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.
What's new with enterprise Redis - Leena Joshi, Redis LabsRedis Labs
Redis Labs manages over 160k+ HA databases, 10k clustered databases, without data loss in spite of one node failure a day and one data center outage per month. Using Enterprise
Redis(RLEC), Redis Labs delivers seamless zero downtime scaling, true high availability with persistence, cross-rack/zone/
datacenter replication and instant automatic failover. Learn how. Join this session for a deep dive into how enterprise Redis makes for no-hassle Redis deployments and the roadmap for new Redis capabilities. Discover new cost savings with Redis on Flash for cost-effective high performance operations and analytics
Managing 50K+ Redis Databases Over 4 Public Clouds ... with a Tiny Devops TeamRedis Labs
A presentation by Redis Labs' CTO, Yiftach Shoolman, given at the July 2nd meet up, hosted by I am OnDemand and IGT Cloud at the Microsoft ILDC Auditorium.
See the video at: https://www.youtube.com/watch?v=eymqHZaUOH4
In this In this session Yiftach shares tips on how the company manages 50,000+ scalable and highly avaliable Redis databases over the 4 largest public clouds, 8 leading Platforms-as-a-Service, and across 10 geographical regions. He explains the service's back-end architecture, the open-source projects it uses, and which tools the company builds in-house. Shoolman also shares what Redis Labs' small DevOps team does automatically, and what it still does manually. Finally, he offers advice on how to build a strong R&D team that lives and breathes DevOps.
Since the company launched its Redis Cloud service, it has dealt with 150+ node failure events and a half-dozen complete data-center outages. In addition, its team has experienced many interesting scenarios, such as hard to believe scaling patterns like 0 to a few hundreds gigabytes of in-memory data in just a few minutes, and 0 to 300K+ ops/sec in just a few seconds.
What's new with enterprise Redis - Leena Joshi, Redis LabsRedis Labs
Redis Labs manages over 160k+ HA databases, 10k clustered databases, without data loss in spite of one node failure a day and one data center outage per month. Using Enterprise
Redis(RLEC), Redis Labs delivers seamless zero downtime scaling, true high availability with persistence, cross-rack/zone/
datacenter replication and instant automatic failover. Learn how. Join this session for a deep dive into how enterprise Redis makes for no-hassle Redis deployments and the roadmap for new Redis capabilities. Discover new cost savings with Redis on Flash for cost-effective high performance operations and analytics
Managing 50K+ Redis Databases Over 4 Public Clouds ... with a Tiny Devops TeamRedis Labs
A presentation by Redis Labs' CTO, Yiftach Shoolman, given at the July 2nd meet up, hosted by I am OnDemand and IGT Cloud at the Microsoft ILDC Auditorium.
See the video at: https://www.youtube.com/watch?v=eymqHZaUOH4
In this In this session Yiftach shares tips on how the company manages 50,000+ scalable and highly avaliable Redis databases over the 4 largest public clouds, 8 leading Platforms-as-a-Service, and across 10 geographical regions. He explains the service's back-end architecture, the open-source projects it uses, and which tools the company builds in-house. Shoolman also shares what Redis Labs' small DevOps team does automatically, and what it still does manually. Finally, he offers advice on how to build a strong R&D team that lives and breathes DevOps.
Since the company launched its Redis Cloud service, it has dealt with 150+ node failure events and a half-dozen complete data-center outages. In addition, its team has experienced many interesting scenarios, such as hard to believe scaling patterns like 0 to a few hundreds gigabytes of in-memory data in just a few minutes, and 0 to 300K+ ops/sec in just a few seconds.
Redis in a Multi Tenant Environment–High Availability, Monitoring & Much More! Redis Labs
Running any
application in a multi-tenant environment poses its challenges. This talk is focused around how we at Rackspace run Redis
in a multi-tenant environment, ensuring security, performance, fault tolerance and high availability. This talk will cover: an
architecture deep dive of multi tenant Redis on the cloud, management of sentinels, monitoring and operations of a large
scale Redis deployment,introducing new Redis versions,scaling, security, some lessons learnt. The target audience for this
talk is anyone who is interested in the deployment/operational aspect of running Redis. This is relevant not only for those
who want to run Redis themselves, but also interested in how a Redis provider might be doing it for them.
