The case study discusses the innovative technical solution to the challenges encountered by the customer in the development of an analytics solution for large datacenter network traffic.
Artificial Intelligence and Analytic Ops to Continuously Improve Business Out...DataWorks Summit
The time for enterprises to gain market advantage through Artificial Intelligence is now. Already many AI-enabled advances are transforming business processes and customer experiences, but the vast majority of AI-enhanced use cases are still to be discovered, developed, and deployed. In order to discover and capture the value available through deployed AI, new deep learning techniques are the focus of feverish research and development in academia and business. However, even successful AI experiments are often never deployed to business operations, resulting in wasted effort, time, and money, and leaving businesses dangerously exposed to competitors that have integrated AI into their ongoing operations.
Experimentation with AI is essential to realizing the promise of AI, but enterprises face substantial risks that their experiments with AI, even successful ones, will do nothing to improve their business outcomes. We present a framework, inspired by DevOps practices used by software engineers to continuously incorporate new ideas and improvements into applications, that de-risks investments in AI by providing a reliable channel for pipelining successful AI experiments and development into continuously deployed and monitored operational analytics.
Speaker
Nick Switanek, Marketing Director of Artificial Intelligence, Teradata
#GeodeSummit - Modern manufacturing powered by Spring XD and GeodePivotalOpenSourceHub
Wondering how to improve on your production yield, increase asset life and activate reliability centered maintenance? TEKsystems has developed “Golden Batch” recommendation engine to realize your goals of modern manufacturing. This is a Predictive analytics framework built on top of Manufacturing Data Lake for analysis and training of machine learning algorithms, and subsequent processing and detection of streaming data from sensors to detect or predict failures. We’ll present a solution architecture featuring Spring XD for data pipelining, Apache Geode for in-memory processing, Hadoop as a data lake, and R for machine learning.
Big Data Pipeline for Analytics at Scale @ FIT CVUT 2014Jaroslav Gergic
The recent boom in big data processing and democratization of the big data space has been enabled by the fact that most of the concepts originated in the research labs of companies such as Google, Amazon, Yahoo and Facebook are now available as open source. Technologies such as Hadoop, Cassandra let businesses around the world to become more data driven and tap into their massive data feeds to mine valuable insights.
At the same time, we are still at a certain stage of the maturity curve of these new big data technologies and of the entire big data technology stack. Many of the technologies originated from a particular use case and attempts to apply them in a more generic fashion are hitting the limits of their technological foundations. In some areas, there are several competing technologies for the same set of use cases, which increases risks and costs of big data implementations.
We will show how GoodData solves the entire big data pipeline today, starting from raw data feeds all the way up to actionable business insights. All this provided as a hosted multi-tenant environment letting its customers to solve their particular analytical use case or many analytical use cases for thousands of their customers all using the same platform and tools while abstracting them away from the technological details of the big data stack.
Data and analytics are at the heart of the digital transformation. Implementing a modern data platform can be challenging; moreover, success requires a shift in culture. Andreas will discuss the ways Munich Re drives cultural and technological change within their company, focusing on three key elements: people, processes, and technology. What does it mean to be a data-driven organization? How can we provide self-service analytics to our internal and external customers in an agile way? How do we get the most value out of our big data lake? How does Munich Re balance technology and culture to meet the data demands of their business?
Speaker
Andreas Kohlmaier, Head of Data Engineering, Munich Re
Artificial Intelligence and Analytic Ops to Continuously Improve Business Out...DataWorks Summit
The time for enterprises to gain market advantage through Artificial Intelligence is now. Already many AI-enabled advances are transforming business processes and customer experiences, but the vast majority of AI-enhanced use cases are still to be discovered, developed, and deployed. In order to discover and capture the value available through deployed AI, new deep learning techniques are the focus of feverish research and development in academia and business. However, even successful AI experiments are often never deployed to business operations, resulting in wasted effort, time, and money, and leaving businesses dangerously exposed to competitors that have integrated AI into their ongoing operations.
Experimentation with AI is essential to realizing the promise of AI, but enterprises face substantial risks that their experiments with AI, even successful ones, will do nothing to improve their business outcomes. We present a framework, inspired by DevOps practices used by software engineers to continuously incorporate new ideas and improvements into applications, that de-risks investments in AI by providing a reliable channel for pipelining successful AI experiments and development into continuously deployed and monitored operational analytics.
