This is a talk that I gave at Stanford's EE203 (Entrepreneurial Engineer) on Tuesday Feb 9th, 2010. It covers my experience at Stanford, VivaSmart, Yahoo, Accel Partners, and Cloudera.
I was meaning to put this talk up for grabs for some time now, but kept forgetting. I was invited to give the keynote speech for the Microstrategy World 2008 conference. The talk was very well received, so here it is.
Introduction to Big data with Hadoop & Spark | Big Data Hadoop Spark Tutorial...CloudxLab
(Big Data with Hadoop & Spark Training: http://bit.ly/2k2wiL9
This CloudxLab Big Data with Hadoop and Spark tutorial helps you to understand Big Data in detail. Below are the topics covered in this tutorial:
1) Data Variety
2) What is Big Data?
3) Characteristics of Big Data - Volume, Velocity, and Variety
4) Why Big Data and why it is important now?
5) Example Big Data Customers
6) Big Data Solutions
7) What is Hadoop?
8) Hadoop Components
9) Apache Spark Introduction & Architecture
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Creating a Data Science Team from an Architect's perspective. This is about team building on how to support a data science team with the right staff, including data engineers and devops.
Learn Big data and Hadoop online at Easylearning Guru. We are offer Instructor led online training and Life Time LMS (Learning Management System). Join Our Free Live Demo Classes of Big Data Hadoop .
I was meaning to put this talk up for grabs for some time now, but kept forgetting. I was invited to give the keynote speech for the Microstrategy World 2008 conference. The talk was very well received, so here it is.
Introduction to Big data with Hadoop & Spark | Big Data Hadoop Spark Tutorial...CloudxLab
(Big Data with Hadoop & Spark Training: http://bit.ly/2k2wiL9
This CloudxLab Big Data with Hadoop and Spark tutorial helps you to understand Big Data in detail. Below are the topics covered in this tutorial:
1) Data Variety
2) What is Big Data?
3) Characteristics of Big Data - Volume, Velocity, and Variety
4) Why Big Data and why it is important now?
5) Example Big Data Customers
6) Big Data Solutions
7) What is Hadoop?
8) Hadoop Components
9) Apache Spark Introduction & Architecture
Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, Map-Reduce,PIG, HIVE, HBase, Zookeeper, SQOOP etc. will be covered in the course.
Creating a Data Science Team from an Architect's perspective. This is about team building on how to support a data science team with the right staff, including data engineers and devops.
Learn Big data and Hadoop online at Easylearning Guru. We are offer Instructor led online training and Life Time LMS (Learning Management System). Join Our Free Live Demo Classes of Big Data Hadoop .
Big Data with Hadoop and HDInsight. This is an intro to the technology. If you are new to BigData or just heard of it. This presentation help you to know just little bit more about the technology.
Apache Hadoop Tutorial | Hadoop Tutorial For Beginners | Big Data Hadoop | Ha...Edureka!
This Edureka "Hadoop tutorial For Beginners" ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand the problem with traditional system while processing Big Data and how Hadoop solves it. This tutorial will provide you a comprehensive idea about HDFS and YARN along with their architecture that has been explained in a very simple manner using examples and practical demonstration. At the end, you will get to know how to analyze Olympic data set using Hadoop and gain useful insights.
Below are the topics covered in this tutorial:
1. Big Data Growth Drivers
2. What is Big Data?
3. Hadoop Introduction
4. Hadoop Master/Slave Architecture
5. Hadoop Core Components
6. HDFS Data Blocks
7. HDFS Read/Write Mechanism
8. What is MapReduce
9. MapReduce Program
10. MapReduce Job Workflow
11. Hadoop Ecosystem
12. Hadoop Use Case: Analyzing Olympic Dataset
Are you confused by Big Data? Get in touch with this new "black gold" and familiarize yourself with undiscovered insights through our complimentary introductory lesson on Big Data and Hadoop!
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
The talk presents the evolution of Big-Data systems from single-purpose MapReduce frameworks to fully general computational infrastructures. In particular, I will follow the evolution of Hadoop, and show the benefits and challenges of a new architectural paradigm that decouples the resource management component (YARN) from the specifics of the application frameworks (e.g., MapReduce, Tez, REEF, Giraph, Naiad, Dryad, Spark,...). We argue that beside the primary goals of increasing scalability and programming model flexibility, this transformation dramatically facilitates innovation.
