The Boston Riak had Sean Kelly from Tapjoy digging into message queue infrastructure at the company. They process billions of requests a day and queuing is an important element of that scale.
To kick us off, we discussed the basics of message queues, distributed systems and why dual writes are evil. Here is that talk with a few links to get you started.
Kibana 4 provides new interactive features for visualizing and analyzing log and search data stored in Elasticsearch, including interactive chart creation, scripted fields, highlights, and metric visualization. The presentation provides an overview of the ELK stack for streaming data analytics using Logstash, Elasticsearch, and Kibana and demonstrates Kibana 4's new features.
Kafka Evaluation - High Throughout Message QueueShafaq Abdullah
This document summarizes Kafka's performance in handling data pipelines and ETL workloads. It discusses Kafka's high-level architecture, scalability, fault tolerance, and monitoring capabilities. The document also includes results from benchmark tests showing Kafka can process over 47 million transactions in under 6 minutes with latency under 2 milliseconds. It proposes using Kafka to integrate data pipelines between various systems and services at a company.
Real time Messages at Scale with Apache Kafka and CouchbaseWill Gardella
Kafka is a scalable, distributed publish subscribe messaging system that's used as a data transmission backbone in many data intensive digital businesses. Couchbase Server is a scalable, flexible document database that's fast, agile, and elastic. Because they both appeal to the same type of customers, Couchbase and Kafka are often used together.
This presentation from a meetup in Mountain View describes Kafka's design and why people use it, Couchbase Server and its uses, and the use cases for both together. Also covered is a description and demo of Couchbase Server writing documents to a Kafka topic and consuming messages from a Kafka topic. using the Couchbase Kafka Connector.
Querying Riak Just Got Easier - Introducing Secondary IndicesRusty Klophaus
This presentation introduces new Riak KV functionality called Secondary Indexes. Secondary Indices allows a developer to retrieve data by attribute value, rather than by primary key.
Currently, a developer coding outside of Riak’s key/value based access must maintain their own indexes into the data using links, other Riak objects, or external systems. This is straightforward for simple use cases, but can add substantial coding and data modeling for complex applications. By formalizing an approach and building index support directly into Riak KV, we remove this burden from the application developer while preserving Riak’s core benefits, including scalability and tolerance against hardware failure and network partitions.
The presentation covers usage, capabilities, limitations, and lessons learned.
Jilles van Gurp presents on the ELK stack and how it is used at Linko to analyze logs from applications servers, Nginx, and Collectd. The ELK stack consists of Elasticsearch for storage and search, Logstash for processing and transporting logs, and Kibana for visualization. At Linko, Logstash collects logs and sends them to Elasticsearch for storage and search. Logs are filtered and parsed by Logstash using grok patterns before being sent to Elasticsearch. Kibana dashboards then allow users to explore and analyze logs in real-time from Elasticsearch. While the ELK stack is powerful, there are some operational gotchas to watch out for like node restarts impacting availability and field data caching
Monitoring Apache Kafka with Confluent Control Center confluent
Presentation by Nick Dearden, Direct, Product and Engineering, Confluent
It’s 3 am. Do you know how your Kafka cluster is doing?
With over 150 metrics to think about, operating a Kafka cluster can be daunting, particularly as a deployment grows. Confluent Control Center is the only complete monitoring and administration product for Apache Kafka and is designed specifically for making the Kafka operators life easier.
Join Confluent as we cover how Control Center is used to simplify deployment, operability, and ensure message delivery.
Watch the recording: https://www.confluent.io/online-talk/monitoring-and-alerting-apache-kafka-with-confluent-control-center/
Distributed stream processing with Apache Kafkaconfluent
The document promotes a 31.4% discount code for the upcoming Kafka Summit conferences in New York and San Francisco, occurring on May 8th and August 28th respectively. The discount is only valid until March 14th at 11:59 PST. The summits are presented by Twitter, Jay Kreps, Confluent, Apache Kafka, and Confluent's blog which provides information on downloading Apache Kafka and the Confluent Platform.