Speaker
Nick Switanek, Marketing Director of Artificial Intelligence, Teradata
#GeodeSummit - Modern manufacturing powered by Spring XD and GeodePivotalOpenSourceHub
Wondering how to improve on your production yield, increase asset life and activate reliability centered maintenance? TEKsystems has developed “Golden Batch” recommendation engine to realize your goals of modern manufacturing. This is a Predictive analytics framework built on top of Manufacturing Data Lake for analysis and training of machine learning algorithms, and subsequent processing and detection of streaming data from sensors to detect or predict failures. We’ll present a solution architecture featuring Spring XD for data pipelining, Apache Geode for in-memory processing, Hadoop as a data lake, and R for machine learning.
Big Data Pipeline for Analytics at Scale @ FIT CVUT 2014Jaroslav Gergic
The recent boom in big data processing and democratization of the big data space has been enabled by the fact that most of the concepts originated in the research labs of companies such as Google, Amazon, Yahoo and Facebook are now available as open source. Technologies such as Hadoop, Cassandra let businesses around the world to become more data driven and tap into their massive data feeds to mine valuable insights.
At the same time, we are still at a certain stage of the maturity curve of these new big data technologies and of the entire big data technology stack. Many of the technologies originated from a particular use case and attempts to apply them in a more generic fashion are hitting the limits of their technological foundations. In some areas, there are several competing technologies for the same set of use cases, which increases risks and costs of big data implementations.
We will show how GoodData solves the entire big data pipeline today, starting from raw data feeds all the way up to actionable business insights. All this provided as a hosted multi-tenant environment letting its customers to solve their particular analytical use case or many analytical use cases for thousands of their customers all using the same platform and tools while abstracting them away from the technological details of the big data stack.
Data and analytics are at the heart of the digital transformation. Implementing a modern data platform can be challenging; moreover, success requires a shift in culture. Andreas will discuss the ways Munich Re drives cultural and technological change within their company, focusing on three key elements: people, processes, and technology. What does it mean to be a data-driven organization? How can we provide self-service analytics to our internal and external customers in an agile way? How do we get the most value out of our big data lake? How does Munich Re balance technology and culture to meet the data demands of their business?
Speaker
Andreas Kohlmaier, Head of Data Engineering, Munich Re
#GeodeSummit: Architecting Data-Driven, Smarter Cloud Native Apps with Real-T...PivotalOpenSourceHub
This talk introduces an open-source solution that integrates cloud native apps running on Cloud Foundry with an open-source hybrid transactions + analytics real-time solution. The architecture is based on the fastest scalable, highly available and fully consistent In-Memory Data Grid (Apache Geode / GemFire), natively integrated to the first open-source massive parallel data warehouse (Greenplum Database) in a hybrid transactional and analytical architecture that is extremely fast, horizontally scalable, highly resilient and open source. This session also features a live demo running on Cloud Foundry, showing a real case of real-time closed-loop analytics and machine learning using the featured solution.
How a Media Data Platform Drives Real-time Insights & Analytics using Apache ...Databricks
Roularta is a leading publishing company in Belgium. As digital news and channels move at a rapid pace and contain massive volumes of data, Roularta decided in 2019 to invest in a Spark-based data platform to drive true real-time website analytics and unlock insights on previously untouched (big) data sources. In this talk we’ll first explain why and how Roularta embarked from a classical data warehouse to a Spark-based Lakehouse using Delta. We’ll outline the series of publishing & marketing use-cases done in the last 12 months and highlight for each use-case the advantages of Spark and how the team further tuned performance to truly deliver insights with high velocity.
Building Identity Graph at Scale for Programmatic Media Buying Using Apache S...Databricks
The proliferation of digital channels has made it mandatory for marketers to understand an individual across multiple touchpoints. In order to develop market effectiveness, marketers need have a pretty good sense of its consumer’s identity so that it can reach him via mobile device, desktop or a big TV screen on living room. Examples of such identity tokens include cookies, app IDs etc.A consumer can use multiple devices at the same time and so the same consumer should not be treated as different people in the advertising space. The idea of identity resolution comes with this mission and goal to have an omnichannel view of a consumer.
