Day 1 General Session RedisConf

May 26, 2016Download as PPTX, PDF2 likes826 views

This document contains information about Redis and its creator Salvatore Sanfilippo. It discusses Redis modules and how to create them. It also lists the schedule for breakout sessions at a Redis conference on May 10, including sessions on using Redis as a message bus, solving latency issues, and building scalable streaming data pipelines.

Tim Savage
Armakuni Co-Founder and Cloud Native Developer

90% of annual public donations
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Key performance metrics
up to 400 donations per second
up to 800,000 donations in total
7 hour window,
ONCE a year with
no 2nd chance

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Can you trust
Redis to save a
life?
to save
10,000?

Itamar Haber
Chief Developer Advocate at RedisLabs

https://groups.google.com/forum/#!msg/redis-db/Z0aiVSRAnRU/XezAFFtgyPUJ
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“Another interesting idea is
to add support for plugins
implementing specific
commands and associated
data types, and the
embedding of a scripting
language.”

STEP II
BUILD ITgithub.com/antirez/redis/unstable
github.com/RedisLabs/RedisModulesSDK
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Uploads by anyone.
Open source modules.
Automated checks.
Community filtered.
Being developed.
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Redis Labs
Module Hubbeta
redismodules.com
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Uploads by anyone.
OS and commercial.
Certified by Redis Labs
for open source Redis,
Redis Cloud & RLEC.
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Thank you and bon appetit 
@itamarhaber @redislabs

Enjoy RedisConf
Updates
• Your morning break is located downstairs in the Sponsor Showcase
• Three concurrent Breakout Sessions will begin at 11:15am
• The Developer Workshop begins at 1:00pm in the Developer Café
• Save your Redis Community Raffle ticket for tomorrow’s drawing
for a chance to win a Phantom Drone

11:15am-12:00pm A Hacker’s Guide To A New Era in Redis
1:00pm-1:45pm Redis as a Message Bus
2:00pm-2:45pm Solving Redis Latency Issues with Transparent
Huge Pages: Make Copy-On-Write Great Again
3:15pm-4:00pm Using Redis as a Distributed Cache for ASP.NET
Apps with IIS
4:15pm-5:00pm Scalable Streaming Data Pipelines with Redis
64
BREAKOUTS: TUESDAY, MAY 10

The document compares the performance of IBM Streams to other streaming analytics offerings using the Linear Road benchmark, finding that IBM Streams achieved an L-Rating of 200 using 4 Azure nodes, significantly outperforming Apache Apex and Apache Storm. It also describes how Walmart uses streaming analytics for real-time inventory control and logistics monitoring, and how IBM Streams was able to implement the Linear Road benchmark in under 15 days of development time.

Redis in a Multi Tenant Environment–High Availability, Monitoring & Much More! Redis Labs

This document discusses best practices for running Redis in a multi-tenant environment. It covers architectural considerations like high availability, security and isolation techniques using ACLs and SSL, and the importance of monitoring and understanding your environment. The key opportunities are that failover is easy to implement, changes can be introduced smoothly, and the architecture is reusable. Challenges include managing global sentinels and Redis drivers. Case studies demonstrate issues like customer spikes causing problems and the importance of monitoring.

Back your App with MySQL & Redis, the Cloud Foundry Way- Kenny Bastani, PivotalRedis Labs

In this session, we will build a minimum viable Spring Data web service with REST API, add a MySQL backing service as the primary data store, and a Redis Labs backing service for caching. We will demonstrate performance metrics without Redis caching enabled and then with Redis caching enabled. I will also provide an intro-level explanation of the platform capabilities within Pivotal Web Services.

Handling Redis failover with ZooKeeperryanlecompte

This document discusses using ZooKeeper to automatically handle Redis failover. ZooKeeper is an open-source tool that provides primitives for building distributed applications and handles tasks like leader election and quorum management. The presenter describes how his redis_failover Ruby gem uses ZooKeeper to monitor Redis servers, detect failures, and automatically inform clients so they reconnect to the new master, preventing downtime during a failover. Several companies already use this approach with redis_failover to make their Redis infrastructure more robust and fault-tolerant.

