"Vector Operator on Kubernetes"
"Vector Operator on Kubernetes" is an authoritative guide to deploying, operating, and scaling high-performance observability pipelines in Kubernetes environments. Beginning with a deep exploration of Vector's architecture and the Kubernetes Operator pattern, this book unpacks the core design principles and operational models behind automated, declarative log and metric data processing. Readers will master custom resource management, lifecycle orchestration, security frameworks, and the advanced interactions between Operators and the Kubernetes API through practical, real-world perspectives.
The book then delves into practical deployment and operational management, from cluster and namespace scoping to high availability, disaster recovery, and seamless configuration management using modern Kubernetes toolchains. Advanced chapters explore dynamic pipeline updates, auto-discovery of log sources, secure handling of secrets, and policy enforcement for large-scale, production-ready telemetry pipelines. Detailed discussions illuminate robust transformation, filtering, enrichment strategies, and the seamless integration of cloud, on-prem, and edge data sinks—with rigorous coverage of reliability, security, and performance at every step.
Rounding out with sections on scaling, compliance, and integration into the wider observability ecosystem, the book provides proven techniques for sharding, resource optimization, regulatory alignment, and multi-cluster telemetry architectures. Comprehensive case studies, failure analyses, and forward-looking coverage of emerging technologies like WASM and eBPF offer pragmatic insights for teams adopting or enhancing Vector Operator. Whether you're an architect, SRE, or platform engineer, "Vector Operator on Kubernetes" is your complete reference for delivering resilient, secure, and future-proof observability in cloud-native systems.