Ceph: Open Source Storage Software Optimizations on Intel® Architecture for C...Odinot Stanislas
Après la petite intro sur le stockage distribué et la description de Ceph, Jian Zhang réalise dans cette présentation quelques benchmarks intéressants : tests séquentiels, tests random et surtout comparaison des résultats avant et après optimisations. Les paramètres de configuration touchés et optimisations (Large page numbers, Omap data sur un disque séparé, ...) apportent au minimum 2x de perf en plus.
Virtual training Intro to the Tick stack and InfluxEnterpriseInfluxData
In this webinar, we will provide an introduction to the components of the TICK Stack and a review the features of InfluxEnterprise and InfluxCloud. We also demo how to install the TICK stack.
How we got to 1 millisecond latency in 99% under repair, compaction, and flus...ScyllaDB
Scylla is an open source reimplementation of Cassandra which performs up to 10X with drop in-replacement compatibility. At ScyllaDB, performance matters but even more importantly, stable performance under any circumstances.
A key factor for our consistent performance is our reliance on userspace schedulers. Scheduling in userspace allows the application, the database in our case to have better control on the different priorities each task has and to provide an SLA to selected operations. Scylla used to have an I/O scheduler and recently won a CPU scheduler.
At ScyllaDB, we make architectural decisions that provide not only low latencies but consistently low latencies at higher percentiles. This begins with our choice of language and key architectural decisions such as not using the Linux page-cache, and is fulfilled by autonomous database control, a set of algorithms, which guarantees that the system will adapt to changes in the workload. In the last year, we have made changes to Scylla that provide latencies that are consistent in every percentile. In this talk, Dor Laor will recap those changes and discuss what ScyllaDB is doing in the future.
Dynomite: A Highly Available, Distributed and Scalable Dynamo Layer--Ioannis ...Redis Labs
Dynomite is a
thin, distributed dynamo layer for different storage engines and protocols. Currently at Netflix, we are focusing on using
Redis as the storage engine. Dynomite supports multi-datacenter replication and is designed for high availability. In the age of high scalability and big data, Dynomite’s design goal is to turn single-server datastore solutions into peer-to-peer, linearly
scalable, clustered systems while still preserving the native client/server protocols of the datastores, e.g., Redis protocol. In this talk, we are going to present Dynomite recent features, and the Dyno client. Both projects are open source and available to the community.
Perforce BTrees: The Arcane and the ProfanePerforce
"Get a tour of Perforce BTree history, its behaviors and configuration. Learn about performance alternatives, space management tools and future projects, too."
Redis Developers Day 2014 - Redis Labs TalksRedis Labs
These are the slides that the Redis Labs team had used to accompany the session that we gave during the first ever Redis Developers Day on October 2nd, 2014, London. It includes some of the ideas we've come up with to tackle operational challenges in the hyper-dense, multi-tenants Redis deployments that our service - Redis Cloud - consists of.
HIgh Performance Redis- Tague Griffith, GoProRedis Labs
High Performance Redis looks at a wide range of techniques - from programming to system tuning - to deploy and maintain an extremely high performing Redis cluster. From the operational
perspective, the talk lays out multiple techniques for clustering (sharding) Redis systems and examines how the different
approaches impact performance time. The talk further examines system settings (Linux network parameters, Redis
system) and how they impact performance (both good and bad). Finally, for the developer, we look at how different ways of structuring data actually demonstrate different performance characteristics
Aerospike AdTech Gets Hacked in Lower ManhattanAerospike
Aerospike's highly reliable and scalable database, using NoSQL and In-memory technology, presentation slides given at Stack Exchange on April 10th with NSOne and advertising technology luminaries.
