Trending Feed

Avatar of z00b
CTO at CircleCI·

Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.

We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.

READ MORE
Update: How CircleCI Processes Over 30 Million Builds Per Month - CircleCI Tech Stack (stackshare.io)
8 upvotes·461.9K views
Avatar of hcatlin
VP of Engineering at Rent The Runway·

We use Sass because I invented it! No, that's not a joke at all! Well, let me explain. So, we used Sass before I started at Rent the Runway because it's the de-facto industry standard for pre-compiled and pre-processed CSS. We do also use PostCSS for stuff like vendor prefixing and various transformations, but Sass (specifically SCSS) is the main developer-focused language for describing our styling. Some internal apps use styled-components and @Aphrodite, but our main website is allllll Sassy. Oh, but the non-joking part is the inventing part. /shrug

READ MORE
4 upvotes·201.5K views

As Mixmax began to scale super quickly, with more and more customers joining the platform, we started to see that the Meteor app was still having a lot of trouble scaling due to how it tried to provide its reactivity layer. To be honest, this led to a brutal summer of playing Galaxy container whack-a-mole as containers would saturate their CPU and become unresponsive. I’ll never forget hacking away at building a new microservice to relieve the load on the system so that we’d stop getting paged every 30-40 minutes. Luckily, we’ve never had to do that again! After stabilizing the system, we had to build out two more microservices to provide the necessary reactivity and authentication layers as we rebuilt our Meteor app from the ground up in Node.js. This also had the added benefit of being able to deploy the entire application in the same AWS VPCs. Thankfully, AWS had also released their ALB product so that we didn’t have to build and maintain our own websocket layer in Amazon EC2. All of our microservices, except for one special Go one, are now in Node with an nginx frontend on each instance, all behind AWS Elastic Load Balancing (ELB) or ALBs running in AWS Elastic Beanstalk.

READ MORE
How Mixmax Uses Node and Go to Process 250M Events a day - Mixmax Tech Stack (stackshare.io)
5 upvotes·164.8K views
Avatar of ptrthomas
Distinguished Engineer at Intuit·
Shared insights
on
Karate DSLKarate DSLGitGit
at

Karate DSL is extremely effective in those situations where you have a microservice still in development, but the "consumer" web-UI dev team needs to make progress. Just create a mock definition (feature) file, and since it is plain-text - it can easily be shared across teams via Git. Since Karate has a binary stand-alone executable, even teams that are not familiar with Java can use it to stand-up mock services. And the best part is that the mock serves as a "contract" - which the server-side team can use to practice test-driven development.

READ MORE
The World's Smallest Micro Service - ptrthomas Tech Stack (stackshare.io)
17 upvotes·2 comments·100.8K views
Avatar of ojburn
Architect at Atlassian·

We recently added new APIs to Jira to associate information about Builds and Deployments to Jira issues.

The new APIs were developed using a spec-first API approach for speed and sanity. The details of this approach are described in this blog post, and we relied on using Swagger and associated tools like Swagger UI.

A new service was created for managing the data. It provides a REST API for external use, and an internal API based on GraphQL. The service is built using Kotlin for increased developer productivity and happiness, and the Spring-Boot framework. PostgreSQL was chosen for the persistence layer, as we have non-trivial requirements that cannot be easily implemented on top of a key-value store.

The front-end has been built using React and querying the back-end service using an internal GraphQL API. We have plans of providing a public GraphQL API in the future.

