SQL-based databases have been around for decades and they power a wide range of applications. So what exactly do NoSQL databases bring to the table? In this webcast, you'll find out how NoSQL can liberate your development cycle, allow your application to scale and improve your system's uptime.
In the world of NoSQL, each database has its own strengths and weaknesses. Understanding which open source database is "the right tool for the job" is half the battle if you want to start building better applications quickly. IBM developer advocate Glynn Bird explores practical examples of how two popular NoSQL databases - the Cloudant JSON document store and the Redis in-memory key-value store - can be used together to create performant and scalable Web applications. It also includes real world use cases you can try today, for free, using the IBM Cloud Data Services suite of fully managed NoSQL databases-as-a-service.
Find out how NoSQL can help your application with practical examples and use-cases from our Cloud Data Services Developer Advocate Glynn Bird. This webinar won't dwell on the science behind the database, but will walk you through real-life use-cases for NoSQL technologies that you can start using today.
Webinar: https://youtu.be/M_Jqw
Learn what you need to consider when moving from the world of relational databases to a NoSQL document store.
Hear from Developer Advocate Glynn Bird as he explains the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
Build 2017 - P4010 - A lap around Azure HDInsight and Cosmos DB Open Source A...Windows Developer
Recently, we released the Spark Connector for our distributed NoSQL service – Azure Cosmos DB (formerly known as Azure DocumentDB). By connecting Apache Spark running on top Azure HDInsight to Azure Cosmos DB, you can accelerate your ability to solve fast-moving data science problems and machine learning. The Spark to Azure Cosmos DB connector efficiently exploits the native Cosmos DB managed indexes and enables updateable columns when performing analytics, push-down predicate filtering against fast-changing globally-distributed data, ranging from IoT, data science, and analytics scenarios. Come learn how you can perform blazing fast planet-scale data processing with Azure Cosmos DB and HDInsight.
In the world of NoSQL, each database has its own strengths and weaknesses. Understanding which open source database is "the right tool for the job" is half the battle if you want to start building better applications quickly. IBM developer advocate Glynn Bird explores practical examples of how two popular NoSQL databases - the Cloudant JSON document store and the Redis in-memory key-value store - can be used together to create performant and scalable Web applications. It also includes real world use cases you can try today, for free, using the IBM Cloud Data Services suite of fully managed NoSQL databases-as-a-service.
Find out how NoSQL can help your application with practical examples and use-cases from our Cloud Data Services Developer Advocate Glynn Bird. This webinar won't dwell on the science behind the database, but will walk you through real-life use-cases for NoSQL technologies that you can start using today.
Webinar: https://youtu.be/M_Jqw
Learn what you need to consider when moving from the world of relational databases to a NoSQL document store.
Hear from Developer Advocate Glynn Bird as he explains the key differences between relational databases and JSON document stores like Cloudant, as well as how to dodge the pitfalls of migrating from a relational database to NoSQL.
Build 2017 - P4010 - A lap around Azure HDInsight and Cosmos DB Open Source A...Windows Developer
Recently, we released the Spark Connector for our distributed NoSQL service – Azure Cosmos DB (formerly known as Azure DocumentDB). By connecting Apache Spark running on top Azure HDInsight to Azure Cosmos DB, you can accelerate your ability to solve fast-moving data science problems and machine learning. The Spark to Azure Cosmos DB connector efficiently exploits the native Cosmos DB managed indexes and enables updateable columns when performing analytics, push-down predicate filtering against fast-changing globally-distributed data, ranging from IoT, data science, and analytics scenarios. Come learn how you can perform blazing fast planet-scale data processing with Azure Cosmos DB and HDInsight.
LinkedIn's Logical Data Access Layer for Hadoop -- Strata London 2016Carl Steinbach
An overview of Dali, LinkedIn's logical data access layer for Hadoop. Dali provides cluster and version-independent access to HDFS filesystems, a dataset API that supports virtualized datasets and dataset versioning, and explicit contract management governing the evolution of datasets.
Slides from workshop held on 12/14 in Asbury Park, NJ
http://www.meetup.com/Jersey-Shore-Tech/events/148118762/?gj=ro2_e&a=ro2_gnl&rv=ro2_e&_af_eid=148118762&_af=event
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups.
Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik.
Agenda:
• Partitioned tables
• The ability to update, delete rows and columns using SQL
• Integration with IAM for fine-grained security policies
• Monitoring w/ StackDriver to track performance and usage
• Query sharing via links, to foster knowledge within orgs
• Cost optimisation strategies
A fotopedia presentation made at the MongoDay 2012 in Paris at Xebia Office.