Anne-Sophie Roessler, International Business Developer, Dataiku - "3 ways to ...Dataconomy Media
Anne-Sophie Roessler, International Business Developer at Dataiku presented "3 ways to Fail your Data Lab Implementation" as part of the Big Data, Berlin v 8.0 meetup organised on the 14th of July 2016 at the WeWork headquarters.
Learn to Use Databricks for the Full ML LifecycleDatabricks
Machine learning development brings many new complexities beyond the traditional software development lifecycle. Unlike traditional software development, ML developers want to try multiple algorithms, tools and parameters to get the best results, and they need to track this information to reproduce work. In addition, developers need to use many distinct systems to productionize models. In this talk, learn how to operationalize ML across the full lifecycle with Databricks Machine Learning.
From Batch to Real Time: Overstock’s Journey Towards Unifying Analytics Acros...Databricks
With great data, comes great responsibility. At Overstock.com, lack of data has never been an issue. We know everything from the color you search most, to which room you’ll redesign next. We can see individuals transition from furnishing their first flat to building their dream home, but processing this data requires some serious firepower. It has fueled our focus on delivering real-time personalization through the unification of data and AI. Databricks is at the crux of this vision – empowering us to leverage cloud-scale with a platform that simplifies data engineering and increases the productivity of our data science team.
Tune in as Chris Robison takes you through marketecture innovations in building a successful marketing technology infrastructure for instantaneous individualized marketing experiences.
Introducing Lucidata Informatics, Analytics Products and ServicesGeoffrey Clark
Lucidata Informatics provides help with complex supply chain, logistics and transportation data. We provide data, data-as-a-service, industry data models, and pre-built analytics solutions. We also provide data modeling and analytics solution architecture services to improve and enrich your analytics for better insights, and also to explore options to monetize your data assets.
a linux server, or docker container ready to help you automate data integration and visualization for supply chain, logistics and transportation freight data flows. Packed with market intelligence data, metadata, a geospatial data analysis portal with many templates, and supply chain web analytics. Let us help you wrangle your data and provide insights through visualization.
Graph Gurus Episode 35: No Code Graph Analytics to Get Insights from Petabyte...TigerGraph
Full Webinar: https://info.tigergraph.com/graph-gurus-35
By attending this webinar you will:
-Learn how to use TigerGraph’s no-code capabilities;
-Understand how TigerGraph is built for scale and performance;
-Get a deep dive into TigerGraph 3.0 feature enhancements.
Lucidata Titan geo-server data container and servicesGeoffrey Clark
a linux server, or docker container to automate data integration enrich data mining, and visualize your supply chain, logistics and transportation freight data. Includes tools like global Omni-Mode Trip Planner (OMTP), granular market and economic intelligence data, metadata, QGIS (a geospatial analysis tool) with many templates, and optional supply chain web analytics. Let us help you wrangle your data and provide insights to your stakeholders.
WSO2 Data Analytics Server is a comprehensive enterprise data analytics platform; it fuses batch and real-time analytics of any source of data with predictive analytics via machine learning.
How to scale your PaaS with OVH infrastructure?OVHcloud
ForePaaS has developed an “as-a-service” platform which lets you automate an infrastructure designed for analytical applications. The company has formed a cloud partnership with OVH in order to deliver flexible solutions for containerised and high-performance tools, such as Kunernetes and Docker.
#GeodeSummit: Architecting Data-Driven, Smarter Cloud Native Apps with Real-T...PivotalOpenSourceHub
This talk introduces an open-source solution that integrates cloud native apps running on Cloud Foundry with an open-source hybrid transactions + analytics real-time solution. The architecture is based on the fastest scalable, highly available and fully consistent In-Memory Data Grid (Apache Geode / GemFire), natively integrated to the first open-source massive parallel data warehouse (Greenplum Database) in a hybrid transactional and analytical architecture that is extremely fast, horizontally scalable, highly resilient and open source. This session also features a live demo running on Cloud Foundry, showing a real case of real-time closed-loop analytics and machine learning using the featured solution.
How a Media Data Platform Drives Real-time Insights & Analytics using Apache ...Databricks
Roularta is a leading publishing company in Belgium. As digital news and channels move at a rapid pace and contain massive volumes of data, Roularta decided in 2019 to invest in a Spark-based data platform to drive true real-time website analytics and unlock insights on previously untouched (big) data sources. In this talk we’ll first explain why and how Roularta embarked from a classical data warehouse to a Spark-based Lakehouse using Delta. We’ll outline the series of publishing & marketing use-cases done in the last 12 months and highlight for each use-case the advantages of Spark and how the team further tuned performance to truly deliver insights with high velocity.
