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Unlock All-in-One Observability for APISIX with DeepFlow
This article aims to elucidate how to leverage DeepFlow's zero-code feature based on eBPF to construct an observability solution for APISIX. On this basis, it integrates the rich data sources of existing APISIX plugins to eliminate data silos and build an all-in-one platform for comprehensive observability of the APISIX gateway. Through DeepFlow, APISIX can achieve comprehensive observability from traffic monitoring and tracing analysis to performance optimization, eliminating data dispersion and providing a centralized view. This accelerates fault diagnosis and performance tuning, making the work of DevOps and SRE teams more efficient. This article will focus on how APISIX's tracing data, metric data, access logs, and performance profiling data can be integrated with DeepFlow.
基于 DeepFlow 构建 APISIX 的统一可观测性能力
本文旨在阐述如何利用 DeepFlow 基于 eBPF 的零侵扰特性构建 APISIX 可观测性解决方案,在此基础上统一集成 APISIX 插件已有的丰富数据源,消除孤岛、构建统一的可观测性平台,以全面监控和分析 APISIX 网关。通过 DeepFlow,APISIX 可以实现从流量监控、追踪分析、到性能优化的全面可观测性,消除数据分散并提供中心化的监控视图,加速故障排查和性能调优,让 DevOps 和 SRE 团队的工作更加高效。本文将重点梳理 APISIX 的追踪数据、指标数据、访日日志及性能剖析数据如何对接 DeepFlow。
使用 DeepFlow 开启 Ingress 可观测性
意识到已有 K8s Ingress 监控数据的缺陷以后,我们动手基于 DeepFlow 生成了一个高效的 K8s Ingress 可观测性 Dashboard,粒度精细到域名、API Endpoint、后端服务,指标量覆盖请求、时延、异常、吞吐,以便快速找到性能瓶颈和故障原因。**得益于 DeepFlow 的 AutoTracing、AutoMetrics、AutoTagging、SmartEncoding 核心机制,我们可以从应用角度分析 K8s Ingress 的调用拓扑、性能指标、访问日志、调用链追踪,无需任何插码、配置修改、进程重启。**