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🚀 ¡Sube de nivel y mejora como programador con cursos especializados!
🔝 Cursos prácticos y sin rodeos impartidos por profesionales con amplia experiencia
👨‍🎓 Podrás hacer TODOS los cursos ya publicados (más de 20 y subiendo)
🎥 Vídeos con calidad de imagen y audio garantizada
📕 En cada lección de cada curso: Posts de acompañamiento a vídeos con código o puntos a destacar + preguntas tipo test para interiorizar conocimientos adquiridos + ejercicios sugeridos para practicar
🆕 Cursos nuevos cada mes
👨‍👩‍👧‍👦 Acceso a la comunidad CodelyTV Pro. Preguntas y respuestas sobre los problemas que te interesan
🔖 Certificado al completar un curso. Añádelo a tu LinkedIn para demostrar interés de mejora continua y acceder a ofertas de trabajo relacionadas
😍 Dar tu apoyo para que podamos seguir publicando cursos en CodelyTV Pro, y screencasts y entrevistas en CodelyTV

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En este curso veremos cómo centralizar logs con una solución muy popular, potente, y además grátis llamada Elastic Stack. Este stack consiste en cuatro herramientas principales: Elasticsearch, Logstash, Kibana y Beats. Aprenderemos a instalar, configurar y por supuesto utilizarlas con brío y salero 🕺\n

¿Qué aprenderás en este curso?\n

🚀 Instalar y configurar Elastic Stack gracias a Docker
🤔 Entender la estructura de la información en Elasticsearh (tipos de nodos, cómo configurar un cluster, agregaciones, transformaciones, y mucho más
🕵️ Realizar consultas complejas a Elasticsearch con su Query DSL. Útil no sólo para buscar logs, si no como motor de indexado fulltext! 🎉
🐘☕🧬 Configurar librerías de logging en PHP, Scala, y Java para enviar tus logs a Elasticsearch a través de Logstash o Beats
📊 Visualiza logs en Kibana agregando toda la información en gráficos para tener un dashboard de control
⚡Reemplaza Logstash por Beats para un mejor rendimiento y simplifica tu stack
🐳 Consideraciones a la hora de usar Elastic Stack con Kubernetes

🤝 Todo esto lo haremos centréndonos en un caso práctico: Reportar toda la información de nuestros logs en cualquier servidor de nuestro ecosistema, para centralizarlos y explotar esa información en un Dashboard único de Kibana.

🤟 No obstante, destacar que en el curso veremos los conceptos en los que se basa Elasticsearch a nivel de Documentos, índices, tipos de nodos, gestión del clúster, y demás. De tal forma que con estos conocimientos podemos montarnos nuestro motor de búsqueda fulltext y páginas de listado de elementos (productos, usuarios, cursos…).

Aquí el primer vídeo del curso para que te hagas una idea de la calidad del contenido 😬

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Experiencia:

4 años como desarrollador PHP en Uvinum aplicando SOLID, Arquitectura Hexagonal, y DDD
2 años como desarrollador Scala en letgo aplicando CQRS, Modelo de Actores, y microservicios basados en Event-Driven Architecture
4 años como profesor del Master en Programación Web de Alto Rendimiento (MPWAR) de LaSalle
Ahora dando el 100% en CodelyTV haciendo nuevos cursos para CodelyTV Pro, vídeos para YouTube, y ayudando a empresas a mejorar con formaciones personalizadas.

","image":"https://pathwright.imgix.net/https%3A%2F%2Fcdn.filestackcontent.com%2Fapi%2Ffile%2FbFGy78YiSq2NaBz8Jbn8%3Fsignature%3D888b9ea3eb997a4d59215bfbe2983c636df3c7da0ff8c6f85811ff74c8982e34%26policy%3DeyJjYWxsIjogWyJyZWFkIiwgInN0YXQiLCAiY29udmVydCJdLCAiZXhwaXJ5IjogNDYyMDM3NzAzMX0%253D?fit=crop&h=115&ixlib=python-1.1.0&w=115&s=d1ab70bfdad4684e9662fc62f38c325f","resources_count":10,"salutation":"","title":"Desarrollador en CodelyTV","slug":"mr-javier-ferrer-gonzalez","order":1,"avatar":"https://cdn.filestackcontent.com/bFGy78YiSq2NaBz8Jbn8"},{"id":2847,"display_name":"Rubén Cougil","first_name":"Rubén","last_name":"Cougil","bio":"

Desarrollador web desde 2011. Actualmente Software Engineer en Magento (Adobe), tras mi paso por Softonic International y CMP Group (Adult Entertainment).

Apasionado de la Arquitectura Hexagonal y de las buenas prácticas (SOLID). No escribo código sin tests, aplicando TDD siempre que sea posible.

Profesor universitario en el Máster Web de Alto Rendimiento de La Salle (Universitat Ramon Llul, Barcelona)

Desarrollador de la Aplicación de recomendación cultural: Rekomendo!

Tecnologías, herramientas y lenguajes principales: PHP, Go, Typescript, Javascript, Symfony, Ionic, Docker, Vagrant, Ansible, Elastic Stack (Elasticsearch), Redis, AWS (Amazon Web Services), RabbitMQ, MySql, CI (Jenkins, Travis, Drone, ... ), DataDog, PHPUnit, Behat

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