Building Identity Graph at Scale for Programmatic Media Buying Using Apache S...Databricks
The proliferation of digital channels has made it mandatory for marketers to understand an individual across multiple touchpoints. In order to develop market effectiveness, marketers need have a pretty good sense of its consumer’s identity so that it can reach him via mobile device, desktop or a big TV screen on living room. Examples of such identity tokens include cookies, app IDs etc.A consumer can use multiple devices at the same time and so the same consumer should not be treated as different people in the advertising space. The idea of identity resolution comes with this mission and goal to have an omnichannel view of a consumer.
Anne-Sophie Roessler, International Business Developer, Dataiku - "3 ways to ...Dataconomy Media
Anne-Sophie Roessler, International Business Developer at Dataiku presented "3 ways to Fail your Data Lab Implementation" as part of the Big Data, Berlin v 8.0 meetup organised on the 14th of July 2016 at the WeWork headquarters.
Learn to Use Databricks for the Full ML LifecycleDatabricks
Machine learning development brings many new complexities beyond the traditional software development lifecycle. Unlike traditional software development, ML developers want to try multiple algorithms, tools and parameters to get the best results, and they need to track this information to reproduce work. In addition, developers need to use many distinct systems to productionize models. In this talk, learn how to operationalize ML across the full lifecycle with Databricks Machine Learning.
From Batch to Real Time: Overstock’s Journey Towards Unifying Analytics Acros...Databricks
With great data, comes great responsibility. At Overstock.com, lack of data has never been an issue. We know everything from the color you search most, to which room you’ll redesign next. We can see individuals transition from furnishing their first flat to building their dream home, but processing this data requires some serious firepower. It has fueled our focus on delivering real-time personalization through the unification of data and AI. Databricks is at the crux of this vision – empowering us to leverage cloud-scale with a platform that simplifies data engineering and increases the productivity of our data science team.
Tune in as Chris Robison takes you through marketecture innovations in building a successful marketing technology infrastructure for instantaneous individualized marketing experiences.
Introducing Lucidata Informatics, Analytics Products and ServicesGeoffrey Clark
Lucidata Informatics provides help with complex supply chain, logistics and transportation data. We provide data, data-as-a-service, industry data models, and pre-built analytics solutions. We also provide data modeling and analytics solution architecture services to improve and enrich your analytics for better insights, and also to explore options to monetize your data assets.
a linux server, or docker container ready to help you automate data integration and visualization for supply chain, logistics and transportation freight data flows. Packed with market intelligence data, metadata, a geospatial data analysis portal with many templates, and supply chain web analytics. Let us help you wrangle your data and provide insights through visualization.
Graph Gurus Episode 35: No Code Graph Analytics to Get Insights from Petabyte...TigerGraph
Full Webinar: https://info.tigergraph.com/graph-gurus-35
By attending this webinar you will:
-Learn how to use TigerGraph’s no-code capabilities;
-Understand how TigerGraph is built for scale and performance;
-Get a deep dive into TigerGraph 3.0 feature enhancements.
Lucidata Titan geo-server data container and servicesGeoffrey Clark
a linux server, or docker container to automate data integration enrich data mining, and visualize your supply chain, logistics and transportation freight data. Includes tools like global Omni-Mode Trip Planner (OMTP), granular market and economic intelligence data, metadata, QGIS (a geospatial analysis tool) with many templates, and optional supply chain web analytics. Let us help you wrangle your data and provide insights to your stakeholders.
WSO2 Data Analytics Server is a comprehensive enterprise data analytics platform; it fuses batch and real-time analytics of any source of data with predictive analytics via machine learning.
How to scale your PaaS with OVH infrastructure?OVHcloud
ForePaaS has developed an “as-a-service” platform which lets you automate an infrastructure designed for analytical applications. The company has formed a cloud partnership with OVH in order to deliver flexible solutions for containerised and high-performance tools, such as Kunernetes and Docker.
Solution Brief: Real-Time Pipeline AcceleratorBlueData, Inc.
Get started with Spark Streaming, Kafka, and Cassandra for real-time data analytics.
