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DevOps & observability · #prometheus
Remote Write Scalability and Memory Pressure Prometheus utilizes a queue-based mechanism to buffer time series data before transmitting it to remote storage endpoints via HTTP POST requests. In high-volume environments, the interaction between max_samples_per_send and the overall capacity within the queue_config determines the memory footprint of the remote
I am unable to identify what the exact issue with the permissions with my setup as shown below. I've looked into all the similar QAs but still unable to solve the issue. The aim is to deploy Prometheus and let it scrape /metrics endpoints that my other applications in the cluster expose fine. Failed to watch *v1.Endpoints: failed to list *v1.Endpoints: endpo
Compare suitability, operational responsibilities and limits before choosing this technology for a project. Which trade-offs should guide the decision?
A performance change should improve the measured workload without sacrificing correctness or wasting capacity. Which measurements and bottlenecks should be considered first?
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?
Goal The aim is to determine which alerting path—Grafana’s built‑in system or an external Prometheus Alertmanager—delivers dynamic recipient templating reliably while avoiding the use of production credentials. Constraints and Uncertainty Built‑in alerting supports a single‑step setup but currently lacks templated recipient support. Alertmanager integration
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?
Configuration must be available to the application without exposing credentials in source control, logs or browser code. What belongs in the runtime and which access controls matter?
Write-Ahead Log Recovery Behavior The Prometheus time series database (TSDB) uses a Write-Ahead Log (WAL) to ensure data durability for samples that have not yet been compacted into permanent blocks. In scenarios involving abrupt power loss or unclean shutdowns (such as a SIGKILL), the trailing segment of the WAL can become malformed. Current server behavior
kubernetes
grafana