In this context, I will present some of our contributions to the evolution of Hadoop (namely: work-preserving preemption, and predictable resource allocation), and comment on the fascinating experience of working on open- source technologies from within Microsoft. The current Hadoop APIs (HDFS and YARN) provide the cluster equivalent of an OS API. With this as a backdrop, I will present our attempt to create the equivalent of stdlib for the cluster: the REEF project.
Carlo A. Curino received a PhD from Politecnico di Milano, and spent two years as Post Doc Associate at CSAIL MIT leading the relational cloud project. He worked at Yahoo! Research as Research Scientist focusing on mobile/cloud platforms and entity deduplication at scale. Carlo is currently a Senior Scientist at Microsoft in the Cloud and Information Services Lab (CISL) where he is working on big-data platforms and cloud computing.
Hadoop Tutorial | What is Hadoop | Hadoop Project on Reddit | EdurekaEdureka!
This Edureka Hadoop Tutorial ( Hadoop Tutorial Blog Series: https://goo.gl/zndT2V ) helps you understand Big Data and Hadoop in detail. This Hadoop Tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Hadoop concepts.
This Edureka Hadoop Tutorial provides knowledge on:
1) What are the driving factors of Big Data and what are its challenges?
2) How Hadoop solves Big Data storage and processing challenges with Facebook use-case?
3) The overview of Hadoop YARN Architecture and its Components.
4) A real-life implementation of a complete end to end Hadoop Project on a Reddit use case on a Hadoop Cluster.
Check our complete Hadoop playlist here: https://goo.gl/ExJdZs
Hadoop Training For Beginners | Hadoop Tutorial | Big Data Training |EdurekaEdureka!
This Edureka Hadoop Training tutorial ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand how Big Data emerged as a problem and how Hadoop solved that problem. This tutorial will be discussing about Hadoop Architecture, HDFS & it's architecture, YARN and MapReduce with a practical Aadhar use-case. Below are the topics covered in this tutorial:
1) What is Big Data?
2) Big Data in Different Domains
3) Problems Associated with Big Data
4) What is Hadoop?
5) HDFS
6) YARN
7) MapReduce
8) Hadoop Ecosystem
9) Aadhar Use-case
10) Edureka Big Data & Hadoop Training
Apache Hadoop is quickly becoming the technology of choice for organizations investing in big data, powering their next generation data architecture. With Hadoop serving as both a scalable data platform and computational engine, data science is re-emerging as a center-piece of enterprise innovation, with applied data solutions such as online product recommendation, automated fraud detection and customer sentiment analysis. In this talk Ofer will provide an overview of data science and how to take advantage of Hadoop for large scale data science projects: * What is data science? * How can techniques like classification, regression, clustering and outlier detection help your organization? * What questions do you ask and which problems do you go after? * How do you instrument and prepare your organization for applied data science with Hadoop? * Who do you hire to solve these problems? You will learn how to plan, design and implement a data science project with Hadoop
What is Hadoop brief intro for Georgian Partners CTO Conference. This outlines the origins of Open Source Apache Hadoop and how Hortonworks fits into this picture. There is also a brief introduction to YARN, the new resource negotiation layer.
This is the first time I introduced the concept of Schema-on-Read vs Schema-on-Write to the public. It was at Berkeley EECS RAD Lab retreat Open Mic Session on May 28th, 2009 at Santa Cruz, California.
Big Data with Hadoop and HDInsight. This is an intro to the technology. If you are new to BigData or just heard of it. This presentation help you to know just little bit more about the technology.
Apache Hadoop Tutorial | Hadoop Tutorial For Beginners | Big Data Hadoop | Ha...Edureka!
This Edureka "Hadoop tutorial For Beginners" ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand the problem with traditional system while processing Big Data and how Hadoop solves it. This tutorial will provide you a comprehensive idea about HDFS and YARN along with their architecture that has been explained in a very simple manner using examples and practical demonstration. At the end, you will get to know how to analyze Olympic data set using Hadoop and gain useful insights.
