Frequently asked questions

Containers share the host OS kernel, so they are much lighter and faster.

Yes, it starts with the basic concepts and evolves towards advanced orchestration.

It is a text script containing instructions to build a Docker image.

A tool to define and run multi-container Docker applications.

It's a public registry where you can find and share Docker images.

Docker's native tool to orchestrate a cluster of Docker engines.

Yes, unless you use Docker volumes to persist data.

To reduce the final image size by excluding compilation tools.

Yes, you can impose CPU and RAM limits when starting it.

Kubernetes uses standard containers (often Docker or containerd) for orchestration.

It is a complete observability platform based on artificial intelligence.

SaaS is hosted by Dynatrace, Managed is installed on your own infrastructure.

A single agent that installs on your hosts to automatically collect all metrics and traces.

Davis AI analyzes billions of dependencies to find the exact root cause of a problem.

Dynatrace's data lakehouse designed specifically for unified observability data.

Yes, Dynatrace integrates perfectly with Docker, Kubernetes, and OpenShift.

The 'Monitoring as Code' tool to manage your Dynatrace configurations as code.

Yes, with synthetic monitors (Synthetic Monitoring).

Thanks to DDUs (Davis Data Units) which allow tracking the consumption of different metrics.

Yes, there are several levels such as Associate, Advanced Observability, etc.

It is an open-source automation tool for configuration management, application deployment, and orchestration of IT tasks.

No, Ansible is 'agentless'. It communicates with remote servers via SSH (for Linux/Unix) or WinRM (for Windows).

It is a YAML formatted file that describes a set of ordered tasks to be executed on one or more target servers (the inventory).

An open source data collection engine to process and enrich events.

A series of data processing steps including inputs, filters, and outputs.

To parse and structure unstructured text into identifiable fields.

Beats is lightweight and collects data at the source, while Logstash is a heavy engine that centralizes and transforms the data.

Un système de supervision et d'alerting open source spécialisé dans les séries temporelles.

Il utilise un modèle 'pull' où le serveur vient récupérer les métriques sur les cibles.

Un agent qui traduit des métriques tierces au format compris par Prometheus.

Le langage d'interrogation puissant permettant de manipuler les séries temporelles.

En utilisant Pushgateway, car le modèle 'pull' n'est pas adapté pour les tâches très courtes.

Non, Prometheus gère uniquement les métriques. Logstash gère les logs.

Prometheus évalue les règles d'alerte et envoie les événements à Alertmanager.

Un outil pour collecter les métriques d'utilisation des conteneurs Docker/Kubernetes.

Oui, Prometheus est la source de données par défaut et la plus utilisée pour Grafana.

Oui, il intègre des mécanismes de découverte de services (Service Discovery).

It is the on-demand access, via the Internet, to shared computing resources (servers, storage, applications) with a pay-as-you-go model.

IaaS provides the core infrastructure, PaaS offers a platform for developers, and SaaS provides finished software accessible via a browser.

It is the ability of a Cloud infrastructure to automatically increase or decrease its resources to adapt to the load in real time.

C'est une plateforme open source de visualisation et d'analyse de métriques.

Grafana supporte de nombreuses sources comme Prometheus, Elasticsearch, InfluxDB, MySQL, PostgreSQL, etc.

Kibana est très lié à Elasticsearch pour les logs, Grafana est plus agnostique et excelle dans les métriques et l'intégration multi-sources.

Oui, Grafana dispose d'un système d'alerting puissant intégré.

Via l'authentification (LDAP, OAuth), le HTTPS et la gestion fine des permissions par dossier et tableau de bord.

Elle permet de rendre les tableaux de bord dynamiques (ex: filtrer par serveur ou environnement).

Oui, au format JSON pour les sauvegarder ou les partager.

Grafana Cloud est un service SaaS managé, l'auto-hébergement vous donne le contrôle total sur l'infrastructure.

Des marqueurs visuels sur les graphiques pour indiquer des événements (déploiements, pannes).

Oui, notamment avec Loki, la solution de logs intégrée à l'écosystème Grafana.

They are lightweight agents from the Elastic stack installed on servers to collect data.

Filebeat collects and sends logs in a lightweight way, while Logstash is a heavy transformation engine.

An agent dedicated to collecting system and service metrics.

Elastic Agent is the new unified solution intended to replace individual Beats.

The centralized interface in Kibana for configuring and updating Elastic Agents at scale.

Yes, Winlogbeat is specifically designed for Windows event logs.

Mainly to Elasticsearch or Logstash, but also to Kafka or Redis.

No, they are written in Go and designed to be very lightweight.

Ready-to-use configurations for common systems (Nginx, MySQL) including dashboards.

Yes, they support SSL/TLS encryption and authentication.

It is an open-source container orchestration system that automates deployment, scaling, and management of containerized applications.

A Pod is the smallest deployable unit in Kubernetes, containing one or more containers. A Deployment is a higher-level object that manages ReplicaSets, which in turn ensure that a specific number of identical Pods are running at all times.

It is an abstraction that defines a logical set of Pods and a policy to access them (via a stable IP and port), acting as an entry point and internal load balancer.

It is an open-source, vendor-neutral telemetry collector designed to replace Grafana Agent. It is OpenTelemetry (OTel) compatible.

Yes, Alloy combines the features of Promtail and Grafana Agent and includes native support for OpenTelemetry.

Alloy uses a declarative syntax based on River (similar to Terraform's HCL) which simplifies pipeline creation.

Absolutely, Alloy offers full native support for receiving, processing, and exporting data (Traces, Logs, Metrics) via the OTLP protocol.