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AWS LearnUp - Intro to AWS Services - Venturesity.
AWS LearnUp - Intro to AWS Services - Venturesity
AWS LearnUp - Intro to AWS Services - Venturesity
Dhilipsiva DS
Serverless applications are a really interesting new trend that promises benefits such as increased scalability and reduced cost. Frameworks like Serverless Application Model (SAM) and Serverless Framework are increasingly used to build them. APIs are a natural part of serverless applications, and in AWS that typically is implemented using the AWS API Gateway backed by Lambdas that implement the actual API endpoint logic. Our research focused on API Gateway Lambda Authorizers. This is a feature that allows developers to use a custom authentication and authorization scheme that uses a bearer token authentication strategy (like JWTs, OAuth or SAML), or that uses request parameters to determine the caller's identity and enforce which API endpoints they are allowed to access. We will present (AFAIK novel) techniques to attack the authentication and authorization of APIs that use Lambda Authorizers. We show how IAM policy injection is possible in theory but highly unlikely in practice due to some good decisions by AWS. We also show a class of problems based on incorrect security assumptions baked into AWS' own documentation and Lambda Authorizer open source code templates. Sample source code will be provided to demonstrate all techniques. Presented at DEF CON 29 Cloud Village.
The Fault in Our Stars - Attack Vectors for APIs Using Amazon API Gateway Lam...
The Fault in Our Stars - Attack Vectors for APIs Using Amazon API Gateway Lam...
Tenchi Security
Aws primer Amazon Web Services
Aws primer Amazon Web Services
Aws primer Amazon Web Services
Mamun Rashid, CCDH
Talk @ AWS Berlin Summit, AWS Loft London
Using Amazon CloudWatch Events, AWS Lambda and Spark Streaming to Process E...
Using Amazon CloudWatch Events, AWS Lambda and Spark Streaming to Process E...
Julien SIMON
Cloud Vulnerabilities and Its Threats
Cloud Vulnerabilities and Its Threats
Cloud Vulnerabilities and Its Threats
Ari Apridana
These are the slides for a talk I presented at the AWS User Group meeting in Singapore. I talked about a specific application I am developing using Amazon SES, SNS, RDS, EBS and S3
Building a Scalable Email Processor With AWS
Building a Scalable Email Processor With AWS
Stephan February
Visualise and Voice-Enable Your Security Security oversight requires you to keep tabs on the near-real-time state of resources within your environment and provides challenges such as the management of large data sets from multiple sources. This session will demonstrate how you can build your own analysis and monitoring platform, providing both visual and audible alerting. Michael Stringer, Solutions Architect, Amazon Web Services and Sumit Patel, Solutions Architect, Amazon Web Services
Visualise and Voice-Enable Your Security - AWS Summit Sydney 2018
Visualise and Voice-Enable Your Security - AWS Summit Sydney 2018
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Open source and business rules
Open source and business rules
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Empfohlen
AWS LearnUp - Intro to AWS Services - Venturesity.
AWS LearnUp - Intro to AWS Services - Venturesity
AWS LearnUp - Intro to AWS Services - Venturesity
Dhilipsiva DS
Serverless applications are a really interesting new trend that promises benefits such as increased scalability and reduced cost. Frameworks like Serverless Application Model (SAM) and Serverless Framework are increasingly used to build them. APIs are a natural part of serverless applications, and in AWS that typically is implemented using the AWS API Gateway backed by Lambdas that implement the actual API endpoint logic. Our research focused on API Gateway Lambda Authorizers. This is a feature that allows developers to use a custom authentication and authorization scheme that uses a bearer token authentication strategy (like JWTs, OAuth or SAML), or that uses request parameters to determine the caller's identity and enforce which API endpoints they are allowed to access. We will present (AFAIK novel) techniques to attack the authentication and authorization of APIs that use Lambda Authorizers. We show how IAM policy injection is possible in theory but highly unlikely in practice due to some good decisions by AWS. We also show a class of problems based on incorrect security assumptions baked into AWS' own documentation and Lambda Authorizer open source code templates. Sample source code will be provided to demonstrate all techniques. Presented at DEF CON 29 Cloud Village.