Below are the topics covered in this tutorial:
1. Big Data Growth Drivers
2. What is Big Data?
3. Hadoop Introduction
4. Hadoop Master/Slave Architecture
5. Hadoop Core Components
6. HDFS Data Blocks
7. HDFS Read/Write Mechanism
8. What is MapReduce
9. MapReduce Program
10. MapReduce Job Workflow
11. Hadoop Ecosystem
12. Hadoop Use Case: Analyzing Olympic Dataset
Are you confused by Big Data? Get in touch with this new "black gold" and familiarize yourself with undiscovered insights through our complimentary introductory lesson on Big Data and Hadoop!
Hadoop is an open source software framework that supports data-intensive distributed applications. Hadoop is licensed under the Apache v2 license. It is therefore generally known as Apache Hadoop. Hadoop has been developed, based on a paper originally written by Google on MapReduce system and applies concepts of functional programming. Hadoop is written in the Java programming language and is the highest-level Apache project being constructed and used by a global community of contributors. Hadoop was developed by Doug Cutting and Michael J. Cafarella. And just don't overlook the charming yellow elephant you see, which is basically named after Doug's son's toy elephant!
The topics covered in presentation are:
1. Big Data Learning Path
2.Big Data Introduction
3. Hadoop and its Eco-system
4.Hadoop Architecture
5.Next Step on how to setup Hadoop
The talk presents the evolution of Big-Data systems from single-purpose MapReduce frameworks to fully general computational infrastructures. In particular, I will follow the evolution of Hadoop, and show the benefits and challenges of a new architectural paradigm that decouples the resource management component (YARN) from the specifics of the application frameworks (e.g., MapReduce, Tez, REEF, Giraph, Naiad, Dryad, Spark,...). We argue that beside the primary goals of increasing scalability and programming model flexibility, this transformation dramatically facilitates innovation.
In this context, I will present some of our contributions to the evolution of Hadoop (namely: work-preserving preemption, and predictable resource allocation), and comment on the fascinating experience of working on open- source technologies from within Microsoft. The current Hadoop APIs (HDFS and YARN) provide the cluster equivalent of an OS API. With this as a backdrop, I will present our attempt to create the equivalent of stdlib for the cluster: the REEF project.
Carlo A. Curino received a PhD from Politecnico di Milano, and spent two years as Post Doc Associate at CSAIL MIT leading the relational cloud project. He worked at Yahoo! Research as Research Scientist focusing on mobile/cloud platforms and entity deduplication at scale. Carlo is currently a Senior Scientist at Microsoft in the Cloud and Information Services Lab (CISL) where he is working on big-data platforms and cloud computing.
Hadoop Tutorial | What is Hadoop | Hadoop Project on Reddit | EdurekaEdureka!
This Edureka Hadoop Tutorial ( Hadoop Tutorial Blog Series: https://goo.gl/zndT2V ) helps you understand Big Data and Hadoop in detail. This Hadoop Tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Hadoop concepts.
This Edureka Hadoop Tutorial provides knowledge on:
1) What are the driving factors of Big Data and what are its challenges?
2) How Hadoop solves Big Data storage and processing challenges with Facebook use-case?
3) The overview of Hadoop YARN Architecture and its Components.
4) A real-life implementation of a complete end to end Hadoop Project on a Reddit use case on a Hadoop Cluster.
Check our complete Hadoop playlist here: https://goo.gl/ExJdZs
Hadoop Training For Beginners | Hadoop Tutorial | Big Data Training |EdurekaEdureka!
This Edureka Hadoop Training tutorial ( Hadoop Blog series: https://goo.gl/LFesy8 ) will help you to understand how Big Data emerged as a problem and how Hadoop solved that problem. This tutorial will be discussing about Hadoop Architecture, HDFS & it's architecture, YARN and MapReduce with a practical Aadhar use-case. Below are the topics covered in this tutorial:
1) What is Big Data?
2) Big Data in Different Domains
3) Problems Associated with Big Data
4) What is Hadoop?