Redis ReplicationIsmaeel Enjreny

Redis replication allows slave servers to mirror the data and state of a master server. It supports asynchronous replication where slaves acknowledge processed data from the master. A master can have multiple slaves in a graph-like structure. Replication is automatic and helps with scalability, high availability, and avoiding costly master disk writes. Partial resynchronization allows replication to resume after a temporary disruption without a full resync.

RedisConf17 - Operationalizing Redis at ScaleRedis Labs

This document discusses how Square operationalized Redis at scale. It describes their goals of standard setup and deployment, security through SSL/TLS, high availability, and monitoring. It then details how they used LXC containers, ghostunnel for SSL/TLS, disabled Redis persistence, relied on replication for durability, and implemented access controls. Looking forward, it discusses automating operations with SpinCycle and hopes for native Redis SSL/TLS and internal patches from Square.

Cloud Foundry Summit 2015: Building a Robust Cloud Foundry (HA, Security and DR)VMware Tanzu

RedisConf17 - Amadeus - Redis-Cluster operatorRedis Labs

This document discusses making Redis cluster deployments easier using an operator on OpenShift. It motivates using Redis cluster for session handling and improved performance. It describes prototypes that deployed Redis cluster but lacked features like simple deployment, updating topology, and rolling updates. The document then presents a Redis manager application that automates cluster operations on OpenShift and proposes developing a Redis operator to improve lifecycle management and support multiple clusters. It concludes by discussing open sourcing the Redis manager and developing it further as an operator.

Sharding Containers: Make Go Apps Computer-Friendly Again by Andrey Sibiryov Docker, Inc.

The document discusses how modern hardware has become more complex with multi-core, multi-socket CPUs and deep cache hierarchies. This complexity introduces latency and performance issues for software. The author describes their service that processes millions of requests per second spending a large amount of time on garbage collection, context switching, and CPU stalls. They developed a tool called Tesson that analyzes hardware topology and shards containerized applications across CPU cores, pinning linked components closer together to improve locality and performance. Tesson integrates with a local load balancer to distribute workloads efficiently utilizing the system resources.

RedisConf18 - Common Redis Use Cases for Cloud Native Apps and MicroservicesRedis Labs

The document discusses cloud native applications and architectures. It explains that cloud native applications are designed to take advantage of cloud computing abilities like scaling up and down on demand and limitless compute. Being cloud native isn't just an architectural pattern but a combination of practices like agile development, continuous delivery, automation, containers, and microservices that change development culture and move to a DevOps model. It also discusses concepts like serverless computing, functions as a service, microservices, and twelve factor applications.

Securing the Helix Platform at CitrixPerforce

RedisConf17 - Redis Cluster at flickr and tripodRedis Labs

Flickr uses Redis extensively across many services for caching, queueing, and more. Some key uses of Redis include caching for the camera roll and activity feed, which each have multiple masters and slaves distributed across data centers. Notifications are also queued in Redis. In total, Flickr operates over 100 physical hosts running 500+ Redis instances to support over 600,000 operations per second across services like the camera roll, activity feed, notifications, and more.

RedisConf17 - Explosion of Data at the Edge in EquinixRedis Labs

This document discusses Equinix's plans to implement a microservices architecture and edge caching capabilities for their DCIM platform. The new architecture aims to address challenges from Equinix's large, global, and heterogeneous infrastructure by breaking the application into independent, containerized microservices. This will improve scalability, performance, fault tolerance, and deployments. The architecture will leverage edge processing by caching data and services at local data centers to reduce latency and enable offline functionality.

Highly scalable caching service on cloud - RedisKrishna-Kumar

Developing with the Go client for Apache KafkaJoe Stein

This document summarizes Joe Stein's go_kafka_client GitHub repository, which provides a Kafka client library written in Go. It describes the motivation for creating a new Go Kafka client, how to use producers and consumers with the library, and distributed processing patterns like mirroring and reactive streams. The client aims to be lightweight with few dependencies while supporting real-world use cases for Kafka producers and high-level consumers.