Talk by Pierre Baillet and Mathieu Poumeyrol.
French Article about the presentation:
http://www.touilleur-express.fr/2012/02/06/mongodb-retour-sur-experience-chez-fotopedia/
Video to come.
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.
Performance comparison: Multi-Model vs. MongoDB and Neo4jArangoDB Database
Native multi-model databases combine different data models like documents or graphs in one tool and even allow to mix them in a single query. How can this concept compete with a pure document store like MongoDB or a graph database like Neo4j? I myself and a lot of folks in the community asked that question.
So here are some benchmark results.
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
How to get the best of both: MongoDB is great for low latency quick access of recent data; Treasure Data is great for infinitely growing store of historical data. In the latter case, one need not worry about scaling.
Building tiered data stores using aesop to bridge sql and no sql systemsRegunath B
Slides from my talk on building tiered data stores using Aesop to bridge SQL and NoSQL data stores. Aesop is a pub-sub like change data capture and propagation system.
Following the classical software architecture patterns we tend to design large monolith of software applications.
These monoliths are typically quite difficult to scale as they often require powerful machines, making the option to scale out very expensive.
In most cases these monoliths of software are designed to run on a single machine only, hence scaling out is complicated or even impossible without refactoring large portions of the application.
Therefore a new design pattern called microservices arose.
The pattern of microservices keeps the need of a clustered server setup in mind and helps to keep the application very modular.
This allows to simplify a scale out of your application and even allows to scale the bottlenecks of your application only and hence reducing the total cost for a scale out approach.
In this talk I will introduce the concept of microservices, how they are defined and how to design an application with them.
Furthermore I will show how to scale the application properly and why this is only possible due to the use of microservices.
Also we will have a look at Node.js and why it is a perfect, though not the only, fit to this design strategy.
However scaling is not the only purpose of microservices, they also increase the flexibility and maintainability of applications, this will also be discussed in the talk.
BM Cloudant is a NoSQL Database-as-a-Service. Discover how you can outsource the data layer of your mobile or web application to Cloudant to provide high availability, scalability and tools to take you to the next level.
LinkedIn's Logical Data Access Layer for Hadoop -- Strata London 2016Carl Steinbach
An overview of Dali, LinkedIn's logical data access layer for Hadoop. Dali provides cluster and version-independent access to HDFS filesystems, a dataset API that supports virtualized datasets and dataset versioning, and explicit contract management governing the evolution of datasets.
Slides from workshop held on 12/14 in Asbury Park, NJ
http://www.meetup.com/Jersey-Shore-Tech/events/148118762/?gj=ro2_e&a=ro2_gnl&rv=ro2_e&_af_eid=148118762&_af=event
Can No-SQL technologies hold for the specific requirements that apply to the Telco domain?
This is the Slideshare Presentation by Ericsson Researcher Nicolas Seyvet to accompany his blog "NoSQL for Telco"
http://labs.ericsson.com/blog/nosql-for-telco
Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups.
Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik.
Agenda:
• Partitioned tables
• The ability to update, delete rows and columns using SQL
• Integration with IAM for fine-grained security policies
• Monitoring w/ StackDriver to track performance and usage
• Query sharing via links, to foster knowledge within orgs
• Cost optimisation strategies
A fotopedia presentation made at the MongoDay 2012 in Paris at Xebia Office.
Talk by Pierre Baillet and Mathieu Poumeyrol.
French Article about the presentation:
http://www.touilleur-express.fr/2012/02/06/mongodb-retour-sur-experience-chez-fotopedia/
Video to come.
MongoDB has been conceived for the cloud age. Making sure that MongoDB is compatible and performant around cloud providers is mandatory to achieve complete integration with platforms and systems. Azure is one of biggest IaaS platforms available and very popular amongst developers that work on Microsoft Stack.
Performance comparison: Multi-Model vs. MongoDB and Neo4jArangoDB Database
Native multi-model databases combine different data models like documents or graphs in one tool and even allow to mix them in a single query. How can this concept compete with a pure document store like MongoDB or a graph database like Neo4j? I myself and a lot of folks in the community asked that question.
So here are some benchmark results.
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
How to get the best of both: MongoDB is great for low latency quick access of recent data; Treasure Data is great for infinitely growing store of historical data. In the latter case, one need not worry about scaling.
Building tiered data stores using aesop to bridge sql and no sql systemsRegunath B
Slides from my talk on building tiered data stores using Aesop to bridge SQL and NoSQL data stores. Aesop is a pub-sub like change data capture and propagation system.
