ReadMeFeed / Community knowledge
Real questions. Useful conversations. Find the people who know your stack.
Developer tools · #rabbitmq
An upgrade needs a compatibility check, a tested release and a recovery path. Which changes deserve particular attention before the new version reaches production?
We are planning an in-place RabbitMQ upgrade and need a rollback plan before we proceed. From the documentation, a node whose data directory has been migrated by a newer version cannot simply be downgraded, and many feature flags cannot be disabled once enabled. So a binary rollback of the same cluster appears to be off the table. Our current thinking is to
The same project needs to behave consistently on developer machines, in CI and after deployment. Which versions, dependencies and configuration should be recorded?
Compare suitability, operational responsibilities and limits before choosing this technology for a project. Which trade-offs should guide the decision?
Recovery needs to recreate the working service and its required data after a machine or process is lost. Which artifacts and state need protection, and how should the restore be checked?
We need to change immutable queue arguments (for example x-queue-type and max-length) on a set of classic queues in production. Since redeclaring with different arguments raises 406 PRECONDITION_FAILED, the plan is a blue-green approach: declare new queues and bindings alongside the old ones, move consumers over, then remove the old topology. The unresolved
A performance change should improve the measured workload without sacrificing correctness or wasting capacity. Which measurements and bottlenecks should be considered first?
I have installed rabbitmq using helm chart on a kubernetes cluster. The rabbitmq pod keeps restarting. On inspecting the pod logs I get the below error 2020-02-26 04:42:31.582 [warning] <0.314.0> Error while waiting for Mnesia tables: {timeout_waiting_for_tables,[rabbit_durable_queue]} 2020-02-26 04:42:31.582 [info] <0.314.0> Waiting for Mnesia t
A failure needs to be narrowed down before settings are changed or operations retried. Which evidence best separates application errors from environment and dependency problems?
kubernetes