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Mastering Prometheus

Mastering Prometheus

By : Hegedus
3.7 (6)
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Mastering Prometheus

Mastering Prometheus

3.7 (6)
By: Hegedus

Overview of this book

With an increased focus on observability and reliability, establishing a scalable and reliable monitoring environment is more important than ever. Over the last decade, Prometheus has emerged as the leading open-source, time-series based monitoring software catering to this demand. This book is your guide to scaling, operating, and extending Prometheus from small on-premises workloads to multi-cloud globally distributed workloads and everything in between. Starting with an introduction to Prometheus and its role in observability, the book provides a walkthrough of its deployment. You’ll explore Prometheus’s query language and TSDB data model, followed by dynamic service discovery for monitoring targets and refining alerting through custom templates and formatting. The book then demonstrates horizontal scaling of Prometheus via sharding and federation, while equipping you with debugging techniques and strategies to fine-tune data ingestion. Advancing through the chapters, you’ll manage Prometheus at scale through CI validations and templating with Jsonnet, and integrate Prometheus with other projects such as OpenTelemetry, Thanos, VictoriaMetrics, and Mimir. By the end of this book, you’ll have practical knowledge of Prometheus and its ecosystem, which will help you discern when, why, and how to scale it to meet your ever-growing needs.
Table of Contents (21 chapters)
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1
Part 1: Fundamentals of Prometheus
7
Part 2: Scaling Prometheus
11
Part 3: Extending Prometheus

Thanos Query

Thanos Query is another of the most fundamental Thanos components. Without it, there’s not much point to Thanos Sidecar. It provides both a web UI and an API that are used to execute PromQL queries across multiple data sources (for example, Prometheus via Thanos Sidecar, metrics in object storage via Thanos Store, and so on).

The web UI will feel familiar to anyone who has used the Prometheus web UI since their functionality and UX are essentially equivalent. The query API is also 100% PromQL compliant and therefore can be used as a Prometheus-typed data source in Grafana. In practice at companies I’ve been at, we’ve even tended to use Thanos Query as our default data source in Grafana.

Thanos Query works by connecting to one or more endpoints that implement Thanos’s gRPC-based StoreAPI. Endpoints can be specified via the repeatable --endpoint flag. This flag supports both static definitions (for example, --endpoint=192.168.1.2:10901)...

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