Software Engineering Social Connection: Yubo’s lean approach to scaling an 80M-user infrastructure
How did Yubo scale its infrastructure for 80 million users with a lean engineering team of just five?
#1about 2 minutes
Scaling Yubo's infrastructure for 80 million users
A small team of five engineers supports 80 million users by adopting a lean infrastructure philosophy and an MVP-first approach.
#2about 1 minute
The initial state of technical debt and complexity
The infrastructure began as a single, poorly optimized 2000-node GKE cluster with significant technical debt and a copy-paste culture.
#3about 2 minutes
Merging data engineering and DevOps for scalability
Internalizing the data engineering team within the infrastructure team enabled proactive database design and reduced production scalability issues.
#4about 4 minutes
Enabling developer autonomy with GitOps and CRDs
Moving from copy-pasted manifests to a GitOps model with ArgoCD, Helm templates, and custom Kubernetes operators empowered developers with self-service capabilities.
#5about 1 minute
Standardizing CI pipelines using Argo Workflows
CI pipelines were standardized using Argo Workflows, allowing developers to configure and launch their own pipelines by editing a simple YAML file.
#6about 2 minutes
Managing data consistency with change data capture
The "one database per feature" model is supported by a change data capture (CDC) pattern using Kafka to replicate data and keep services in sync.
#7about 2 minutes
Applying templates to ML and new application deployments
The same templating and CRD system used for applications is applied to simplify machine learning deployments and rapidly replicate the entire infrastructure for new products.
#8about 5 minutes
Building a cost-effective hybrid observability platform
A hybrid observability strategy combines SaaS tools like Datadog with open source solutions to control costs using dual shipping and metric compression patterns.
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