Based on the information provided, it would be to your advantage to switch your choice. Let me explain:
- Originally there was a 1/3 chance the car was behind your chosen door #3
- When the host opened door #2 to reveal a goat, that means the car must now be either behind your original choice of door #3 or the remaining unopened door #1
- So now there is a 1/2 chance the car is behind door #1 if you switch
- By sticking with your original choice of door #3, there remains only a 1/3 chance of winning the car
- Therefore, by switching your choice to the remaining closed door #1, you increase your chances of winning the car from
Kibana 4 provides new interactive features for visualizing and analyzing log and search data stored in Elasticsearch, including interactive chart creation, scripted fields, highlights, and metric visualization. The presentation provides an overview of the ELK stack for streaming data analytics using Logstash, Elasticsearch, and Kibana and demonstrates Kibana 4's new features.
Kafka Evaluation - High Throughout Message QueueShafaq Abdullah
This document summarizes Kafka's performance in handling data pipelines and ETL workloads. It discusses Kafka's high-level architecture, scalability, fault tolerance, and monitoring capabilities. The document also includes results from benchmark tests showing Kafka can process over 47 million transactions in under 6 minutes with latency under 2 milliseconds. It proposes using Kafka to integrate data pipelines between various systems and services at a company.
Real time Messages at Scale with Apache Kafka and CouchbaseWill Gardella
Kafka is a scalable, distributed publish subscribe messaging system that's used as a data transmission backbone in many data intensive digital businesses. Couchbase Server is a scalable, flexible document database that's fast, agile, and elastic. Because they both appeal to the same type of customers, Couchbase and Kafka are often used together.
This presentation from a meetup in Mountain View describes Kafka's design and why people use it, Couchbase Server and its uses, and the use cases for both together. Also covered is a description and demo of Couchbase Server writing documents to a Kafka topic and consuming messages from a Kafka topic. using the Couchbase Kafka Connector.
Querying Riak Just Got Easier - Introducing Secondary IndicesRusty Klophaus
This presentation introduces new Riak KV functionality called Secondary Indexes. Secondary Indices allows a developer to retrieve data by attribute value, rather than by primary key.
Currently, a developer coding outside of Riak’s key/value based access must maintain their own indexes into the data using links, other Riak objects, or external systems. This is straightforward for simple use cases, but can add substantial coding and data modeling for complex applications. By formalizing an approach and building index support directly into Riak KV, we remove this burden from the application developer while preserving Riak’s core benefits, including scalability and tolerance against hardware failure and network partitions.
The presentation covers usage, capabilities, limitations, and lessons learned.
Jilles van Gurp presents on the ELK stack and how it is used at Linko to analyze logs from applications servers, Nginx, and Collectd. The ELK stack consists of Elasticsearch for storage and search, Logstash for processing and transporting logs, and Kibana for visualization. At Linko, Logstash collects logs and sends them to Elasticsearch for storage and search. Logs are filtered and parsed by Logstash using grok patterns before being sent to Elasticsearch. Kibana dashboards then allow users to explore and analyze logs in real-time from Elasticsearch. While the ELK stack is powerful, there are some operational gotchas to watch out for like node restarts impacting availability and field data caching
Monitoring Apache Kafka with Confluent Control Center confluent
Presentation by Nick Dearden, Direct, Product and Engineering, Confluent
It’s 3 am. Do you know how your Kafka cluster is doing?
With over 150 metrics to think about, operating a Kafka cluster can be daunting, particularly as a deployment grows. Confluent Control Center is the only complete monitoring and administration product for Apache Kafka and is designed specifically for making the Kafka operators life easier.
Join Confluent as we cover how Control Center is used to simplify deployment, operability, and ensure message delivery.
Watch the recording: https://www.confluent.io/online-talk/monitoring-and-alerting-apache-kafka-with-confluent-control-center/
Distributed stream processing with Apache Kafkaconfluent
The document promotes a 31.4% discount code for the upcoming Kafka Summit conferences in New York and San Francisco, occurring on May 8th and August 28th respectively. The discount is only valid until March 14th at 11:59 PST. The summits are presented by Twitter, Jay Kreps, Confluent, Apache Kafka, and Confluent's blog which provides information on downloading Apache Kafka and the Confluent Platform.