5) HDFS
6) YARN
7) MapReduce
8) Hadoop Ecosystem
9) Aadhar Use-case
10) Edureka Big Data & Hadoop Training
Apache Hadoop is quickly becoming the technology of choice for organizations investing in big data, powering their next generation data architecture. With Hadoop serving as both a scalable data platform and computational engine, data science is re-emerging as a center-piece of enterprise innovation, with applied data solutions such as online product recommendation, automated fraud detection and customer sentiment analysis. In this talk Ofer will provide an overview of data science and how to take advantage of Hadoop for large scale data science projects: * What is data science? * How can techniques like classification, regression, clustering and outlier detection help your organization? * What questions do you ask and which problems do you go after? * How do you instrument and prepare your organization for applied data science with Hadoop? * Who do you hire to solve these problems? You will learn how to plan, design and implement a data science project with Hadoop
What is Hadoop brief intro for Georgian Partners CTO Conference. This outlines the origins of Open Source Apache Hadoop and how Hortonworks fits into this picture. There is also a brief introduction to YARN, the new resource negotiation layer.
This is the first time I introduced the concept of Schema-on-Read vs Schema-on-Write to the public. It was at Berkeley EECS RAD Lab retreat Open Mic Session on May 28th, 2009 at Santa Cruz, California.
Service Primitives for Internet Scale ApplicationsAmr Awadallah
A general framework to describe internet scale applications and characterize the functional properties that can be traded away to improve the following operational metrics:
* Throughput (how many user requests/sec?)
* Interactivity (latency, how fast user requests finish?)
* Availability (% of time user perceives service as up), including fast recovery to improve availability
* TCO (Total Cost of Ownership)
Hadoop World 2011: How Hadoop Revolutionized Business Intelligence and Advanc...Cloudera, Inc.
"Amr Awadallah served as the VP of Engineering of Yahoo's Product
Intelligence Engineering (PIE) team for a number of years. The PIE
team was responsible for business intelligence and advanced data
analytics across a number of Yahoo's key consumer facing properties (search, mail, news, finance, sports, etc). Amr will share the data architecture that PIE had implementted before Hadoop was deployed and the headaches that architecture entailed. Amr will then show how most, if not all of these headaches were eliminated once Hadoop was deployed. Amr will illustrate how Hadoop and Relational Database complement each other within the traditional business intelligence data stack, and how that enables organizations to access all their data under different
operational and economic constraints."
ElasticES-Hadoop: Bridging the world of Hadoop and ElasticsearchMapR Technologies
In this talk, we will provide an overview of Elasticsearch for Apache Hadoop (ES-Hadoop), which includes integrations between the various Hadoop libraries, whether batch (Map/Reduce, Pig, Hive) or stream oriented (such as Apache Spark). We will also cover the YARN support and the HDFS snapshot/restore plugin available as part of ES-Hadoop. We will talk about the upcoming ES-Hadoop 2.1 GA release and near-term roadmap.
Real-time Puppies and Ponies - Evolving Indicator Recommendations in Real-timeTed Dunning
This talk describes how indicator-based recommendations can be evolved in real time. Normally, indicator-based recommendations use a large off-line computation to understand the general structure of items to be recommended and then make recommendations in real-time to users based on a comparison of their recent history versus the large-scale product of the off-line computation.
In this talk, I show how the same components of the off-line computation that guarantee linear scalability in a batch setting also give strict real-time bounds on the cost of a practical real-time implementation of the indicator computation.
In this Strata+Hadoop World 2015 presentation, Ron Bodkin, President of Think Big, a Teradata company, explains changes for data modeling on big data systems and five important new analytic patterns becoming more commonplace as companies grow their data driven capabilities.
Baptist Health: Solving Healthcare Problems with Big DataMapR Technologies
Editor’s Note: Download the complimentary MapR Guide to Big Data in Healthcare for more information: https://mapr.com/mapr-guide-big-data-healthcare/
There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics.
Join this webinar to hear how Baptist Health is using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer—through their consumer- centric approach.
MapR Technologies will cover broader big data healthcare trends and production use cases that demonstrate how to converge data and compute power to deliver data-driven healthcare applications.
Apache Drill is the next generation of SQL query engines. It builds on ANSI SQL 2003, and extends it to handle new formats like JSON, Parquet, ORC, and the usual CSV, TSV, XML and other Hadoop formats. Most importantly, it melts away the barriers that have caused databases to become silos of data. It does so by able to handle schema-changes on the fly, enabling a whole new world of self-service and data agility never seen before.
Big Data Hadoop Briefing Hosted by Cisco, WWT and MapR: MapR Overview Present...ervogler
Learn more about how MapR gives you the most technologically advanced distribution for Hadoop, with the product, services, and partner network to ensure production success and continued success.