AdTech Gets Hacked in Lower Manhattan
Stack Exchange, 110 William St 28th Floor,
New York, NY 10038
Have you heard that all in-memory databases are equally fast but unreliable, inconsistent and expensive? This session highlights in-memory technology that busts all those myths.
Redis, the fastest database on the planet, is not a simply in-memory key-value data-store; but rather a rich in-memory data-structure engine that serves the world’s most popular apps. Redis Labs’ unique clustering technology enables Redis to be highly reliable, keeping every data byte intact despite hundreds of cloud instance failures and dozens of complete data-center outages. It delivers full CP system characteristics at high performance. And with the latest Redis on Flash technology, Redis Labs achieves close to in-memory performance at 70% lower operational costs. Learn about the best uses of in-memory computing to accelerate everyday applications such as high volume transactions, real time analytics, IoT data ingestion and more.
Redis in a Multi Tenant Environment–High Availability, Monitoring & Much More! Redis Labs
Running any
application in a multi-tenant environment poses its challenges. This talk is focused around how we at Rackspace run Redis
in a multi-tenant environment, ensuring security, performance, fault tolerance and high availability. This talk will cover: an
architecture deep dive of multi tenant Redis on the cloud, management of sentinels, monitoring and operations of a large
scale Redis deployment,introducing new Redis versions,scaling, security, some lessons learnt. The target audience for this
talk is anyone who is interested in the deployment/operational aspect of running Redis. This is relevant not only for those
who want to run Redis themselves, but also interested in how a Redis provider might be doing it for them.
Ceph: Open Source Storage Software Optimizations on Intel® Architecture for C...Odinot Stanislas
Après la petite intro sur le stockage distribué et la description de Ceph, Jian Zhang réalise dans cette présentation quelques benchmarks intéressants : tests séquentiels, tests random et surtout comparaison des résultats avant et après optimisations. Les paramètres de configuration touchés et optimisations (Large page numbers, Omap data sur un disque séparé, ...) apportent au minimum 2x de perf en plus.
Virtual training Intro to the Tick stack and InfluxEnterpriseInfluxData
In this webinar, we will provide an introduction to the components of the TICK Stack and a review the features of InfluxEnterprise and InfluxCloud. We also demo how to install the TICK stack.
How we got to 1 millisecond latency in 99% under repair, compaction, and flus...ScyllaDB
Scylla is an open source reimplementation of Cassandra which performs up to 10X with drop in-replacement compatibility. At ScyllaDB, performance matters but even more importantly, stable performance under any circumstances.
A key factor for our consistent performance is our reliance on userspace schedulers. Scheduling in userspace allows the application, the database in our case to have better control on the different priorities each task has and to provide an SLA to selected operations. Scylla used to have an I/O scheduler and recently won a CPU scheduler.
At ScyllaDB, we make architectural decisions that provide not only low latencies but consistently low latencies at higher percentiles. This begins with our choice of language and key architectural decisions such as not using the Linux page-cache, and is fulfilled by autonomous database control, a set of algorithms, which guarantees that the system will adapt to changes in the workload. In the last year, we have made changes to Scylla that provide latencies that are consistent in every percentile. In this talk, Dor Laor will recap those changes and discuss what ScyllaDB is doing in the future.
Dynomite: A Highly Available, Distributed and Scalable Dynamo Layer--Ioannis ...Redis Labs
Dynomite is a
thin, distributed dynamo layer for different storage engines and protocols. Currently at Netflix, we are focusing on using
Redis as the storage engine. Dynomite supports multi-datacenter replication and is designed for high availability. In the age of high scalability and big data, Dynomite’s design goal is to turn single-server datastore solutions into peer-to-peer, linearly
scalable, clustered systems while still preserving the native client/server protocols of the datastores, e.g., Redis protocol. In this talk, we are going to present Dynomite recent features, and the Dyno client. Both projects are open source and available to the community.
Perforce BTrees: The Arcane and the ProfanePerforce
"Get a tour of Perforce BTree history, its behaviors and configuration. Learn about performance alternatives, space management tools and future projects, too."
