We need a set o tools for monitoring user activities on a Plone site. This presentation is a quick overview on what we have now and what we want for the future.
Plog2014 - Saucelabs - a perspective on tiles to empower your plone editorssimahawk
Overview on sauceslabs.com migration to Plone CMS.
The official public website is in the process o migrating to Plone. We empowered their editors using Plone and a custom interface for building composite pages with predefined tiles.
Doxia Web Design can create a variety of websites including e-commerce sites, small business sites, portfolio sites, and more. They offer website design, development, hosting, and maintenance services. Their goal is to help businesses and individuals create an attractive, user-friendly website to meet their goals and needs.
Cassandra stands out amongst the big data products in its ability to handle optimized writes of large amounts of data while providing configurable fault tolerance and data integrity. Two popular libraries that allow the JVM developer to leverage these capabilities are Hector and the recently open sourced Astyanax. In this talk, Joe presents examples of storing time series data in a Cassandra data store using both of these libraries. There will be code! As an added bonus, a mechanism to unit test using an embedded Cassandra client will be presented.
Code can be downloaded from https://github.com/jmctee/Cassandra-Client-Tutorial
Plog2014 - Saucelabs - a perspective on tiles to empower your plone editorssimahawk
Overview on sauceslabs.com migration to Plone CMS.
The official public website is in the process o migrating to Plone. We empowered their editors using Plone and a custom interface for building composite pages with predefined tiles.
Doxia Web Design can create a variety of websites including e-commerce sites, small business sites, portfolio sites, and more. They offer website design, development, hosting, and maintenance services. Their goal is to help businesses and individuals create an attractive, user-friendly website to meet their goals and needs.
Cassandra stands out amongst the big data products in its ability to handle optimized writes of large amounts of data while providing configurable fault tolerance and data integrity. Two popular libraries that allow the JVM developer to leverage these capabilities are Hector and the recently open sourced Astyanax. In this talk, Joe presents examples of storing time series data in a Cassandra data store using both of these libraries. There will be code! As an added bonus, a mechanism to unit test using an embedded Cassandra client will be presented.
Code can be downloaded from https://github.com/jmctee/Cassandra-Client-Tutorial
- Prashant Agrawal has over 5 years of experience as a Big Data Analyst with expertise in log analytics, search engine solutions, and ETL using tools like Spark, Elasticsearch, Logstash, and Kibana.
- He has strong skills in distributed computing systems like Hadoop, Spark, and working with Hortonworks Data Platform clusters.
- His projects include log analytics and visualization using ELK, data lake modules in Spark, Spark ETL, and developing a big data platform for predictive analysis of system logs.
Spark is used to perform in-memory transformations on customer data collected by Totango to generate analytics and insights. Luigi is used as a workflow engine to manage dependencies between batch processing tasks like metrics generation, health scoring, and alerting. The tasks are run on Spark and output to S3. A custom Gameboy controller provides monitoring and management of the Luigi workflow.
Developing Spatial Applications with CARTO for React v1.1CARTO
In this hands-on webinar, we introduce the new features of CARTO for React v1.1 and showcase how this framework can be used to accelerate the development of cloud-native geospatial applications. You can watch the recorded webinar at: https://go.carto.com/webinars/carto-react-developers
21 people attended the July 2014 program meeting hosted by BDPA Cincinnati chapter. The topic was 'Open Source Tools and Resources'. The guest speaker was Greg Greenlee (Blacks In Technology).
'Open source' refers to a computer program in which the source code is available to the general public for use or modification from its original design. Open source code is typically created as a collaborative effort in which programmers improve upon the code and share the changes within the community. Open source sprouted in the technological community as a response to proprietary software owned by corporations. Over 85% of enterprises are using open source software. Managers are quickly realizing the benefit that community-based development can have on their businesses. This month, we put on our geek hats and detective gloves to learn how we can monitor our computers’ environments using open source tools. This meetup covered some of the most popular ‘Free and Open Source Software’ (FOSS) tools used to monitor various aspects of your computer environment.
What are the basic key points to focus on while learning Full-stack web devel...kzayra69
Mastering full-stack web development with Django involves Python fundamentals, HTML/CSS/JavaScript, Django basics, database management, and deployment, with Django's template language simplifying dynamic content rendering and promoting code maintainability.
