As your company accumulates more data, it’s important to leverage all of it to develop new advanced machine learning models. And now, you can scale Spark using Kubernetes. Thanks to the new native integration between Apache Spark’s and Kubernetes, scaling data processing has never been easier. Apache Spark is a well designed high level application that can increase your data processing speed and accuracy. It can handle batch and real-time analytic and data processing workloads. This high level and efficient technology can be used with Java/Spark/Python and R. Joined with Kubernetes, you can get twice the efficiency. Kubernetes is a great engine with the most popular framework for managing compute resources. Unfortunately, running Apache Spark on Kubernetes can be a pain for first-time users.
Join CTO of cnvrg.io Leah Kolben as she brings you through a step by step tutorial on how to run Spark on Kubernetes. You’ll have your Spark up and running on Kubernetes in just 30 minutes.
Running Spark on Kubernetes will help you:
Process larger amounts of data
Segment your data into sub groups
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
SignalFx Elasticsearch Metrics Monitoring and AlertingSignalFx
From our Feb 25, 2016 webcast on operating Elasticsearch at scale, the metrics to monitor, and how to create low-noise meaningful alerts on Elasticsearch performance.
Engineering Leader opportunity @ Netflix - Playback Data SystemsPhilip Fisher-Ogden
Across the globe, 75M Netflix members love watching 125M hours per day of TV shows and movies. They love the ease of starting on one device and resuming on another, and the Playback Data Systems team makes that happen. We’re looking for a senior engineering manager to lead this high-impact team at Netflix.
Attributions for images:
https://www.flickr.com/photos/theholyllama/5738164504/ and https://www.flickr.com/photos/brewbooks/7780990192/, no changes made, https://creativecommons.org/licenses/by-sa/2.0/
https://www.flickr.com/photos/crschmidt/2956721498/, no changes made, https://creativecommons.org/licenses/by/2.0/
A 20 minute talk about how WePay runs airflow. Discusses usage and operations. Also covers running Airflow in Google cloud.
Video of the talk is available here:
https://wepayinc.box.com/s/hf1chwmthuet29ux2a83f5quc8o5q18k
Triangle Devops Meetup covering Netflix open source, cloud architecture, and what Andrew did in his first year working as a senior software engineer in the cloud platform group.
As your company accumulates more data, it’s important to leverage all of it to develop new advanced machine learning models. And now, you can scale Spark using Kubernetes. Thanks to the new native integration between Apache Spark’s and Kubernetes, scaling data processing has never been easier. Apache Spark is a well designed high level application that can increase your data processing speed and accuracy. It can handle batch and real-time analytic and data processing workloads. This high level and efficient technology can be used with Java/Spark/Python and R. Joined with Kubernetes, you can get twice the efficiency. Kubernetes is a great engine with the most popular framework for managing compute resources. Unfortunately, running Apache Spark on Kubernetes can be a pain for first-time users.
Join CTO of cnvrg.io Leah Kolben as she brings you through a step by step tutorial on how to run Spark on Kubernetes. You’ll have your Spark up and running on Kubernetes in just 30 minutes.
Running Spark on Kubernetes will help you:
Process larger amounts of data
Segment your data into sub groups
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
SignalFx Elasticsearch Metrics Monitoring and AlertingSignalFx
From our Feb 25, 2016 webcast on operating Elasticsearch at scale, the metrics to monitor, and how to create low-noise meaningful alerts on Elasticsearch performance.
Engineering Leader opportunity @ Netflix - Playback Data SystemsPhilip Fisher-Ogden
Across the globe, 75M Netflix members love watching 125M hours per day of TV shows and movies. They love the ease of starting on one device and resuming on another, and the Playback Data Systems team makes that happen. We’re looking for a senior engineering manager to lead this high-impact team at Netflix.
Attributions for images:
https://www.flickr.com/photos/theholyllama/5738164504/ and https://www.flickr.com/photos/brewbooks/7780990192/, no changes made, https://creativecommons.org/licenses/by-sa/2.0/
https://www.flickr.com/photos/crschmidt/2956721498/, no changes made, https://creativecommons.org/licenses/by/2.0/
A 20 minute talk about how WePay runs airflow. Discusses usage and operations. Also covers running Airflow in Google cloud.
Video of the talk is available here:
https://wepayinc.box.com/s/hf1chwmthuet29ux2a83f5quc8o5q18k
Triangle Devops Meetup covering Netflix open source, cloud architecture, and what Andrew did in his first year working as a senior software engineer in the cloud platform group.
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.
