Proporciona etiquetado clave-valor y "time-series". La propia documentación de Prometheus explica cómo se gestiona el almacenamiento en disco (Prometheus Time-Series DB). La ingestión de datos se agrupa en bloques de dos horas, donde cada bloque es un directorio conteniendo uno o más "chunk files" (los datos), además de un fichero de metadatos y un fichero index:
Almacenamiento de datos en disco (Prometheus Time-Series DB):

./data/01BKGV7JBM69T2G1BGBGM6KB12
./data/01BKGV7JBM69T2G1BGBGM6KB12/meta.json
./data/01BKGV7JBM69T2G1BGBGM6KB12/wal
./data/01BKGV7JBM69T2G1BGBGM6KB12/wal/000002
./data/01BKGV7JBM69T2G1BGBGM6KB12/wal/000001
```text

- Un proceso en segundo plano compacta los bloques de dos horas en otros más grandes.
- Es posible almacenar los datos en otras soluciones de "Time-Series Database" como **InfluxDB**.

## Prometheus SLO Service Level Objectives

- [Sloth 🌟](https://github.com/slok/sloth) Easy and simple Prometheus SLO (service level objectives) generator
    - [itnext.io: SLOs should be easy, say hi to Sloth 🌟](https://itnext.io/slos-should-be-easy-say-hi-to-sloth-9c8a225df0d4)
- [PromTools: SLOs with Prometheus 🌟](https://promtools.dev) Multiple Burn Rate Alerts. This page will generate, with the data you provide in the form, the necessary Prometheus alerting and recording rules for Multiple Burn Rate which you might know from The Site Reliability Workbook. These rules will evaluate based on the available metrics in the last 30 days.
    - [slo-libsonnet](https://github.com/metalmatze/slo-libsonnet) Generate Prometheus alerting & recording rules and Grafana dashboards for your SLOs.
- [opensource.google: Prometheus SLO example](https://github.com/google/prometheus-slo-burn-example) An end to end example of implementing SLOs with Prometheus, Grafana and Go
- [SLO Generator](https://github.com/google/slo-generator) SLO Generator is a tool to compute SLIs, SLOs, Error Budgets and Burn rate and export an SLO report to supported exporters.

### Scalability, High Availability (HA) and Long-Term Storage

- Prometheus fue diseñado para ser fácil de desplegar. Es extremadamente fácil ponerlo en marcha, recoger algunas métricas, y empezar a construir nuestra propia herramienta de monitorización. Las cosas se complican cuando se intenta operar a un nivel de escalado considerable.
- Para entender si esto va a ser un problema, conviene plantearse las siguiente preguntas:
    -	¿Cuántas métricas puede ingerir el sistema de monitorización y cuántas son necesarias?
    -	¿Cuál es la cardinalidad de las métricas? La cardinalidad es el número de etiquetas que cada métrica puede tener. Es una cuestión muy frecuente en las métricas pertenecientes a entornos dinámicos donde a los contenedores se les asignan un ID ó nombre diferente cada vez que son lanzados, reiniciados o movidos entre nodos (caso de kubernetes).
    -	¿Es necesaria la Alta Disponibilidad (HA)?
    -	¿Durante cuánto tiempo es necesario mantener las métricas y con qué resolución?
- La implementación de HA es laboriosa porque la funcionalidad de cluster requiere añadir plugins de terceros al servidor Prometheus. Es necesario tratar con "backups" y "restores", y el almacenamiento de métricas por un periodo de tiempo extendido hará que la base de datos crezca exponencialmente. Los servidores Prometheus proporcionan almacenamiento persistente, pero Prometheus no fue creado para el almacenamiento distribuido de métricas a lo largo de múltiples nodos de un cluster con replicación y capacidad curativa (como es el caso de Kubernetes).  Esto es conocido como **"almacenamiento a largo-plazo" (Long-Term)** y actualmente es un requisito en unos pocos casos de uso, por ejemplo en la planificación de la capacidad para monitorizar cómo la infraestructura necesita evolucionar, contracargos para facturar diferentes equipos ó departamentos para un caso específico que han hecho de la infraestructura, análisis de tendencias de uso, o adherirse a regulaciones para verticales específicos como banca, seguros, etc.

### Storage Solutions for Prometheus

- [monitoring2.substack.com: Big Prometheus. Thanos, Cortex, M3DB and VictoriaMetrics at scale 🌟](https://monitoring2.substack.com/p/big-prometheus)
- [**Prometheus TSDB**](https://prometheus.io/docs/prometheus/latest/storage)
- [**Cortex**:](https://cortexmetrics.io) Provides horizontally scalable, highly available, multi-tenant, long term storage for Prometheus. Cortex allows for storing time series data in a key-value store like Cassandra, AWS DynamoDB, or Google BigTable. It offers a Prometheus compatible query API, and you can push metrics into a write endpoint. This makes it best suited for cloud environments and multi-tenant scenarios like service providers building hosted and managed platforms.
    - [github.com/cortexproject/cortex](https://github.com/cortexproject/cortex)
    - [Weave Cortex SaaS (Hosted Prometheus - Public Cloud)](https://www.weave.works/)
- [**Thanos**:](https://thanos.io) Open source, **highly available Prometheus setup with long term storage capabilities**.
    - Thanos stores time series data in an object store like AWS S3, Google Cloud Storage, etc. Thanos pushes metrics through a side-car container from each Prometheus server through the gRPC store API to the query service in order to provide a global query view.
    - [github.com/ruanbekker: Thanos Cluster Setup](https://github.com/ruanbekker/thanos-cluster-setup) How to deploy a HA Prometheus setup with Unlimited Data Retention Capabilities on aws cloud S3 with Thanos Metrics.