Based on the information provided, it would be to your advantage to switch your choice. Let me explain:
- Originally there was a 1/3 chance the car was behind your chosen door #3
- When the host opened door #2 to reveal a goat, that means the car must now be either behind your original choice of door #3 or the remaining unopened door #1
- So now there is a 1/2 chance the car is behind door #1 if you switch
- By sticking with your original choice of door #3, there remains only a 1/3 chance of winning the car
- Therefore, by switching your choice to the remaining closed door #1, you increase your chances of winning the car from
Time Series data is proliferating with literally every step that we take, just think about things like Fit Bit bracelets that track your every move and financial trading data all of which is timestamped.
Time series data requires high performance reads and writes even with a huge number of data sources. Both speed and scale are integral to success, which makes for a unique challenge for your database.
A time series NoSQL data model requires flexibility to support unstructured, and semi-structured data as well as the ability to write range queries to analyze your time series data. So how can you tackle speed, scale and flexibility all at once?
Join Professional Services Architect Drew Kerrigan and Developer Advocate Matt Brender for a discussion of:
Examples of time series data sets, from IoT to Finance to jet engines
What makes time series queries different from other database queries
How to model your dataset to answer the right questions about your data
How to store, query and analyze a set of time series data points
Learn how a NoSQL database model and Riak TS can help you address the unique challenges of time series data.
1) Technology trends like big data, IoT, and hybrid cloud are allowing businesses to operate faster and more efficiently but require robust data management foundations.
2) As data and unstructured data grows exponentially, companies are moving to NoSQL databases that can better handle massive amounts of flexible data compared to traditional SQL databases.
3) Whitepages, which provides contact information for over 55 million monthly users, selected Basho Riak KV as their NoSQL database solution due to its high availability, scalability, fault tolerance, and operational simplicity.
The document discusses distributed database systems and properties of the Riak database. It defines distributed systems and discusses key aspects like availability, fault tolerance, and latency. It explains Riak's masterless architecture and how it provides high availability and scalability through horizontal scaling on commodity servers. The document also covers consistency models and how Riak allows tuning availability and consistency based on use cases.
This is a presentation by Peter Coppola, VP of Product and Marketing at Basho Technologies and Matthew Aslett, Research Director at 451 Research. Join them as they discuss whether multi-model databases and polyglot persistence have increased operational complexity. They'll discuss the benefits and importance of NoSQL databases and how the Basho Data Platform helps enterprises leverage Big Data applications.
Here's a walkthrough of the set CRDT within Riak and a bucket strategy that leads to Riak being the best choice. You'll see that conflict is inevitable. The set bucket type allows developers to rely on eventually consistency adding up to the data set that we expect.
For more on sets and CRDTs see:
http://basho.com/distributed-data-types-riak-2-0/
http://basho.com/data-modeling-with-riak/
http://docs.basho.com/riak/latest/dev/using/data-types/
Here's an example of how to code with Riak using cURL and ruby to do a basic PUT, GET and more. We then index the data using Apache Solr integration.
No matter what platform we’re discussing, we’re beyond the view of rows and columns. Data is more diverse than ever. More difficult to parse. Here is some of that story.
This is a presentation given by Matt Brender (@mjbrender) at Big Data TechCon 2015.
In this class, we will discuss why companies choose Riak over a relational database with a specific focus on availability, scalability, and the key/value data model. We then analyze the decision points that should be considered when choosing a non-relational solution and review data modeling, querying, and consistency guarantees. Finally, we end with simple patterns for building common applications in Riak using its key/value design, dealing with data conflicts that emerge in an eventually consistent system, and discuss multi-datacenter replication.
Here is Matt Brender's presentation at Big Data TechCon centered on understanding how distributed systems play a role in Big Data.