Redis Developers Day 2014 - Redis Labs TalksRedis Labs
These are the slides that the Redis Labs team had used to accompany the session that we gave during the first ever Redis Developers Day on October 2nd, 2014, London. It includes some of the ideas we've come up with to tackle operational challenges in the hyper-dense, multi-tenants Redis deployments that our service - Redis Cloud - consists of.
HIgh Performance Redis- Tague Griffith, GoProRedis Labs
High Performance Redis looks at a wide range of techniques - from programming to system tuning - to deploy and maintain an extremely high performing Redis cluster. From the operational
perspective, the talk lays out multiple techniques for clustering (sharding) Redis systems and examines how the different
approaches impact performance time. The talk further examines system settings (Linux network parameters, Redis
system) and how they impact performance (both good and bad). Finally, for the developer, we look at how different ways of structuring data actually demonstrate different performance characteristics
Aerospike AdTech Gets Hacked in Lower ManhattanAerospike
Aerospike's highly reliable and scalable database, using NoSQL and In-memory technology, presentation slides given at Stack Exchange on April 10th with NSOne and advertising technology luminaries.
AdTech Gets Hacked in Lower Manhattan
Stack Exchange, 110 William St 28th Floor,
New York, NY 10038
Have you heard that all in-memory databases are equally fast but unreliable, inconsistent and expensive? This session highlights in-memory technology that busts all those myths.
Redis, the fastest database on the planet, is not a simply in-memory key-value data-store; but rather a rich in-memory data-structure engine that serves the world’s most popular apps. Redis Labs’ unique clustering technology enables Redis to be highly reliable, keeping every data byte intact despite hundreds of cloud instance failures and dozens of complete data-center outages. It delivers full CP system characteristics at high performance. And with the latest Redis on Flash technology, Redis Labs achieves close to in-memory performance at 70% lower operational costs. Learn about the best uses of in-memory computing to accelerate everyday applications such as high volume transactions, real time analytics, IoT data ingestion and more.
Building Hopsworks, a cloud-native managed feature store for machine learning Jim Dowling
Cloud Native London talk about the control layer of Hopsworks.ai and our choice of cloud native services. We built our own multi-tenant services as cloud native services, for the most part.
MySQL NDB Cluster 8.0 SQL faster than NoSQL Bernd Ocklin
MySQL NDB Cluster running SQL faster than most NoSQL databases. Benchmark results, comparisons and introduction into NDB's parallel distributed in-memory query engine. MySQL Day before FOSDEM 2020.
MongoDB has taken a clear lead in adoption among the new generation of databases, including the enormous variety of NoSQL offerings. A key reason for this lead has been a unique combination of agility and scalability. Agility provides business units with a quick start and flexibility to maintain development velocity, despite changing data and requirements. Scalability maintains that flexibility while providing fast, interactive performance as data volume and usage increase. We'll address the key organizational, operational, and engineering considerations to ensure that agility and scalability stay aligned at increasing scale, from small development instances to web-scale applications. We will also survey some key examples of highly-scaled customer applications of MongoDB.
SF Big Analytics & SF Machine Learning Meetup: Machine Learning at the Limit ...Chester Chen
Machine Learning at the Limit
John Canny, UC Berkeley
How fast can machine learning and graph algorithms be? In "roofline" design, every kernel is driven toward the limits imposed by CPU, memory, network etc. This can lead to dramatic improvements: BIDMach is a toolkit for machine learning that uses rooflined design and GPUs to achieve two- to three-orders of magnitude improvements over other toolkits on single machines. These speedups are larger than have been reported for *cluster* systems (e.g. Spark/MLLib, Powergraph) running on hundreds of nodes, and BIDMach with a GPU outperforms these systems for most common machine learning tasks. For algorithms (e.g. graph algorithms) which do require cluster computing, we have developed a rooflined network primitive called "Kylix". We can show that Kylix approaches the rooline limits for sparse Allreduce, and empirically holds the record for distributed Pagerank. Beyond rooflining, we believe there are great opportunities from deep algorithm/hardware codesign. Gibbs Sampling (GS) is a very general tool for inference, but is typically much slower than alternatives. SAME (State Augmentation for Marginal Estimation) is a variation of GS which was developed for marginal parameter estimation. We show that it has high parallelism, and a fast GPU implementation. Using SAME, we developed a GS implementation of Latent Dirichlet Allocation whose running time is 100x faster than other samplers, and within 3x of the fastest symbolic methods. We are extending this approach to general graphical models, an area where there is currently a void of (practically) fast tools. It seems at least plausible that a general-purpose solution based on these techniques can closely approach the performance of custom algorithms.