Serverless Presentation from Devoxx 2017 Casablanca (AWS Lambda / FaaS / Fn ...Frank Munz

DockerCon EU 2015: What's New with Docker Trusted RegistryDocker, Inc.

RedisConf17 - Doing More With Redis - Ofer Bengal and Yiftach ShoolmanRedis Labs

This document summarizes RedisConf 2017, covering several topics: 1. Running Redis on Flash in a DBaaS model for improved performance and cost savings compared to other NoSQL databases. 2. Redis modules gaining momentum with over 50 created so far, and the importance of multi-threading for high performance. Useful modules highlighted include RediSearch, ReJSON, Redis-ML, and Redis-Graph. 3. Using Redis for IoT applications, with challenges around small edge devices and clusters, high throughput from thousands of devices, and varied functionality needs addressed through Redis modules.

Network Infrastructure as Code with Chef and CiscoMatt Ray

Chef is an open source framework for managing infrastructure as code. It uses a declarative language and recipes to describe and configure systems to match a desired state. Chef works by having clients pull policies from a server and apply them locally, then reporting the state back. Cisco and Chef are working together to bring official Chef support to Cisco's NX-OS and IOS-XR platforms through Omnibus packages and a Cisco cookbook with resources for managing Cisco devices. This will allow network infrastructures to be managed as code through testing, versioning, and continuous delivery practices.

Production Ready Containers from IBM and DockerDocker, Inc.

Containers are quickly becoming the default foundation for modern applications. As a public cloud provider, IBM has been an early champion of containers in the cloud and has built an enterprise ready container service as part of IBM Bluemix. IBM has a long heritage of supporting, contributing to, and building offerings on top of open technologies and IBM carries this commitment to the open development of container solutions by being an active/founding member of the Open Containers Initiative and Cloud Native Computing Foundation. In this session, we will explore the enduring commitment to open technology as well as the advantages of using a pure containers service where the user has access to total solution life cycle management through integration of lessons learned, cutting edge enhancements/development and end-to-end support on the user's underlying infrastructure. We will explore topics such as exploiting bare metal servers, applying overlay networking to containers, ensuring isolation and security in a truly multi-tenant container environment and managing a global service deployment.

OpenStack Upgrade - It can be done! Koby Holzer, Liran Cohen - OpenStack Day ...Cloud Native Day Tel Aviv

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USENIX LISA15: How TubeMogul Handles over One Trillion HTTP Requests a MonthNicolas Brousse

TubeMogul grew from few servers to over two thousands servers and handling over one trillion http requests a month, processed in less than 50ms each. To keep up with the fast growth, the SRE team had to implement an efficient Continuous Delivery infrastructure that allowed to do over 10,000 puppet deployment and 8,500 application deployment in 2014. In this presentation, we will cover the nuts and bolts of the TubeMogul operations engineering team and how they overcome challenges.

Real Time Recommendations Using WebSockets and Redis - Ninad Divadkar, InuitRedis Labs

WebSockets connect the browser to your app server. But what if the processing happens on some other server? In that case you need to connect the worker process to the app process via a messaging system. After experimenting with RabbitMQ, we settled on Redis as a great pub sub and a caching system. This presentation will describe the architecture of the system and how we use spring-websockets and spring-data-Redis to power the system. As a bonus, we will show a great way to find out in real time how many users are currently using your system.

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Docker Networking in Production at Visa - Sasi Kannappan, Visa and Mark Churc...Docker, Inc.

Docker has developed a new way of delivering applications, and with that, containers have also changed some aspects of how we approach networking. Visa will detail how they use Docker networking to connect applications in a dynamic environment by using Swarm overlays, service discovery, and load balancing. By switching to overlay networking they will show that they were able to reduce complexity and increase performance. By the end of the talk, you'll learn about the different Docker networking drivers and how you can use Docker networking to architect dynamic and resilient networks.

Kafka & Hadoop - for NYC Kafka MeetupGwen (Chen) Shapira

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The document discusses serverless architectures and function as a service (FaaS) platforms. It provides an overview of FaaS implementations from Amazon, Google, Microsoft and Oracle. Key benefits of FaaS include pay per use pricing, automatic scaling, and eliminating the need to manage servers. Challenges include limitations on runtimes and resource usage as well as vendor lock-in. The document argues that FaaS fulfills the definition of microservices and could replace traditional container-based microservice architectures.