OSMC 2022 | Unifying Observability Weaving Prometheus, Jaeger, and Open Sourc...NETWAYS
Observability is a hugely popular topic, however, for open-source users, significant challenges remain. For starters, related licensing is frequently problematic—and even when it works, there is no pure Apache 2.0 licensed technology to get data collection and visibility into your logs, metrics, and traces. Thankfully, this is gradually changing as the community builds new capabilities into OpenSearch Dashboards to unify the visualization of logs from OpenSearch, metrics from PromQL compatible systems, and traces from Jaeger. In this session, we’ll examine how this important project is evolving as a fork of the previously popular ELK stack. We’ll also take a closer look at the current state of OpenSearch and Jaeger and discuss how these efforts are going to provide a foundation for unified observability to the open-source communities. By using OpenTelemetry for data collection, this foundation provides a pure Apache 2.0 licensed open-source platform for unified observability. OpenSearch also includes features like Alerting and Machine Learning, which are not part of Jaeger today. The work on this foundational integration is well underway and will provide open-source users with a solid alternative to vendor controlled and provided solutions. This also opens up the marketplace for solutions to be created to host and manage these at scale, something we’ve seen with countless other CNCF projects. This talk will be presented by a contributor and maintainer of OpenSearch, Jaeger, and OpenTelemetry, which are all vibrant user communities. Join the conversation!
PostgreSQL Finland October meetup - PostgreSQL monitoring in ZalandoUri Savelchev
This document discusses PostgreSQL monitoring at Zalando. Zalando migrated their PostgreSQL databases to AWS RDS in 2015 and later began using the PostgreSQL operator to deploy PostgreSQL clusters on Kubernetes. Zalando's monitoring system, ZMON, is used to collect metrics from Kubernetes, AWS, and PostgreSQL internal views to monitor infrastructure and databases. The ZMON workers run in each Kubernetes cluster and use separate credentials to connect to databases and query views and tables while respecting explicit permissions.
ELK Stack Online Training - Elasticsearch Online Training Course.pptxeshwarvisualpath
Visualpath is the best ELK Stack Online Training, and Providing Elasticsearch Online Training Course with Real-Time trainers.VisualPath has good placement record. We are providing material, interview questions & Real time projects. Schedule a Demo! Call on +91-9989971070.
Visit: https://visualpath.in/elk-stack-online-training.html
WhatsApp: https://www.whatsapp.com/catalog/917032290546/
Visit Blog: https://visualpathblogs.com/
Applying graph analytics on data stored in relational databases can provide tremendous value in many application domains. We discuss the importance of leveraging these analyses, and the challenges in enabling them. We present a tool, called GraphGen, that allows users to visually explore, and rapidly analyze (using NetworkX) different graph structures present in their databases.
GraphGen: Conducting Graph Analytics over Relational DatabasesPyData
This document discusses GraphGen, a tool for conducting graph analytics over relational databases. It begins by introducing graph analytics and its applications. It then discusses the current state of graph analytics, which is fragmented with no single solution. Most organizations store data relationally and have "hidden" graphs that can be extracted. GraphGen provides a declarative language to define nodes and edges to extract these graphs without ETL. It supports various interfaces like Java, Python, and a web application to enable graph analytics over relational data in an intuitive way.
Integrating Structured Data (to an SEO Plan) for the Win _ WTSWorkshop '23.pptxBegum Kaya
This document provides an overview of structured data and how to plan and implement it effectively. It discusses the giant global graph and semantic web concepts. Schema.org is introduced as a way to add structured data tags to pages. The benefits of structured data like improved rankings and user experience are outlined. The document then covers how to plan structured data by auditing pages, identifying appropriate schema types and properties. Implementation tips around templating, testing and monitoring structured data are provided. Common pitfalls to avoid are also highlighted.
Data Science Salon: A Journey of Deploying a Data Science Engine to ProductionFormulatedby
Presented by Mostafa Madjipour., Senior Data Scientist at Time Inc.
Next DSS NYC Event 👉 https://datascience.salon/newyork/
Next DSS LA Event 👉 https://datascience.salon/la/
Reducing the gap between R&D and production is still a challenge for data science/ machine learning engineering groups in many companies. Typically, data scientists develop the data-driven models in a research-oriented programming environment (such as R and python). Next, the data/machine learning engineers rewrite the code (typically in another programming language) in a way that is easy to integrate with production services.
This process has some disadvantages: 1) It is time consuming; 2) slows the impact of data science team on business; 3) code rewriting is prone to errors.
A possible solution to overcome the aforementioned disadvantages would be to implement a deployment strategy that easily embeds/transforms the model created by data scientists. Packages such as jPMML, MLeap, PFA, and PMML among others are developed for this purpose.