The Fault in Our Stars - Attack Vectors for APIs Using Amazon API Gateway Lam...
The Fault in Our Stars - Attack Vectors for APIs Using Amazon API Gateway Lam...
Tenchi Security
Aws primer Amazon Web Services
Aws primer Amazon Web Services
Aws primer Amazon Web Services
Mamun Rashid, CCDH
Talk @ AWS Berlin Summit, AWS Loft London
Using Amazon CloudWatch Events, AWS Lambda and Spark Streaming to Process E...
Using Amazon CloudWatch Events, AWS Lambda and Spark Streaming to Process E...
Julien SIMON
Cloud Vulnerabilities and Its Threats
Cloud Vulnerabilities and Its Threats
Cloud Vulnerabilities and Its Threats
Ari Apridana
These are the slides for a talk I presented at the AWS User Group meeting in Singapore. I talked about a specific application I am developing using Amazon SES, SNS, RDS, EBS and S3
Building a Scalable Email Processor With AWS
Building a Scalable Email Processor With AWS
Stephan February
Visualise and Voice-Enable Your Security Security oversight requires you to keep tabs on the near-real-time state of resources within your environment and provides challenges such as the management of large data sets from multiple sources. This session will demonstrate how you can build your own analysis and monitoring platform, providing both visual and audible alerting. Michael Stringer, Solutions Architect, Amazon Web Services and Sumit Patel, Solutions Architect, Amazon Web Services
Visualise and Voice-Enable Your Security - AWS Summit Sydney 2018
Visualise and Voice-Enable Your Security - AWS Summit Sydney 2018
Amazon Web Services
Open source and business rules
Open source and business rules
Geoffrey De Smet
Introduction to Drools
Introduction to Drools
giurca
Presented this at the FOSS4Gov 2013 Conference, which was held in Colombo on 24/09/2013
FOSS in the Enterprise
FOSS in the Enterprise
Crishantha Nanayakkara
Jboss drools 4 scope - benefits, shortfalls
Jboss drools 4 scope - benefits, shortfalls
Zoran Hristov
Slides from the 2013 Drools & jBPM Workshops hold in central london
Drools & jBPM Workshop London 2013
Drools & jBPM Workshop London 2013
Mauricio (Salaboy) Salatino
The JBoss Drools platform at BeJUG: Drools Expert, Drools Guvnor, Drools IDE, Drools Planner, Drools Flow and Drools Fusion. By Geoffrey De Smet and Kris Verlaenen.
Drools BeJUG 2010
Drools BeJUG 2010
Geoffrey De Smet
Presenter: Kenn Knowles, Software Engineer, Google & Apache Beam (incubating) PPMC member Apache Beam (incubating) is a programming model and library for unified batch & streaming big data processing. This talk will cover the Beam programming model broadly, including its origin story and vision for the future. We will dig into how Beam separates concerns for authors of streaming data processing pipelines, isolating what you want to compute from where your data is distributed in time and when you want to produce output. Time permitting, we might dive deeper into what goes into building a Beam runner, for example atop Apache Apex.
Apache Beam (incubating)
Apache Beam (incubating)
Apache Apex
For more information please visit: http://salaboy.wordpress.com/2011/02/23/drools-5-community-training-announced-roadmap/
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
Mauricio (Salaboy) Salatino
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
DataWorks Summit/Hadoop Summit
This documentations contains a number of over view pages with lots of images for Drools & jBPM.