Full description:
Whether you’re an experienced user of Hadoop or a recent convert to Spark, you recognize that data is powerful when stored and analyzed. Analysis, as a workload, can be contrasted with the initial creation and storage of that data. These “active” workloads are what generate the data we covet.
Understanding this persistence of data as workload requires an appreciation of distributed systems. We will explore what factors affect your choice in database technology and particularly how to prioritize the choice in core architectural underpinnings present in NoSQL designs. We will also explore what these technologies solve and suggestions for how to align them with your business objectives.
You’ll leave this session with an understanding of the basic principles of NoSQL architectural design and a deeper understanding of the considerations when identifying a persistence solution for your active workloads.
Basho and Riak at GOTO Stockholm: "Don't Use My Database."Basho Technologies
What are common use cases for NoSQL? When should I avoid NoSQL? When is RDBMS just fine?
This presentation, delivered at the GOTO NoSQL Roadshow events in London and Stockholm in November of 2011 by Basho co-founder and COO, Antony Falco, take a no-BS look at the tradeoffs one must make to gain the advantages offered by distributed databases like Riak.
Using Basho Bench to Load Test Distributed ApplicationsBasho Technologies
This document discusses benchmarking Riak and provides an overview of benchmarking best practices. It describes the different types of benchmarks, including throughput and latency tests. The document outlines the steps to benchmarking, including starting a test cluster, configuring a test, running the test, and generating graphs to analyze results. It introduces the basho_bench tool for benchmarking and provides examples of key and value distributions. Some challenges of benchmarking like designing accurate tests and accounting for system limits are also covered. The document recommends conducting application-specific benchmarks based on real usage patterns.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeAftab Hussain
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
- These are slides of the talk given at InteNSE'23: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, co-located with the 45th International Conference on Software Engineering, ICSE 2023, Melbourne Australia
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
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
Time Series data is proliferating with literally every step that we take, just think about things like Fit Bit bracelets that track your every move and financial trading data all of which is timestamped.
Time series data requires high performance reads and writes even with a huge number of data sources. Both speed and scale are integral to success, which makes for a unique challenge for your database.
A time series NoSQL data model requires flexibility to support unstructured, and semi-structured data as well as the ability to write range queries to analyze your time series data. So how can you tackle speed, scale and flexibility all at once?
Join Professional Services Architect Drew Kerrigan and Developer Advocate Matt Brender for a discussion of:
Examples of time series data sets, from IoT to Finance to jet engines
What makes time series queries different from other database queries
How to model your dataset to answer the right questions about your data
How to store, query and analyze a set of time series data points
Learn how a NoSQL database model and Riak TS can help you address the unique challenges of time series data.
1) Technology trends like big data, IoT, and hybrid cloud are allowing businesses to operate faster and more efficiently but require robust data management foundations.
2) As data and unstructured data grows exponentially, companies are moving to NoSQL databases that can better handle massive amounts of flexible data compared to traditional SQL databases.
3) Whitepages, which provides contact information for over 55 million monthly users, selected Basho Riak KV as their NoSQL database solution due to its high availability, scalability, fault tolerance, and operational simplicity.
The document discusses distributed database systems and properties of the Riak database. It defines distributed systems and discusses key aspects like availability, fault tolerance, and latency. It explains Riak's masterless architecture and how it provides high availability and scalability through horizontal scaling on commodity servers. The document also covers consistency models and how Riak allows tuning availability and consistency based on use cases.
This is a presentation by Peter Coppola, VP of Product and Marketing at Basho Technologies and Matthew Aslett, Research Director at 451 Research. Join them as they discuss whether multi-model databases and polyglot persistence have increased operational complexity. They'll discuss the benefits and importance of NoSQL databases and how the Basho Data Platform helps enterprises leverage Big Data applications.
Here's a walkthrough of the set CRDT within Riak and a bucket strategy that leads to Riak being the best choice. You'll see that conflict is inevitable. The set bucket type allows developers to rely on eventually consistency adding up to the data set that we expect.
