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Jane Paek, from Redis Labs, talks about how we scaled Redis to 1M Ops/Sec. Paek talks about the concepts behind clustering and partitioning, in addition to patterns and anti-patterns to scaling Redis. She then goes on to talk about the tools available to Redis Users for benchmarking. Stay tuned for the demo!
Ever wonder how clustering works? Curious about how and when a cluster resolves a node failure? Join Justin as we take a sneak peak into Redis University's Running Redis at Scale course available now! ▬ Links ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ RU301: Running Redis at Scale → 🤍 Redis Cluster Tutorial → 🤍 Redis Cluster Specification → 🤍 Need a Redis cluster now? Sign up for a free Redis Cloud Essentials account → 🤍 RedisInsight → 🤍 Redis University → 🤍 Redis Inc → 🤍
Redis providers such as AWS ElastiCache, Google MemoryStore, Azure Cache for Redis, and Heroku Redis do not optimize Redis to minimize your costs. Database solutions such as DynamoDB can be expensive and slower than Redis, with queries upwards of 10 milliseconds or more. With Redis Enterprise you can take advantage of Redis on Flash to store terabytes of data while keeping costs down and still achieving sub-millisecond latencies. This results in up to 80% in savings versus Redis from other cloud providers. Redis Enterprise is not only feature rich and blazing fast, it’s also cost-effective for businesses of any size. Try Redis Enterprise Cloud FREE → 🤍 See the possibilities of Redis on Redis Launchpad → 🤍 Learn more about developing with Redis → 🤍 LinkedIn → 🤍 Twitter → 🤍 Facebook → 🤍
Redis PubSub is a popular choice for a message bus, but scaling it can prove difficult. This session presents an approach for doing that. Link to slides: 🤍 🤍
Twitter runs some of the largest Redis clusters in production. To adapt Redis to Twitter's use cases, we have come up with both configuration best practices and several new features. This talk is to provide a case study of running Redis at scale- with numbers and stories, and what we have in mind for the future. About Yao Yu Yao has been on the cache team at Twitter for over three years. She worked on in-memory caching technologies, including Twitter's fork of of Redis, Twemcache, and created an analytic framework for cache backends. She has strong bias toward clean abstractions, efficient data processing and good code aesthetics. 🤍thinkingfish This event was organized by the San Francisco Redis Meetup group (🤍 If you are doing something interesting and fun with Redis and would like to share your stories get in touch with ben.arent🤍rackspace.com Event produced by Rackspace and filmed at Geekdom San Francisco on July 17, 2014. Follow 🤍GeekdomSF for upcoming events and inquire about SF coworking membership at 🤍
Learn about how Redis Enterprise can scale with shards, nodes, the proxy, and with the Cluster API.
This course is a complete step-by-setup guide on how to build real-time web applications using ASP.NET Core SignalR. By the end of this course, you'll be able to build real world, scalable, production applications using the tools and techniques provided in this course. Get the course for free: 🤍 🔔 Subscribe: 🤍 💥 Join this channel to get access to source code, demos, and slides! 🤍 📝 Blog: 🤍 📚 Book Recommendations Domain-Driven Design 🤍 Patterns of Enterprise Application Architecture 🤍 Refactoring: Improving the Design of Existing Code 🤍 Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith 🤍 RESTful Web Clients: Enabling Reuse Through Hypermedia 🤍 CodeOpinon: 🤍 Twitter: 🤍
In this video I want to demonstrate how to scale websockets connection to multiple servers using a load balancer such as HAProxy. 0:00 Intro 1:00 What are WebSockets? 2:40 WebSockets Scaling 7:44 Chat WebSocket App Code * WebSockets * WebSockets Scaling * Live chat application (microservices) * Demo Source Code 🤍 🏭 Software Architecture Videos 🤍 💾 Database Engineering Videos 🤍 🛰 Network Engineering Videos 🤍 🏰 Load Balancing and Proxies Videos 🤍 🐘 Postgres Videos 🤍 🚢Docker 🤍 🧮 Programming Pattern Videos 🤍 🛡 Web Security Videos 🤍 🦠 HTTP Videos 🤍 🐍 Python Videos 🤍 🔆 Javascript Videos 🤍 👾Discord Server 🤍 Support me on PayPal 🤍 Become a Patreon 🤍 Stay Awesome, Hussein
Redis has 10 different data structures (String, Hash, List, Set, Sorted Set, Bit Array, Bit Field, Hyperloglog, Geospatial Index, Streams) plus Redis Modules. In this talk, Dave will give at least 1 example of how to use each data structure to scale your website. He will start with the basics, such as a SQL cache and User session management. Then he will demonstrate storing user generated tags, leaderboards and counting things with hyberloglog. He will end with a demo of Redis Streams which can be used to scale your Microservices-based architecture.