BlueData makes it easy to deploy Spark infrastructure and applications on- premises. The BlueData EPIC software platform is purpose-built to simplify and accelerate the deployment of Spark, Hadoop, and other tools for Big Data analytics—leveraging Docker containers and virtualized infrastructure.
Our new Real-Time Pipeline Accelerator solution provides the software and professional services you need for building data pipelines in a multi-tenant environment for Spark Streaming, Kafka, and Cassandra. With help from the BlueData team, you’ll also have two end-to-end real-time data pipelines as a starting point.
Learn more about BlueData at www.bluedata.com
Processing Real-Time Data at Scale: A streaming platform as a central nervous...confluent
(Marcus Urbatschek, Confluent)
Presentation during Confluent’s streaming event in Munich. This three-day hands-on course focused on how to build, manage, and monitor clusters using industry best-practices developed by the world’s foremost Apache Kafka™ experts. The sessions focused on how Kafka and the Confluent Platform work, how their main subsystems interact, and how to set up, manage, monitor, and tune your cluster.
QuantHouse enables our customers to manage the ever-increasing demand for low latency market data and to meet the changing requirements of today’s trading environment with new trading venues, fragmentation of liquidity and rapidly increasing volumes of data.
Gluon Consulting - Specialized Software Development for FinanceDennis Cabarroguis
Gluon offers specialized software development and consultancy services for fintechs and financial services SMEs.
Our unique delivery model combines London based analysis, project management and QA with delivery from our team of talented developers in the Philippines.
Results, service and care levels are those you would expect from the best front-office tech teams in London, New York and Silicon Valley. Costs? Refreshingly close to your average total outsourcing initiative, but without the risk and the hassle.
OVER 40 YEARS OF EXPERIENCE IN LONDON
Our core team members are veteran software consultants and enterprise architects with a combined 40 years of experience writing high-performance, robust and scalable software for some of the world's largest financial organizations and independent technology providers.
TECH BEFORE FINTECH
In our journeys, we built trading and portfolio analytics platforms, distributed and parallel calculation and workflow engines, high volume messaging middleware, dashboards with advanced interaction and visualization features. We did numerical and statistical computing, machine learning and semantic processing.
We produced real-time, interactive scenario analysis for one of the most profitable trading desks on the planet. We helped e-commerce and brokerage companies to scale their operations without breaking a sweat. We contributed to pioneering robotics and field automation platforms before IoT and event streams were cool.
For more info, please contact
Dennis Cabarroguis
dennis.cabarroguis@gluonconsulting.com
Apache Kafka® + Machine Learning for Supply Chain confluent
Watch this talk here: https://www.confluent.io/online-talks/apache-kafka-machine-learning-for-supply-chain
Automating multifaceted, complex workflows requires hybrid solutions like streaming analytics of IoT data, batch analytics like machine learning solutions, and real-time visualizations. Leaders in organizations who are responsible for global supply chain planning are responsible for working with and integrating with data from disparate sources around the world. Many of these data sources output information in real-time, which assists planners in operationalizing plans and interacting with manufacturing output. IoT sensors on manufacturing equipment and inventory control systems feed real-time processing pipelines to match actual production figures against planned schedules to calculate yield efficiency.
Using information from both real-time systems and batch optimization, supply chain managers are able to economize operations and automate tedious inventory and manufacturing accounting processes. Sitting on top of all these systems is a supply chain visualization tool, enabling users' visibility over the global supply chain. If you are responsible for key data integration initiatives, join for a detailed walk through of a customer's use of this system built using Confluent and Expero tools.
WHAT YOU'LL LEARN:
• See different use cases in automation industry and Industrial IoT (IIoT) where an event streaming platform adds business value.
• Understand different architecture options to leverage Apache Kafka and Confluent.
• How to leverage different analytics tools and machine learning frameworks in a flexible and scalable way.
• How real-time visualization ties together streaming and batch analytics for business users, interpreters, and analysts.
• Understand how streaming and batch analytics optimize the supply chain planning workflow.
• Conceptualize the intersection between resource utilization and manufacturing assets with long term planning and supply chain optimization.
IIoT with Kafka and Machine Learning for Supply Chain Optimization In Real Ti...Kai Wähner
I did a webinar with Confluent's partner Expero about "Apache Kafka and Machine Learning for Real Time Supply Chain Optimization". This is a great example for anybody in automation industry / Industrial IoT (IIoT) like automotive, manufacturing, logistics, etc.