Following the classical software architecture patterns we tend to design large monolith of software applications.
These monoliths are typically quite difficult to scale as they often require powerful machines, making the option to scale out very expensive.
In most cases these monoliths of software are designed to run on a single machine only, hence scaling out is complicated or even impossible without refactoring large portions of the application.
Therefore a new design pattern called microservices arose.
The pattern of microservices keeps the need of a clustered server setup in mind and helps to keep the application very modular.
This allows to simplify a scale out of your application and even allows to scale the bottlenecks of your application only and hence reducing the total cost for a scale out approach.
In this talk I will introduce the concept of microservices, how they are defined and how to design an application with them.
Furthermore I will show how to scale the application properly and why this is only possible due to the use of microservices.
Also we will have a look at Node.js and why it is a perfect, though not the only, fit to this design strategy.
However scaling is not the only purpose of microservices, they also increase the flexibility and maintainability of applications, this will also be discussed in the talk.
BM Cloudant is a NoSQL Database-as-a-Service. Discover how you can outsource the data layer of your mobile or web application to Cloudant to provide high availability, scalability and tools to take you to the next level.
MongoDB Schema Design: Practical Applications and ImplicationsMongoDB
Presented by Austin Zellner, Solutions Architect, MongoDB
Schema design is as much art as it is science, but it is central to understanding how to get the most out of MongoDB. Attendees will walk away with an understanding of how to approach schema design, what influences it, and the science behind the art. After this session, attendees will be ready to design new schemas, as well as re-evaluate existing schemas with a new mental model.
This is a run-through at a 200 level of the Microsoft Azure Big Data Analytics for the Cloud data platform based on the Cortana Intelligence Suite offerings.
MongoDB ne fonctionne pas comme les autres bases de données. Son modèle de données orienté documents, son partitionnement en gammes et sa cohérence forte sont bien adaptés à certains problèmes et moins adaptés à d'autres. Dans ce séminaire Web, nous étudierons des exemples réels d'utilisation de MongoDB mettant à profit ces fonctionnalités uniques. Nous évoquerons le cas de clients spécifiques qui utilisent MongoDB et nous verrons la façon dont ils ont implémenté leur solution. Nous vous montrerons également comment construire une solution du même type pour votre entreprise.
MongoDb is a document oriented database and very flexible one as it gives horizontal scalability.
In this presentation basic study about mongodb with installation steps and basic commands are described.
Webinar: Enterprise Data Management in the Era of MongoDB and Data LakesMongoDB
With so much talk of how Big Data is revolutionizing the world and how a data lake with Hadoop and/or Spark will solve all your data problems, it is hard to tell what is hype, reality, or somewhere in-between.
In working with dozens of enterprises in varying stages of their enterprise data management (EDM) strategy, MongoDB enterprise architect, Matt Kalan, sees the same challenges and misunderstandings arise again and again.
In this session, he will explain common challenges in data management, what capabilities are necessary, and what the future state of architecture looks like. MongoDB is uniquely capable of filling common gaps in the data lake strategy.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
Technical feature review of features introduced by MongoDB 3.4 on graph capabilities, MongoDB UI tool: Compass, improvements on the replication and aggregation framework stages and utils. Operations improvements on Ops Manager and MongoDB Atlas.
QuerySurge Slide Deck for Big Data Testing WebinarRTTS
This is a slide deck from QuerySurge's Big Data Testing webinar.
Learn why Testing is pivotal to the success of your Big Data Strategy .
Learn more at www.querysurge.com
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data, Hadoop and NoSQL. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data warehouse - all with one ETL testing tool.
This information is geared towards:
- Big Data & Data Warehouse Architects,
- ETL Developers
- ETL Testers, Big Data Testers
- Data Analysts
- Operations teams
- Business Intelligence (BI) Architects
- Data Management Officers & Directors
You will learn how to:
- Improve your Data Quality
- Accelerate your data testing cycles
- Reduce your costs & risks
- Provide a huge ROI (as high as 1,300%)
Since GeoJSON is a standard for storing geographic data in JSON format, it is a best practice to adhere to this format when storing geo-coordinates in Cloudant and CouchDB.
The concept of data movement lies at the heart of Apache CouchDB. CouchDB’s replication protocol lets developers synchronize copies of their data to remote CouchDB-based systems – including Cloudant – at the push of a button. Replication jobs can also run continuously, and in both directions.
Mango allows users to declaratively define and query Apache CouchDB indexes. Mango leverages Lucene not only to perform text search, but also to enable ad-hoc querying capabilities.