This video will help you understand how Redis Enterprise scales with shards.
Learn how to scale Redis beyond a single instance using Redis Cluster. This video describes many of the problems and pitfalls you're likely to encounter when setting up Redis Cluster, and ways to overcome them. It also demonstrates how Redis Cluster compares to ScaleOut StateServer, a commercial alternative to Redis Cluster and sponsor of this video. Related article: 🤍 CAP and Microservices: 🤍 Intro music: Ringside - Dyalla via YouTube Music
Check out my courses: 🤍 Become a Patreon and get source code access: 🤍 Hello everybody I'm Nick and in this video I will show you how you can integrate Redis into .NET 7's brand new output caching. Using a distributed cache that is extremely fast and scalable, like Redis, will allow you application to scale horizontaly while using one single cache for all your responses. Don't forget to comment, like and subscribe :) Social Media: Follow me on GitHub: 🤍 Follow me on Twitter: 🤍 Connect on LinkedIn: 🤍 Keep coding merch: 🤍 #csharp #dotnet #caching
Building and scaling microservice architectures can be a big challenge. Use Redis Enterprise to simplify. 🤍 Increased latency and complexity start to affect the top and bottom lines of most businesses. Watch this quick video and understand how ... - Microservices architecture can be really hard to scale Redis Enterprise has multiple solutions to help with these pains of building and scaling microservices architecture - Redis Enterprise is the defacto solution to help with microservices architecture, and there is more to learn. Download the solution brief! 🤍 #redis #data #microservices
Peter Karp, from BuzzFeed, talks about how the use of Redis as a job cache in autoscaling, distributing and rendering pipeline. Video rendering is the process of compositing multimedia such as video, images, text or audio one frame at a time to create a video. As longer videos needed processing we implemented distributed parallel-processing to reduce time and allow the creation of longer videos. Redis is used to coordinate the rendering jobs running on separate servers. The common tools for video editing are complex and memory intensive and do not provide simple scripting for bulk batching of routine tasks. Content often needs to be formatted for different platforms, or cropped and trimmed to be re-purposed in new ways. International distribution means adding captions or updating on-screen text. We created Stitcher, a video rendering service to perform these post-production tasks as well as rendering video for Vidder our innovative in-house video editing application. Like many media companies, BuzzFeed creates hours of video content every day and has an extensive catalog going back several years. As our users created longer videos in Vidder and required new features such as captions Stitcher's original sequential rendering approach showed its limitations. Stitcher v.2 took advantage of the way Vidder structured video into independent cells where one video clip was composited with text and images. Stitcher v.2 renders each cell on a server giving true multiprocessor parallelism and coordinated with a Redis job cache. This talk describes some of the requirements and problems found in high volume video production environments, the limits we hit and how our new approach using parallel processing along with Redis solved them. Stitcher is built with Python 3, Redis, moviepy and ffmpeg.
RedisConf 2021 Speaker: Erik Brandsberg Track: Build with Redis Learn the techniques and optimizations Heimdall Data uses with Redis to implement automated caching and reader offload for database clusters, how you can use these techniques yourself, and how to resolve pitfalls such as data consistency. Try Free at 🤍
In this video, we look at how you can scale out and speed up your web scraping using multiple workers(Spiders) using scrapy-redis. The article that goes along with this video: 🤍 Scrapy project used in this tutorial: 🤍 Where you can sign up for a free cloud Redis instance: 🤍 Where you can download RedisInsite the Redis desktop manager: 🤍 00:00 - Intro 00:37 - Things to think about when scaling 03:01 - Setting up Redis 05:31 - Adding list of urls to be scraped to Redis queue 08:21 - Scraping with one worker (spider) 12:49 - Scraping with two workers (spiders) 16:59 - Outro
Redis customer Razorpay at RedisDays India describes how they scale payments with machine learning with Redis. Try Redis Cloud for free: 🤍 How does Redis serve the financial services industry: 🤍 How Redis combats fraud detection: 🤍 #redis #machinelearning #webinar
RedisConf 2021 Speaker: Medha Atre Track: Operate Redis at Scale Eydle reimagines distributed, deep learning technology to optimize training speed and cost. It is reinventing the technology to handle fault tolerance, variable network latency and heterogeneity of devices leading to 70-90% reduction in cost. By using Redis as an eventual consistency key-value store for model parameters, the Eydle team has achieved 1.5x faster transaction times. Watch this session to learn the detailed results of Eydle's experiments with using Redis in various situations, and see how the results measure up against MySQL. Try Free at 🤍
Erik Brandsberg from Heimdall speaking at RedisConf19
In this video we will show you how to scale from open-source Redis up to Redis Enterprise.
