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Robert Zuber
Robert Zuber
CTO at CircleCI · | 22 upvotes · 72.6K views
atCircleCICircleCI
Amazon S3
Amazon S3
GitHub
GitHub
Redis
Redis
PostgreSQL
PostgreSQL
MongoDB
MongoDB

We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

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Priit Kaasik
Priit Kaasik
Engineering Lead at Katana MRP · | 4 upvotes · 2.9K views
atKatana MRPKatana MRP
redux-saga
redux-saga
Redux
Redux
React
React

Back at early 2017 the confusion and controversy around the future of AngularJS was at full swing. Also, the Angular 2 looked quite restrictive (or prescriptive even) when we did the assessment what to choose for Katana. React came out on top because it's community looked healthier, future more solid. And as you all know, one decision leads to many others: Redux, redux-saga , Axios

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Justin Dorfman
Justin Dorfman
Developer Evangelist at StackShare · | 8 upvotes · 8.6K views
Atom
Atom
Visual Studio Code
Visual Studio Code

A few months ago, I decided I would try Visual Studio Code. I resisted for so long because I knew I would love it and would then have to find alternative extensions for the ones I have installed in Atom. Fast forward to today and I'm kicking myself for not doing it sooner.

Extensions that I use:

What VSCode extensions do you use? 👇

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Simon Bettison
Simon Bettison
Managing Director at Bettison.org Limited · | 6 upvotes · 69.6K views
atBettison.org LimitedBettison.org Limited
Amazon EC2 Container Service
Amazon EC2 Container Service
Docker
Docker
Amazon VPC
Amazon VPC
Amazon Route 53
Amazon Route 53
Amazon SQS
Amazon SQS
Amazon SES
Amazon SES
Amazon CloudFront
Amazon CloudFront
nginx
nginx
Unicorn
Unicorn
Ruby
Ruby
Travis CI
Travis CI
Selenium
Selenium
RSpec
RSpec
Rails
Rails
Amazon ElastiCache
Amazon ElastiCache
Redis
Redis
Sidekiq
Sidekiq
Elasticsearch
Elasticsearch
PostgreSQL
PostgreSQL

In 2010 we made the very difficult decision to entirely re-engineer our existing monolithic LAMP application from the ground up in order to address some growing concerns about it's long term viability as a platform.

Full application re-write is almost always never the answer, because of the risks involved. However the situation warranted drastic action as it was clear that the existing product was going to face severe scaling issues. We felt it better address these sooner rather than later and also take the opportunity to improve the international architecture and also to refactor the database in. order that it better matched the changes in core functionality.

PostgreSQL was chosen for its reputation as being solid ACID compliant database backend, it was available as an offering AWS RDS service which reduced the management overhead of us having to configure it ourselves. In order to reduce read load on the primary database we implemented an Elasticsearch layer for fast and scalable search operations. Synchronisation of these indexes was to be achieved through the use of Sidekiq's Redis based background workers on Amazon ElastiCache. Again the AWS solution here looked to be an easy way to keep our involvement in managing this part of the platform at a minimum. Allowing us to focus on our core business.

Rails ls was chosen for its ability to quickly get core functionality up and running, its MVC architecture and also its focus on Test Driven Development using RSpec and Selenium with Travis CI providing continual integration. We also liked Ruby for its terse, clean and elegant syntax. Though YMMV on that one!

Unicorn was chosen for its continual deployment and reputation as a reliable application server, nginx for its reputation as a fast and stable reverse-proxy. We also took advantage of the Amazon CloudFront CDN here to further improve performance by caching static assets globally.

We tried to strike a balance between having control over management and configuration of our core application with the convenience of being able to leverage AWS hosted services for ancillary functions (Amazon SES , Amazon SQS Amazon Route 53 all hosted securely inside Amazon VPC of course!).

Whilst there is some compromise here with potential vendor lock in, the tasks being performed by these ancillary services are no particularly specialised which should mitigate this risk. Furthermore we have already containerised the stack in our development using Docker environment, and looking to how best to bring this into production - potentially using Amazon EC2 Container Service

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Cyril Duchon-Doris
Cyril Duchon-Doris
CTO at My Job Glasses · | 9 upvotes · 16.4K views
atMy Job GlassesMy Job Glasses
Slack
Slack
Amazon CloudWatch
Amazon CloudWatch
Rails
Rails
Sidekiq
Sidekiq
Redis
Redis
Amazon SNS
Amazon SNS
Amazon S3
Amazon S3
Amazon SES
Amazon SES
AWS Lambda
AWS Lambda

We decided to use AWS Lambda for several serverless tasks such as

  • Managing AWS backups
  • Processing emails received on Amazon SES and stored to Amazon S3 and notified via Amazon SNS, so as to push a message on our Redis so our Sidekiq Rails workers can process inbound emails
  • Pushing some relevant Amazon CloudWatch metrics and alarms to Slack
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