#206
B+
Rank #104
Zammad
Full-featured helpdesk and ticketing system with multi-channel intake (email, chat, social, phone). Standout trait is its search-driven UI backed by Elasticsearch for fast full-text ticket search.
70.3
/ 100
⚙ Full Stack
Ruby on Rails app server backed by PostgreSQL for transactional data, Elasticsearch for search indexing, and Redis for background job queues (Sidekiq). Four cooperating services make this one of the heavier stacks in this batch.
📈 Scaling Analysis
Rails app tier scales horizontally fine since state lives in Postgres/Redis, and Elasticsearch can be scaled to a cluster for search load. The four-service topology and ES memory requirements make small deployments comparatively expensive versus lighter helpdesk tools.
🚀 Running on Nexlayer
Needs four pods — zammad-railsserver, zammad-websocket, postgres, and elasticsearch — wired via <podName>.pod:<port> (e.g. postgres.pod:5432, elasticsearch.pod:9200); pull official images through mirror.gcr.io. Elasticsearch's memory floor (~1-2GB heap) is the main sizing gotcha on smaller Nexlayer nodepools.