Hadoop application architectures - using Customer 360 as an examplehadooparchbook
Hadoop application architectures - using Customer 360 (more generally, Entity 360) as an example. By Ted Malaska, Jonathan Seidman and Mark Grover at Strata + Hadoop World 2016 in NYC.
Introduction to Apache HBase, MapR Tables and SecurityMapR Technologies
This talk with focus on two key aspects of applications that are using the HBase APIs. The first part will provide a basic overview of how HBase works followed by an introduction to the HBase APIs with a simple example. The second part will extend what we've learned to secure the HBase application running on MapR's industry leading Hadoop.
Keys Botzum is a Senior Principal Technologist with MapR Technologies. He has over 15 years of experience in large scale distributed system design. At MapR his primary responsibility is working with customers as a consultant, but he also teaches classes, contributes to documentation, and works with MapR engineering. Previously he was a Senior Technical Staff Member with IBM and a respected author of many articles on WebSphere Application Server as well as a book. He holds a Masters degree in Computer Science from Stanford University and a B.S. in Applied Mathematics/Computer Science from Carnegie Mellon University.
Apache Drill: Building Highly Flexible, High Performance Query Engines by M.C...The Hive
SQL is one of the most widely used languages to access, analyze, and manipulate structured data. As Hadoop gains traction within enterprise data architectures across industries, the need for SQL for both structured and loosely-structured data on Hadoop is growing rapidly Apache Drill started off with the audacious goal of delivering consistent, millisecond ANSI SQL query capability across wide range of data formats. At a high level, this translates to two key requirements – Schema Flexibility and Performance. This session will delve into the architectural details in delivering these two requirements and will share with the audience the nuances and pitfalls we ran into while developing Apache Drill.
Convergence - Diverse Journeys to the Same Truthjack_maher
We are all pilgrims on a common journey with many shared paths on our way to improving our capabilities and helping our organizations create and deliver value.
Presented and discussed at Agile Cincinnati on June 11, 2020.
Open for Business: A Quick Guide to Starting Your Venture in the CloudKasey Bayne
The crew at Kashoo has put together this free guide to starting your new business in the cloud. From document store to project management (and yes, accounting too!), we recommend tools & tips for running your business in the cloud. Check it out and let us know what you think - answers@kashoo.com anytime!
Hear the views of Doubi Ajami on what Dell and Salesforce have in common. Also how the major acquisitions of both companies are allowing each to transform more quickly for the enterprise markets. Dany de Vleeschhauwer gave an overview of the 70 new projects delivered by ABSI over the year in CRM Salesforce, Private Cloud/Managed services and Datacenter Infrastructure.
Intelligence artificielle. Pourquoi et comment. Web à Québec 2017.Sylvain Carle
Pourquoi il y a tant de “buzz” autour de l’intelligence artificielle maintenant? Un peu de recul pour comprendre ce qui s’est passé dans les dernières années, l’état de la situation actuelle et un peu de perspective sur ce qui s’en vient (si mes intuitions sont bonnes). https://webaquebec.org/programmation/opportunites-et-defis-de-lintelligence-artificielle-pour-les-developpeurs
This is a small study on Google comany.It contains the history, products and the current position of Google...I hope that this will be helpful to others..
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
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/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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/
2. Outline About Me The VivaSmart Story The EIR Experience The Cloudera Story .. so far What is Hadoop? Open Source Business Models Lessons Learned & Advice
3. About Me I got BS and MS from Cairo University in Egypt. I came to US in 1995 to get my PhD from Stanford, with goal to go back to Egypt and teach. I got infected by the Entrepreneurship bug, it is rampant at Stanford, hopefully you’ll get infected too In 1999 I took a leave of absence from PhD to start VivaSmart, which I sold to Yahoo in 2000. I stayed with Yahoo till mid-2008, also finished my PhD in mid-2007 with Mendel Rosenblum. I started Cloudera in fall of 2008.
4. The VivaSmart Story It started as Booksmart in Spring of 1999. Initial prototype was built by Thai Tran. We got funded by a great angel (Frank Marshall). Couldn’t raise VC money, but we were able to raise more angel money, and got lighthouse customers. Noticed that it is hard to drive traffic, decided to focus on catalog management technology (Aptivia). Got initial acquisition termsheet from Excite@Home for $12M but they reneged at last minute (4/2000) Yahoo Shopping acquired us for $9M in June 2000.
