Lambda Architecture with Cassandra (Vaibhav Puranik, GumGum) | C* Summit 2016

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Over the past year data at GumGum has quadrupled. Now a days we process 20 TB of new data every day. New data/reporting requirements pour in every week. Usage of the real time data is growing with the daily data. In this talk we are tying to answer the following questions: How do we serve real time data with daily batched data to our consumers together? What is Lambda Architecture and how does it help? What role does Cassandra play in Lambda Architecture at GumGum? How did we solve few bottlenecks in the architecture using Cassandra? How Cassandra can help you avoid microbatching and give you a true realtime data? About the Speaker Vaibhav Puranik VP of Engineering, Big Data & Platform, GumGum Vaibhav has 15 years of experience in Software. He began his career with Johnson Space Center in Houston and has a masters degree in computer science. For past 5 years Vaibhav has been responsible for architecting multiple big data systems at GumGum. He manages Data Science, Data Engineering and DevOps teams at GumGum.

Vaibhav Puranik
Lambda Architecture with Cassandra

About me

Invented In Image advertising in 2008
http://gumgum.com/gallery
Computer Vision
Processing 2.6B image impressions / month
10B events / day
2000 premium publishers
165 employees in 3 continents

Lambda
Architecture

Lambda Architecture

Architecture Before Cassandra
500 Ad Servers

Caps
Geo Filter
Keyword Filter
Cap Filter
Other Filters
Sort by revenue and pick one

Real Time Pipeline - The Problem
500 Ad Servers

The Problem
6 mins
roundtrip time

Enter Cassandra - Phase 1
500 Ad Servers
Cassandra: US East - 21 Nodes, US West: 18 Nodes, EU West:
12 Nodes - r3.2xlarge

Caps
Geo Filter
Other Filters
Cassandra Cap Filter
Old Cap Filter
Sort by revenue and pick one

The Solution
6 mins 10 ms

Enter Cassandra - Phase 2
500 Ad Servers
Cassandra: US East - 21 Nodes, US West: 18 Nodes, EU West:
12 Nodes - r3.2xlarge
Load data
every 8 mins
async way

Caps
Geo Filter
Other Filters
Cassandra Realtime
Cap Filter
Cassandra Batch
Data Filter
Sort by revenue and pick one

Scale
21 + 18 + 12 + 9 = 60 r3.2xlarge instances (Metadata)
9 + 6 + 3 = 18 r3.2xlarge instances (Tally)
400,000 records loaded every 8 mins by each Ad Server
20,000 read requests per second
10,000 write requests per second

Batch Layer
Realtime View
Batch Views
Lambda Architecture
Speed
Layer

gumgum.com/careers

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Handling 20 billion requests a month

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刘诚忠：Running cloudera impala on postgre sql

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GeeksLab Odessa

Cassandra at Finn.io — May 30th 2013

Cassandra at Finn.io — May 30th 2013

Cassandra at Finn.io — May 30th 2013

DataStax Academy

Lambda-less stream processing - linked in

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DataWorks Summit/Hadoop Summit

It is common for consumer Internet companies to start off with popular third-party tools for analytics needs. Then, when the user base and the company grows, they end up building their own analytics data pipeline and query engine to cope with their data scale, satisfy custom data enrichment and reporting needs and achieve high quality of their data. That’s exactly the path that was taken at Grammarly, the popular online proofreading service. In this session, Grammarly will share how they improved business and marketing analytics, previously done with Mixpanel, by building their own in-house analytics engine and application on top of Apache Spark. Chernetsov wil touch upon several Spark tweaks and gotchas that they experienced along the way: – Outputting data to several storages in a single Spark job – Dealing with Spark memory model, building a custom spillable data-structure for your data traversal – Implementing a custom query language with parser combinators on top of Spark sql parser – Custom query optimizer and analyzer when you want not exactly sql – Flexible-schema storage and query against multi-schema data with schema conflicts – Custom aggregation functions in Spark SQL

Building a Versatile Analytics Pipeline on Top of Apache Spark with Mikhail C...