Bio
John Canny is a professor in computer science at UC Berkeley. He is an ACM dissertation award winner and a Packard Fellow. He is currently a Data Science Senior Fellow in Berkeley's new Institute for Data Science and holds a INRIA (France) International Chair. Since 2002, he has been developing and deploying large-scale behavioral modeling systems. He designed and protyped production systems for Overstock.com, Yahoo, Ebay, Quantcast and Microsoft. He currently works on several applications of data mining for human learning (MOOCs and early language learning), health and well-being, and applications in the sciences.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all of your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing, scale-out architecture, and columnar direct-attached storage to minimize I/O time and maximize performance. Learn how you can gain deeper business insights and save money and time by migrating to Amazon Redshift. Take away strategies for migrating from on-premises data warehousing solutions, tuning schema and queries, and utilizing third party solutions.
Those who out-compute can many times out-compete. The cloud gives you access to a massive amount of compute power when you need it. This talk will present an introduction to HPC in the cloud, including, the benefits of HPC in the cloud, how to get started, some tools to use, and how you can manage data. We will showcase several examples of HPC in the cloud by a number of public sector and commercial customers.
Created by: Dr. Jeff Layton, Principal, Solutions Architect
AWS provides a wide set of services to manage your data, which allow our customers to choose the right tool to the right workload. Learn how to make your databases up to 10x faster and less expensive with Amazon ElastiCache for Redis and utilize DynamoDB Accelerator (DAX) to access your data on DynamoDB faster with no additional development efforts. If you need fast access to your data, these services might be the right services for your workload.
Apache Spark AI Use Case in Telco: Network Quality Analysis and Prediction wi...Databricks
In this talk, we will present how we analyze, predict, and visualize network quality data, as a spark AI use case in a telecommunications company. SK Telecom is the largest wireless telecommunications provider in South Korea with 300,000 cells and 27 million subscribers. These 300,000 cells generate data every 10 seconds, the total size of which is 60TB, 120 billion records per day.
In order to address previous problems of Spark based on HDFS, we have developed a new data store for SparkSQL consisting of Redis and RocksDB that allows us to distribute and store these data in real time and analyze it right away, We were not satisfied with being able to analyze network quality in real-time, we tried to predict network quality in near future in order to quickly detect and recover network device failures, by designing network signal pattern-aware DNN model and a new in-memory data pipeline from spark to tensorflow.
In addition, by integrating Apache Livy and MapboxGL to SparkSQL and our new store, we have built a geospatial visualization system that shows the current population and signal strength of 300,000 cells on the map in real time.
Slides from the High Performance Cloud Computing tutorial at Supercomputing 2011 in Seattle. Additional materials available from: cloudsupercomputing.net.
ElastiCache Deep Dive: Best Practices and Usage Patterns - March 2017 AWS Onl...Amazon Web Services
Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory data stores, instead of relying entirely on slower disk-based databases. In this tech talk, we’ll provide a peek behind the scenes to learn about Amazon ElastiCache's design and architecture. You’ll see common design patterns with our Redis and Memcached offerings and how customers have used them for in-memory operations to reduce latency and improve application throughput. During this session, we review ElastiCache best practices, design patterns, and anti-patterns.