    - [Highly Available Prometheus Metrics for Distributed SQL with Thanos on GKE](https://blog.yugabyte.com/highly-available-prometheus-metrics-for-distributed-sql-with-thanos-on-gke)
    - [infracloud.io: Achieving multi-tenancy in monitoring with Prometheus & the mighty Thanos Receiver](https://www.infracloud.io/blogs/multi-tenancy-monitoring-thanos-receiver)
    - [particule.io: Multi-Cluster Monitoring with Thanos](https://particule.io/en/blog/thanos-monitoring)
    - [Thanos Architecture Overview 🌟](https://github.com/thanos-io/thanos#architecture-overview)
    - [enmilocalfunciona.io: Aprende a configurar Thanos usando docker-compose](https://www.enmilocalfunciona.io/aprende-a-configurar-thanos-usando-docker-compose)
    - [goatlas-io/atlas](https://github.com/goatlas-io/atlas) Atlas provides the ability to easily run a secure distributed Thanos deployment.
    - [==thanos-io/kube-thanos: Kubernetes specific configuration for deploying Thanos==](https://github.com/thanos-io/kube-thanos)
    - [medium.com/nerd-for-tech: Deep Dive into Thanos-Part I | Pavan Kumar](https://medium.com/nerd-for-tech/deep-dive-into-thanos-part-i-f72ecba39f76) Monitoring Kubernetes Workloads with Thanos and Prometheus Operator.
    - [particule.io: Multi-Cluster Monitoring with Thanos 🌟](https://particule.io/en/blog/thanos-monitoring) you'll learn the limitations of a Prometheus-only monitoring stack and why moving to a Thanos-based stack can improve metrics retention and reduce overall costs for your clusters
- [**M3**:](https://m3db.io) An open source, large-scale metrics platform developed by Uber. It has its own time series database, M3DB. Like Thanos, M3 also uses a side-car container to push the metrics to the DB. In addition, it supports metric deduplication and merging, and provides distributed query support.
Although it's exciting to see attempts to address the challenges of running Prometheus at scale, these are very young projects that are not widely used yet.
- [VictoriaMetrics](https://victoriametrics.com)

#### InfluxDB and InfluxDB Templates

- [**InfluxDB**:](https://www.influxdata.com) An [open-source time series database (TSDB)](https://en.wikipedia.org/wiki/Time_series_database) developed by InfluxData. It is written in [Go](https://en.wikipedia.org/wiki/Go_(programming_language)) and optimized for fast, high-availability storage and retrieval of [time series](https://en.wikipedia.org/wiki/Time_series) data in fields such as operations monitoring, application metrics, [Internet of Things](https://en.wikipedia.org/wiki/Internet_of_Things) sensor data, and real-time analytics. It also has support for processing data from [Graphite](https://en.wikipedia.org/wiki/Graphite_(software)).
- [en.wikipedia.org/wiki/InfluxDB](https://en.wikipedia.org/wiki/MIT_License)
- [influxdata.com: Building a Metrics & Alerts as a Service (MaaS) Monitoring Solution Using the InfluxDB Stack](https://www.influxdata.com/blog/building-a-metrics-alerts-as-a-service-maas-monitoring-solution-using-the-influxdb-stack)
- [en.wikipedia.org/wiki/MIT_License](https://en.wikipedia.org/wiki/MIT_License)
- [dzone: Flux queries](https://dzone.com/articles/flux-windowing-and-aggregation) New language being developed at InfluxData.
- [influxdb-templates](https://www.influxdata.com) Build and share InfluxDB templates for monitoring solutions that deliver faster time to awesome.
    - [thenewstack.io: Make a GitOps Workflow Using InfluxDB Templates](https://thenewstack.io/make-a-gitops-workflow-using-influxdb-templates)
- [influxdata.com: Running InfluxDB 2.0 and Telegraf Using Docker](https://www.influxdata.com/blog/running-influxdb-2-0-and-telegraf-using-docker)
- [influxdata.com: InfluxDB Tech Tips: API Invokable Scripts in InfluxDB Cloud](https://www.influxdata.com/blog/tldr-influxdb-tech-tips-api-invokable-scripts-influxdb-cloud)

## Collectors. Software exposing Prometheus metrics

- http://localhost:9090/targets : you should see a list of targets that you Prometheus server is scraping.

### Prometheus Exporters. Plug-in architecture and extensibility with Prometheus Exporters (collectors)

- Prometheus proporciona un ecosistema de **"exporters"**, los cuales permiten que herramientas de terceros puedan exportar sus datos en Prometheus. Muchos componentes de software de código abierto son compatibles por defecto.
- [exporterhub.io 🌟](https://exporterhub.io) Exporterhub is a curated List of Prometheus Exporters
- **Un "exporter" expone las métricas de uno ó varios "collectors".**
- [Prometheus Exporters](https://prometheus.io/docs/instrumenting/exporters)
    - [prometheus.io/download/](https://prometheus.io/download)
    - [github.com/prometheus](https://github.com/prometheus)
- [Prometheus JMX Exporter 🌟](https://github.com/prometheus/jmx_exporter) A process for exposing JMX Beans via HTTP for Prometheus consumption.
- [blackbox_exporter 🌟](https://github.com/prometheus/blackbox_exporter) The blackbox exporter allows blackbox probing of endpoints over HTTP, HTTPS, DNS, TCP and ICMP.
- [Example: How to Use Prometheus Monitoring With Java to Gather Data. Gathering Java Metrics with Prometheus Monitoring (ActiveMQ)](https://www.openlogic.com/blog/prometheus-java-monitoring-and-gathering-data)
- [Maven Prometheus instrumentation library for JVM applications (client library)](https://mvnrepository.com/artifact/io.prometheus)
    - [github.com/prometheus/client_java](https://github.com/prometheus/client_java)
- [Example: JMX Exporter with ActiveMQ](https://www.openlogic.com/blog/prometheus-java-monitoring-and-gathering-data)