We explain how a real time event streaming platform can integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database (like AWS S3, Snowflake or MongoDB) or analytic / machine learning framework (like TensorFlow, PyTorch or Azure Machine Learning Service).
QuantHouse enables our customers to manage the ever-increasing demand for low latency market data and to meet the changing requirements of today’s trading environment with new trading venues, fragmentation of liquidity and rapidly increas¬ing volumes of data, QuantHouse has developed an end-to-end product offering encompassing data capture within the exchange, ultra-fast data normalization and dissemination over QuantHouse’s proprietary fibre optic network.
Thomas Weise, Apache Apex PMC Member and Architect/Co-Founder, DataTorrent - ...Dataconomy Media
Thomas Weise, Apache Apex PMC Member and Architect/Co-Founder of DataTorrent presented "Streaming Analytics with Apache Apex" as part of the Big Data, Berlin v 8.0 meetup organised on the 14th of July 2016 at the WeWork headquarters.
70% less troubleshooting time and reduced network operation costsComputaris
The use case sets the business scenario for extensive automation of telecom network operations to enhance network visibility and monitoring, failure pattern recognition and proactive network fault detection. The end benefits lie in improved network performance, reduced network operation costs, better subscriber experience and reduced churn.
https://www.computaris.com/70-less-troubleshooting-time-and-reduced-network-operation-costs/
DevOps and 5G cloud native solutions supported by Computaris automated testin...Computaris
Looking ahead to future projects in the area of cloud and 5G, read about Computaris TOP Testing Suite as a key tool in the client’s technology roadmap.
Complex cloudification: Porting bare metal apps to telco cloud vnfComputaris
Case study regarding the complex cloudification of sensitive core applications. The project consisted in porting a collection of bare metal applications in the core network of tier-1 operator to telco cloud VNF.
Romanian software market statistics and forecastComputaris
Infographic about the general context of the software industry in Romania and how it can favour the growth of the product development segment. Based on the “Software & IT Services in Romania 2017” report, published by ANIS Romania.
The benefits of using the rules engine paradigm in telco systems Computaris
The presentation discusses the benefits of implementing the rule engines in telecom IT systems to achieve high solution flexibility, ease of use and cost effectiveness for the operators.
It also shares from the Computaris experience with implementing open source products such as CLIPS and DROOLS in telecom projects including SMS router, SS7 firewall, real time antifraud systems.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
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2. Customer profile
The customer operates on the market for IP traffic classification
and network intelligence technology used in physical, SDN and
NFV architectures. The company provides software for vendors
who embed real-time application visibility in their products for traffic
optimization, service chaining, quality of service, analytics, cyber
security, etc.
The company is based in Paris, France, and has offices in Santa
Clara, CA, Singapore and Tokyo.
Business challenge
The customer turned to Computaris for a proof of concept in
developing an analytics solution for large datacenter network
traffic.
The challenge encountered by the customer’s development team
was the particularly large volume of information which needed to
be stored. The objective was to store up to 90% of 6 million
information per minute for a “live period” of 10 days or the
equivalent of 5TB of information (the system’s limit), whichever
occurred first.
Computaris contribution and solution
Computaris undertook the consulting and development role in
finding, proposing and building a viable solution to the customer’s
challenge.
The solution consisted of deep packet inspection (DPI) probes
collecting traffic information and sending all data to a Kafka cluster
and aggregated it for extracting relevant data using specific
widgets with specific filters and on different periods of time.
Computaris experts tested for different technologies, finally
suggesting an innovative solution based on a combination of
Apache Kafka and Elasticsearch, with stream processing custom
Java implementation based on Kafka Consumer Groups, and
distributed stateless Java applications (running at least 5 times
faster than a Spark streaming based implementation).
Thus the solution was designed and proven to achieve high
performance parameters, such as:
- ingestion speed at 150,000 records per second;
- 90,000 records per second inserted in Elasticsearch;
- 5 concurrent users being able to view auto-refreshing
dashboards with complex aggregations.
Combining their expertise in the latest technologies with a thorough
understanding of the customer’s business case, Computaris
specialists succeeded to develop and implement an innovative
solution to the challenges faced by the client’s own development
team. In addition to the solid technical skills, the customer highly
appreciated Computaris’ innovative approach and valuable role as
a consulting partner.
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Computaris builds solution for analytics of large datacenter network traffic