Netflix viewing data architecture evolution - EBJUG Nov 2014Philip Fisher-Ogden
Netflix's architecture for viewing data has evolved as streaming usage has grown. Each generation was designed for the next order of magnitude, and was informed by learnings from the previous. From SQL to NoSQL, from data center to cloud, from proprietary to open source, look inside to learn how this system has evolved. (slides from a talk given at the East Bay Java Users Group MeetUp in Nov 2014)
Joel Jacobson (Datastax) - Diagnosing Cassandra Problems in ProductionOutlyer
This sessions covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Attendees will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster.
Video: https://www.youtube.com/watch?v=9XrHoAxd0Is
Join DevOps Exchange London here: http://www.meetup.com/DevOps-Exchange-London
Follow DOXLON on twitter http://www.twitter.com/doxlon
So Your OpenStack Cloud is Built... Now What's Next - Walter Bentley - OpenSt...Cloud Native Day Tel Aviv
So you have spent months convincing your leadership to go with OpenStack. Finally the keys of the cloud are turned over to you as the Cloud Operator, you then look over at your co-workers and say “now what”. The next set of phrases normally are something like: Now how do we best administer this cloud? Cloud is supposed to be easier, right?
Audience Takeaways:
* Discover some common day-to-day operator tasks
* Learn why OpenStack works well with open sourced automation tools
* Review some automation considerations before getting started
* Step thru how to automate a few of the operator tasks using open sourced automation tools
* Benefits of adopting an ‘Administration DevOps’ state of mind and next steps
The goal of data science teams are to build and deploy high impact models. Data scientists prefer to focus on building algorithms, while data engineers focus on performance and productionizing machine learning. Kubernetes is an orchestration platform that can be deployed anywhere and can serve any kind of machine and deep learning environment. Kubernetes is a great tool for data scientists to use to stay productive and for data engineers to get production-ready results. In this free workshop you’ll learn how to build your own Kubernetes to use in your next machine learning pipeline.
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
Through the looking glass an intro to scalable, distributed counting in data...Geoff Cooney
Lightning talk I gave at GCP Boston meetup for a quick hands on intro to google dataflow. Example based on the public pubsub topic described here: https://github.com/googlecodelabs/cloud-dataflow-nyc-taxi-tycoon
An application designer usually has to choose where to trade flexibility for specificity (and thus usually performance); knowing when and where to do so is an art and requires experience. This talk will share over a decades worth of experience making these decisions and the learnings from developing Pivotal's successful Real Time Intelligence (RTI) product using the latest versions of Spring projects: Integration, Data, Boot, MVC/REST and XD. A walk through the RTI architecture will provide the base for an explanation about how Spring performs at hundreds (and millions) of events/operations per second and the techniques that you can use right now in your own Spring applications to minimise resource utilisation and gain performance.
Kubernetes & Google Container Engine @ mablJoseph Lust
Validating 100 Million Pages a Month using Kubernetes and Google Container Engine (GKE).
How we used Docker to build our ML testing engine in four months. Lessons learned, best practices, and demonstrations.
Boston Google Cloud Meetup September Presentation @ mabl
https://www.meetup.com/Boston-Google-Cloud-Meetup/events/242964121/
Michael Still, Compute PTL, outlines the changes made in the Icehouse release as well as upcoming updates for Juno.
Learn more about Compute (Nova) here: https://wiki.openstack.org/wiki/Nova
SimScale: Unparalleled CFD Speeds with Parallel ComputingSimScale
SimScale reduces the lead time of industrial aerodynamic simulations from weeks to hours, using the Lattice Boltzmann Method, provided by Numeric Systems, and high-performance cloud computing, provided by Amazon web services. Proof of concept and level of accuracy is demonstrated with the "DrivAer" geometry —a standard automotive validation case for both CFD and wind tunnel experiments. The results show that SimScale provides a solution to significantly reduce turnaround times for 10x less cost with fantastic accuracy.
Tips and tricks to maximize performance and minimize serverless costs with Firebase and Google Cloud Functions. Live examples and analysis to show that GCF is the cheapest function provider, compared to Azure Functions and AWS Lambda.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
When moving to Feature-Driven Development (FDD), with geographically distributed development centers, it is customary to have a dedicated light weight environment per feature-development effort and to have robust automation support for the build and deploy life cycle of each feature branch at your own will.
In this session, learn about the Feature-Driven Development transition story of a cloud-based supply chain leader that shows how AWS services helped provide a highly scalable, elastic, and cost-effective solution to facilitate on-demand Feature Development Environments supported by an independent build, deployment, and test-automation framework.