- [k8s-image-availability-exporter](https://github.com/deckhouse/k8s-image-availability-exporter) is a Prometheus exporter that warns you proactively about images that are defined in Kubernetes objects (e.g., an image field in the Deployment) but are not available in the container registry (such as Docker Registry, etc.).
- [engineeringblog.yelp.com: Improving the performance of the Prometheus JMX Exporter](https://engineeringblog.yelp.com/2020/10/improving-the-performance-of-the-prometheus-jmx-exporter.html)
- [sysdig.com: How to monitor an Oracle database with Prometheus. The OracleDB Prometheus exporter](https://www.sysdig.com/blog/monitor-oracle-database-prometheus)
- [YACE - yet another cloudwatch exporter 🌟](https://github.com/prometheus-community/yet-another-cloudwatch-exporter) AWS cloudwatch to prometheus exporter - Discovers services through AWS tags, gets cloudwatch data and provides them as prometheus metrics with AWS tags as labels
- [prometheus-community/elasticsearch_exporter](https://github.com/prometheus-community/elasticsearch_exporter) Prometheus exporter for various metrics about ElasticSearch, written in Go.
- [medium.com/@akashjoffical08: Monitor Uptime of Endpoints in K8s using Blackbox Exporter 🌟](https://medium.com/@akashjoffical08/monitor-uptime-of-endpoints-in-k8s-using-blackbox-exporter-f80166a328e9)
- [sstarcher/helm-exporter](https://github.com/sstarcher/helm-exporter) Helm-exporter exports Helm releases, charts, and version statistics in the Prometheus format
- [blog.devops.dev: Monitoring MySQL using Prometheus, Grafana and mysqld_exporter in Kubernetes](https://blog.devops.dev/monitoring-mysql-using-prometheus-and-grafana-in-kubernetes-16e7ae3de5dd)

#### Certificates Expiration

- [muxinc/certificate-expiry-monitor](https://github.com/muxinc/certificate-expiry-monitor) Utility that exposes the expiry of TLS certificates as Prometheus metrics
- [enix/x509-certificate-exporter](https://github.com/enix/x509-certificate-exporter) A Prometheus exporter to monitor x509 certificates expiration in Kubernetes clusters or standalone, written in Go. Designed to monitor Kubernetes clusters from inside, it can also be used as a standalone exporter.

### Prometheus Exporters Development. Node Exporter

- Node exporter puede ser utilizado para exportar las métricas de nuestra aplicación ya que permite exportar un "text-file". Nuestra aplicación puede escribir datos en un fichero de texto con el formato de datos de Prometheus. Este fichero de texto con datos agregados sería exportado a Prometheus con Node Exporter.
- [dzone.com: Monitoring Self-Destructing Apps Using Prometheus](https://dzone.com/articles/prometheus-collectors) Learn how to configure Prometheus collectors and their use cases.
- [prometheus.io: Writing Exporters](https://prometheus.io/docs/instrumenting/writing_exporters)
- [devconnected.com: Complete Node Exporter Mastery with Prometheus](https://devconnected.com/complete-node-exporter-mastery-with-prometheus)
- [aws.amazon.com: Building a Prometheus remote write exporter for the OpenTelemetry Go SDK](https://aws.amazon.com/blogs/opensource/building-a-prometheus-remote-write-exporter-for-the-opentelemetry-go-sdk)
- [medium.com/@dast04: Writing Custom Prometheus Exporters (in Python) — Kubernetes](https://medium.com/@dast04/writing-custom-prometheus-exporters-in-python-kubernetes-73626b66d78c)

### Prometheus Third-party Collectors/Exporters

- Some third-party software exposes metrics in the Prometheus format, so no separate exporters are needed.
- [Prometheus Third Party Exporters](https://prometheus.io/docs/instrumenting/exporters)

#### OpenTelemetry Collector

- [OpenTelemetry Collector](https://github.com/open-telemetry/opentelemetry-collector)
- [thenewstack.io: Lightstep’s OpenTelemetry Launchers Simplify Integration to Line of Code](https://thenewstack.io/lightsteps-opentelemetry-launchers-simplify-integration-to-line-of-code)
- [OpenTelemetry Launchers 🌟](https://github.com/search?q=org%3Alightstep+launcher)
- [thenewstack.io: Demystifying Distributed Traces in OpenTelemetry](https://thenewstack.io/demystifying-distributed-traces-in-opentelemetry)
- [medium: OpenTelemetry Specification v1.0.0, Tracing Edition](https://medium.com/opentelemetry/opentelemetry-specification-v1-0-0-tracing-edition-72dd08936978)
- [cncf.io: From distributed tracing to APM: Taking OpenTelemetry and Jaeger up a level](https://www.cncf.io/blog/2021/04/29/from-distributed-tracing-to-apm-taking-opentelemetry-and-jaeger-up-a-level/?utm_source=thenewstack&utm_medium=twitter&utm_campaign=platform)
- [medium: Tracing in eDreams ODIGEO Lodging with Open Telemetry and Grafana Tempo](https://medium.com/edreams-odigeo-tech/tracing-in-edreams-odigeo-lodging-with-open-telemetry-and-grafana-tempo-bd1f20ddf49d)
- [newrelic.com: Understand OpenTelemetry Part 4: Instrument a Java App with OpenTelemetry](https://newrelic.com/blog/apm/java-opentelemetry)
- https://github.com/jenkinsci/opentelemetry-plugin Publish Jenkins performances metrics to an OpenTelemetry endpoint, including distributed traces of job executions and health metrics of the controller.
- https://github.com/cyrille-leclerc/opentelemetry-maven-extension Maven extension to observe Maven builds as distributed traces using OpenTelemetry
- https://github.com/equinix-labs/otel-cli OpenTelemetry command-line tool for sending events from shell scripts & similar environments
- https://github.com/ansible-collections/community.general/pull/3091 Send distributed traces for the ansible runs with OpenTelemetry