Drools & jBPM Info Sheet
Drools & jBPM Info Sheet
Mark Proctor
Deck from a talk given at the St Louis Gateway JUG on March 6, 2012. Source for the examples can be found at https://github.com/rayploski/drools-JUG-talk
Intro to Drools - St Louis Gateway JUG
Intro to Drools - St Louis Gateway JUG
Ray Ploski
Rules Programming tutorial
Rules Programming tutorial
Srinath Perera
Talk at Scala by the Bay, Nov 2016
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Neville Li
Introduce to Apache Beam Dive in to Beam's architecture and live demo running data pipeline on different runners such as Google Dataflow, Flink and Spark
Apache Beam @ GCPUG.TW Flink.TW 20161006
Apache Beam @ GCPUG.TW Flink.TW 20161006
Randy Huang
Session at DataCamp Salzburg: https://www.meetup.com/Salzburg-Big-Data-Meetup/events/231844168/
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Sergio Fernández
Apache Beam (incubating) is a unified batch and streaming data processing programming model that is efficient and portable. Beam evolved from a decade of system-building at Google, and Beam pipelines run today on both open source (Apache Flink, Apache Spark) and proprietary (Google Cloud Dataflow) runners. This talk will focus on I/O and connectors in Apache Beam, specifically its APIs for efficient, parallel, adaptive I/O. Google will discuss how these APIs enable a Beam data processing pipeline runner to dynamically rebalance work at runtime, to work around stragglers, and to automatically scale up and down cluster size as a job’s workload changes. Together these APIs and techniques enable Apache Beam runners to efficiently use computing resources without compromising on performance or correctness. Practical examples and a demonstration of Beam will be included.
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Dan Halperin
Overview of business rules engine with specific details on JBoss's Drools.
Drools
Drools
John Paulett
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Jamie Grier
Meetup presentation: How Apache Apex consumes from Kafka topics for real-time time processing and analytics. Learn about features of the Apex Kafka Connector, which is one of the most popular operators in the Apex Malhar operator library, and powers several production use cases. We explain the advanced features this operator provides for high throughput, low latency ingest and how it enables fault tolerant topologies with exactly once processing semantics.
Stream data from Apache Kafka for processing with Apache Apex
Stream data from Apache Kafka for processing with Apache Apex
Apache Apex
Drools is a Rule Engine that uses the rule-based approach to implement an Expert System The inference engine matches the rules against the facts (objects) in memory and can match the next set of rules based on the changed facts. Please use the presentation and the source code referred in the presentation to get started on what a rule engine is and how to use JBoss Drools for inference based rules using the Java programming language.
JBoss Drools - Pure Java Rule Engine
JBoss Drools - Pure Java Rule Engine
Anil Allewar
Cognitive IBM Watson Services for Bluemix Developers https://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/ http://heidloff.net/article/ibm-watson-samples-get-started
Cognitive IBM Watson Services for Bluemix Developers
Cognitive IBM Watson Services for Bluemix Developers
Niklas Heidloff
talk from the "vision" track of escience 2019 conference
Esciencetalk
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containers2016
containers2016
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Introduction to Drools
Introduction to Drools
giurca
Presented this at the FOSS4Gov 2013 Conference, which was held in Colombo on 24/09/2013
FOSS in the Enterprise
FOSS in the Enterprise
Crishantha Nanayakkara
Jboss drools 4 scope - benefits, shortfalls
Jboss drools 4 scope - benefits, shortfalls
Zoran Hristov
Slides from the 2013 Drools & jBPM Workshops hold in central london
Drools & jBPM Workshop London 2013
Drools & jBPM Workshop London 2013
Mauricio (Salaboy) Salatino
The JBoss Drools platform at BeJUG: Drools Expert, Drools Guvnor, Drools IDE, Drools Planner, Drools Flow and Drools Fusion. By Geoffrey De Smet and Kris Verlaenen.
Drools BeJUG 2010
Drools BeJUG 2010
Geoffrey De Smet
Presenter: Kenn Knowles, Software Engineer, Google & Apache Beam (incubating) PPMC member Apache Beam (incubating) is a programming model and library for unified batch & streaming big data processing. This talk will cover the Beam programming model broadly, including its origin story and vision for the future. We will dig into how Beam separates concerns for authors of streaming data processing pipelines, isolating what you want to compute from where your data is distributed in time and when you want to produce output. Time permitting, we might dive deeper into what goes into building a Beam runner, for example atop Apache Apex.
