apache

Recursos de programación de apache
For many use cases such as fraud detection or reacting on sensor data the response times of traditional batch processing are simply to slow. In order to be able to react to such events close to real-time, we need to go beyond the classical batch processing and utilize stream processing systems such as Apache Spark Streaming, Apache Flink, or Apache Storm. But these systems are not sufficient by itself. One common example for such fast data pipelines is the SMACK stack using Apache Spark, Mesos, Kafka, Akka, Cassandra, Kafka
El tema de hoy seguro que no deja a nadie indiferente Serverless, olvida los problemas del backend y céntrate en la UX. Un buen comienzo puedes encontrarlo en este artículo: ServerlessDurante el episodio hablamos de PaaS (Jelastic), IaaS, SaaS,... de paquetes de desarrollo (Serverless.com) y las tecnologías cloud orientadas a esta tecnología:Cloud PúblicosAWS LambdaGoogle Cloud FunctionsAzure FunctionsIBM BluemixCloud PrivadosIron FunctionsOpenStack PicassoFissionApache OpenWhiskOpenFaaSY para los que quieran empezar ya en su equipo local a programar como locos sus propias funciones ready to FaaS, aquí os dejamos los ejemplos de Iron Functions para empezar Iron Functions Examples, y la guía para empezar a trabajar con Iron FunctionsTodos los que tengáis comentarios o sugerencias para el podcast podéis enviarnos un correo a programaresunamierda@gmail.com o dejarnos un comentario en Twitter: @progesunam .No olvidéis de suscribiros a nuestro podcast en iVoox o iTunes, o si lo preferís agregad el RSS a vuestra app de podcast preferida. En cualquier caso siempre agradeceremos reviews del podcast en cualquiera de las plataformas.
El tema de hoy seguro que no deja a nadie indiferente Serverless, olvida los problemas del backend y céntrate en la UX. Un buen comienzo puedes encontrarlo en este artículo: ServerlessDurante el episodio hablamos de PaaS (Jelastic), IaaS, SaaS,... de paquetes de desarrollo (Serverless.com) y las tecnologías cloud orientadas a esta tecnología:Cloud PúblicosAWS LambdaGoogle Cloud FunctionsAzure FunctionsIBM BluemixCloud PrivadosIron FunctionsOpenStack PicassoFissionApache OpenWhiskOpenFaaSY para los que quieran empezar ya en su equipo local a programar como locos sus propias funciones ready to FaaS, aquí os dejamos los ejemplos de Iron Functions para empezar Iron Functions Examples, y la guía para empezar a trabajar con Iron FunctionsTodos los que tengáis comentarios o sugerencias para el podcast podéis enviarnos un correo a programaresunamierda@gmail.com o dejarnos un comentario en Twitter: @progesunam .No olvidéis de suscribiros a nuestro podcast en iVoox o iTunes, o si lo preferís agregad el RSS a vuestra app de podcast preferida. En cualquier caso siempre agradeceremos reviews del podcast en cualquiera de las plataformas.
Pub-Sub / Publish-Subscribe"In software architecture, publish–subscribe is a messaging pattern where senders of messages, called publishers, do not program the messages to be sent directly to specific receivers, called subscribers, but instead categorize published messages into classes without knowledge of which subscribers, if any, there may be. Similarly, subscribers express interest in one or more classes and only receive messages that are of interest, without kn...
Pub-Sub / Publish-Subscribe"In software architecture, publish–subscribe is a messaging pattern where senders of messages, called publishers, do not program the messages to be sent directly to specific receivers, called subscribers, but instead categorize published messages into classes without knowledge of which subscribers, if any, there may be. Similarly, subscribers express interest in one or more classes and only receive messages that are of interest, without kn...
TL;DR A queue is a good choice when you have one kind of job to do that you can divide in independent smaller jobs that can execute in any order and a distributed log is a good choice when you have several kinds of jobs or functionalities for the same stream of data (logs, events, etc.).Queues vs Distributed LogsThis blog post tries to explain the typical use for Queues and for Distributed Log, but of course, a system usually uses these solutions in combination or in other ways. But I...
TL;DR A queue is a good choice when you have one kind of job to do that you can divide in independent smaller jobs that can execute in any order and a distributed log is a good choice when you have several kinds of jobs or functionalities for the same stream of data (logs, events, etc.).Queues vs Distributed LogsThis blog post tries to explain the typical use for Queues and for Distributed Log, but of course, a system usually uses these solutions in combination or in other ways. But I...
ScyllaDB is a NoSQL database compatible with Apache Cassandra, distinguishing itself by supporting millions of operations per second, per node, with predictably low latency, on similar hardware. Achieving such speed requires a great deal of diligent, deliberate mechanical sympathy: ScyllaDB employs a totally asynchronous, share-nothing programming model, relies on its own memory allocators, and meticulously schedules all its IO requests. In this talk we will go over the low-level details of all the techniques involved - from a log-structured memory allocator to an advanced cache design -, covering how they are implemented and how they fully utilize the hardware resources they target.