- [medium.com/@tathagatapaul7: OpenTelemetry in Kubernetes: Deploying your Collector and Metrics Backend](https://medium.com/@tathagatapaul7/opentelemetry-in-kubernetes-deploying-your-collector-and-metrics-backend-b8ec86ac4a43) OpenTelemetry is a great way to instrument your applications to provide metrics in a vendor-agnostic way to any observability backend. But lots of people face issues while deploying it on Kubernetes. For me, I had the knowledge of how Kubernetes works, but I had trouble deploying the collector or at times instrumenting my application. The resources on the internet are a bit scattered and it requires a lot of time to go through them. There is a lack of resources that can show you a concrete implementation of OpenTelemetry in Kubernetes from start to finish (or some of them are very cleverly hidden). So I decided to write this blog to demonstrate a very simple implementation of how to deploy a collector to collect metrics and then export the data to various backends for observability. In another blog, I will show how an application in GoLang can be instrumented to expose metrics.
- [thenewstack.io: Maximizing Kubernetes Efficiency with OpenTelemetry Tracing](https://thenewstack.io/maximizing-kubernetes-efficiency-with-opentelemetry-tracing) OTEL tracing can collect detailed data on request execution and provide visibility into the entire system. By catching performance issues early on, it can improve the user experience and reduce the risk of application failures.

#### Telegraf Collector

- [Telegraf Collector](https://www.influxdata.com/time-series-platform/telegraf)
- [Telegraf Prometheus Output Plugin](https://github.com/influxdata/telegraf/tree/master/plugins/outputs/prometheus_client)
- [Telegraf Ansible Role](https://github.com/rossmcdonald/telegraf)
- [Grafana Dashboards with Telegraf Collectors](https://grafana.com/grafana/dashboards/?collector=Telegraf)
- [dzone: Synthetic Monitoring With Telegraf (white-box monitoring) [ARCHIVED]]( http://web.archive.org/web/20220927234147/https://dzone.com/articles/synthetic-monitoring-with-telegraf) Monitoring based on metrics exposed by the internals of the system
- [grafana.com: Using Telegraf plugins to visualize industrial IoT data with the Grafana Cloud Hosted Prometheus service](https://grafana.com/blog/using-telegraf-plugins-to-visualize-industrial-iot-data-with-the-grafana-cloud-hosted-prometheus-service)
- [sysadminxpert.com: How to Monitor Linux System with Grafana and Telegraf](https://sysadminxpert.com/monitor-linux-system-with-grafana-and-telegraf)
- [influxdata.com: Three Ways to Keep Cardinality Under Control When Using Telegraf](https://www.influxdata.com/blog/three-ways-to-keep-cardinality-under-control-when-using-telegraf)

#### Micrometer Collector

- [**Micrometer** Collector](http://micrometer.io)

## Prometheus Alarms and Event Tracking

- Prometheus no soporta rastreo de eventos (event tracking), pero ofrece un soporte completo de alarmas y gestión de alarmas. El lenguaje de consultas (queries) de Prometheus permite en cambio implementar rastreo de eventos por cuenta propia.

## Prometheus and Cloud Monitoring

- AWS CloudWatch is supported by Prometheus.
- https://aws.amazon.com/prometheus/
- [cloud.google.com: Get planet-scale monitoring with Managed Service for Prometheus](https://cloud.google.com/blog/products/operations/introducing-google-cloud-managed-service-for-prometheus) Prometheus, the de facto standard for Kubernetes monitoring, works well for many basic deployments, but managing Prometheus infrastructure can become challenging at scale. As Kubernetes deployments continue to play a bigger role in enterprise IT, scaling Prometheus for a large number of metrics across a global footprint has become a pressing need for many organizations. Today, we’re excited to announce the public preview of Google Cloud Managed Service for Prometheus, a new monitoring offering designed for scale and ease of use that maintains compatibility with the open-source Prometheus ecosystem.

## Prometheus Installers
  - [Setup Prometheus Using Helm Chart on Kubernetes](https://devopscube.com/setup-prometheus-helm-chart) 🌟 - A detailed guide on how to set up Prometheus on a Kubernetes cluster using the official community Helm chart, including best practices and an overview of the components involved like Alertmanager, Kube State Metrics, and Node Exporter.

### Binaries, source code or Docker

- [prometheus.io: Installarion](https://prometheus.io/docs/prometheus/latest/installation)
- [prometheus.io: Getting Started](https://prometheus.io/docs/prometheus/latest/getting_started)
- [github.com/prometheus/prometheus](https://github.com/prometheus/prometheus)

### Ansible Roles

- **Cloud Alchemy**: Deploy prometheus node exporter using ansible.
    - [galaxy.ansible.com/cloudalchemy/node-exporter](https://galaxy.ansible.com/cloudalchemy/node-exporter)
    - [github.com/cloudalchemy/ansible-prometheus](https://github.com/cloudalchemy/ansible-prometheus)
- [Idealista: This ansible role installs a Prometheus Node Exporter in a debian environment](https://github.com/idealista/prometheus_jmx_exporter_role)
    - [galaxy.ansible.com/alexdzyoba/jmx-exporter](https://galaxy.ansible.com/alexdzyoba/jmx-exporter)
    - [github.com/alexdzyoba/ansible-jmx-exporter](https://github.com/alexdzyoba/ansible-jmx-exporter)
- **Mesaguy**: Installs and manages Prometheus and Prometheus exporters.
    - Installs and manages Prometheus server, Alertmanager, PushGateway, and numerous Prometheus exporters
    - This role was designed to allow adding new exporters with ease. Regular releases ensure it always provides the latest Prometheus software.
    - This role can register client exporters with the Prometheus server/s automatically (see tgroup management below).