Building a Versatile Analytics Pipeline on Top of Apache Spark with Mikhail C...

Building a Versatile Analytics Pipeline on Top of Apache Spark with Mikhail C...

(Diapositivas de presentación son en inglés.) Cada vez estamos produciendo un mayor volumen de datos, y los negocios necesitan del análisis de está información al segundo (o incluso al milisegundo). AWS proporciona tecnologías para resolver los problemas del Big Data, pero qué servicios debo usar, porqué, cuándo, cómo?. En esta sesión hablaremos de las diferentes fases en el análisis de los datos: ingesta, almacenamiento, procesamiento y visualización, y de como elegir la tecnología adecuada para cada una de ellas.

Big Data: Mejores prácticas en AWS

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Amazon Web Services

M|18 What's New in the MariaDB AX Platform

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Bank of China (HK) Tech Talk 1: Dive Into Apache Kafka

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Ian Ward, Platform and Security Engineer from Mapbox, discusses how the AWS global edge network helps improve the availability and performance of delivering hundreds of billions of map tiles to hundreds of millions of end users across the globe on mobile devices, in cars, and over the web. In this session, Ian shares insights on how Mapbox manages day-to-day edge operations using Amazon CloudFront logs, dashboards, and ad hoc queries, and how Mapbox has configured CloudFront with dozens of behaviors and origins to customize their content delivery. Mapbox has grown from using a single AWS region to using several regions, so Ian also explains how his team uses Amazon Route 53 and open source tools to simplify complexity around regional failover, and how Mapbox leverages AWS WAF to deter attacks and abuse.

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Amazon Web Services

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M|18 Real-time Analytics with the New Streaming Data Adapters

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Tweaking performance on high-load projects

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Amazon EC2 Spot instances provide acceleration, scale, and deep cost savings to run time-critical, hyper-scale workloads for rapid data analysis. In this session, AOL and Metamarkets will present lessons learned and best practices from scaling their big data workloads using popular platforms like Presto, Spark and Druid. AOL will present how they process, store, and analyze big data securely and cost effectively using Presto. AOL achieved 70% savings by separating compute and storage, dynamically resizing clusters based on volume and complexity, and using AWS Lambda to orchestrate processing pipelines. Metamarkets, an industry leader in interactive analytics, will present how they leverage Amazon EBS to persist 185 TiB of (compressed) state to run Druid historical nodes on EC2 Spot instances. They will also cover how they run Spark for batch jobs to process 1-4 PiB of data across 200 B to 1 T events/day, saving more than 60% in costs.

AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)

AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)

AWS re:Invent 2016: Disrupting Big Data with Cost-effective Compute (CMP302)

Amazon Web Services

Matei Zaharia is an assistant professor of computer science at Stanford University, Chief Technologist and Co-founder of Databricks. He started the Spark project at UC Berkeley and continues to serve as its vice president at Apache. Matei also co-started the Apache Mesos project and is a committer on Apache Hadoop. Matei’s research work on datacenter systems was recognized through two Best Paper awards and the 2014 ACM Doctoral Dissertation Award.

Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia

Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia

Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia

Inneractive - Spark meetup2

Inneractive - Spark meetup2

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Handling 20 billion requests a month

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AWS re:Invent 2016: How Mapbox Uses the AWS Edge to Deliver Fast Maps for Mob...

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Deep learning and streaming in Apache Spark 2.2 by Matei Zaharia

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Be a holiday hero—not a sorry statistic. View this on-demand webinar to learn how to drive revenue, business growth, customer satisfaction, and loyalty during the holiday season, and achieve operational excellence (and sanity!) at the same time. You’ll also hear real-world stories of companies that have experienced Black Friday nightmares—and learn how they turned things back around. View webinar: https://pages.datastax.com/20191003-NAM-Webinar-IsYourEnterpriseReadytoShinethisHolidaySeason_1-Registration-LP.html Explore all DataStax webinars: www.datastax.com/webinars

Is Your Enterprise Ready to Shine This Holiday Season?