Using Redis as Distributed Cache for ASP.NET apps - Peter Kellner, 73rd Stre...Redis Labs

I will build from scratch in this session a Microsoft ASP.NET website that caches WebAPI REST calls with both MSOpenTech’s Redis implementation for running while developing in Visual Studio as well as running on a Windows server running IIS. I will show you how to build a safe reusable caching library in c# that can be used in any .net project. I will also demonstrate how to use the Redis cache services that are available on Microsoft’s Azure cloud platform. Further, I’ll demonstrate a real world web site that uses Azure Redis cache and show statistics on how Redis improves performance consistently and reliably.

RedisConf 2016 - Redis usage and ecosystemFrançois-Guillaume Ribreau

This document summarizes insights from Redis usage data collected by Redsmin, a service for administrating and monitoring Redis servers. It finds that most Redis servers are running version 3.0 or 2.8, have uptimes of less than one year, use plain text connections without authentication, and have the slowlog enabled. Over 90% of servers do not have maxmemory configured to limit memory usage. The document suggests warning users to configure maxmemory and consider 32-bit Redis if maxmemory is set below 4GB for a 64-bit installation.

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1) Learn about Myplanet's Headless CMS solution using Gatsby Preview and Contentful’s UI Extensions (https://www.contentful.com/resources/serverless/) 2) their Serverless project with IBM - using Apache OpenWhisk (https://www.ibm.com/cloud/functions) 3) how Myplanet got involved with AWS DeepRacer - a fun way to get started with Reinforcement Learning (RL), and their racing experience at re:Invent DeepRacer League (https://reinvent.awsevents.com/learn/deepracer/) 4) their Machine Learning (ML) research related to finding DeepRacer’s ideal line (https://medium.com/myplanet-musings/the-best-path-a-deepracer-can-learn-2a468a3f6d64). BONUS: Two TED Talks referenced in the intro 5) When ideas have sex | Matt Ridley | Jul 14, 2010 https://www.ted.com/talks/matt_ridley_when_ideas_have_sex 6) Why The Best Leaders Make Love The Top Priority | Matt Tenney | Dec 5, 2019 https://www.youtube.com/watch?v=qCVoohdyI6I VIDEO: https://youtu.be/ZH1xxmBNx5k

DevOps and the C64: what's your excuseTodd Whitehead

The document discusses DevOps concepts applied to developing software for a Commodore 64 computer system. It describes setting up a productive development environment on the C64 with tools for coding, compiling, and testing software. It then discusses applying DevOps practices like source control, work tracking, continuous integration, and continuous delivery to deploy updates to the C64. This would allow automated testing and delivery of changes to applications running on real C64 hardware or bulletin board systems.

Cloud Native Cost Optimization UCCAdrian Cockcroft

Docker Seattle Meetup, May 2017Stephen Walli

RedisConf18 - Redis in Dev, Test, and Prod with the OpenShift Service CatalogRedis Labs

This document discusses using Redis in development, test, and production environments with the OpenShift Service Catalog. It demonstrates using Redis for iterative development with ephemeral instances in development. In testing, it shows production-like configurations with immutable infrastructure, recovery testing, and zero-downtime deployments. For production, it notes the Service Catalog can provide targeted Redis instances and make external services discoverable. It promotes the Open Service Broker API and OpenShift Service Catalog for expanding service options.

Cincom Smalltalk: Present, Future & Smalltalk AdvocacyESUG

Web Velocity is a tool for developing web applications entirely within a web browser. It uses VisualWorks Smalltalk, the Seaside framework, and object-relational mapping to allow users to build, test, and debug dynamic Ajax-enabled web applications directly in the browser. The document discusses where Cincom's Smalltalk products are currently and outlines priorities for future development, including internationalization support, 64-bit virtual machines, improved graphics capabilities, and leveraging multi-core processors. It also emphasizes the importance of advocacy for the Smalltalk language and community.

