier
GitHub
New Relic
#GitHubAnalytics
#OpenSourceCommunityAnalytics
#CommunityAnalytics
#RepoAnalytics

I've used more and more of New Relic Insights here in my work at Kong. New Relic Insights is a "time series event database as a service" with a super-easy API for inserting custom events, and a flexible query language for building visualization widgets and dashboards.

I'm a big fan of New Relic Insights when I have data I know I need to analyze, but perhaps I'm not exactly sure how I want to analyze it in the future. For example, at Kong we recently wanted to get some understanding of our open source community's activity on our GitHub repos. I was able to quickly configure GitHub to send webhooks to Zapier , which in turn posted the JSON to New Relic Insights.

Insights is schema-less and configuration-less - just start posting JSON key value pairs, then start querying your data.

Within minutes, data was flowing from GitHub to Insights, and I was building widgets on my Insights dashboard to help my colleagues visualize the activity of our open source community.

#GitHubAnalytics #OpenSourceCommunityAnalytics #CommunityAnalytics #RepoAnalytics

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9 upvotes·18.1K views
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Loguru - Python logging made (stupidly) simple
5 days ago · 
github.com
Python logging made (stupidly) simple. Contribute to Delgan/loguru development by creating an account on GitHub.
296 points
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Craig Buchanan
Founder/CEO at AppAttack · 9 days ago
Kubernetes
DigitalOcean
#CloudHosting

I use DigitalOcean because of the simplicity of using their basic offerings, such as droplets. In AppAttack, we need low-level control of our infrastructure so we can rapidly deploy a custom training web application on-demand for each training session, and building a Kubernetes cluster on top of DigitalOcean droplets allowed us to do exactly that.

#CloudHosting

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9 upvotes·15.6K views
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Managing Kubernetes Just Got a Lot Simpler
2 days ago · 
blog.digitalocean.com
Today we are opening up DigitalOcean Kubernetes to everyone! We designed DOK8s to be powerfully simple. Read about current features and the planned roadmap.
0 points
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Zach Holman
Zach Holman · 10 days ago
JavaScript
Rails
Apollo
React

Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

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16 upvotes·3 comments·22.3K views
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