Ex-Google Tech Lead Patrick Shyu talks about scalability, and how he grew a website to handle 10 million users (per month). I cover load balancing, content delivery networks, mysql query optimization, database master/slave replication, horizontal/vertical sharding, and more. * Note, these experiences were from projects before I began working at Google, so I'm talking about my individual experiences (Google uses a ton more techniques, though the basic concepts are similar). I'm sure I missed some things, so please share in the comments below if you have thoughts on how to scale! I'd love to hear. Join me in DeFi Pro and make passive income with crypto. 🤍 Join ex-Google/ex-Facebook engineers for my coding interview training: 🤍 💻 100+ Videos of programming interview problems explained: 🤍 📷 Learn how to build a $1,000,000+ business on YouTube: 🤍 💻 Sign up for my FREE daily coding interview practice: 🤍 🛒 All my computer/camera gear: 🤍 ⌨️ My favorite keyboards: 🤍 🎉 Party up: 🤍 🤍 Disclosure: Some links are affiliate links to products. I may receive a small commission for purchases made through these links. #techlead
Featuring: Ben Clark, Chief Architect at Wayfair Description: At Wayfair, we had to take the caching layer for our customer-facing web sites from a simple master/slave pair of Memcached nodes in 2012, to a set of consistently hashed clusters of in-memory cache servers and persistent key-value stores, in multiple data centers, in time for the holiday rush of 2013. Building on the work of giants and innovators, particularly Akamai, Last.fm, and Twitter, we used composable tools: Memcached, Redis, Ketama, Twemproxy, Zookeeper, to create a resilient distributed system. It's big. Well. That’s always relative. Maybe that’s too bold a claim, considering some of the others speakers at this conference. Let's say it seems big to us, and we've been through some explosive growth over the last few years! It's definitely inexpensive, strong, and fast, and Ben Clark will describe our techniques and add-ons, which are available on github, and explain how to do it yourself.
Andrey Belik, Senior Product Manager discusses Amazon ElastiCache for Redis provides fully managed, automatic scaling to maintain steady performance for your application demands. ElastiCache will automatically scale your cluster based on these scaling plans, enabling you to save on overall cloud spend by matching provisioned resources with changing capacity requirements. To get started with Auto Scaling for Amazon ElastiCache for Redis visit 🤍 Subscribe: More AWS videos 🤍 More AWS events videos 🤍 ABOUT AWS Amazon Web Services (AWS) hosts events, both online and in-person, bringing the cloud computing community together to connect, collaborate, and learn from AWS experts. AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster. #AWS #AmazonWebServices #CloudComputing #AWSOnAir
In this session, I will be going over Ekata’s journey from moving off of ElasticCache as a primary datastore onto Redis on Flash. This move provided Ekata with cost savings without sacrificing on latency Learn more about Redis on Flash here: 🤍 Try Redis Enterprise Cloud for free: 🤍
Jon Hyman, Co-Founder and CTO of Braze, talks about solving problems at scale at Redis Day New York 2019. Hyman talks about how Redis helps Braze, a platform that has 1.6 billion monthly active users, to solve their biggest challenges. Stay tuned!
Caching in distributed systems is an important aspect for designing scalable systems. We first discuss what is a cache and why we use it. We then talk about what are the key features of a cache in a distributed system. The cache management policies of LRU and Sliding Window are mentioned here. For high performance, the cache eviction policy must be chosen carefully. To keep data consistent and memory footprint low, we must choose a write through or write back consistency policy. Cache management is important because of its relation to cache hit ratios and performance. We talk about various scenarios in a distributed environment. System Design Video Course: 🤍?source_id=youtubecaching A complete course on how systems are designed. Along with video lectures, the course has architecture diagrams, capacity planning, API contracts and evaluation tests. Use the coupon code 'earlybird' for a 20% discount! System Design Playlist: 🤍 Designing Data Intensive Applications - 🤍 Code: 🤍 You can follow me on: Facebook: 🤍 Quora: 🤍 LinkedIn: 🤍 Twitter: 🤍 References: Guava Cache - 🤍 LRU - 🤍 🤍 Implementation of Sliding Window Cache policies (Caffeine) - 🤍 🤍 🤍 #SystemDesign #Caching #DistributedSystems
David Maier and Anna Iskra, from Redis Labs, talk about how to scale Redis Enterprise. They discuss situations when Redis shards hit max memory, max CPU, and re-sharding. Also covered are Redis on Flash, overcoming network saturation, and much more. 🤍
In this session, we'll discover what Redis is, and the many ways Azure Redis Cache can help you optimize your .Net Core applications, especially for cache-aside, transactions, and messaging. We'll also look at the various offerings available at Azure, why you might choose each one, and how they can offer full HADR options to create robust and resilient solutions. We'll also implement a simple app that leverages a deployed Azure Cache instance to show how easy it is to get up and running.