Learning Objectives:
- Learn how to integrate Amazon ElastiCache in your workloads
- Understand the benefits of an In-Memory data store
- Learn how to apply various caching strategies in your applications
- Hands on demonstration using Amazon ElastiCache
Amazon Elasticache Deep Dive - March 2017 AWS Online Tech TalksAmazon Web Services
Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory data stores, instead of relying entirely on slower disk-based databases. In this tech talk, we’ll provide a peek behind the scenes to learn about Amazon ElastiCache's design and architecture. You’ll see common design patterns with our Redis and Memcached offerings and how customers have used them for in-memory operations to reduce latency and improve application throughput. During this session, we review ElastiCache best practices, design patterns, and anti-patterns.
Learning Objectives:
- Learn how to integrate Amazon ElastiCache in your workloads
- Understand the benefits of an In-Memory data store
- Learn how to apply various caching strategies in your applications
- Hands on demonstration using Amazon ElastiCache
High performance Redis is popular among developers for its incredible performance, versatility and simplicity. The powerful combination of low cost memory and high performance Redis brings to life new next generation analytic uses - such as simultaneous real time transaction and analytics processing. With Redis Labs' RLEC Flash on AWS SSD instances, you can get fantastic performance at up to 70% lower costs. Join this session to learn how next generation Flash from leading memory provider Intel has made significant strides in performance while retaining its cost advantage to memory. Using a combination of AWS' powerful SSD instances, and Redis Labs' RLEC Flash, you can achieve up to 3M ops/sec at sub millisecond latencies, with a combination of RAM and Flash. The session will also feature customer use cases from a large university, a large customer engagement company and a pioneer of online Flash sales. Session sponsored by Redis Labs.
Similar to RedisConf17 - Doing More With Redis - Ofer Bengal and Yiftach Shoolman (20)
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
8. Flash Memory - What Has Changed During Last Year
New NVMe based local SSD that can be attached to a Cloud Instance
9. Flash Memory - What Has Changed During Last Year
New NVMe based local SSD that can be attached to a Cloud Instance
New NVMe based SSD I3 Instances
10. I3 (NVMe) are x2.6 Faster and 80% Cheaper than I2 (SATA)
Single node @ <1msec latency
11. Flash Memory - What Has Changed During Last Year
New NVMe based local SSD that can be attached to a Cloud Instance
New NVMe based SSD I3 Instances
New Flash-GT card with multiple NVMes integrated
12. Flash Memory - What Has Changed During Last Year
New NVMe based local SSD that can be attached to a Cloud Instance
New NVMe based SSD I3 Instances
New Flash-GT card with multiple NVMes integrated
New 3D XPoint chipset on NVME Devices
13. Redise Flash + Intel® Optane™ SSD
2040
1380
590
728
142
64
0
500
1000
1500
2000
2500
95% 85% 50%
KOps/sec
RAM hit ratio
item size = 1000B; read/write = 50%/50%
Optane
P3700
Up to x9
Similar to what runs on:
34. Real World Example
• Ads serving company
• Need to serve 20,000 ads/sec @ 50msec data-center latency
• Runs 1k campaigns
35. Real World Example
• Runs 1k campaigns 1K random forest
• Each forest has 15K trees
• On average each tree has 7 levels (depth)
20K x 1K x 15K x 3.5 = 1.05 trillion ops/sec
36. Challenge #2 - Accurate Models are Expensive to Serve!
Item Calculation Total
Max ops/sec on the
strongest AWS
instance vcore
2.6Ghz x
0.9 (OS overhead) x
0.1 (10 lines of code per ops) x
0.1 (Java overhead)
23.4 million
# of vcores needed 1.05 trillion / 23.4 million 44,872
# of c4.8xlarge
instances needed
44,872 / 36 1,247
Total cost
reserved instances
1,247 x 9213 ~$11.5M/yr
37. Ads Serving Use-Case w/ and w/o Redise + ML
Homegrown
1,247 x c4.8xlarge 35 x c4.8xlarge
Cut computing infrastructure by
97%
38. How ML/DL Should be Severed
(1) Training (2) Creating a model (3) Serving the model
48. The Feature List is Long
1. Full-Text indexing of multiple fields in documents
2. Incremental indexing without performance loss
3. Document ranking (provided manually by the user at
index time)
4. Complex Boolean queries with AND, OR, NOT operators
between sub-queries
5. Optional query clauses
6. Prefix based searches
7. Field weights
8. Auto-complete suggestions (with fuzzy prefix
suggestions)
9. Exact Phrase Search, Slop based search
10. Stemming based query expansion in many
languages (using Snowball)
11. Support for custom functions for query expansion
and scoring (see Extensions)
12. Limiting searches to specific document fields (up
to 8 fields supported)
13. Numeric filters and ranges
14. Geo filtering using Redis' own Geo-commands
15. Supports any utf-8 encoded text
16. Retrieve full document content or just ids
17. Automatically index existing HASH keys as
documents
18. Document deletion and updating with index garbage
collection.