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Data resiliency and availability are mission-critical for enterprises today—yet we live in a world where outages are an everyday occurrence. Whether the problem is a single server failure or losing connectivity to an entire data center, if your applications aren’t designed to be fault tolerant, recovery from an outage can be painful and slow. Watch this on-demand webinar to look at best practices for developing fault-tolerant applications with DataStax Drivers for Apache Cassandra and DataStax Enterprise (DSE). View recording: https://youtu.be/NT2-i3u5wo0 Explore all DataStax webinars: https://www.datastax.com/resources/webinars

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To simplify deploying and managing modern applications, enterprises have been combining the benefits of hyperconverged infrastructure (HCI) with the performance and scale of a NoSQL database — and the results have been remarkable. With this combination, IT organizations have experienced more agility, improved reliability, and better application performance. Watch this on-demand webinar where you’ll learn specifically how VMware HCI with DataStax Enterprise (DSE) and Apache Cassandra™ are transforming the enterprise. View recording: https://youtu.be/FCLGHMIB0L4 Explore all DataStax Webinars: https://www.datastax.com/resources/webinars

Running DataStax Enterprise in VMware Cloud and Hybrid Environments

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A distributed graph database is the most powerful means of discovering and leveraging the relationships in your data. With the right techniques combined with the right enterprise graph features, you can build modern applications at scale for real-time use-cases. But how exactly should you manage and model your data for a distributed graph database? And how can you leverage the relationships in that data? Watch this on-demand webinar as our graph expert answers those questions and shares tips and insights into creating production apps with distributed graph data. View recording: https://youtu.be/TSs_qPnhOas

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Best Practices for Getting to Production with DataStax Enterprise Graph

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Data management may be the hardest part of making the transition to the cloud, but enterprises including Intuit and Macy’s have figured out how to do it right. So what do they know that you might not? Join Robin Schumacher, Chief Product Officer at DataStax as he explores best practices for defining and implementing data management strategies for the cloud. He outlines a four-step journey that will take you from your first deployment in the cloud through to a true intercloud implementation and walk through a real-world use case where a major retailer has evolved through the four phases over a period of four years and is now benefiting from a highly resilient multi-cloud deployment. View webinar: https://youtu.be/RrTxQ2BAxjg

Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step Journey

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In this webinar, you will leverage free and open source tools as well as enterprise-grade utilities developed by DataStax to get a solid grasp on the performance of a masterless distributed database like Cassandra. You’ll also get the opportunity to walk through DataStax Enterprise Insights dashboards and see exactly how to identify performance bottlenecks. View Recording: https://youtu.be/McZg_MMzVjI

Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...

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In this webinar, you’ll also be introduced to DataStax Apache Kafka Connector, and get a brief demonstration of this groundbreaking technology. You’ll directly experience how this tool can help you stream data from Kafka topics into DataStax Enterprise versions of Cassandra. The future of your organization won’t wait. Register now to reserve your spot in this exciting new webinar. Youtube: https://youtu.be/HmkNb8twUNk

Webinar | Better Together: Apache Cassandra and Apache Kafka

Webinar | Better Together: Apache Cassandra and Apache Kafka

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No matter how diligent your organization is at driving toward efficiency, databases are complex and it’s easy to make mistakes on your way to production. The good news is, these mistakes are completely avoidable. In this webinar, Jeff Carpenter shares with you exactly how to get started in the right direction — and stay on the path to a successful database launch. View recording: https://youtu.be/K9Zj3bhjdQg Explore all DataStax webinars: https://www.datastax.com/resources/webinars

Top 10 Best Practices for Apache Cassandra and DataStax Enterprise

Top 10 Best Practices for Apache Cassandra and DataStax Enterprise

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Apache Cassandra has been a driving force for applications that scale for over 10 years. This open-source database now powers 30% of the Fortune 100.Now is your chance to get an inside look, guided by the company that’s responsible for 85% of the code commits.You won’t want to miss this deep dive into the database that has become the power behind the moment — the force behind game-changing, scalable cloud applications - Patrick McFadin, VP Developer Relations at DataStax, is going behind the Cassandra curtain in an exclusive webinar. View recording: https://youtu.be/z8fLn8GL5as Explore all DataStax webinars: https://www.datastax.com/resources/webinars