In this talk we review some of the mentioned packages, motivated by a project at Time Inc. The project involves development of a near real-time recommender system, which includes a predictor engine, paired with a set of business rules.
This document discusses ways to optimize logging by centralizing and proactively using log data. It recommends using Monolog to log from application code in a standardized format. Rsyslog can then collect logs centrally from applications and systems. Logstash can further process logs with filters and output them to destinations like Elasticsearch. Graylog2 provides a web interface for powerful log searching, analytics, and alerting. Centralizing, standardizing, and proactively analyzing logs with these open source tools allows for improved monitoring and troubleshooting.
Everybody in our team knows how to create stable and scalable software products. But in this case, we are using Docker... and it really helps us to concentrate on development and spend more time on code review & tests instead of troubleshooting issues with servers.
Enabling IoT Devices’ Hardware and Software Interoperability, IPSO Alliance (...Open Mobile Alliance
Presentation delivered during the Internet of Things World, Santa Clara pre-event workshop by Christian Legare - IPSO Alliance Chairman, Chief of Software Engineering, Micrium (Part of Silicon Labs)
Internet Protocol for Smart Objects (IPSO) is an alliance that, among other things, defines a data model to represent sensor values and attributes. OMA uses IPSO Smart Objects v1.0 as its resource model to expose sensor information to a remote LwM2M Server. From the speaker from IPSO Alliance, you will learn:
● What is an IPSO Smart Object data model
● What do these Objects and Resources look like
● How to create and register your own resources
● What is next for IPSO Alliance
Company Visitor Management System Report.docxfantabulous2024
The document provides an overview of a Company Visitor Management System project. It includes sections on the project introduction, modules, requirements, analysis and design, database tables, implementation, evaluation, and conclusion. The system is a web-based application built with Python, Django, and MySQL to more effectively manage and track company visitors through features like adding visitors, generating reports, and password recovery/management. UML diagrams including use cases, classes, entities, and data flow are included to visualize the system design.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
- Prashant Agrawal has over 5 years of experience as a Big Data Analyst with expertise in log analytics, search engine solutions, and ETL using tools like Spark, Elasticsearch, Logstash, and Kibana.
- He has strong skills in distributed computing systems like Hadoop, Spark, and working with Hortonworks Data Platform clusters.
- His projects include log analytics and visualization using ELK, data lake modules in Spark, Spark ETL, and developing a big data platform for predictive analysis of system logs.
Spark is used to perform in-memory transformations on customer data collected by Totango to generate analytics and insights. Luigi is used as a workflow engine to manage dependencies between batch processing tasks like metrics generation, health scoring, and alerting. The tasks are run on Spark and output to S3. A custom Gameboy controller provides monitoring and management of the Luigi workflow.
Developing Spatial Applications with CARTO for React v1.1CARTO
In this hands-on webinar, we introduce the new features of CARTO for React v1.1 and showcase how this framework can be used to accelerate the development of cloud-native geospatial applications. You can watch the recorded webinar at: https://go.carto.com/webinars/carto-react-developers
21 people attended the July 2014 program meeting hosted by BDPA Cincinnati chapter. The topic was 'Open Source Tools and Resources'. The guest speaker was Greg Greenlee (Blacks In Technology).
'Open source' refers to a computer program in which the source code is available to the general public for use or modification from its original design. Open source code is typically created as a collaborative effort in which programmers improve upon the code and share the changes within the community. Open source sprouted in the technological community as a response to proprietary software owned by corporations. Over 85% of enterprises are using open source software. Managers are quickly realizing the benefit that community-based development can have on their businesses. This month, we put on our geek hats and detective gloves to learn how we can monitor our computers’ environments using open source tools. This meetup covered some of the most popular ‘Free and Open Source Software’ (FOSS) tools used to monitor various aspects of your computer environment.
What are the basic key points to focus on while learning Full-stack web devel...kzayra69
Mastering full-stack web development with Django involves Python fundamentals, HTML/CSS/JavaScript, Django basics, database management, and deployment, with Django's template language simplifying dynamic content rendering and promoting code maintainability.
