As microservice architectures and cloud-native scale grow, traditional threshold-based alerting can no longer meet the need for rapid incident response. This article explores how deep learning-based anomaly detection systems help SRE teams shift from reactive responses to proactive prediction.
This article explores the practical aspects of building high-concurrency microservice systems using Go, including API contract design, service discovery, and load balancing strategies.
Use Chaos Mesh to simulate network latency, node failures, and Pod anomalies to continuously verify system resilience and automated self-healing mechanisms.
Deep dive into control plane multi-active deployment, etcd cluster tuning, Pod anti-affinity strategies, and custom Controller-based fault self-healing best practices.
Leverage LangChain + Chroma vector database to transform historical Runbooks, incident reports, and operations documents into a retrievable intelligent knowledge base for rapid root cause localization in on-call scenarios.
Build a large language model inference infrastructure from scratch, covering vLLM distributed deployment, GPU memory optimization strategies, and NVIDIA MIG partitioning practices.
Looking back from mid-2026, from Cloud-Native to AI-Native, from Microservices to Agent collaboration, technical architecture is undergoing an unprecedented paradigm shift. This article documents an SRE engineer's observations and reflections.
Explore GitOps best practices for Kubernetes cluster management, using ArgoCD to achieve declarative deployment and automated rollback, improving release efficiency and operational stability.
An in-depth analysis of Python's asyncio library, from coroutine definitions and event loop scheduling to async context management, helping developers write high-performance concurrent code.