New Jira Integrations: Bitbucket CircleCI AWS CodePipeline Octopus Deploy jFrog Azure Pipelines

READ MORE
6 integrations every Jira Software Cloud team NEED... - Atlassian Community (community.atlassian.com)
12 upvotes·277.3K views
Avatar of ecolson
Chief Algorithms Officer at Stitch Fix·

The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

For more info:

#DataScience #DataStack #Data

READ MORE
Stitch Fix Algorithms Tour (algorithms-tour.stitchfix.com)
19 upvotes·1.1M views
Avatar of jordanschuetz
Developer Advocate at MuleSoft·
Shared insights
on
PubNubPubNubUnityUnity

PubNub is a great tool for developers looking for an easy to use, real-time messaging service. PubNub's Publish/Subscribe APIs are some of the easiest to use in the industry, and their speed and reliability of service are unparrell. While many companies out there offer a wide range of pubsub and message queuing services, I've personally found that PubNub is the easiest to setup and get started with. When I was an indie game developer, I used PubNub as the realtime chat component in my application, and it also powered realtime drawing between players. The cost compared to spinning up my own servers globally was much cheaper, and I was happy that I decided to go with PubNub. While you could build it yourself, why when PubNub makes it so easy to get something up and running. Spend less time coding and more time marketing, that's always been my philosophy. PubNub Unity

READ MORE
6 upvotes·58.7K views
Avatar of deepakk
Sr. DevOps Engineer ·
Shared insights
on
Visual Studio CodeVisual Studio Code
at

I use Visual Studio Code because of community support and popularity it gained in very short period and many more extensions that are being contributed by community every day. I like the Python Engine in VSCode makes my work life productive. My most fav extensions are

  • Gitlense
  • Kubernetes
  • Docker
  • Chef

Themes are always fun and make your development IDE productive especially with colors and error indicators etc..

READ MORE
7 upvotes·64.3K views

I love Python and JavaScript . You can do the same JavaScript async operations in Python by using asyncio. This is particularly useful when you need to do socket programming in Python. With streaming sockets, data can be sent or received at any time. In case your Python program is in the middle of executing some code, other threads can handle the new socket data. Libraries like asyncio implement multiple threads, so your Python program can work in an asynchronous fashion. PubNub makes bi-directional data streaming between devices even easier.

READ MORE
Socket Programming with Python and PubNub - PubNub Tech Stack (stackshare.io)
21 upvotes·2 comments·96.4K views
Avatar of nzoschke
Engineering Manager at Segment·

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. A public API is only as good as its #documentation. For the API reference doc we are using Postman.

Postman is an “API development environment”. You download the desktop app, and build API requests by URL and payload. Over time you can build up a set of requests and organize them into a “Postman Collection”. You can generalize a collection with “collection variables”. This allows you to parameterize things like username, password and workspace_name so a user can fill their own values in before making an API call. This makes it possible to use Postman for one-off API tasks instead of writing code.

Then you can add Markdown content to the entire collection, a folder of related methods, and/or every API method to explain how the APIs work. You can publish a collection and easily share it with a URL.

This turns Postman from a personal #API utility to full-blown public interactive API documentation. The result is a great looking web page with all the API calls, docs and sample requests and responses in one place. Check out the results here.

Postman’s powers don’t end here. You can automate Postman with “test scripts” and have it periodically run a collection scripts as “monitors”. We now have #QA around all the APIs in public docs to make sure they are always correct

Along the way we tried other techniques for documenting APIs like ReadMe.io or Swagger UI. These required a lot of effort to customize.

Writing and maintaining a Postman collection takes some work, but the resulting documentation site, interactivity and API testing tools are well worth it.

READ MORE
Announcing Config API: convenient and extensible workspace configuration · Segment Blog (segment.com)
29 upvotes·1 comment·1M views
Avatar of idosh
The Elegant Monkeys·

Kubernetes powers our #backend services as it is very easy in terms of #devops (the managed version). We deploy everything using @helm charts as it provides us to manage deployments the same way we manage our code on GitHub . On every commit a CircleCI job is triggered to run the tests, build Docker images and deploy them to the registry. Finally on every master commit CircleCI also deploys the relevant service using Helm chart to our Kubernetes cluster

READ MORE
6 upvotes·201.8K views

I built a project using Quasar Framework with Vue.js, vuex and axios on the frontend and Go, Gin Gonic and PostgreSQL on the backend. Deployment was realized using Docker and Docker Compose. Now I can build the desktop and the mobile app using a single code base on the frontend. UI responsiveness and performance of this stack is amazing.