5. The EIR Experience EIR = Entrepreneur in Residence. Joined Accel Partners in June 2008 as an EIR. Spent most of the summer researching possible ideas for my next venture, also helped with due diligence for a number of companies. Experienced the fund raising process from the VC side, very useful to see how they think. Met my Cloudera co-founders through Accel Andrew Braccia (agb) and Ping Li (pli) from Accel Partners joined the Cloudera Board of Directors.
6. The Cloudera Story … so far Oct 2008: Got $5M round A funding from Accel Partners and a number of strategic angel investors. Four founders (too many?): Mike Olson (Oracle) Jeff Hammerbacher (Facebook) Christophe Bisciglia (Google) AmrAwadallah (Yahoo) Announced the company in March of 2009. May 2009: Got $6M in funding from Greylock Ventures (opportunistic B round) AneelBhusri joined our board from Greylock
7. Cloudera’s Elevator Pitch A single,consolidated repository to enable insights across complex and structured data. Complex Data Documents Web feeds System logs Online forums SharePoint Sensor data EMB archives Photo/Video Structured Data (“relational”) CRM Financials Logistics Inventory Sales records HR records
8. What is Hadoop? The foundation of our system is built on top of Apache Hadoop, which is a scalable distributed data processing system. The scalability of Hadoop comes from marriage of: HDFS: Self-Healing High-Bandwidth Clustered Storage. MapReduce: Fault-Tolerant Distributed Processing. The software manages and heals it self. Leverages the economies of scale of commodity hardware (multi-core chips, many disks per system) Compute moves to data (not other way around).
9. Hadoop History 2002-2004: Doug Cutting and Mike Cafarella started working on Nutch 2003-2004: Google publishes GFS and MapReduce papers 2004: Cutting adds DFS & MapReduce support to Nutch 2006: Yahoo! hires Cutting, Hadoop spins out of Nutch 2007: NY Times converts 4TB of archives over 100 EC2s 2008: Web-scale deployments at Y!, Facebook, Last.fm April 2008: Yahoo does fastest sort of a TB, 3.5mins over 910 nodes May 2009: Yahoo does fastest sort of a TB, 62secs over 1460 nodes Yahoo sorts a PB in 16.25hours over 3658 nodes June 2009, Oct 2009: Hadoop Summit (750), Hadoop World (500) September 2009: Doug Cutting joins Cloudera
10. Open Source Software Business Models Open Source is attractive since it gets you: Free Distribution: People can download and try it out Darwinian Effect: Lots of developers try to solve the problem, best solution wins. Faster Innovation: Customers build the product with you! OSS Business Models: Support/Maintenance/Service agreements Open Core: core is free, but there is value-add proprietary technology around it (“Community” vs “Enterprise” Edition) Monetization through enablement of other services (e.g. Firefox makes money from Google Search).
11. Lessons Learned & Advice Make sure your idea can actually make money! Hire great people (corollary: Fire swiftly). Make sure you are passionate about your idea. Listen to customers, but look for the problems, it is your job to come up with solutions. Be agile, iterate quickly, don’t spend a year planning, don’t be afraid to make mistakes. Don’t be afraid to fail, but don’t persist in your failing ways, learn from failure quickly and evolve (Moore) Have faith, but don’t let it blind you from reality
12. Books I Recommend “Blue Ocean Strategy”, W. Chan Kim, Renée Mauborgne. “The Innovator’s Dilemma”, Clayton Christensen “The Innovator’s Solution”, Clayton Christensen, and Michael Raynor “Good to Great”, Jim Collins “The Seven Habits of Highly Effective People”, Stephen Covey “Crossing the Chasm”,“Tornado”, Geoffrey Moore “The Black Swan”, NassimTaleb.
13. Contact Information We Are Hiring: jobs+ee203@cloudera.com AmrAwadallah CTO, Cloudera Inc. http://twitter.com/awadallah Online Training Videos and Info: http://cloudera.com/hadoop-training http://cloudera.com/blog http://twitter.com/cloudera
Editor's Notes
http://developer.yahoo.net/blogs/hadoop/2009/05/hadoop_sorts_a_petabyte_in_162.html100s of deployments worldwide (http://wiki.apache.org/hadoop/PoweredBy)