This article explains how to design and implement a TB‑level log monitoring system for microservice environments using the ELK stack, detailing log collection with FileBeat, tracing via Elastic APM, resource‑efficient processing with Kafka Streams, and visualization through Grafana and Kibana.
This article explains how to design and implement a centralized log monitoring platform using the ELK stack, Filebeat, Elastic APM, Prometheus, and Kafka Streams to collect, filter, visualize, and alert on petabyte‑level logs across thousands of microservices.
This article explains how to design and implement a TB‑level log monitoring platform for micro‑service environments using ELK Stack, Filebeat, Elastic APM, Kafka Streams, Prometheus, and Grafana, covering data collection, filtering, storage, and visualization while addressing cost and resource constraints.
In large‑scale microservice environments, centralized log collection, filtering, and visualization using Filebeat, Elastic APM, Kafka Streams, Grafana and Prometheus can turn scattered logs into actionable operational data while controlling resource costs.
The article describes an enterprise‑grade log monitoring solution that unifies log collection, filtering, cleaning, and visualization across hundreds of microservices using tools such as Filebeat, Elastic APM, Kafka Streams, Prometheus, Grafana and Kibana to improve troubleshooting, performance analysis, and operational efficiency.
This article details how the Chinese travel platform “要出发” transformed its Spring Cloud‑based micro‑service architecture to a UK8S‑powered Kubernetes environment, introducing Spring Cloud Kubernetes discovery, Prometheus JVM monitoring, HPA‑driven autoscaling, Elastic APM tracing, and Istio service governance to achieve higher elasticity, observability, and operational efficiency.
This guide explains Elastic APM’s architecture—including agents, server, Elasticsearch, and Kibana—provides step‑by‑step instructions for deploying the APM server with Docker, configuring it, installing agents for various languages, and visualizing performance data in Kibana, enabling developers to monitor and troubleshoot application latency and errors.