Cloud-Native .Net des applications containerisées .Net sur Linux, Windows e...VMware Tanzu

DCSF19 How To Build Your Containerization Strategy Docker, Inc.

The Microservices and DevOps JourneyC4Media

DCEU 18: How To Build Your Containerization StrategyDocker, Inc.

Red Hat OpenShift Enterprise 2 Launch Webcast Slides Dec 3, 2013asheshbadani

DockerCon EU 2015: Day 1 General SessionDocker, Inc.

DevOps Handbook: Experiments in Accelerating DeliveryJim Grafmeyer

Docker AWS TechCONNECT Boston, 28-July-2015Docker, Inc

Better Operations into the CloudFabio Ferrari

OpenIO A3techlive in London - March 2016OpenIO Object Storage

Securing Red Hat OpenShift Containerized Applications At Enterprise ScaleDevOps.com

Docker Bday #5, SF Edition: Introduction to DockerDocker, Inc.

Designing API Platforms that Developers Love - New York Life Build Blue May 2017Deepak Nadig

OpenShift: Devops Made EasyBent Terp

Serverless projects at MyplanetDaniel Zivkovic

DevOps and the C64: what's your excuseTodd Whitehead

Cloud Native Cost Optimization UCCAdrian Cockcroft

Docker Seattle Meetup, May 2017Stephen Walli

RedisConf18 - Redis in Dev, Test, and Prod with the OpenShift Service CatalogRedis Labs

Cincom Smalltalk: Present, Future & Smalltalk AdvocacyESUG

Cloud-Native .Net des applications containerisées .Net sur Linux, Windows e...VMware Tanzu

More from Redis Labs (20)

Redis Day Bangalore 2020 - Session state caching with redisRedis Labs

This document discusses using Redis caching to improve performance for the DBS Paylah mobile wallet application. Paylah aims to significantly increase its user base which will increase load on its backend systems. Caching application data and session state in Redis can reduce latency, improve responsiveness for users, and reduce costs by lowering load on legacy backend databases and mainframes. The document outlines some key Paylah use cases where caching transaction histories and account details in Redis would accelerate retrieval and improve the mobile experience by avoiding the need to access slower backend systems on each request.

Protecting Your API with Redis by Jane Paek - Redis Day Seattle 2020Redis Labs

The document discusses rate limiting and metering using Redis. It begins by introducing rate limiting and metering and why Redis is well-suited for these tasks. It then covers different Redis data structures that can be used, such as lists, hashes, sorted sets and strings. Common Redis commands for counting, setting keys and checking time to live are also presented. Different rate limiting design patterns and anti-patterns are described, including fixed window, sliding window and token bucket approaches. Finally, resources for further information are provided.

The Happy Marriage of Redis and Protobuf by Scott Haines of Twilio - Redis Da...Redis Labs

The document summarizes a presentation about using Protocol Buffers and Redis together. It discusses how Protocol Buffers provide strict data types, versioning, and serialization/deserialization benefits. It then outlines Redis key patterns using namespaces, versions, data categories and identifiers. Examples are provided to show how Protocol Buffers messages can be stored in Redis using these key patterns, including storing connections data in sets, sorted sets and individual messages. Benefits discussed include structure, readability, testing and abstraction.

SQL, Redis and Kubernetes by Paul Stanton of Windocks - Redis Day Seattle 2020Redis Labs

The document discusses common use cases for combining SQL, Redis, and Kubernetes including caching, session management, rate limiting, and data ingestion. It outlines how Kubernetes can be used for scaling microservices while Redis is used for data service scaling. The presentation proposes combining Redis, SQL Server, and Kubernetes with a proxy service, and describes using Redis for caching, session storage, and rate limiting of SQL data. It also discusses running Redis and front-end apps on Kubernetes and deploying SQL as a Kubernetes service through a proxy.

Rust and Redis - Solving Problems for Kubernetes by Ravi Jagannathan of VMwar...Redis Labs

This document discusses using Rust and Redis to build cloud native platforms. It first provides context about devops and the need to do more with less. It then discusses how platforms are becoming more distributed and Kubernetes upends distribution paradigms. The document dives into how Rust addresses issues like concurrency and systems programming. It also discusses how Redis can be used for caching, queues, streams and more. Finally, it mentions that Rust and Redis will be demonstrated.

