Engineering Meetup #4| Kubernetes, Elasticsearch Internals & Payments

In the 4th installment of Crowd Analyzer’s Engineering Meetups and the 1st in 2020, Crowd Analyzer’s engineers will cover important issues in deploying microservices with Kubernetes, Elasticsearch Internals and a first look at Crowd Analyzer’s story of designing, building and deploying a Payments solution. Discover the agenda below.

The event happens on Wednesday 29th of January at KMT house, Maadi starting at 6 PM. Email confirmations are a MUST for attendance, so hurry up!

Don’t forget to register via the URL below. Seats are limited so we encourage you to take the time to register because we will be sending out confirmation emails to people selected three days prior to the event.

https://www.crowdanalyzer.com/engineering-meetup-january-2020

NOTE: Registration ends on January 25th, 2020 at Midnight. So Hurry up!

The Agenda:

Deploying Microservices with Kubernetes
In our fourth episode of Microservices Architecture at Crowd Analyzer, we cover the inns of our production environment. This talk walks you through provisioning a Kubernetes cluster, dockerizing & deploying a microservice, and adding a continuous deployment pipeline. It also tackles areas like managing environment variables and handling persistent data stores in
Kubernetes.

A First look at Elasticsearch Internals
Elasticsearch is used extensively inside Crowd Analyzer. We operate a staggering 55 nodes, 8 clusters setup, availing more than 2.5 billion documents for search and aggregation. Through the past six years, we learned a lot about the internals of Elasticsearch to fine-tune its performance. In this pilot episode of Search in Crowd Analyzer, we cover some of the internals. This talks should fulfill your curiosity about how Elasticsearch stores its data, runs its cluster, and what algorithms and data structure does it use to provide such fast search performance compared to other databases.

Architecting our Payments Solution
This is our story building a Payments Microservice at Crowd Analyzer. Throughout this journey, we learned how to integrate with payment gateways like Stripe, using fault-tolerant patterns like retry and transactions to create a resilient microservice, and managing the billing states using the old gold finite state machine.