For more on sets and CRDTs see:
http://basho.com/distributed-data-types-riak-2-0/
http://basho.com/data-modeling-with-riak/
http://docs.basho.com/riak/latest/dev/using/data-types/
Here's an example of how to code with Riak using cURL and ruby to do a basic PUT, GET and more. We then index the data using Apache Solr integration.
No matter what platform we’re discussing, we’re beyond the view of rows and columns. Data is more diverse than ever. More difficult to parse. Here is some of that story.
This is a presentation given by Matt Brender (@mjbrender) at Big Data TechCon 2015.
In this class, we will discuss why companies choose Riak over a relational database with a specific focus on availability, scalability, and the key/value data model. We then analyze the decision points that should be considered when choosing a non-relational solution and review data modeling, querying, and consistency guarantees. Finally, we end with simple patterns for building common applications in Riak using its key/value design, dealing with data conflicts that emerge in an eventually consistent system, and discuss multi-datacenter replication.
Here is Matt Brender's presentation at Big Data TechCon centered on understanding how distributed systems play a role in Big Data.
Full description:
Whether you’re an experienced user of Hadoop or a recent convert to Spark, you recognize that data is powerful when stored and analyzed. Analysis, as a workload, can be contrasted with the initial creation and storage of that data. These “active” workloads are what generate the data we covet.
Understanding this persistence of data as workload requires an appreciation of distributed systems. We will explore what factors affect your choice in database technology and particularly how to prioritize the choice in core architectural underpinnings present in NoSQL designs. We will also explore what these technologies solve and suggestions for how to align them with your business objectives.
You’ll leave this session with an understanding of the basic principles of NoSQL architectural design and a deeper understanding of the considerations when identifying a persistence solution for your active workloads.
Basho and Riak at GOTO Stockholm: "Don't Use My Database."Basho Technologies
What are common use cases for NoSQL? When should I avoid NoSQL? When is RDBMS just fine?
This presentation, delivered at the GOTO NoSQL Roadshow events in London and Stockholm in November of 2011 by Basho co-founder and COO, Antony Falco, take a no-BS look at the tradeoffs one must make to gain the advantages offered by distributed databases like Riak.
Using Basho Bench to Load Test Distributed ApplicationsBasho Technologies
This document discusses benchmarking Riak and provides an overview of benchmarking best practices. It describes the different types of benchmarks, including throughput and latency tests. The document outlines the steps to benchmarking, including starting a test cluster, configuring a test, running the test, and generating graphs to analyze results. It introduces the basho_bench tool for benchmarking and provides examples of key and value distributions. Some challenges of benchmarking like designing accurate tests and accounting for system limits are also covered. The document recommends conducting application-specific benchmarks based on real usage patterns.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeAftab Hussain
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
- These are slides of the talk given at InteNSE'23: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, co-located with the 45th International Conference on Software Engineering, ICSE 2023, Melbourne Australia
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
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
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Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
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What is Augmented Reality Image Trackingpavan998932
Augmented Reality (AR) Image Tracking is a technology that enables AR applications to recognize and track images in the real world, overlaying digital content onto them. This enhances the user's interaction with their environment by providing additional information and interactive elements directly tied to physical images.
Takashi Kobayashi and Hironori Washizaki, "SWEBOK Guide and Future of SE Education," First International Symposium on the Future of Software Engineering (FUSE), June 3-6, 2024, Okinawa, Japan
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
SOCRadar's Aviation Industry Q1 Incident Report is out now!
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I find this personally and professionally interesting.
I’m going to make sure we’re all starting from the same assumptions by discussing common factors in the state of data management.
And then we’ll work through a disturbingly common pattern that our systems end up. From this pain point, we’ll look into some of the structural considerations for your application.
IDC and EMC project that data will grow to 40 zettabytes by 2020, resulting in a 50-fold growth from the beginning of 2010.[3] Computer World states that unstructured information might account for more than 70%–80% of all data in organizations.[4]
I’ve implemented exactly zero of what I’m talking about. What I do offer is the good fortune of speaking to people who build these systems, basically non-stop. There is a lot to learn from just listening.