    - This Ansible role will be migrated to an Ansible Collection.
    - [galaxy.ansible.com/mesaguy/prometheus](https://galaxy.ansible.com/mesaguy/prometheus)
    - [github.com/mesaguy/ansible-prometheus](https://github.com/mesaguy/ansible-prometheus)
- **William Yeh**: Prometheus for Ansible Galaxy. This role only installs 3 components: Prometheus server, Node exporter, and Alertmanager.
    - [galaxy.ansible.com/William-Yeh/prometheus](https://galaxy.ansible.com/William-Yeh/prometheus)
    - [github.com/William-Yeh/ansible-prometheus](https://github.com/William-Yeh/ansible-prometheus)
    - [awesomeopensource.com/project/William-Yeh/ansible-prometheus](https://awesomeopensource.com/project/William-Yeh/ansible-prometheus)
- **Undergreen**: An Ansible role that installs Prometheus Node Exporter on Ubuntu|Debian|redhat-based machines with systemd|Upstart|sysvinit.
    - [galaxy.ansible.com/UnderGreen/prometheus-node-exporter](https://galaxy.ansible.com/UnderGreen/prometheus-node-exporter)
    - [github.com/UnderGreen/ansible-prometheus-node-exporter](https://github.com/UnderGreen/ansible-prometheus-node-exporter)
- **Mitesh Sharma**: Prometheus With Grafana Using Ansible
    - [itnext.io/prometheus-with-grafana-using-ansible-549e575c9dfa](https://itnext.io/prometheus-with-grafana-using-ansible-549e575c9dfa)
    - [github.com/MiteshSharma/PrometheusWithGrafana](https://github.com/MiteshSharma/PrometheusWithGrafana)

## Prometheus Operator

### kube Prometheus

- [kube-prometheus](https://github.com/prometheus-operator/kube-prometheus) Use Prometheus to monitor Kubernetes and applications running on Kubernetes.
- [arthursens.medium.com: Risk analysis and security compliance in Kube-prometheus](https://arthursens.medium.com/risk-analysis-and-security-compliance-in-kube-prometheus-10c8cfb180b8)

#### Prometheus Operator with Helm3

- [devstack.in: Deploy Prometheus Operator with Helm3 and Private Registry 🌟](https://devstack.in/2020/05/25/deploy-prometheus-operator-with-helm3-and-private-registry)

#### Kube-prometheus-stack (best choice)

- [prometheus-community/kube-prometheus-stack 🌟🌟](https://artifacthub.io/packages/helm/prometheus-community/kube-prometheus-stack) **kube-prometheus-stack collects Kubernetes manifests, Grafana dashboards, and Prometheus rules combined with documentation and scripts to provide easy to operate end-to-end Kubernetes cluster monitoring with Prometheus using the Prometheus Operator.**
- [medium.com/israeli-tech-radar: How to create a Monitoring Stack using Kube-Prometheus-stack (Part 1)](https://medium.com/israeli-tech-radar/how-to-create-a-monitoring-stack-using-kube-prometheus-stack-part-1-eff8bf7ba9a9)

#### Kubernetes Cluster Monitoring Stack based on Prometheus Operator

- [Cluster Monitoring stack for ARM / X86-64 platforms](https://github.com/carlosedp/cluster-monitoring) Updated the cluster-monitoring stack for kubernetes to latest versions. Fresh Grafana 7, Prometheus Operator and more. This repository collects Kubernetes manifests, Grafana dashboards, and Prometheus rules combined with documentation and scripts to provide easy to operate end-to-end Kubernetes cluster monitoring with Prometheus using the Prometheus Operator.

## Prometheus SaaS Solutions

- [Weave Cortex SaaS (Hosted Prometheus - Public Cloud)](https://www.weave.works/)
- [logz.io](https://logz.io)
    - [logz.io: Logz.io’s Prometheus-as-a-Service is Generally Available 🌟](https://logz.io/blog/prometheus-as-a-service-launch)
- [Amazon Managed Service for Prometheus](https://aws.amazon.com/prometheus)

## Proof of Concept: ActiveMQ Monitoring with Prometheus

The aim of this Proof of Concept is to learn Prometheus by example being [Red Hat AMQ 7 (broker)](https://developers.redhat.com/products/amq/overview) on RHEL the application to be monitored. Red Hat AMQ Broker is based on ActiveMQ Artemis, being this the reason why one of the following proof of concepts is done with Artemis (the other one was run in order to learn telegraf, prometheus and grafana). The same solution tested with Artemis on RHEL is valid for Red Hat AMQ 7 Broker on RHEL.

Red Hat AMQ 7 Broker is OpenShift 3.11 compliant as Technical Preview and deployed as Operator.

Red Hat AMQ 7 Operator is fully supported in OpenShift 4.x, initially with Prometheus and Grafana monitoring already setup and maintained by AMQ Operator. It is recommended to check the metrics collected and displayed by AMQ Operator with another Proof of Concept in OpenShift 4.x.

### PoC: ActiveMQ 5.x Monitoring with Telegraf Collector, Prometheus and Grafana Dashboard 10702

- Latest releases of Telegraf and Prometheus have been used in this Proof of Concept:
    - [telegraf-1.14.0-1 (rpm)](https://www.influxdata.com/time-series-platform/telegraf)
    - [grafana-6.3.2-1.x86_64 (rpm)](https://grafana.com) This is the release specified as requirement for this grafana dashboard. Newer releases of grafana are probably compliant.
    - [prometheus-2.17.1.linux-amd64 (.tar.gz)](https://prometheus.io)
    - [apache-activemq-5.15.12 (.tar.g)](https://activemq.apache.org/components/classic)
- References:
    - [activemq.apache.org/components/classic/documentation](https://activemq.apache.org/components/classic/documentation)
    - [grafana.com/grafana/dashboards/10702](https://grafana.com/grafana/dashboards/10702-activemq)
    - [github.com/influxdata/telegraf/tree/master/plugins/inputs/activemq](https://github.com/influxdata/telegraf/tree/master/plugins/inputs/activemq)
    - [docs.wavefront.com/activemq.html](https://docs.wavefront.com/activemq.html)

#### Deployment and Configuration

- Systemd