OSMC 2022 | Unifying Observability Weaving Prometheus, Jaeger, and Open Sourc...NETWAYS
Observability is a hugely popular topic, however, for open-source users, significant challenges remain. For starters, related licensing is frequently problematic—and even when it works, there is no pure Apache 2.0 licensed technology to get data collection and visibility into your logs, metrics, and traces. Thankfully, this is gradually changing as the community builds new capabilities into OpenSearch Dashboards to unify the visualization of logs from OpenSearch, metrics from PromQL compatible systems, and traces from Jaeger. In this session, we’ll examine how this important project is evolving as a fork of the previously popular ELK stack. We’ll also take a closer look at the current state of OpenSearch and Jaeger and discuss how these efforts are going to provide a foundation for unified observability to the open-source communities. By using OpenTelemetry for data collection, this foundation provides a pure Apache 2.0 licensed open-source platform for unified observability. OpenSearch also includes features like Alerting and Machine Learning, which are not part of Jaeger today. The work on this foundational integration is well underway and will provide open-source users with a solid alternative to vendor controlled and provided solutions. This also opens up the marketplace for solutions to be created to host and manage these at scale, something we’ve seen with countless other CNCF projects. This talk will be presented by a contributor and maintainer of OpenSearch, Jaeger, and OpenTelemetry, which are all vibrant user communities. Join the conversation!
PostgreSQL Finland October meetup - PostgreSQL monitoring in ZalandoUri Savelchev
This document discusses PostgreSQL monitoring at Zalando. Zalando migrated their PostgreSQL databases to AWS RDS in 2015 and later began using the PostgreSQL operator to deploy PostgreSQL clusters on Kubernetes. Zalando's monitoring system, ZMON, is used to collect metrics from Kubernetes, AWS, and PostgreSQL internal views to monitor infrastructure and databases. The ZMON workers run in each Kubernetes cluster and use separate credentials to connect to databases and query views and tables while respecting explicit permissions.
ELK Stack Online Training - Elasticsearch Online Training Course.pptxeshwarvisualpath
Visualpath is the best ELK Stack Online Training, and Providing Elasticsearch Online Training Course with Real-Time trainers.VisualPath has good placement record. We are providing material, interview questions & Real time projects. Schedule a Demo! Call on +91-9989971070.
Visit: https://visualpath.in/elk-stack-online-training.html
WhatsApp: https://www.whatsapp.com/catalog/917032290546/
Visit Blog: https://visualpathblogs.com/
Applying graph analytics on data stored in relational databases can provide tremendous value in many application domains. We discuss the importance of leveraging these analyses, and the challenges in enabling them. We present a tool, called GraphGen, that allows users to visually explore, and rapidly analyze (using NetworkX) different graph structures present in their databases.
GraphGen: Conducting Graph Analytics over Relational DatabasesPyData
This document discusses GraphGen, a tool for conducting graph analytics over relational databases. It begins by introducing graph analytics and its applications. It then discusses the current state of graph analytics, which is fragmented with no single solution. Most organizations store data relationally and have "hidden" graphs that can be extracted. GraphGen provides a declarative language to define nodes and edges to extract these graphs without ETL. It supports various interfaces like Java, Python, and a web application to enable graph analytics over relational data in an intuitive way.
Integrating Structured Data (to an SEO Plan) for the Win _ WTSWorkshop '23.pptxBegum Kaya
This document provides an overview of structured data and how to plan and implement it effectively. It discusses the giant global graph and semantic web concepts. Schema.org is introduced as a way to add structured data tags to pages. The benefits of structured data like improved rankings and user experience are outlined. The document then covers how to plan structured data by auditing pages, identifying appropriate schema types and properties. Implementation tips around templating, testing and monitoring structured data are provided. Common pitfalls to avoid are also highlighted.
Data Science Salon: A Journey of Deploying a Data Science Engine to ProductionFormulatedby
Presented by Mostafa Madjipour., Senior Data Scientist at Time Inc.
Next DSS NYC Event 👉 https://datascience.salon/newyork/
Next DSS LA Event 👉 https://datascience.salon/la/
Reducing the gap between R&D and production is still a challenge for data science/ machine learning engineering groups in many companies. Typically, data scientists develop the data-driven models in a research-oriented programming environment (such as R and python). Next, the data/machine learning engineers rewrite the code (typically in another programming language) in a way that is easy to integrate with production services.
This process has some disadvantages: 1) It is time consuming; 2) slows the impact of data science team on business; 3) code rewriting is prone to errors.
A possible solution to overcome the aforementioned disadvantages would be to implement a deployment strategy that easily embeds/transforms the model created by data scientists. Packages such as jPMML, MLeap, PFA, and PMML among others are developed for this purpose.
In this talk we review some of the mentioned packages, motivated by a project at Time Inc. The project involves development of a near real-time recommender system, which includes a predictor engine, paired with a set of business rules.