Introduction to Apache Cassandra™ + What’s New in 4.0

Introduction to Apache Cassandra™ + What’s New in 4.0

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In this webinar, we’ll discuss how an Active Everywhere database—a masterless architecture where multiple servers (or nodes) are grouped together in a cluster—provides a consistent data fabric between on-premises data centers and public clouds, enabling enterprises to effortlessly scale their hybrid cloud deployments and easily transition to the new hybrid cloud world, without changes to existing applications. View recording: https://youtu.be/ob6tr-9YiF4

Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...

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The European Union’s General Data Protection Regulation (GDPR) has sweeping effects on how enterprises manage their data. Without the right policies and safeguards in place, a tiny data mishap could end up turning into a catastrophic mistake. Join Datastax and our partner Thales eSecurity for a live webinar to learn how GDPR effects impact data management and the various ways enterprises can both comply and thrive in a hybrid cloud environment. View recording: https://youtu.be/QZ48_qkK9PU Explore all DataStax webinars: https://www.datastax.com/resources/webinars

Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud Realities

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Join Designing a Distributed Cloud Database for Dummies—the webinar. The webinar “stars” industry vet Patrick McFadin, best known among developers for his seven years at Apache Cassandra, where he held pivotal community roles. Register for the webinar today to learn: why you need distributed cloud databases, the technology you need to create the best used experience, the benefits of data autonomy and much more. View the recording: https://youtu.be/azC7lB0QU7E To explore all DataStax webinars: https://www.datastax.com/resources/webinars

Designing a Distributed Cloud Database for Dummies

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Most enterprises understand the value of hybrid cloud. In fact, your enterprise is already working in a multi-cloud or hybrid cloud environment, whether you know it or not. View this SlideShare to gain a greater understanding of the requirements of a geo-distributed cloud database in hybrid and multi-cloud environments. View recording: https://youtu.be/tHukS-p6lUI Explore all DataStax webinars: https://www.datastax.com/resources/webinars

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View these slides to discover the advantages of a distributed cloud database designed for hybrid cloud along with examples of how companies are delivering innovative and personalized ecommerce experiences. We'll discuss the sources of common data challenges and the hidden impact they have on business, the database requirements for improved customer experiences and innovative application delivery, and how leading organizations such as eBay, Sony, Macy’s, and Comcast are transforming the eCommerce experience with DataStax Enterprise 6. View recording: https://youtu.be/4UXrJ3xtmGg Explore all DataStax webinars: https://www.datastax.com/resources/webinars

How to Evaluate Cloud Databases for eCommerce

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Today’s customers want experiences that are contextual, always on, and above all — delightful. To be able to provide this, enterprises need a distributed, hybrid cloud-ready database that can easily crunch massive volumes of data from disparate sources while offering data autonomy and operational simplicity. Don’t miss this webinar, where you’ll learn how DataStax Enterprise 6 maintains hybrid cloud flexibility with all the benefits of a distributed cloud database, delivers all the advantages of Apache Cassandra with none of the complexities, doubles performance, and provides additional capabilities around robust transactional analytics, graph, search, and more. View recording: https://youtu.be/tuiWAt2jwBw Explore all DataStax webinars: https://www.datastax.com/resources/webinars

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Today’s Right-Now Economy means employees and customers alike expect applications to be always on, real time, and contextual. But how do you manage applications that collect data from a variety of sources, at cloud scale, and provide instant insights? And, can you embrace the public cloud while still retaining control of your data? Join us to hear from Microsoft Cloud Architect and Azure Global Black Belt Ron Abellera to learn how an enterprise-ready hybrid cloud data layer can help to accelerate time to market and scale linearly, ensure continuous availability, and achieve data autonomy with a hybrid cloud strategy. View webinar recording: https://youtu.be/_-GqmAk5C_I Explore all DataStax webinars: https://www.datastax.com/resources/webinars

