技術スタック

メルカリグループにおける、各サービスやチームの技術スタックを紹介します。

メルカリグループの技術スタック

メルカリグループのエンジニアリング組織の技術スタックをご紹介します。サービスやプロダクトに相応しい最適な技術を選定し、チームが自律的に意思決定できるような体制をつくっています。
 
*最終更新日:2023年2月14日

CategoryTechnology Stack
Programming Languages/
Library etc.
Web Frontend
HTML, CSS, JavaScript, TypeScript, React, Gatsby, Next.js, GraphQL, Apollo Client, Redux, Cypress, Rendertron, Lit, Playwright, Vue.js, Nuxt, Jest
Android
Kotlin, Gradle Kotlin DSL, Jetpack Compose, Hilt, RxJava, Kotlin Coroutines, Protocol Buffers, JUnit, Espresso, Java
iOS
Swift, SwiftUI, UIKit, Swift Concurrency, Combine, Protocol Buffers, Bazel, Xcode
Backend
Go, PHP, gRPC, Java, Scala, GraphQL, Python, TypeScript, Node.js, NestJS
DataPlatform
Python, Java, Scala
InfrastructureGoogle Cloud Platform, Amazon Web Services
MiddlewareNGINX, Istio, Cloud Pub/Sub, Memorystore for Redis, Hashicorp Vault, Apache Spark, Apache Flink, Cloud Functions, AWS Lambda, Kafka, Debezium, Polyaxon, Neo4j, Unleash
DatabaseCloud Spanner, MySQL, Cloud SQL(MySQL, PostgreSQL), Datastore, BigTable, Firestore [Storage] Google Cloud Storage, Amazon S3
MonitoringDatadog, Mackerel, PagerDuty, Kibana, Cloud Monitoring, Sentry, Crashlytics
Data analytics BigQuery, Looker, Superset, Data Studio, Cloud Logging, Splunk Cloud
Environment setup (環境構築)Docker, Terraform, Spinnaker, Cloud Build, Ansible, Bazel, CUE
Container OrchestrationKubernetes, Cloud Run
CICircleCI, GitHub Actions, Cloud Build
Machine learning LibraryKubeflow, scikit-learn, TensorFlow, PyTorch, LightGBM, Optuna, PyTorch Lightning, ONNX, Vertex AI, Feature Store(FEAST), Neo4j, networkx, Python
Search EngineElasticsearch, Apache Solr, Elastic Search Cloud
Workflow EngineApache Airflow, DigDag, Argo Workflows, Dataflow, Cloud Workflows
Code ManagementGitHub, Gerrit
Test automation toolsJavaScript, Go, gRPC, GitHub, CircleCI, Cypress, Postman