CouchDB is a document database. It stores JSON objects with a few special field names. The _id field represents a unique identifier for a document. The _rev field is the revision marker for a document. The _rev field is used for Multi-Version Concurrency Control, a form of optimistic concurrency.
Apache CouchDB is accessed through an HTTP API. HTTP Basic authentication is a simple way to authenticate with an HTTP server. Other approaches, such as cookies and OAuth, are often used as well.
For more than 10 years, developers have relied on Apache(R) CouchDB(TM) - a versatile and highly scalable open source database - to build apps for web, mobile and IoT platforms.
The release of CouchDB 2.0 in 2016 has generated even more interest in the freely available JSON database, which now includes clustering capabilities contributed from IBM Cloudant for high availability and performance.
IBM Cloudant describe the geospatial tools used in their database-as-a-service offering (DBaaS). Based upon Apache CouchDB, the geospatial extensions used by IBM Cloudant rely on a number of well known open source libraries to provide geospatial indexing, query and projection support to Apache CouchDB. Discussion topics include:
- Overview of the architecture & tools
- Best practices for building geospatial apps with NoSQL doc stores
- Use cases for leveraging geospatial capabilities of a NoSQL doc store
John Park, Offering Manager, for IBM Cloud Data Services covers the touchstones for tomorrow’s information systems: data and integration. Stovepipe applications are no longer acceptable, and siloed data sources must evolve and open up to the full enterprise. All this in an environment where more is expected faster, and at a lower cost. If your GIS doesn’t watch out, it will be replaced by less capable alternatives that “fit better” into mainstream IT. But dashDB, a cloud-native offspring of DB2, can provide a bridge that keeps both sides happy. This session introduce this popular cloud data warehousing solution and illustrate how it works in concert with ArcGIS. You will learn about the built-in geospatial functions in dashDB and how you can easily use them to build applications rapidly. You’ll see an application that uses weather data and mobile application data to calculate insurance risk, detect potential fraud, and prevent damage.
Our March 2, 2016 event featured Billy Beane, Executive Vice President of Baseball Operations at the Oakland As and Derek Schoettle, GM of Analytics Platform Services at IBM. Billy and Derek shared their experiences of how professional sports teams and businesses alike are gaining hidden insights and competitive advantages by using the latest data discovery techniques and platforms.
Presented by David Taieb, Architect, IBM Cloud Data Services
Along with Spark Streaming, Spark SQL and GraphX, MLLib is one of the four key architectural components of Spark. It provides easy-to-use (even for beginners), powerful Machine Learning APIs that are designed to work in parallel using Spark RDDs. In this session, we’ll introduce the different algorithms available in MLLib, e.g. supervised learning with classification (binary and multi class) and regression but also unsupervised learning with clustering (K-means) and recommendation systems. We’ll conclude the presentation with a deep dive on a sample machine learning application built with Spark MLLib that predicts whether a scheduled flight will be delayed or not. This application trains a model using data from real flight information. The labeled flight data is combined with weather data from the “Insight for Weather” service available on IBM Bluemix Cloud Platform to form the training, test and blind data. Even if you are not a black belt in machine learning, you will learn in this session how to leverage powerful Machine Learning algorithms available in Spark to build interesting predictive and prescriptive applications.
About the Speaker: For the last 4 years, David has been the lead architect for the Watson Core UI & Tooling team based in Littleton, Massachusetts. During that time, he led the design and development of a Unified Tooling Platform to support all the Watson Tools including accuracy analysis, test experiments, corpus ingestion, and training data generation. Before that, he was the lead architect for the Domino Server OSGi team responsible for integrating the eXpeditor J2EE Web Container in Domino and building first class APIs for the developer community. He started with IBM in 1996, working on various globalization technologies and products including Domino Global Workbench (used to develop multilingual Notes/Domino NSF applications) and a multilingual Content Management system for the Websphere Application Server. David enjoys sharing his experience by speaking at conferences. You’ll find him at various events like the Unicode conference, Eclipsecon, and Lotusphere. He’s also passionate about building tools that help improve developer productivity and overall experience.
Mobile web apps shouldn't stop working when there's no network connection. Offline-enabled apps built using PouchDB can provide a better, faster user experience while potentially reducing battery and bandwidth usage.
Hear from Developer Advocate Glynn Bird to find out how to use the HTML5 Offline Application Cache, PouchDB, IBM Cloudant and Cordova/PhoneGap to develop fully-featured and cross-platform native apps and responsive mobile web apps that work just as well offline as they do online.
