redis

Salvatore Sanfilippo, Keynoter at Codemotion Milan 2017, talking about REDIS and related technologies.

Running Redis for 8 years what I learned about people and technology - Considerations about human and technological factors, learned on the field while creating, supporting and handling the community of the Redis database project.

@asafmesika "To mock or not to mock" that is the question which has been dividing the developer community for quite a while. The discussion climaxed after the heated debate between DHH, Kent Beck and Martin Fowler - “Is TDD Dead?”. The developers siding with mocks do it primarily due to the difficulty of launching third party components. Some are written in Java - like Kafka or Elasticsearch - which makes it easier to use the real thing - but some are not, which leaves you only with binaries, like MySQL, Redis or Consul. Launching binaries using the shell from Java, being platform agnostic, and taking care of downloading the correct platform binary are just some of the difficulties developers are facing. In this lecture I will show how the existence of Docker transforms the way tests are written. I will introduce you to the innovative library Testcontainers, which provides a complete toolset for controlling Docker in tests. For example, we will take a look at how it enables starting up Consul or MySQL using three lines of code. We will review what the Testing Dichotomy looks like with this power in your hands. At the end of this lecture the audience will know how to test in a pragmatic way making it productively as a result. I believe this approach is mandatory as the world shifts heavily towards team autonomy which means automating your tests on your own - i.e. No QA team dependency. https://www.autentia.com

In hardly any other area we've had as much change and improvement as in the field of databases. Just a few years ago everyone had "their" database that was used for each project. Today you are confronted with a variety of approaches and implementations. We start off with a brief look at the theoretical background of distributed systems and databases in particular. On the basis of this, we take a look at traditional relational databases such as PostgreSQL and MySQL. Additionally, we dive into newer NoSQL systems like MongoDB, Redis, Cassandra, or Elasticsearch. After that, we discuss possible scenarios as well as the advantages and disadvantages of several databases: * Why SQL is in fashion (again). * Why MongoDB's document structure fits object-oriented programming so well. * How you can capture visitor hits with Redis efficiently. * Why Cassandra is so scalable and fail-safe. * How full-text search works with Elasticsearch. The right choice of database(s) hasn't become easier through the wide range of possibilities, but all the more interesting!

I've just listened to this interesting Software Engineering Radio podcast with Josiah Carlson talking about Redis: Josiah Carlson on Redis - por Garajeando

¿Quieres saber más? https://www.paradigmadigital.com/ Índice interactivo aquí debajo: 00:12 Presentación 02:04 Kafka y python 03:01 ¿Quién soy? 03:23 Kafka/origen 04:56 Kafka/origen 05:50 Kafka/motivation 06:58 Kafka/ How to? 08:34 Kafka/ Básicos 09:11 Kafka/ Cluster: Topics & Partitions 11:22 Kafka/ Partitions & Replication 14:13 Kafka/ Producers 16:06 Kafka/ Consumers 18:27 Kafka/ Efficiency 19:45 Kafka/ Python Clients 20:21 Kafka/ Python Clients/ Kafka-python 25:51 Kafka/ Python Clients/ Demo 26:16 Kafka y Python/ Questions 29:40 Redis 29:56 Índice 30:22 1. Introducción a Redis 30:24 Características generales 31:04 Casos de uso 31:28 Detalles de implementación 32:25 Operaciones atómicas 33:00 Tipos de datos 33:35 Consola de Redis (redis-cli) 34:16 Ejemplo String 34:42 Ejemplo List 35:01 Ejemplo Hash 35:24 Ejemplo Transacción 36:07 2. Algo de código 36:13 Clientes Redis 36:24 Cliente Python 37:08 Un ejemplo básico 38:25 Productor/consumidor 40:22 PUB/SUB 41:38 Queueing jobs 42:14 3. Algo sobre administración 42:16 Replicación (I) 43:30 Replicación (II) 43:32 Persistencia 45:15 Particiones/ Sharding 46:47 4. La competencia 46:55 La competencia (I) 47:59 La competencia (II) 49:02 La competencia (III) 49:30 Conclusiones 50:59 Preguntas 53:18 Presentación Python y Flink 53:57 Índice 53:59 ¿Quiénes somos? 54:13 Introducción 54:15 Aclaraciones 54:35 Madurez del BigData 55:30 Arquitectura típica 56:10 Despliegue 56:40 ¿Por qué Apache Flink? 56:43 Apache Flink 57:48 Ventanas 58:29 Ventanas por clave 59:04 Tiggers y Evictors 1:00:02 El tiempo es importante 1:00:43 Rendimiento 1:02:44 Funcionalidades 1:04:50 Experiencia con Python 1:05:36 Según la documentación 1:06:49 Prueba básica 1:09:06 Poca actividad 1:10:01 Conclusiones 1:11:12 Preguntas 1:13:00 Backup slides 1:13:02 Terasort 1:14:35 Streaming-Yahoo

Sin descripción.

Software libre. Redis

¿Quieres saber más? https://www.paradigmadigital.com/ Índice interactivo aquí debajo: ¿Quieres saber más? https://www.paradigmadigital.com/ Índice interactivo aquí debajo: 00:25 Introducción a Redis 01:13 Sistemas actuales 02:32 Bases de datos NoSQL 04:14 ¿Qué es Redis? 05:07 Ventajas e incovenientes de redis 07:24 Redis como base de datos clave / valor NoSQL 09:33 Tipos de datos en Redis 10:49 Strings 11:27 Hash tables 12:17 Tables 14:07 Sorted sets 15:08 Redis como caché 16:27 Expiración del dato 17:44 Redis como bróker de mensajería 18:40 Persistencia en disco 32:49 FIN

En esta charla veremos como usar python3 con asyncio, websockets y redis para construir un servicio distribuido de colas virtuales con los que controlar de forma ordenada el acceso a un servicio con elevada carga pico.