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Welcome to the Right-Now Economy. To win in the Right-Now Economy, your enterprise needs to be able to provide delightful, always-on, instantaneously responsive applications via a data layer that can handle data rapidly, in real time, and at cloud scale. Don’t miss our upcoming webinar in which Forrester Principal Analyst Brendan Witcher will discuss why a singular, contextual, 360-degree view of the customer in real-time is critical to CX success and how companies are using data to deliver real-time personalization and recommendations. View recording: https://youtu.be/e6prezfIGMY Explore all DataStax webinars: https://www.datastax.com/resources/webinars

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Customer expectations are changing fast, while customer-related data is pouring in at an unprecedented rate and volume. Join this webinar, to hear leading experts from DataStax, discuss how DataStax Enterprise, the data management platform trusted by 9 out of the top 15 global banks, enables innovation and industry transformation. They’ll cover how the right data management platform can help break down data silos and modernize old systems of record as an operational data layer that scales to meet the distributed, real-time, always available demands of the enterprise. Register now to learn how the right data management platform allows you to power innovative banking applications, gain instant insight into comprehensive customer interactions, and beat fraud before it happens. Video: https://youtu.be/319NnKEKJzI Explore all DataStax webinars: https://www.datastax.com/resources/webinars

An Operational Data Layer is Critical for Transformative Banking Applications

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Customer expectations are changing fast, while customer-related data is pouring in at an unprecedented rate and volume. How can you contextualize and analyze all this customer data in real time to meet increasingly demanding customer expectations? Join Mike Rowland, Director and National Practice Leader for CX Strategy at West Monroe Partners, and Kartavya Jain, Product Marketing Manager at DataStax, for an in-depth conversation about how customer experience frameworks, driven by Design Thinking, can help enterprises: understand their customers and their needs, define their strategy for real-time CX, create value from contextual and instant insights.

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AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

VictorSzoltysek

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OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...

OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...

OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...

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ManageIQ - Sprint 236 Review - Slide Deck

ManageIQ - Sprint 236 Review - Slide Deck

ManageIQ - Sprint 236 Review - Slide Deck

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Conference: Engage2024 in Antwerp Type: Workshop Speakers: Florian Vogler, Henning Kunz, Christoph Adler Title: Navigating the Future with The Hitchhiker's Guide to Notes and Domino 14 Abstract: Embark on an exhilarating journey with industry trailblazers Florian Vogler, Henning Kunz, and Christoph Adler in this not-to-be-missed workshop at the forefront of the tech universe. Get ready for a thrilling kick-off as we navigate the current state of the HCL universe, setting the stage for an exploration of the groundbreaking Notes and Domino 14. Discover the latest enhancements and revolutionary features that will redefine your experience. In this interactive session, unlock a treasure trove of tips and tricks to elevate your utilization of version 14, both with and without the game-changing panagenda MarvelClient. Brace yourself for also diving into Nomad, Nomad Web, and VoltMX, expanding your horizons in the expansive HCL landscape. Be a part of this exclusive opportunity to stay ahead in the ever-evolving world of HCL technologies. Your journey to mastering Notes and Domino 14 begins here. And remember, in the spirit of intergalactic exploration, don't forget to bring your towel!

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

In an era where security concerns are paramount, the integration of artificial intelligence (AI) into CCTV cameras has revolutionized surveillance capabilities. One of the most significant advancements is the ability to achieve real-time threat detection, enabling immediate responses to potential security breaches. This blog explores how AI is reshaping surveillance through real-time threat detection and the implications of this technology.

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

Craft an AI & Machine Learning Pitch with our Editable Professional PowerPoint Template. Ignite your AI & Machine Learning pitch with our cutting-edge PowerPoint template tailored for the industry. Perfect for AI conferences, investor presentations, sales pitches to tech-focused companies, training sessions, and educational programs. - 20+ editable slides: Get a variety of options to choose from for your presentation. - Time-saving solution: Download, replace text/images with a few clicks. - User-friendly customization: Easy to use and personalize. - Modern and attractive design: Captivating visuals, sleek layout. - Tailored to your requirements: Fully alterable for customization. - Well-organized slides: Complete control over content. - Thematic specificity: Reflects healthcare industry with relevant graphics. - Showcase your business idea: Communicate value proposition effectively.