Cloud and Software as a Service (SaaS) can make a huge impact on a business. Unfortunately, most start the evaluation of SaaS from an IT perspective and traditional data center advantages (i.e. on-premises costs, staffing and savings). While savings are important, cloud is about agility and speed. For these reasons, line-of-business (LOB) leaders have been more interested in SaaS solutions. Learn how Cognos Business Intelligence on Cloud and IBM dashdb make it simple to get started with collaboration, reporting and analytics.
Many Oracle pros are looking to take their data warehousing strategy to the cloud, but have been waiting for a cloud solution that offers both compatibility and ease of use. Well, the wait is over - with IBM dashDB, you can leverage your existing Oracle (as well as SQL) application skills, and get all the cost, scalability and performance advantages of a fully managed data warehousing service in the IBM Cloud.
Learn about IBM's Hadoop offering called BigInsights. We will look at the new features in version 4 (including a discussion on the Open Data Platform), review a couple of customer examples, talk about the overall offering and differentiators, and then provide a brief demonstration on how to get started quickly by creating a new cloud instance, uploading data, and generating a visualization using the built-in spreadsheet tooling called BigSheets.
dashDB Enterprise MPP is a new fully managed cloud data warehouse service with massive scale and performance. Powered by IBM's network cluster architecture, dashDB MPP is an easy to use, self service solution for building: standalone data warehouses; data science data marts; hybrid warehousing; development and QA environments; and analytics for NoSQL. It is available through IBM Bluemix along with IBM's other Cloud Data Services, including Cloudant and SQL DB.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
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."
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
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.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
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/
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
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!
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.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
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
5. RDBMs
Relational Database Management Systems
SQL language developed by IBM in the 1970s
RDBMs power lots of IT systems
Oracle, IBM DB2, MySQL, PostgreSQL etc
5
10. SQL vs NoSQL - Development Cycle
Build
Migrate staging database
Test
Migrate production
Deploy
10
Build
Test
Deploy
11. Database migrations are costly
Adding/updating/deleting columns
May cause interruption to service
Often performed "out of hours"
Have to be carefully planned in multi-server deployments
11
15. Scaling a Cloudant database
15
• Database-as-a-Service
• Free/PAYG/Dedicated/Local
• Sign up and start using
• Scale by adding nodes
• More data
• More concurrency
19. SQL
19
SELECT * from users
LEFT JOIN socialmediaprofiles
ON users.userid =
socialmediaprofiles.userid
WHERE registration_date > "2015-01-01"
AND verified = true
AND socialmedia = true
ORDER BY registration_date
24. 24
CRUD – Document Primary
Index
Secondary Index
(view)
Search
Index
GeoSpatial Index Cloudant
Query
• Direct document
look up by _id
• Exists “OOTB”
• stored in a b-tree
• Primary key
doc._id
• Built using
MapReduce
• stored in a b-tree
• Key user-
defined field(s)
• Built using Lucene
• FTI: Any or all
fields can be
indexed
• stored in R*, TPR,
KD tree
• Lat/Long
coorindates in
GeoJSON
• “Mongo-style”
querying
• Built natively in
erlang
• Use when you
want a single
document and
can find by its _id
• Use when you can
find documents
based on their _id
• Pull back a range
of keys
• Use when you
need to analyze
data or get a
range of keys
• Ex: count data
fields,
sum/average
numeric results,
advanced stats,
group by date,
etc.
• Ad-hoc queries
• Find documents
based on their
contents
• Can do groups,
facets, and basic
geo queries (bbox
& sort by
distance)
• Complex
geometries
(polygon,
circularstring, etc.)
• Advanced
relations
(intersect,
overlaps, etc.)
• Ad-hoc queries
• Lots of operators
(>, <, IN, OR,
AND, etc.)
• Intuitive for people
coming from
Mongo or SQL
backgrounds
26. Cloudant Replication
26
• Replicate data from one cluster to another
• Replicate data to browser/mobile and back
• No data loss
• Offline-first apps/websites
• http://www.glynnbird.com/
28. Simple Search Service
Free, open-source Bluemix App – install
with one click
Upload your .csv or .tsv
– Imports data into Cloudant
– Indexes everything for search
– Presents HTTP Search API
Demo!
28
https://developer.ibm.com/clouddataservices/simple-search-service/
31. Cloudant use-cases
Big Data – Large data sets
Scalable operational data store
Search – faceted, full-text search
Geo-spatial – geographic, GIS systems, GeoJSON
Offline-first – replicating data to mobile devices
31