Apache Beam (incubating)
Apache Beam (incubating)
Apache Apex
For more information please visit: http://salaboy.wordpress.com/2011/02/23/drools-5-community-training-announced-roadmap/
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
Mauricio (Salaboy) Salatino
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
DataWorks Summit/Hadoop Summit
This documentations contains a number of over view pages with lots of images for Drools & jBPM.
Drools & jBPM Info Sheet
Drools & jBPM Info Sheet
Mark Proctor
Deck from a talk given at the St Louis Gateway JUG on March 6, 2012. Source for the examples can be found at https://github.com/rayploski/drools-JUG-talk
Intro to Drools - St Louis Gateway JUG
Intro to Drools - St Louis Gateway JUG
Ray Ploski
Rules Programming tutorial
Rules Programming tutorial
Srinath Perera
Talk at Scala by the Bay, Nov 2016
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Neville Li
Introduce to Apache Beam Dive in to Beam's architecture and live demo running data pipeline on different runners such as Google Dataflow, Flink and Spark
Apache Beam @ GCPUG.TW Flink.TW 20161006
Apache Beam @ GCPUG.TW Flink.TW 20161006
Randy Huang
Session at DataCamp Salzburg: https://www.meetup.com/Salzburg-Big-Data-Meetup/events/231844168/
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Sergio Fernández
Apache Beam (incubating) is a unified batch and streaming data processing programming model that is efficient and portable. Beam evolved from a decade of system-building at Google, and Beam pipelines run today on both open source (Apache Flink, Apache Spark) and proprietary (Google Cloud Dataflow) runners. This talk will focus on I/O and connectors in Apache Beam, specifically its APIs for efficient, parallel, adaptive I/O. Google will discuss how these APIs enable a Beam data processing pipeline runner to dynamically rebalance work at runtime, to work around stragglers, and to automatically scale up and down cluster size as a job’s workload changes. Together these APIs and techniques enable Apache Beam runners to efficiently use computing resources without compromising on performance or correctness. Practical examples and a demonstration of Beam will be included.
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Dan Halperin
Overview of business rules engine with specific details on JBoss's Drools.
Drools
Drools
John Paulett
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Jamie Grier
Meetup presentation: How Apache Apex consumes from Kafka topics for real-time time processing and analytics. Learn about features of the Apex Kafka Connector, which is one of the most popular operators in the Apex Malhar operator library, and powers several production use cases. We explain the advanced features this operator provides for high throughput, low latency ingest and how it enables fault tolerant topologies with exactly once processing semantics.
Stream data from Apache Kafka for processing with Apache Apex
Stream data from Apache Kafka for processing with Apache Apex
Apache Apex
Drools is a Rule Engine that uses the rule-based approach to implement an Expert System The inference engine matches the rules against the facts (objects) in memory and can match the next set of rules based on the changed facts. Please use the presentation and the source code referred in the presentation to get started on what a rule engine is and how to use JBoss Drools for inference based rules using the Java programming language.
JBoss Drools - Pure Java Rule Engine
JBoss Drools - Pure Java Rule Engine
Anil Allewar
Cognitive IBM Watson Services for Bluemix Developers https://www.ibm.com/smarterplanet/us/en/ibmwatson/developercloud/ http://heidloff.net/article/ibm-watson-samples-get-started
Cognitive IBM Watson Services for Bluemix Developers
Cognitive IBM Watson Services for Bluemix Developers
Niklas Heidloff
Andere mochten auch
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Introduction to Drools
Introduction to Drools
FOSS in the Enterprise
FOSS in the Enterprise
Jboss drools 4 scope - benefits, shortfalls
Jboss drools 4 scope - benefits, shortfalls
Drools & jBPM Workshop London 2013
Drools & jBPM Workshop London 2013
Drools BeJUG 2010
Drools BeJUG 2010
Apache Beam (incubating)
Apache Beam (incubating)
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
Drools5 Community Training Module 5 Drools BLIP Architectural Overview + Demos
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
Drools & jBPM Info Sheet
Drools & jBPM Info Sheet
Intro to Drools - St Louis Gateway JUG
Intro to Drools - St Louis Gateway JUG
Rules Programming tutorial
Rules Programming tutorial
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Scio - A Scala API for Google Cloud Dataflow & Apache Beam
Apache Beam @ GCPUG.TW Flink.TW 20161006
Apache Beam @ GCPUG.TW Flink.TW 20161006
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Introduction to Apache Beam (incubating) - DataCamp Salzburg - 7 dec 2016
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Introduction to Apache Beam & No Shard Left Behind: APIs for Massive Parallel...