I’ve spoken to hundreds of developers from companies of every shape and size. I’ve argued with ops engineers, I’ve listened to data scientists. I’ve read the 8 years of posts, from Amazon’s Dynamo paper in 2007 that Basho actually designed Riak after.
And I have the good fortune to listen in to a ton of conversations.
Our database at Basho, Riak, is used by many companies to store everything from session data to log aggregation. In these conversations, I always pivot to asking about their architecture - the how, the why, and the waht could be better.
You’ll also see some hand drawn slides, complements of Martin Kleppmann. He gave me permissions to reuse his work after I tweeted him and I want to give back to him by letting you know about this book. Designing Data-Intensive Applications is a must read.
“The buzzwords that fill this space are a sign of enthusiasm for the new possibilities, which is a great thing. However, as software engineers and architects, we also need to have a technically accurate and precise understanding of the various technologies and their trade-offs if we want to build good applications. For that understanding, we have to dig deeper than buzzwords.”
What I’m going to talk about today isn’t really new — some people have known about these ideas for a long time. However, they aren’t as widely known as they should be. If you work on a non-trivial application, something with more than just one database, you’ll probably find these ideas very useful.
We start with a simple web app. It has multiple clients for HTTP and native mobile.
This is all successfully stored on our familiar RDBMS.
And we’re successful!
But success comes with more demand. Demand needs we need to speed things up.
Let’s assume that you’re working on a web application. In the simplest case, it probably has the stereotypical three-tier architecture: you have some clients (which may be web browsers, or mobile apps, or both), which make requests to a web application running on your servers. The web application is where your application code or “business logic” lives.
So we add a cache. We see performance improve for our users and all is well again. Then another need arrives.
Perhaps you get more users, making more requests, your database gets slow, and you add a cache to speed it up – perhaps memcached or Redis, for example.
We need search, which our RDBMS was not scoped to handle or does not give us the symatics we want, so we add a searching solution like Apache Solr or ElasticSearch.
Perhaps you need to add full-text search to your application, and the basic search facility built into your database is not good enough, so you end up setting a separate indexing service such as Elasticsearch or Solr.
Perhaps you need to move some expensive operations out of the web request flow, and into an asynchronous background process, so you add a message queue which lets you send jobs to your background workers.
ActiveMQ, RabbitMQ, something home grown on top of Redis..
Now that your business analytics are working, you find that your search system is no longer keeping up… but you realise that since you have all the data in HDFS anyway, you could actually build your search indexes in Hadoop and push them out to the search servers, and the system just keeps getting more and more complicated…
…and the result is complete and utter insanity.
We’re left with an incoherent jumble of services that all communicate with essentially the same data. Updates are terrifying because we fear the complexity we’ve relied on.
How did we get into that state? How did we end up with such complexity, where everything is calling everything else, and nobody understands what is going on?
It’s not that any particular decision we made along the way was bad. There is no one database or tool that can do everything that our application requires – we use the best tool for the job, and for an application with a variety of features that implies using a variety of tools.
Also, as a system grows, you need a way of decomposing it into smaller components in order to keep it manageable. That’s what microservices are all about. But if your system becomes a tangled mess of interdependent components, that’s not manageable either.
So how do we keep these different data systems in sync? There are a few different techniques.
A popular approach is so-called dual writes:
Dual writes is simple: it’s your application code’s responsibility to update data in all the right places. For example, if a user submits some data to your web app, there’s some code in the web app that first writes the data to your database, then invalidates or refreshes the appropriate cache entries, then re-indexes the document in your full-text search index, and so on. (Or maybe it does those things in parallel – doesn’t matter for our purposes.)
The dual writes approach is popular because it’s easy to build, and it more or less works at first. But I’d like to argue that it’s a really bad idea, because it has some fundamental problems. The first problem is race conditions.
The following diagram shows two clients making dual writes to two datastores. Time flows from left to right, following the black arrows:
Here, the first client (teal) is setting the key X to be some value A. They first make a request to the first datastore – perhaps that’s the database, for example – and set X=A. The datastore responds saying the write was successful. Then the client makes a request to the second datastore – perhaps that’s the search index – and also sets X=A.