AI & Machine Learning Presentation Template

AI & Machine Learning Presentation Template

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Presentation.STUDIO

Define the academic and professional writing..pdf

Define the academic and professional writing..pdf

Define the academic and professional writing..pdf

PearlKirahMaeRagusta1

A great deal of attention in medical devices has shifted towards cybersecurity with the ratification of section 524B of the FD&C act. This new law enables the FDA to enforce cybersecurity controls in any medical device that is capable of networked communications or that has software. In this webinar we will recap the process for managing vulnerabilities, identify categories of vulnerabilities and solutions and more.

The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...

The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...

The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...

At the recent Microsoft Ignite 2023 conference, Microsoft unveiled a groundbreaking strategy that will redefine enterprise work management. The plan involves integrating Microsoft’s key planning tools, Microsoft To Do, Microsoft Planner, and Microsoft Project for the web into a unified experience called “Microsoft Planner.” What does this new strategy from Microsoft mean for current users? Join us and learn how best to take advantage of this announcement while gaining a clear path on how to elevate the current state of Microsoft Planner from a basic task manager to a comprehensive tool for Enterprise Work Management using OnePlan. Learn how OnePlan’s integration with Microsoft Planner allows for strategic alignment with business goals through advanced features like strategic planning, portfolio management, resource management, financial management, and more!

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

OnePlan Solutions

Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

MarTech Trend 2024 Book : Marketing Technology Trends (2024 Edition) How Data...

MarTech Trend 2024 Book : Marketing Technology Trends (2024 Edition) How Data...

MarTech Trend 2024 Book : Marketing Technology Trends (2024 Edition) How Data...

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Pharm-D Biostatistics and Research methodology

Pharm-D Biostatistics and Research methodology

Pharm-D Biostatistics and Research methodology

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AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

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Optimizing AI for immediate response in Smart CCTV

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Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

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Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

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MarTech Trend 2024 Book : Marketing Technology Trends (2024 Edition) How Data...

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Lambda Architecture with Cassandra (Vaibhav Puranik, GumGum) | C* Summit 2016

1. Vaibhav Puranik Lambda Architecture with Cassandra

3. Invented In Image advertising in 2008 http://gumgum.com/gallery Computer Vision Processing 2.6B image impressions / month 10B events / day 2000 premium publishers 165 employees in 3 continents

4.

5.

6. Lambda Architecture

7. Lambda Architecture

8. Architecture Before Cassandra 500 Ad Servers

9. Caps Geo Filter Keyword Filter Cap Filter Other Filters Sort by revenue and pick one

10. Real Time Pipeline - The Problem 500 Ad Servers

11. The Problem 6 mins roundtrip time

12. Enter Cassandra - Phase 1 500 Ad Servers Cassandra: US East - 21 Nodes, US West: 18 Nodes, EU West: 12 Nodes - r3.2xlarge

13. Caps Geo Filter Other Filters Cassandra Cap Filter Old Cap Filter Sort by revenue and pick one

14. The Solution 6 mins 10 ms

15. Enter Cassandra - Phase 2 500 Ad Servers Cassandra: US East - 21 Nodes, US West: 18 Nodes, EU West: 12 Nodes - r3.2xlarge Load data every 8 mins async way

16. Caps Geo Filter Other Filters Cassandra Realtime Cap Filter Cassandra Batch Data Filter Sort by revenue and pick one

17.

18.

19. Scale 21 + 18 + 12 + 9 = 60 r3.2xlarge instances (Metadata) 9 + 6 + 3 = 18 r3.2xlarge instances (Tally) 400,000 records loaded every 8 mins by each Ad Server 20,000 read requests per second 10,000 write requests per second

20. Batch Layer Realtime View Batch Views Lambda Architecture Speed Layer

21. gumgum.com/careers