READ MORE
Migrating from Vuetify to Quasar - Quasar Framework - Medium (medium.com)
8 upvotes·90.8K views
Avatar of shosti
Senior Architect at Rainforest QA·

We recently moved our main applications from Heroku to Kubernetes . The 3 main driving factors behind the switch were scalability (database size limits), security (the inability to set up PostgreSQL instances in private networks), and costs (GCP is cheaper for raw computing resources).

We prefer using managed services, so we are using Google Kubernetes Engine with Google Cloud SQL for PostgreSQL for our PostgreSQL databases and Google Cloud Memorystore for Redis . For our CI/CD pipeline, we are using CircleCI and Google Cloud Build to deploy applications managed with Helm . The new infrastructure is managed with Terraform .

Read the blog post to go more in depth.

READ MORE
Why Rainforest QA Moved from Heroku to Google Kubernetes Engine (rainforestqa.com)
12 upvotes·1 comment·391.9K views
Shared insights
on
Auth0Auth0

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.

READ MORE
12 upvotes·68.9K views
Avatar of tabbott
Founder at Zulip·
Shared insights
on
WebpackWebpack
at
()

We use Webpack because it's the standard toolchain for managing frontend dependencies in 2019, and it's hard to make a nice frontend development user experience without it.

I don't like it -- their configuration system is a mess, requiring a ton of reading or expertise to do things that essentially every project wants to do by default. It has a lot of great features, which is why we use it. But as an example, it's development server hot reloading is really cool, but doesn't handle changes in the webpack configuration file itself (so adding a new file requires a restart).

My hope is that the sheer fact that everyone is using it will eventually lead to these problems being fixed or it being replaced by a similar system with a better design.

READ MORE
6 upvotes·16.5K views
Avatar of tim_nolet
Founder, Engineer & Dishwasher at Checkly·

PostgreSQL Heroku Heroku Postgres Node.js Knex.js

Last week we rolled out a simple patch that decimated the response time of a Postgres query crucial to Checkly. It quite literally went from an average of ~100ms with peaks to 1 second to a steady 1ms to 10ms.

However, that patch was just the last step of a longer journey:

  1. I looked at what API endpoints were using which queries and how their response time grew over time. Specifically the customer facing API endpoints that are directly responsible for rendering the first dashboard page of the product are crucial.

  2. I looked at the Heroku metrics such as those reported by heroku pg:outlier and cross references that with "slowest response time" statistics.

  3. I reproduced the production situation as best as possible on a local development machine and test my hypothesis that an composite index on a uuid field and a timestampz field would reduce response times.

This method secured the victory and we rolled out a new index last week. Response times plummeted. Read the full story in the blog post.

READ MORE
How I decimated Postgres response times for my SaaS (blog.checklyhq.com)
10 upvotes·106.9K views
Avatar of danielquinn
Senior Developer at Workfinder·
Shared insights
on
AsanaAsana
in

I'm routinely frustrated by Asana because it's clearly a tool created by designers, imposed on developers.

  • No integration with code repositories.
    • No task numbers
    • You can't reference a ticket in a commit and expect any feedback in Asana
    • You certainly can't close a ticket with a commit.
    • There's no link between CI progress and a ticket.
  • No Markdown support (you can't even put links on text!)
  • Boards and task lists aren't linked.
  • It suppresses middle-click so you can't open more than one ticket at once.
  • It logs every last change to things like assignments, but then folds up the conversation to suppress past comments.

Here's what it does have:

  • Pretty backgrounds
  • Cute little creatures that appear at random

This is not a tool for engineering. Please don't force your nerds to use it.

READ MORE
13 upvotes·2 comments·31.4K views
Avatar of tim_nolet
Founder, Engineer & Dishwasher at Checkly·

PostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

In a nutshell:cPostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

In a nutshell:

  • We use Postgres on Heroku.
  • We use a "one database, on schema" approach for partitioning customer data.
  • We use an accounts, memberships and users table to create a many-to-many relation between users and accounts.
  • We completely decouple prices, payments and the exact ingredients for a customer's plan.