```text
/etc/systemd/system/prometheus.service
/etc/systemd/system/activemq.service
/usr/lib/systemd/system/telegraf.service
/usr/lib/systemd/system/grafana-server.service
```text

- Systemctl

```bash
systemctl daemon-reload
for service in activemq telegraf prometheus grafana-server; do systemctl status $service; done
for service in activemq telegraf prometheus grafana-server; do systemctl restart $service; done
for service in activemq telegraf prometheus grafana-server; do systemctl stop $service; done
for service in activemq telegraf prometheus grafana-server; do systemctl start $service; done
```text

- Jolokia Permissions already integrated in ActiveMQ by default. Jolokia permissions have been disabled by renaming "jolokia-access.xml" to "jolokia-access.xmlORIG" (this is a Proof of Concept):

```bash
mv /opt/activemq/webapps/api/WEB-INF/classes/jolokia-access.xml /opt/activemq/webapps/api/WEB-INF/classes/jolokia-access.xmlORIG
```text

- Telegraf Jolokia Input Plugin /etc/telegraf/telegraf.d/activemq.conf

```text
[[inputs.jolokia2_agent]]
urls = ["http://localhost:8161/api/jolokia"]
name_prefix = "activemq."
username = "admin"
password = "admin"
### JVM Generic
[[inputs.jolokia2_agent.metric]]
name  = "OperatingSystem"
mbean = "java.lang:type=OperatingSystem"
paths = ["ProcessCpuLoad","SystemLoadAverage","SystemCpuLoad"]
[[inputs.jolokia2_agent.metric]]
name  = "jvm_runtime"
mbean = "java.lang:type=Runtime"
paths = ["Uptime"]
[[inputs.jolokia2_agent.metric]]
name  = "jvm_memory"
mbean = "java.lang:type=Memory"
paths = ["HeapMemoryUsage", "NonHeapMemoryUsage", "ObjectPendingFinalizationCount"]
[[inputs.jolokia2_agent.metric]]
name     = "jvm_garbage_collector"
mbean    = "java.lang:name=*,type=GarbageCollector"
paths    = ["CollectionTime", "CollectionCount"]
tag_keys = ["name"]
[[inputs.jolokia2_agent.metric]]
name       = "jvm_memory_pool"
mbean      = "java.lang:name=*,type=MemoryPool"
paths      = ["Usage", "PeakUsage", "CollectionUsage"]
tag_keys   = ["name"]
tag_prefix = "pool_"
### ACTIVEMQ
[[inputs.jolokia2_agent.metric]]
name     = "queue"
mbean    = "org.apache.activemq:brokerName=*,destinationName=*,destinationType=Queue,type=Broker"
paths    = ["QueueSize","EnqueueCount","ConsumerCount","DispatchCount","DequeueCount","ProducerCount","InFlightCount"]
tag_keys = ["brokerName","destinationName"]
[[inputs.jolokia2_agent.metric]]
name     = "topic"
mbean    = "org.apache.activemq:brokerName=*,destinationName=*,destinationType=Topic,type=Broker"
paths    = ["ProducerCount","DequeueCount","ConsumerCount","QueueSize","EnqueueCount"]
tag_keys = ["brokerName","destinationName"]
[[inputs.jolokia2_agent.metric]]
name     = "broker"
mbean    = "org.apache.activemq:brokerName=*,type=Broker"
paths    = ["TotalConsumerCount","TotalMessageCount","TotalEnqueueCount","TotalDequeueCount","MemoryLimit","MemoryPercentUsage","StoreLimi
t","StorePercentUsage","TempPercentUsage","TempLimit"]
tag_keys = ["brokerName"]
```text

- InfluxDB: Not required.
- Defautl /etc/telegraf/telegraf.conf file is modified to allow Prometheus to collect ActiveMQ metrics by pulling Telegraf metrics:

```text
  # # Configuration for the Prometheus client to spawn
  [[outputs.prometheus_client]]
  #   ## Address to listen on
      listen = ":9273"
      ## Path to publish the metrics on.
      path = "/metrics"
  ...
  ...
  # # Gather ActiveMQ metrics
  [[inputs.activemq]]
  #   ## ActiveMQ WebConsole URL
  url = "http://127.0.0.1:8161"
  #   ## Credentials for basic HTTP authentication
  username = "admin"
  password = "admin"
  ...
  ...
```text

- scrape_configs in /opt/prometheus/prometheus.yml

```text
  scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'prometheus'
      # metrics_path defaults to '/metrics'
      # scheme defaults to 'http'.
      static_configs:
      - targets: ['localhost:9090']
  - job_name: 'broker'
      static_configs:
      - targets: ['localhost:9273']
```text

- Grafana Dashboard [10702](https://grafana.com/grafana/dashboards/10702-activemq) is imported from Grafana UI -> "import dashboard". Prometheus data source is connected manually with Grafana via Grafana UI.

### PoC: ActiveMQ Artemis Monitoring with Prometheus Metrics Plugin (Micrometer Collector) and Prometheus. Grafana Dashboard not available

- Latest releases of ActiveMQ Artemis and Prometheus have been used in this Proof of Concept:
    - [grafana-6.7.2-1.x86_64.rpm](https://grafana.com)
    - [prometheus-2.17.1.linux-amd64](https://prometheus.io)
    - [apache-artemis-2.11.0](https://artemis.apache.org/components/artemis)
    - [apache-maven-3.6.3](https://maven.apache.org)
- ActiveMQ Artemis can export metrics to several monitoring systems via [Artemis Prometheus Metrics Plugin](https://github.com/rh-messaging/artemis-prometheus-metrics-plugin), which uses [Micrometer Collector](https://micrometer.io). Check [this link](http://activemq.apache.org/components/artemis/documentation/latest/metrics.html).
- Unfortunately, there's no Grafana Dashboard available for this plugin. In consequence [a new Grafana Dashboard has to be developed from scratch](https://www.openlogic.com/blog/how-visualize-prometheus-data-grafana).
- [Artemis Prometheus Metrics Plugin](https://github.com/rh-messaging/artemis-prometheus-metrics-plugin) is the recommended approach. Use [JMX Exporter](https://github.com/prometheus/jmx_exporter) to export other metrics.
- References:
    - [Apache ActiveMQ Artemis Using the Server](https://artemis.apache.org/components/artemis/documentation/latest/using-server.html)
    - [Apache ActiveMQ Artemis Management Console](https://artemis.apache.org/components/artemis/documentation/latest/management-console.html)
    - [Apache ActiveMQ Artemis Metrics](http://activemq.apache.org/components/artemis/documentation/latest/metrics.html)

#### Deployment and Configuration

- systemd

```text
/etc/systemd/system/prometheus.service
/etc/systemd/system/artemis.service
/usr/lib/systemd/system/grafana-server.service
```text

- systemctl

```bash
# systemctl enable artemis
# systemctl daemon-reload

 for service in artemis prometheus grafana-server; do systemctl status $service; done
 for service in artemis prometheus grafana-server; do systemctl restart $service; done
 for service in artemis prometheus grafana-server; do systemctl stop $service; done
 for service in artemis prometheus grafana-server; do systemctl start $service; done
```text

- Creation of Artemis Broker

```bash
cd /var/lib
/opt/artemis/bin/artemis create --addresses 192.168.1.38 --allow-anonymous --home /opt/artemis --host <my_servername.my_domain> --http-host <my_servername.my_domain> --name <my_servername.my_domain> --queues queue1,queue2 --user artemisuser --password artemispassword artemisbroker

Creating ActiveMQ Artemis instance at: /var/lib/artemisbroker

Auto tuning journal ...
done! Your system can make 13.89 writes per millisecond, your journal-buffer-timeout will be 72000

You can now start the broker by executing:

   "/var/lib/artemisbroker/bin/artemis" run

Or you can run the broker in the background using:

   "/var/lib/artemisbroker/bin/artemis-service" start
```text

- Permissions change in broker directory

```bash
# chown -R activemq. /var/lib/artemisbroker/
```text

- Running artemis broker

```bash
# su - activemq
$ cd /var/lib/artemisbroker/
$ /var/lib/artemisbroker/bin/artemis run
```text

- Artemis Prometehus Console Access. We can now access to Artemis Console via http://my_servername.my_domain:8161/console using the credentials specified during the CLI deployment (artemisuser / artemispassword)

- [Artemis Prometheus Plugin](https://github.com/rh-messaging/artemis-prometheus-metrics-plugin)

```bash
activemq@my_servername ~]$ pwd
/home/activemq
[activemq@my_servername ~]$ cd artemis-prometheus-metrics-plugin/
[activemq@my_servername artemis-prometheus-metrics-plugin]$ mvn install
...
[INFO] Replacing /home/activemq/artemis-prometheus-metrics-plugin/artemis-prometheus-metrics-plugin/target/artemis-prometheus-metrics-plug
in-1.0.0.CR1.jar with /home/activemq/artemis-prometheus-metrics-plugin/artemis-prometheus-metrics-plugin/target/artemis-prometheus-metrics
-plugin-1.0.0.CR1-shaded.jar
[INFO] Dependency-reduced POM written at: /home/activemq/artemis-prometheus-metrics-plugin/artemis-prometheus-metrics-plugin/dependency-re
duced-pom.xml
[INFO]
[INFO] --- maven-install-plugin:2.4:install (default-install) @ artemis-prometheus-metrics-plugin ---
[INFO] Installing /home/activemq/artemis-prometheus-metrics-plugin/artemis-prometheus-metrics-plugin/target/artemis-prometheus-metrics-plu
gin-1.0.0.CR1.jar to /home/activemq/.m2/repository/org/apache/activemq/artemis-prometheus-metrics-plugin/1.0.0.CR1/artemis-prometheus-metr
ics-plugin-1.0.0.CR1.jar
[INFO] Installing /home/activemq/artemis-prometheus-metrics-plugin/artemis-prometheus-metrics-plugin/dependency-reduced-pom.xml to /home/a
ctivemq/.m2/repository/org/apache/activemq/artemis-prometheus-metrics-plugin/1.0.0.CR1/artemis-prometheus-metrics-plugin-1.0.0.CR1.pom
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary for artemis-prometheus-metrics-pom 1.0.0.CR1:
[INFO]
[INFO] artemis-prometheus-metrics-pom ..................... SUCCESS [0.328 s]
[INFO] ActiveMQ Artemis Prometheus Metrics Plugin Servlet . SUCCESS [7.964 s]
[INFO] ActiveMQ Artemis Prometheus Metrics Plugin ......... SUCCESS [34.596 s]
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time:  43.030 s
[INFO] Finished at: 2020-04-10T13:36:27+02:00
[INFO] ------------------------------------------------------------------------
```text

- New artifact is copied to artemis broker. Artefact artemis-prometheus-metrics-plugin/target/artemis-prometheus-metrics-plugin-VERSION.jar is copied to our broker:

```bash
[activemq@my_servername artemis-prometheus-metrics-plugin]$ cp artemis-prometheus-metrics-plugin/target/artemis-prometheus-metrics-plugin-
1.0.0.CR1.jar /var/lib/artemisbroker/lib/
```text

- Edition of file /var/lib/artemisbroker/etc/broker.xml

```text
<metrics-plugin class-name="org.apache.activemq.artemis.core.server.metrics.plugins.ArtemisPrometheusMetricsPlugin"/>
```text

- Creation of <artemis_instance>/web

```text
[activemq@my_servername artemisbroker]$ mkdir /var/lib/artemisbroker/web
```text

- Artifact artemis-prometheus-metrics-plugin-servlet/target/metrics.war is copied to <ARTEMIS_INSTANCE>/web :

```bash
[activemq@my_servername artemis-prometheus-metrics-plugin]$ cp artemis-prometheus-metrics-plugin-servlet/target/metrics.war /var/lib/artem
isbroker/web/
```text

- Below web component added to <ARTEMIS_INSTANCE>/etc/bootstrap.xml :

```text
[activemq@my_servername artemis-prometheus-metrics-plugin]$ vim /var/lib/artemisbroker/etc/bootstrap.xml
...
<app url="metrics" war="metrics.war"/>
...

```text

- Restart of Artemis Broker
- Prometheus configuration, scrape_configs in /opt/prometheus/prometheus.yml :

```text
scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'prometheus'

    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.

    static_configs:
    - targets: ['localhost:9090']
  - job_name: 'broker'
    static_configs:
    - targets: ['localhost:8161']
```text

- Last step: Apparently there's not Grafana Dashboard available for this use case. It is required to [develop a new Grafana Dashboard](https://www.openlogic.com/blog/how-visualize-prometheus-data-grafana).

### Validation of Artemis Broker Monitoring with JMeter

- In order to validate our Artemis Broker Monitoring solution we need to "inject traffic/data/metrics" with for example Pub/Sub messages.
- We can achieve this with a little of java code or by sending messages via Artemis Web Console -> **"Operations"** tab.
- Another option is running the jmeter test plans available on [Artemis' github repo](https://github.com/apache/artemis). The procedure is described below. Remember to create the queues and addresses (topics) defined in jmeter example test plans.

#### JMeter Example Test Plans

- Latest release of [Apache JMeter](https://jmeter.apache.org) deployed in /opt
- Library artemis-jms-client-all-2.11.0.jar is copied to $JMETER_HOME/lib :

```bash
$ cp /opt/artemis/lib/client/artemis-jms-client-all-2.11.0.jar /opt/apache-jmeter-5.2.1/lib/
```text

- jndi.properties file is modified with Artemis' IP address (it is not listening on localhost):

```bash
$ vim /opt/artemis/examples/perf/jmeter/jndi.properties
$ cat /opt/artemis/examples/perf/jmeter/jndi.properties
connectionFactory.ConnectionFactory=tcp://192.168.1.38:61616
```text

- jndi.properties is packaged in a jar file and moved to $JMETER_HOME/lib :

