Managing Worker Load with Scalingo Auto-scaling
Learn how to implement auto-scaling for worker processes in Scalingo to handle traffic bursts while controlling costs and avoiding resource thrashing.
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scalingoMocha --parallel: test files collide on shared ports and database state when run across workers
Mocha's --parallel mode distributes test files across a pool of worker processes, each loading its files in isolation. That isolation ends at the process boundary: any external resource a suite touches — a TCP port, a database schema, a temp directory — is still shared by every worker on the machine. The design goal here is to keep an existing suite green un
mochaSIGSEGV in worker process after prolonged HTTP/1.1 keepalive traffic
Goal: verify that nginx ≥ 1.19.8 resolves the upstream keepalive memory leak that manifested as SIGSEGV in worker processes under prolonged HTTP/1.1 keepalive traffic, and determine whether the worker_processes auto setting still produces uneven load distribution on heterogeneous CPU architectures when worker_process_auto_affinity is enabled. Constraints: wh
nginx