Presentada en la Mesa redonda, Acceso abierto en España: servicios, proyectos, resultados que tuvo lugar en la Biblioteca Nacional de España (BNE), el 25 de octubre de 2013
Feature description and demonstration of the 52°North implementation of the OGC Web Processing Service interface 1.0.0 along with plans for future development.
Prese
This presentation covers how to setup an Airflow instance as a cluster which spans multiple machines instead of the traditional 1 machine distribution. In addition, it covers an added step you can take to ensure High Availability in that cluster.
Netflix viewing data architecture evolution - EBJUG Nov 2014Philip Fisher-Ogden
Netflix's architecture for viewing data has evolved as streaming usage has grown. Each generation was designed for the next order of magnitude, and was informed by learnings from the previous. From SQL to NoSQL, from data center to cloud, from proprietary to open source, look inside to learn how this system has evolved. (slides from a talk given at the East Bay Java Users Group MeetUp in Nov 2014)
Joel Jacobson (Datastax) - Diagnosing Cassandra Problems in ProductionOutlyer
This sessions covers diagnosing and solving common problems encountered in production, using performance profiling tools. We’ll also give a crash course to basic JVM garbage collection tuning. Attendees will leave with a better understanding of what they should look for when they encounter problems with their in-production Cassandra cluster.
Video: https://www.youtube.com/watch?v=9XrHoAxd0Is
Join DevOps Exchange London here: http://www.meetup.com/DevOps-Exchange-London
Follow DOXLON on twitter http://www.twitter.com/doxlon
So Your OpenStack Cloud is Built... Now What's Next - Walter Bentley - OpenSt...Cloud Native Day Tel Aviv
So you have spent months convincing your leadership to go with OpenStack. Finally the keys of the cloud are turned over to you as the Cloud Operator, you then look over at your co-workers and say “now what”. The next set of phrases normally are something like: Now how do we best administer this cloud? Cloud is supposed to be easier, right?
Audience Takeaways:
* Discover some common day-to-day operator tasks
* Learn why OpenStack works well with open sourced automation tools
* Review some automation considerations before getting started
* Step thru how to automate a few of the operator tasks using open sourced automation tools
* Benefits of adopting an ‘Administration DevOps’ state of mind and next steps
The goal of data science teams are to build and deploy high impact models. Data scientists prefer to focus on building algorithms, while data engineers focus on performance and productionizing machine learning. Kubernetes is an orchestration platform that can be deployed anywhere and can serve any kind of machine and deep learning environment. Kubernetes is a great tool for data scientists to use to stay productive and for data engineers to get production-ready results. In this free workshop you’ll learn how to build your own Kubernetes to use in your next machine learning pipeline.
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
Through the looking glass an intro to scalable, distributed counting in data...Geoff Cooney
Lightning talk I gave at GCP Boston meetup for a quick hands on intro to google dataflow. Example based on the public pubsub topic described here: https://github.com/googlecodelabs/cloud-dataflow-nyc-taxi-tycoon
An application designer usually has to choose where to trade flexibility for specificity (and thus usually performance); knowing when and where to do so is an art and requires experience. This talk will share over a decades worth of experience making these decisions and the learnings from developing Pivotal's successful Real Time Intelligence (RTI) product using the latest versions of Spring projects: Integration, Data, Boot, MVC/REST and XD. A walk through the RTI architecture will provide the base for an explanation about how Spring performs at hundreds (and millions) of events/operations per second and the techniques that you can use right now in your own Spring applications to minimise resource utilisation and gain performance.
Kubernetes & Google Container Engine @ mablJoseph Lust
Validating 100 Million Pages a Month using Kubernetes and Google Container Engine (GKE).
How we used Docker to build our ML testing engine in four months. Lessons learned, best practices, and demonstrations.
Boston Google Cloud Meetup September Presentation @ mabl
https://www.meetup.com/Boston-Google-Cloud-Meetup/events/242964121/
Michael Still, Compute PTL, outlines the changes made in the Icehouse release as well as upcoming updates for Juno.
Learn more about Compute (Nova) here: https://wiki.openstack.org/wiki/Nova
SimScale: Unparalleled CFD Speeds with Parallel ComputingSimScale
SimScale reduces the lead time of industrial aerodynamic simulations from weeks to hours, using the Lattice Boltzmann Method, provided by Numeric Systems, and high-performance cloud computing, provided by Amazon web services. Proof of concept and level of accuracy is demonstrated with the "DrivAer" geometry —a standard automotive validation case for both CFD and wind tunnel experiments. The results show that SimScale provides a solution to significantly reduce turnaround times for 10x less cost with fantastic accuracy.
Tips and tricks to maximize performance and minimize serverless costs with Firebase and Google Cloud Functions. Live examples and analysis to show that GCF is the cheapest function provider, compared to Azure Functions and AWS Lambda.