77. Challenge #2 – Conflict Resolution for Complex Data-Types
• Application level solution too complex to write
• LWW (Last Write Wins) doesn’t work for many of the Redis use cases, e.g.:
• Counters
• Sets
• Sorted Sets
• Lists
• Modules’ new datatypes
79. CRDT
• Years of academic research
• Based on consensus free protocol
• Strong eventual consistency
• Built to resolve conflicts with complex data types
82. Solving Conflicts – Counters
Replica A:
C = 500
Replica B:
C = 500
Replica C:
C = 500
83. Solving Conflicts – Counters
Replica A:
C = 500
INCRBY 200
Replica B:
C = 500
Replica C:
C = 500
84. Solving Conflicts – Counters
Replica A:
C = 500
INCRBY 200
Replica B:
C = 500
DECRBY 300
Replica C:
C = 500
85. Solving Conflicts – Counters
Replica A:
C = 500
INCRBY 200
Replica B:
C = 500
DECRBY 300
Replica C:
C = 500
INCRBY 1000
86. Solving Conflicts – Counters
Replica A:
C = 500
INCRBY 200
Replica B:
C = 500
DECRBY 300
Replica C:
C = 500
INCRBY 1000
Convergence Function (commutative):
500 + ΣC(i) =
= 500 +200 -300 +1000
= 1400
87. Solving Conflicts – Sets
Replica A:
S = {A, B, C}
Replica B:
S = {A, B, C}
Replica C:
S = {A, B, C}
88. Solving Conflicts – Sets
Replica A:
S = {A, B, C}
SADD D
Replica B:
S = {A, B, C}
Replica C:
S = {A, B, C}
89. Solving Conflicts – Sets
Replica A:
S = {A, B, C}
SADD D
Replica B:
S = {A, B, C}
SADD A
Replica C:
S = {A, B, C}
90. Solving Conflicts – Sets
Replica A:
S = {A, B, C}
SADD D
Replica B:
S = {A, B, C}
SADD A
Replica C:
S = {A, B, C}
SREM A
91. Solving Conflicts – Sets
Replica A:
S = {A, B, C}
SADD D
Replica B:
S = {A, B, C}
SADD A
Replica C:
S = {A, B, C}
SREM A
Convergence Function (associative):
• S = S + D + A - A =
{A, B, C, D}
• Observed Removed + Add wins
92. Solving Conflicts – Sorted Sets
Replica A:
SS =
{A:35, B:23, C:4}
Replica B:
SS =
{A:35, B:23, C:4}
Replica C:
SS =
{A:35, B:23, C:4}
93. Solving Conflicts – Sorted Sets
Replica A:
SS =
{A:35, B:23, C:4}
Replica B:
SS =
{A:35, B:23, C:4}
Replica C:
SS =
{A:35, B:23, C:4}
Convergence Function
(associative & commutative):
Counters + Sets
97. What’s Unique About Redis-CRDT
• Based on a Redis module (CRDB)
• Support bi-direction replication
• Multiple topologies
• Solves a new set of problems
• Counters deletion
• Expiry
• Cluster configuration
• Etc.
RingFully-Connected
98. A Deep Dive on Multi-Master:
Salon 8 @ 3:15 pm