Redis for Data Science and Engineering by Dmitry Polyakovsky of OracleRedis Labs

This document contains a presentation about using Redis for data science and engineering. It introduces the presenter and provides an agenda that covers using Redis for data science and data engineering. The presentation notes that Redis can be used as both a data store and job queue, has flexible data structures and is fast, though it uses RAM and cannot query by value. It also lists Python Pandas and includes a demo and links for further information.

Practical Use Cases for ACLs in Redis 6 by Jamie Scott - Redis Day Seattle 2020Redis Labs

Jamie Scott from RedisLabs presented on practical use cases for access control lists (ACLs) in Redis 6. The presentation covered new security features in Redis 6 including encryption in transit, key space and command restrictions, and multiple access control list users. It demonstrated how ACLs allow users to define access based on key labels and restrictions. ACLs can facilitate discretionary and mandatory access controls. The presentation showed examples of using ACLs to restrict user access by key labels and commands to enhance operational security.

Moving Beyond Cache by Yiftach Shoolman Redis Labs - Redis Day Seattle 2020Redis Labs

This document summarizes a presentation about Redis version 6 and beyond. Some key points include: - Redis version 6 includes new features like ACL for security, client-side caching, diskless replication, and multi-threaded I/O. - Redis is positioned as both a cache and a database due to its speed, data structures, and ability to handle complex data models through modules. - Redis Enterprise provides additional capabilities like durability, high availability, geo-distribution, security and multi-tenancy. - Modern data models in Redis modules include Streams, RediSearch, RedisGraph, RedisTimeSeries, RedisAI, RedisJSON and RedisBloom. - RedisInsight is

Leveraging Redis for System Monitoring by Adam McCormick of SBG - Redis Day S...Redis Labs

The document discusses how Sinclair Broadcast Group leverages Redis for system monitoring of its content delivery network. It operates 193 news stations with 10,000 active pages daily and millions in archive. New stories are posted every 15 seconds and must be visible across its 1,000+ targets within 1 minute. Redis is used to track performance across the multi-level CDN and ensure service level agreements are met with real-time resolution and alerting. It provides a black box view of the audience experience and can scale monitoring to all relevant pages within 30 seconds. Redis acts as a distributed data store to parallelize the monitoring task across the large scale of the network.

JSON in Redis - When to use RedisJSON by Jay Won of Coupang - Redis Day Seatt...Redis Labs

The document summarizes a presentation about when to use the RedisJSON data type. It discusses how Coupang uses Redis extensively for their ad platform. It then compares the performance and memory usage of storing JSON data as strings, hashes, or using the RedisJSON data type. Benchmark results show RedisJSON can provide better performance for retrieving and updating JSON fields compared to strings and hashes, though it uses more memory. The document recommends using RedisJSON for smaller JSON payloads after benchmarking and memory monitoring.

Highly Available Persistent Session Management Service by Mohamed Elmergawi o...Redis Labs

The document discusses the challenges of building a highly available persistent session management service. It describes Zulily's legacy architecture which lacked high availability and required manual intervention. A new architecture is proposed using Redis for persistent storage, Dynomite for real-time replication across data centers, and a connection pooling proxy to improve efficiency and distribute load. The architecture provides high availability through replication, reduces overhead through connection pooling, and handles failures through consistent hashing and health checks. It was tested through simulations and showed a failure rate of only 0.42% during outages.

Anatomy of a Redis Command by Madelyn Olson of Amazon Web Services - Redis Da...Redis Labs

The document describes the process that a Redis command follows from the client side to the server side. On the client side, the command is sent over the network to the Redis server. On the server side, the command is read from the kernel buffers, validated, executed by calling the relevant command handler, and the response is written back to the client over the network. The core functions involved on the server side are ReadQueryFromClient(), ProcessInputBuffer(), ProcessCommand(), Call(), and handleClientsWithPendingWrites(). Redis 6.0 introduced I/O threads to handle reads and writes in parallel for improved performance while still maintaining Redis' single-threaded processing model.

