En esta última parte de la serie de cursos de Dataflow, presentaremos los componentes del modelo operativo de Dataflow. Examinaremos las herramientas y técnicas que permiten solucionar problemas y optimizar el rendimiento de las canalizaciones. Luego, revisaremos las prácticas recomendadas de las pruebas, la implementación y la confiabilidad en relación con las canalizaciones de Dataflow. Concluiremos con una revisión de las plantillas, que facilitan el ajuste de escala de las canalizaciones de Dataflow para organizaciones con cientos de usuarios. Estas clases asegurarán que su plataforma de datos sea estable y resiliente ante circunstancias inesperadas.
This course is part of the Serverless Data Processing with Dataflow en Español Specialization
Serverless Data Processing with Dataflow: Operations en Español
About this Course
What you will learn
Realizar actividades de supervisión, solución de problemas, pruebas y CI/CD en las canalizaciones de Dataflow.
Implementar canalizaciones de Dataflow pensando en la confiabilidad para maximizar la estabilidad de su plataforma de procesamiento de datos.
Skills you will gain
- Approximation Error
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Syllabus - What you will learn from this course
En este módulo, se aborda la descripción del curso.
En este módulo, aprenderemos a usar la página Lista de trabajos para filtrar los trabajos que deseamos supervisar o investigar. Observaremos cómo las pestañas Gráfico del trabajo, Información del trabajo y Métricas del trabajo brindan en conjunto un resumen completo de su trabajo de Dataflow. Por último, aprenderemos a usar la integración de Dataflow en el Explorador de métricas a fin de crear políticas de alertas para métricas de Dataflow.
Informes de errores y registros
En este módulo, aprenderemos a usar el panel Registro ubicado al final de las páginas Grafo de trabajo y Métricas del trabajo, y sobre la página Informes de errores centralizada.
Solución de problemas y depuración
En este módulo, aprenderemos a depurar canalizaciones de Dataflow y solucionar sus problemas. También revisaremos los cuatro modos habituales de fallas de Dataflow: falla en la compilación de canalizaciones, falla en el inicio de la canalización de Dataflow, falla en la ejecución de canalizaciones y problemas de rendimiento.
En este módulo, analizaremos las consideraciones de rendimiento que se deben tener presentes cuando se desarrollan canalizaciones por lotes y de transmisión en Dataflow.
Testing y CI/CD
En este módulo, analizaremos cómo realizar pruebas de unidades de las canalizaciones de Dataflow. También presentaremos los frameworks y las funciones disponibles a fin de optimizar su flujo de trabajo de CI/CD para las canalizaciones de Dataflow.
En este módulo, analizaremos métodos para compilar sistemas que sean resilientes ante la corrupción de datos y las interrupciones de los centros de datos.
En este módulo, se abordan las plantillas flexibles, una función que ayuda a los equipos de ingeniería a estandarizar y reutilizar el código de las canalizaciones de Dataflow. Muchos desafíos operativos se pueden solucionar con las plantillas flexibles.
En este módulo, se revisan los temas abordados en el curso.
About the Serverless Data Processing with Dataflow en Español Specialization
Cada vez es más difícil mantener una pila de tecnología que pueda mantenerse al día con las crecientes demandas de un negocio basado en datos. Todos los profesionales de Big Data están familiarizados con las tres V de Big Data: volumen, velocidad y variedad. ¿Qué pasaría si existiera una tecnología a prueba de incrustaciones diseñada para satisfacer estas demandas? Ingrese al flujo de datos de la nube de Google. Google Cloud Dataflow simplifica el procesamiento de datos al unificar el procesamiento por lotes y de transmisión y brindar una experiencia sin servidor que permite a los usuarios concentrarse en el análisis, no en la infraestructura. Esta especialización está destinada a clientes y socios que buscan mejorar su comprensión de Dataflow para avanzar en sus aplicaciones de procesamiento de datos. Esta especialización contiene tres cursos:
Foundations, que explica cómo Apache Beam y Dataflow trabajan juntos para satisfacer sus necesidades de procesamiento de datos sin el riesgo de depender de un proveedor. Developing Pipelines, que cubre cómo convertir nuestra lógica comercial en aplicaciones de procesamiento de datos que pueden ejecutarse en Dataflow Operations, que repasa las lecciones más importantes para operar una aplicación de datos en Dataflow, incluido el monitoreo, la resolución de problemas, las pruebas y la confiabilidad.
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The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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Last Updated: September 1, 2015
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