This document discusses ways to optimize logging by centralizing and proactively using log data. It recommends using Monolog to log from application code in a standardized format. Rsyslog can then collect logs centrally from applications and systems. Logstash can further process logs with filters and output them to destinations like Elasticsearch. Graylog2 provides a web interface for powerful log searching, analytics, and alerting. Centralizing, standardizing, and proactively analyzing logs with these open source tools allows for improved monitoring and troubleshooting.
Everybody in our team knows how to create stable and scalable software products. But in this case, we are using Docker... and it really helps us to concentrate on development and spend more time on code review & tests instead of troubleshooting issues with servers.
Enabling IoT Devices’ Hardware and Software Interoperability, IPSO Alliance (...Open Mobile Alliance
Presentation delivered during the Internet of Things World, Santa Clara pre-event workshop by Christian Legare - IPSO Alliance Chairman, Chief of Software Engineering, Micrium (Part of Silicon Labs)
Internet Protocol for Smart Objects (IPSO) is an alliance that, among other things, defines a data model to represent sensor values and attributes. OMA uses IPSO Smart Objects v1.0 as its resource model to expose sensor information to a remote LwM2M Server. From the speaker from IPSO Alliance, you will learn:
● What is an IPSO Smart Object data model
● What do these Objects and Resources look like
● How to create and register your own resources
● What is next for IPSO Alliance
Company Visitor Management System Report.docxfantabulous2024
The document provides an overview of a Company Visitor Management System project. It includes sections on the project introduction, modules, requirements, analysis and design, database tables, implementation, evaluation, and conclusion. The system is a web-based application built with Python, Django, and MySQL to more effectively manage and track company visitors through features like adding visitors, generating reports, and password recovery/management. UML diagrams including use cases, classes, entities, and data flow are included to visualize the system design.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
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1. Plone Analytics
A set of tools to analyze your Plone site usage
Simone Orsi - simone.orsi@abstract.it
2. Who Am I
Simone Orsi aka #simahawk
Python Web Developer
@ Abstract
Abstract for PLOG 2013
3. Customer needs: track users' activity.
● View users' last login time;
● View items published since users' last login;
● View items published since users' registration date;
● View items published between a specific date range;
● more?
Abstract for PLOG 2013
4. Customer needs: visualization and
manipulation.
● View / build graphics on users' stats;
● Export or expose data (CSV, XLS, JSON, etc)
Abstract for PLOG 2013
7. collective.contentstats by Raphael Ritz
"A configlet for Plone showing some content statistics (type/state)"
Last release: 1.0.1 (2011-05-09)
Features:
● Works on catalog data exclusively - no content is touched;
● Only lists portal types that are used;
● Only lists review states used;
● Works with custom add-ons right away;
● Supports CSV export of summary data;
Limits: no search. Only display info on review state.
Abstract for PLOG 2013
8. collective.pygal.plonestats by Christian Ledermann
"collective.pygal.plonestats is mainly meant to demonstrate the
ease of use and integration of pygal into plone."
Last release: 0.1 (2012/04/02)
Features:
● Keywords;
● Content by Creator;
● Content by types;
● Review states;
● Created items by year;
● Created items by month;
Limits: no search. Prove of concept.
Abstract for PLOG 2013
9. quintagroup.analytics
"Plone site's statistics."
Last release: 1.1.1 (2012-05-31)
Features:
● Content Ownership by Type;
● Content Ownership by State;
● Content Types by State;
● Site Portlets;
● Legacy Portlets - information about legacy assigned throughout site sections;
● Properties stats - information on certain property values for all site objects, such as
titles, descriptions, etc.
Limits: no search. Some not-needed features.
Abstract for PLOG 2013
11. Advanced search.
Search by:
● user properties (name, fullname, email, etc);
● date filter on range (compared to last login time, registration date, etc);
● content types;
● review state;
● path;
● more?
Abstract for PLOG 2013
12. Visualization.
Show:
● table;
● chart;
Some good starting point could be pygals and daviz.
Abstract for PLOG 2013
14. Flexibility.
● Add / remove columns to views and exported data;
● Custom visualization manipulators for converting
value / labels to be displayed;
● Custom export manipulators for converting value /
labels to be exported;
● Custom configuration of graphics (ala Daviz).
All of this should be possbile both from FS code and TTW scripting /
TALES expressions.
Abstract for PLOG 2013
15. Sprint.
The goal of the sprint is to come up with a draft of a suite of packages
for providing a pluggable set of tools.
1. indentify real must-have features;
2. outline architecture;
3. cherry picking features from existings packages;
4. code!
Abstract for PLOG 2013