Building a Multi-dimensional Analytics Engine with RedisGraph by Matthew Goos...Redis Labs

This document discusses MDmetrix, a healthcare data intelligence company that uses RedisGraph to provide flexible analysis of hospital data. RedisGraph is a graph database that represents data as nodes and relationships and uses an adjacency matrix and linear algebra to query the graph. MDmetrix models its healthcare data as a property graph in RedisGraph to allow for complex queries across different data dimensions like patients, facilities, procedures and drugs. RedisGraph allows MDmetrix to query the data more easily than traditional OLAP cubes or relational databases due to the semi-structured and flexible nature of the graph model.

RediSearch 1.6 by Pieter Cailliau - Redis Day Bangalore 2020Redis Labs

RediSearch 1.6 includes a new low-level API that allows other Redis modules to embed RediSearch indexing capabilities. It also introduces index aliasing and several performance improvements such as forked thread garbage collection. Based on benchmarks, RediSearch 1.6 shows 48-73% better performance than version 1.4, particularly during high update rates where it maintains more stable read latencies.

RedisGraph 2.0 by Pieter Cailliau - Redis Day Bangalore 2020Redis Labs

RedisGraph 2.0 provides significant improvements including: - Full text search support through embedded RediSearch 1.6 enabling graph-aided search. - Support for returning full graph responses to enable better visualization. - Broad support for Cypher including triadic closure and new graph-aided search capabilities. - Performance improvements of up to 3.7x faster operations per second and 3.9x faster query times compared to RedisGraph v1.2. - Support for benchmarking including the LDBC benchmark.

RedisTimeSeries 1.2 by Pieter Cailliau - Redis Day Bangalore 2020Redis Labs

RedisTimeSeries is a time-series database that provides compression to reduce memory usage by up to 98% and improve performance. The RedisTimeSeries 1.2 release includes compression algorithms based on a Facebook paper that provide stable ingestion times independent of the number of data points. It also includes a reviewed API with performance improvements and clearer functionality. Performance testing showed ingestion throughput improved by 2-3% and query performance increased from 15-70% with the new release compared to the previous version.

RedisAI 0.9 by Sherin Thomas of Tensorwerk - Redis Day Bangalore 2020Redis Labs

This document summarizes RedisAI 0.9 and its capabilities for model deployment and benchmarking. It introduces RedisAI's new tensor data type and ability to deploy models to CPU and GPU. It then discusses AIBench, a tool developed to benchmark AI serving solutions like RedisAI, TensorFlow Serving, and REST APIs. The benchmarks show RedisAI providing 5.5x and 2.5x more inferences than REST APIs and TensorFlow Serving respectively, due to its data locality. The document concludes by mentioning RedisAI's integration with MLFlow for model deployment with a single command.

Rate-Limiting 30 Million requests by Vijay Lakshminarayanan and Girish Koundi...Redis Labs

The document discusses how Freshworks uses Redis Labs to rate limit 30 million API requests per day through their API gateway called Fluffy. Fluffy stores rate limit policies and maintains counters to track requests. Redis Labs allows Fluffy to easily scale to handle the high volume of requests by providing a fast, in-memory data store for managing rate limiting counters. The system was able to successfully rate limit 30 million requests per day with Redis Labs.

Three Pillars of Observability by Rajalakshmi Raji Srinivasan of Site24x7 Zoh...Redis Labs

Solving Complex Scaling Problems by Prashant Kumar and Abhishek Jain of Myntr...Redis Labs

Redis was used by Myntra to solve several complex scaling problems. It was used to build a scalable user segment service to support high read throughput of up to 5 million requests per minute with low latency. Redis allowed the service to scale beyond a single instance and included features like automatic backups and memory management. Redis also helped build a scalable mobile verification platform to reliably handle 100,000 requests per minute and scale to support higher future volumes. It was used as both a transient store and persistent backend. Finally, Redis locks helped build a scalable A/B testing platform by allowing experiments to be created and updated in an orderly concurrent fashion.