Ever wanted to set up your own clustered database from the command-line but never had the time nor patience? Join Justin as he sets up an 8-node Redis cluster in no time! ▬ Links ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Creating a Cluster in Redis Step-By-Step Instructions → 🤍 Check out RU301: Running Redis at Scale → 🤍 Redis University → 🤍 Redis, Inc. → 🤍 Join our discord server → 🤍
Done via GitLab v11.11.3 on Ubuntu 18 servers Sections: - Learn about horizontal scaling, Part 1: Consul - 🤍 - Learn about horizontal scaling, Part 2: Databases and PgBouncer - 🤍 - Learn about horizontal scaling, Part 3: Redis and Sentinel - 🤍 - Learn about horizontal scaling, Part 4: NFS and Load Balancer - 🤍 - Learn about horizontal scaling, Part 5: Application Servers - 🤍 Commands used in this video: - sudo gitlab-ctl reconfigure - sudo touch /etc/gitlab/skip-auto-reconfigure
Redis Enterprise has been making waves in the world of data storage, offering lightning-fast performance and unparalleled scalability. In this talk, we explore how Redis Enterprise is revolutionizing the future of data storage and unlocking new possibilities for businesses of all sizes. From real-time analytics to machine learning and beyond, Redis Enterprise is empowering developers to build high-performance solutions that can keep up with the demands of today's fast-paced world. *Speakers:* * Tara Hutton * Sean Noyes *Session Information:* This video is one of many sessions delivered for the Microsoft Build 2023 event. View the full session schedule and learn more about Microsoft Build at 🤍 ODFP235 | English (US) | Data platform #MSBuild
It’s time to move from Redis open source to fully managed Redis Enterprise Cloud. Try it for free: 🤍 How do you migrate from Redis open source to Redis Enterprise on Google Cloud without disrupting your business or losing data? In this webinar, we will demo how to deploy a fully functioning microservices application on Google Cloud using Redis open source, show you how to migrate the data to Redis Enterprise with minimal downtime, and provide terraform automation so you can try it out for yourself. Read more about Redis Enterprise and Google Cloud: 🤍 From the blog: Legacy Database Migration - What to Know Before You Start - 🤍 #Redis #GoogleCloud #opensource
Ye Gu joins Scott Hanselman to discuss Azure Cache for Redis, a popular open-source in-memory data store that uses DRAM to store the most frequently used or time-sensitive data for fast retrieval. With it, you can create applications on Azure that handle millions of requests per second at down to sub-millisecond latency. Now, Azure Cache for Redis is becoming even more powerful through the integration of Redis Enterprise in partnership with Redis Labs. 0:00 – Introduction 0:46 – Presentation 6:34 – Demo 15:48 – Discussion & wrap-up ◉ Meeting developer needs with powerful new features in Azure Cache for Redis – 🤍 ◉ Azure Cache for Redis – 🤍 ◉ Quickstart: Create an Enterprise tier cache (preview) – 🤍 ◉ How to Improve Your Azure SQL Performance by up to 800% – 🤍 ◉ Optimize your web applications by caching read-only data with Redis – 🤍 ◉ Create a free account (Azure) – 🤍 #Microsoft #Azure #AzureFriday
Slide deck: 🤍 This talk will cover the design choices made in our tooling and environment configuration in our path at Square to operationalizing Redis. We will discuss how we developed our custom tools and how they work, specifically looking at our failover, monitoring, and data recovery procedures.
Here we take a look at how we can scale Server Sent Events horizontally in NestJS using Redis & pm2. We'll also fix a timeout/SSE getting disconnected after a minute bug when we've put our application behind nginx reverse proxy, which common in production environments. Source: github.com/MustagheesButt/ScalingSSE
Moe Chaieb, an Infrastructure Engineer from Shopify, talks about the challenges Shopify faced when scaling. Shopify is one of the oldest and largest Ruby on Rails monoliths, with 170K peak RPS and 2 billion background jobs a day. Chaieb explains how Redis helped scale Shopify, increased its reliability, even during their flash sales, and allowed them to horizontally scale.
Timely genome analysis requires a fresh approach to platform design for big data problems. Louisiana State University has tested enterprise cluster deployments of Redis with a unique solution that allows flash memory to act as extended RAM. Learn about how this solution allows large amounts of data to be handled with a fraction of the memory needed for a typical deployment.
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