At the same time as this is happening, another client (red) is also active. It wants to write to the same key X, but it wants to set the key to a different value B. The client proceeds in the same way: it first sends a request X=B to the first datastore, and then sends a request X=B to the second datastore.
All these writes are successful. However, look at what value is stored in each database over time:
In the first datastore, the value is first set to A by the teal client, and then set to B by the red client, so the final value is B.
In the second datastore, the requests arrive in a different order: the value is first set to B, and then set to A, so the final value is A. Now the two datastores are inconsistent with each other, and they will permanently remain inconsistent until sometime later someone comes and overwrites X again.
An the worst thing: we probably won’t even notice that your database and your search indexes have gone out of sync, because no errors occurred. You’ll probably only realize six months later, while you’re doing something completely different, that your database and your indexes don’t match up, and you’ll have no idea how that could have happened.
In this case, the most straightforward approach is quite fundamentally flawed.
We need to balance the availability of information, what queriable state it is in and whether or not we can afford the complexity.
The same information in many places.
The basics of all these choices is an ability to move out of the synchronous, low-latency flow of an application request.
We have many choices and many angles to our balancing act to keep in mind. So let’s walk through a few that are incredibly important in the choice of your database.
Message queues is a universal name for what acts as a data highway from your applications to your database services in order to keep data synchronized and avoid the insanity architecture above.
NoSQL tells you nothing about what’s important. We’ll get into that further.
Hadoop is actually a collection of tools, not a single solution in and of itself.
The Hadoop Distributed Filesystem is a multi-server filesystem designed for high throughput and high latency. It tolerates some failure scenarios and falls into the Data Warehouse world.
Unlike NoSQL, there are no low latency applications that write and then read from HDFS! That’s not what it’s intended to do.
Map/Reduce is fundamentally a querying system designed for parallel computation. It’s loved for getting people off of multi-million dollar systems and allowing them to scale out and it comes at the cost of its own mapper and reducer design.
Spark, another Apache project, is largely recognized as the successor to Map/Reduce. It provides a map/reduce-backwards compatability while also exposing all the data science processing available in its clients - Python and Scala. Data is pulled from disk and manuplicated in memory.
YARN = framework for job parallelization
All often misappropriated a the same problem set.
http://java.dzone.com/articles/exploring-message-brokers
Apache ActiveMQ is the most popular and powerful open source messaging and Integration Patterns server.
Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License
Supported by Pivotal.
Robust messaging for applications
Easy to use
Runs on all major operating systems
Supports a huge number of developer platforms
Open source and commercially supported
Supported by Confluent.io - founded at LinkedIn.
Apache Kafka is publish-subscribe messaging rethought as a distributed commit log.
Fast
A single Kafka broker can handle hundreds of megabytes of reads and writes per second from thousands of clients.
Scalable
Kafka is designed to allow a single cluster to serve as the central data backbone for a large organization. It can be elastically and transparently expanded without downtime. Data streams are partitioned and spread over a cluster of machines to allow data streams larger than the capability of any single machine and to allow clusters of co-ordinated consumers
Durable
Messages are persisted on disk and replicated within the cluster to prevent data loss. Each broker can handle terabytes of messages without performance impact.
Distributed by Design
Kafka has a modern cluster-centric design that offers strong durability and fault-tolerance guarantees.
ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services.
All of these kinds of services are used in some form or another by distributed applications. Each time they are implemented there is a lot of work that goes into fixing the bugs and race conditions that are inevitable. Because of the difficulty of implementing these kinds of services, applications initially usually skimp on them ,which make them brittle in the presence of change and difficult to manage. Even when done correctly, different implementations of these services lead to management complexity when the applications are deployed.
Not a question so much as a challenge for you: Get Hands-on with technology, right away.
Sometimes you just have to experience the system first hand to see its value. Don’t be scared of it. Whether you have the benefit of choicing an open source solution or simply need to spin up a server to test something, go use it right now. Don’t want to architecture the perfect solution because so much of what you’ll need will come from using it.