Building a Data Pipeline using Apache Airflow (on AWS / GCP)Yohei Onishi
This is the slide I presented at PyCon SG 2019. I talked about overview of Airflow and how we can use Airflow and the other data engineering services on AWS and GCP to build data pipelines.
When moving to Feature-Driven Development (FDD), with geographically distributed development centers, it is customary to have a dedicated light weight environment per feature-development effort and to have robust automation support for the build and deploy life cycle of each feature branch at your own will.
In this session, learn about the Feature-Driven Development transition story of a cloud-based supply chain leader that shows how AWS services helped provide a highly scalable, elastic, and cost-effective solution to facilitate on-demand Feature Development Environments supported by an independent build, deployment, and test-automation framework.
Presentada en la Mesa redonda, Acceso abierto en España: servicios, proyectos, resultados que tuvo lugar en la Biblioteca Nacional de España (BNE), el 25 de octubre de 2013
Feature description and demonstration of the 52°North implementation of the OGC Web Processing Service interface 1.0.0 along with plans for future development.
Prese
Présentation de FormaVia et des projets liées au développement des compétences numériques des acteurs de la formation tout au long de la vie et de la médiation numérique réalisée dans le cadre du BarcampClermont - 1" décembre 2013
Zwei Software-Komponenten brauchen eine Schnittstelle. Leider ist dieses Szenario in vielen Fällen problembehaftet. Die Gründe sind vielfältig, liegen aber oft nicht an der technischen Umsetzung, sondern an der Konzeption, der Performance, der Verfügbarkeit und anderem. Um das zu vermeiden, müssen konkrete Antworten auf folgende Fragen her:
Konzeption der Schnittstelle,
Performance-Aspekte,
Sicherheits-Aspekte,
Transport-Layer, Architektur (SOAP, REST),
Datenformat (JSON, XML),
Change Management
1st Generation: Network Resources Mgmt for Grids
2nd Generation: Secure Multi-Domain Brokering
Demo-ed at Supercomputing 2004
3rd Generation: Intercept the WS Workflow Curve (Today)
Web Services (WS) boost opportunities for business development
Workflow defines the automation of a business process
With new SOA solutions, for WS: BPEL4WS, for Grid: GSFL
Streamlines application jobs in terms of WS and Grids activities
Workflow has a host of applications
eCommerce: B2B, financial brokerage, travel planning
Enterprise: concurrent design, data center, human resources
eScience: computing, data, visualization, sensor Grids
Workflow INtegrated NEtwork Resource orchestration
Orchestrates network resources in harmonization with workflows
Enhances business processes with resource extensions
Employs network services to perform resource operations
Druid provides sub-second query latency and Flink provides SQL on streams allowing rich transformation/enrichment of events as it happens. In this talk we will learn how Lyft
uses flink sql and druid together to support real time analytics.
Meetup: https://www.meetup.com/druidio/events/252515792/
This slide is part of Advanced Topics course for Software Design and Analysis Laboratory, Nara Institute of Science and Technology. It contains basic information on my graduation project at Kasetsart University.
Due to status of the project, I cannot fully claim copyright to it (project owned by HPCNC Kasetsart University, and slide made during my coursework at SDLAB NAIST). Please contact me if you need the slide -- I will forward the requests accordingly.
Microsoft Azure Cloud Services offers a way to run applications designed to run on the Windows platform from nearly any device using a component of Remote Desktop Services called RemoteApp. This slide presentation, made to Oregon Computer Consultants Association on May 31, 2016 by David Cornelius, helps explain RemoteApp, how to setup a custom image, and highlights pricing considerations.
Reaching State Zero Without Losing Your VersionsSSP Innovations
Reaching State 0 without losing your Versions
Describes how we successfully helped Intermountain Rural Electric Assn (a Colorado utility) take their Esri/Schneider Electric GIS system to "state zero" (where no outstanding versions exist), without losing their many crucial versions and edits within those versions. Utilizing the SSP All Edits Reporting & QA Tool and the SSP Nightly Batch Suite product, we were able to record all version and edit information for critical versions that could not be lost, then delete the versions completely, taking the system to state zero. IREA was then able to perform various maintenance activities that are enjoyed at state zero. Once completed, SSP replayed the edits and versions back into the GIS, and users were utilizing the system as if nothing ever happened.