Drools
Drools
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Extending the Yahoo Streaming Benchmark + MapR Benchmarks
Stream data from Apache Kafka for processing with Apache Apex
Stream data from Apache Kafka for processing with Apache Apex
JBoss Drools - Pure Java Rule Engine
JBoss Drools - Pure Java Rule Engine
Cognitive IBM Watson Services for Bluemix Developers
Cognitive IBM Watson Services for Bluemix Developers
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talk from the "vision" track of escience 2019 conference
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Accelerating your Research with Microsoft Azure (June 2015)
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this is the deck from my keynote talk at the IEEE Cloud Conference in New York 2015. Survey of cloud architecture, cloud programming and more
ieee cloud 2015 keynote talk
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Machine learning using Microsoft Azure at the Microsoft Research - Moscow State University Joint Research Centre. Specifically, this describes the Adaptive Skip-gram (AdaGram) model; a nonparametric extension of famous Skip-gram model implemented in word2vec software which is able to learn multiple representations per word capturing different word meanings. This projects implements AdaGram in Julia language. The team uses Microsoft Azure to run at scale, allowing analysis of the Wikipedia corpus on large virtual machines. MSU Bayes Group homepage - http://bayesgroup.ru/ Github project - https://github.com/sbos/AdaGram.jl Research paper preprint - http://arxiv.org/abs/1502.07257
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How cloud computing can accelerate your research. Presentation given at Moscow State University on 19th May 2015. Apply for Azure for Research Awards at http://research.microsoft.com/en-US/projects/azure/awards.aspx
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The Fourth Paradigm - Deltares Data Science Day, 31 October 2014
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Scientific instruments, environmental sensors, and large-scale simulations are creating more scientific data than ever before. By using advanced, large-scale information processing facilities, scientists are now able to analyze massive volumes of data in ways that never would have been possible just a few years ago. While a few researchers have access to these large computer systems, most are limited by the processing capacity they can access conveniently and quickly. Cloud computing solutions utilizing Microsoft Azure allow environmental science researchers to access the compute and storage resources that they need, when they need them—without the up-front financial investment required—and helps reduce the time between progress and breakthroughs. Microsoft Azure brings on-demand computing and data access to environmental scientists and researchers everywhere.
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This talk describes our experiences from hosting scientific research application in the Microsoft Cloud. Covers an overview of Microsoft Azure capabilities, examples of big data analysis for science, data collections, science gateways and science virtual machine libraries.
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A presentation at the NIH Workshop on Advanced Networking for Data-Intensive Biomedical Research. The talk covers our work with the science community on using cloud computing to enhance and improve basic research for data analysis and scientific discovery
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Big data - from consumers and patients, to the sea and stars
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Research results in peer-reviewed publications are reproducible, right? If only it was so clear cut. With high profile paper retractions and pushes for better data sharing by funders, publishers and the community, the spotlight is now focussing on the whole way research is conducted around the world. This talk from the Software Sustainability Institute's Collaborations Workshop 2014 describes how cloud computing, with Microsoft Azure, is helping researchers realize the goals of scientific reproducibility. Find out more at www.azure4research.com
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Keynote IEEE International Workshop on Cloud Analytics. Dennis Gannon
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