All the details including a database schema diagram are in the linked blog post.

READ MORE
Building a multi-tenant SaaS data model (blog.checklyhq.com)
8 upvotes·83.5K views
Avatar of benduran
Senior Software Engineer at Netflix·
Shared insights
on
JavaScriptJavaScript
at

I use JavaScript because it is important to understand the fundamentals of any language you are using. jQuery was a revolutionary JS library for making DOM access and manipulation easier, but native APIs have been implemented that make it just as easy to do without a library.

READ MORE
6 upvotes·516.5K views
Avatar of kamukondiwa
Web Solutions Architect at Adthena·
Shared insights
on
Node.jsNode.js
at
()

We use Node.js because it is a really powerful Javascript runtime for building network applications. There is a large ecosystem of tools and packages available to help engineers build effective solutions to their problems . We have built robust and flexible server and client side solutions using Javascript and Node.js.

READ MORE
5 upvotes·14.7K views
Avatar of NickCraver
Architecture Lead at Stack Overflow·
Shared insights
on
.NET.NET
at

We use .NET Core for our web socket servers, mail relays, and scheduling applications. Soon, it will power all of Stack Overflow. The ability to run on any platform, further extend and plug especially the ASP.NET bits and treat almost everything as a building block you can move around has been a huge win. We're headed towards an appliance model and with .NET Core we can finally put everything in box...on Linux. We can re-use more code, fit all our deployment scenarios both during the move and after, and also ditch a lot of performance workarounds we had to scale...they're in-box now.

And testing. The ability to fire up a web server and request and access both in a single method is an orders of magnitude improvement over ASP.NET 5. We're looking forward to tremendously improving our automated test coverage in places it's finally reasonable in both time and effort for devs to do so. In short: we're getting a lot more for the same dev time spent in .NET Core.

READ MORE
4 upvotes·1 comment·62.5K views
Avatar of vishalnarkhede
Javascript Developer at getStream.io·

Recently, the team at Stream published a React Native SDK for our new Chat by Stream product. React Native brings the power of JavaScript to the world of mobile development, making it easy to develop apps for multiple platforms. We decided to publish two different endpoints for the SDK – Expo and React Native (non-expo), to avoid the hurdle and setup of using the Expo library in React Native only projects on the consumer side.

The capability of style customization is one a large deal breaker for frontend SDKs. To solve this, we decided to use styled-components in our SDK, which makes it easy to add support for themes on top of our existing components. This practice reduces the maintenance effort for stylings of custom components and keeps the overall codebase clean.

For module bundling, we decided to go with Rollup.js instead of Webpack due to its simplicity and performance in the area of library/module providers. We are using Babel for transpiling code, enabling our team to use JavaScript's next-generation features. Additionally, we are using the React Styleguidist component documentation, which makes documenting the React Native code a breeze.

READ MORE
React Native Chat Tutorial (getstream.io)
19 upvotes·1 comment·287.7K views
Avatar of cristoirmac
VP, Engineering at SparkPost·

The recent move of our CI/CD tooling to AWS CodeBuild / AWS CodeDeploy (with GitHub ) as well as moving to Amazon EC2 Container Service / AWS Lambda for our deployment architecture for most of our services has helped us significantly reduce our deployment times while improving both feature velocity and overall reliability. In one extreme case, we got one service down from 90 minutes to a very reasonable 15 minutes. Container-based build and deployments have made so many things simpler and easier and the integration between the tools has been helpful. There is still some work to do on our service mesh & API proxy approach to further simplify our environment.

READ MORE
9 upvotes·2 comments·96.2K views
Avatar of Yshayy
Software Engineer ·

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...

READ MORE
GitHub - Soluto/tweek: Tweek - an open source feature management solution (github.com)
31 upvotes·2 comments·1.2M views