Building occasionally connected applications using event sourcingDennis Doomen
I've recently got the opportunity to work on a large enterprise-class system that needs to be deployed on multiple occasionally connected oil platforms and boats. Already the system's architecture was based on the Command Query Separation principles, this gave us a completely new challenge. After several months of looking at alternatives, we decided to go the Event Sourcing direction. In this in-depth session, I'd like you to learn the many alternatives we observed, the pros and cons, and the technical details of our final solution in which we use EventStore 3.0 and elements of NCQRS and Lokad.CQRS to synchronize systems over unreliable connections in a very efficient way.
The number of production CI environments increased from 2 in Arno to 8 with Brahmaputra, each dedicated to a particular installer version (OPNFV flavor and scenario). In future in order to improve overall robustness of the platform production test resources should be independent from installers and scenarios. Furthermore testing between OPNFV deployments will be needed to ensure the promise of data-center interoperability. This presentation deals with mid and long term challenges of the OPNFV testing infrastructure.
WS boosts up new opportunity of business development
Web Services (WS): service providers to customers
WS is interoperable and trustable among business partners
WS increases productivity by component service development and reduces cost by sharing services and avoiding function duplications
New opportunity for WS providers, publishers, applications and …
Globus is offering WSRF, as GT4 comes
Workflow defines the automation of a business process
Streamlines the application job: WS and Grids
Evolves from object-oriented programming (OOP) to service-oriented architecture (SOA)
New support for WS: BPEL4WS, for Grid: GSFL
Workflow has a bandwagon of applications
E-commercial: B2B, financial brokerage, travel planning
Enterprise: concurrent design, data center, human resources
E-Science: Grid computing, hi-energy computation
Use AWS to learn how much players love your game by analyzing in-game metrics to measure engagement and retention. Start simple by uploading data to S3 and analyzing it with Redshift. Add additional game data sources and dive deeper with Cohort analysis. Finally I cover real-time analytics with Kinesis and Spark.
IT in the Jungle
GAMA ProjEx are specialist providers of project management and field support services in the oil exploration sector. GAMA operate in environments that are extremely challenging in all respects, not least the provision of the robust wide ranging IT services that oil exploration surveys demand. Imagine the challenge of providing quality IT services to a string of camps in the PNG highlands: low bandwidth, compute intensive applications, large shared data sets, shifting camps, satellite links, a virtual back office, helicopter access only. Come and hear how GAMA meets these challenges with the support of Auckland based Managed Services partner Eagle Technology and extensive use of the AWS platform.
Speakers:
Mark Askey, PNG Seismic Project Manager, GAMA ProjEx and Mark Mulholland, Senior Consultant, Eagle Technology
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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!
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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/
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
4. 52° North WPS
•
•
•
•
•
written in Java
available as Open Source implementation
support of WPS 1.0.0 specification
synchronous and asynchronous processing
Process backends:
–
–
–
–
–
–
GRASS GIS
Sextante Spatial Data Analysis Library
ArcGIS Server
R
Java Topology Suite
Batch processes
• Process upload via Web Console
• GRID support
• Transactional support
http://52north.org/wps
2014-01-23 52°North WPS Use Cases
52N WPS
Parsers
Processes
Generators
GML
Process 1
GML
KML
Process 2
KML
SHP
…
SHP
Process n
…
4
5. Features (cont‘d)
•
•
•
•
Fast & easy process creation using Java annotations
Automatic creation of process description
Automatic (un-)marshalling of inputs/outputs
Upload via Web Console
2014-01-23 52°North WPS Use Cases
5
6. Fast & easy process creation using Java
annotations
• Demo
2014-01-23 52°North WPS Use Cases
6
7. Features (cont‘d)
• Semi-automatic creation of WPS processes out of Rscripts
• User needs to annotate inputs/outputs
• Rserve is used to execute scripts
• Upload via Web Console
2014-01-23 52°North WPS Use Cases
7
13. USGS Geo Data Portal
2014-01-23 52°North WPS Use Cases
13
14. INTAMAP
• Real-time mapping of environmental radioactivity
• WPS provides automatic Kriging interpolation
2014-01-23 52°North WPS Use Cases
14
15. UncertWeb
• WPS4R was developed
• Different models were coupled with the WPS
• Uncertainty handling introduced to WPS
2014-01-23 52°North WPS Use Cases
15
17. UncertWeb
• Demo chain with UncertWeb components
Air quality
observations
(SOS)
O&M
INTAMAP
service
(WPS)
Interpolation of background
concentration
UncertML
+ GML
Uncertainty enabled
Austal model
(UPS + WPS + UTS)
Estimation of air pollution
from local emissions at
point locations
2014-01-23 52°North WPS Use Cases
UncertML
realisations
Overlay
Service
(WPS + UTS)
UncertML
JSON
Web-based
Visualisation
client
Adding both outputs to
final concentration map
17