```bash
[activemq@my_servername ~]$ cd /opt/artemis/examples/perf/jmeter/
[activemq@my_servername jmeter]$ ls -l
total 28
-rw-rw-r-- 1 activemq activemq 11887 Jan 10 16:22 1.jms_p2p_test.jmx
-rw-rw-r-- 1 activemq activemq  8442 Jan 10 16:22 2.pub_sub_test.jmx
-rw-rw-r-- 1 activemq activemq   833 Jan 10 16:22 jndi.properties
[activemq@my_servername jmeter]$ jar -cf artemis-jndi.jar jndi.properties
[activemq@my_servername jmeter]$ ls -l
total 32
-rw-rw-r-- 1 activemq activemq 11887 Jan 10 16:22 1.jms_p2p_test.jmx
-rw-rw-r-- 1 activemq activemq  8442 Jan 10 16:22 2.pub_sub_test.jmx
-rw-rw-r-- 1 activemq activemq   946 May 15 08:46 artemis-jndi.jar
-rw-rw-r-- 1 activemq activemq   833 Jan 10 16:22 jndi.properties
[activemq@my_servername jmeter]$ cp artemis-jndi.jar /opt/apache-jmeter-5.2.1/lib/
```text

- Example Test Plans available at Artemis GitHub Repo are run by JMeter (from within the GUI or the CLI):

```bash
[activemq@my_servername ~]$ cd /opt/artemis/examples/perf/jmeter/
[activemq@my_servername jmeter]$ ls -la
total 32
drwxrwxr-x 2 activemq activemq   101 May 15 08:46 .
drwxrwxr-x 3 activemq activemq    19 Jan 10 16:22 ..
-rw-rw-r-- 1 activemq activemq 11887 Jan 10 16:22 1.jms_p2p_test.jmx
-rw-rw-r-- 1 activemq activemq  8442 Jan 10 16:22 2.pub_sub_test.jmx
-rw-rw-r-- 1 activemq activemq   946 May 15 08:46 artemis-jndi.jar
-rw-rw-r-- 1 activemq activemq   833 Jan 10 16:22 jndi.properties
[activemq@my_servername jmeter]$
[activemq@my_servername bin]$ cd
[activemq@my_servername ~]$ pwd
/home/activemq
[activemq@my_servername ~]$ /opt/apache-jmeter-5.2.1/bin/jmeter.sh -n -t /opt/artemis/examples/perf/jmeter/1.jms_p2p_test.jmx -l results-file-1.txt -j 1.log
[activemq@my_servername ~]$ /opt/apache-jmeter-5.2.1/bin/jmeter.sh -n -t /opt/artemis/examples/perf/jmeter/2.pub_sub_test.jmx -l results-file-2.txt -j 2.log

```text

- We can now see metrics displayed on Grafana and Artemis Dashboard:

JMeter|Artemis Grafana|Artemis Dashboard
:-------:|:---------:|:-------:
![jmeter artemis](images/jmeter_artemis.png)|![artemis grafana](images/artemis_grafana.png)|![artemis dashboard monitoring](images/artemis_dashboard_mon.png)

## Prometheus and Azure

- [Promitor 🌟](https://promitor.io) An Azure Monitor scraper for Prometheus

## Managed Prometheus in AWS

- [Managed Prometheus in AWS](prometheus.md#aws-managed-services-for-prometheus-and-grafana)

## Managed Prometheus in GCP

- [==cloud.google.com: Google Cloud Managed Service for Prometheus==](https://docs.cloud.google.com/stackdriver/docs/managed-prometheus) A top option in the market. It's a drop-in replacement for what you have now, and offers leading scale, price, and retention, all with a global backplane.
- [cloud.google.com: Google Cloud Managed Service for Prometheus is now generally available](https://cloud.google.com/blog/products/devops-sre/easy-managed-prometheus-metrics-service-for-kubernetes)

## Videos

<details>
  <summary>Click to expand!</summary>

<center markdown="1">

<iframe width="560" height="315" src="https://www.youtube.com/embed/h4Sl21AKiDg" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/QoDqxm7ybLc" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/mLPg49b33sA" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/r8UvWSX3KA8" title="YouTube video player" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

</center>
</details>

## Tweets

<details>
  <summary>Click to expand!</summary>

<center markdown="1">

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Over the last months we have added a lot of functionalities to <a href="https://twitter.com/PrometheusIO?ref_src=twsrc%5Etfw">@PrometheusIO</a> to help admins limit the risks of targets blowing up servers ⬇️</p>&mdash; Julien Pivotto (@roidelapluie) <a href="https://twitter.com/roidelapluie/status/1458698615082344451?ref_src=twsrc%5Etfw">November 11, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">The why and how of the Prometheus Agent, an Efficient and Cloud-Native Way for Metric Forwarding, by <a href="https://twitter.com/bwplotka?ref_src=twsrc%5Etfw">@bwplotka</a><a href="https://t.co/rEc2krU2nd">https://t.co/rEc2krU2nd</a></p>&mdash; PrometheusMonitoring (@PrometheusIO) <a href="https://twitter.com/PrometheusIO/status/1460629280963153930?ref_src=twsrc%5Etfw">November 16, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Prometheus Agent is a great alternative with better resource usage footprint especially for those who run Prometheus server to only scrape metrics to send samples via remote write. It will allow fleet wide optimizations. <a href="https://t.co/wGd0I9xyaH">https://t.co/wGd0I9xyaH</a></p>&mdash; Jaana Dogan ヤナ ドガン (@rakyll) <a href="https://twitter.com/rakyll/status/1461061166734589954?ref_src=twsrc%5Etfw">November 17, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Prometheus 101 (thread)<br><br>1⃣ Metrics<br><br>A metric is a feature (i.e., a characteristic) of a system that is being measured.<br><br>Typical examples:<br><br>- http_requests_total<br>- http_request_size_bytes<br>- system_memory_used_bytes<br>- node_network_receive_bytes_total <a href="https://t.co/lDZHezBmUH">pic.twitter.com/lDZHezBmUH</a></p>&mdash; Ivan Velichko (@iximiuz) <a href="https://twitter.com/iximiuz/status/1482363582100684801?ref_src=twsrc%5Etfw">January 15, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

</center>
</details>

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