Quali vantaggi ci da Azure? Dal punto di vista dello sviluppo software, uno di questi è certamente la varietà dei servizi di gestione dei dati. Questo ci permette di cominciare a non essere SQL centrici ma utilizzare il servizio giusto per il problema giusto fino ad applicare una strategia di Polyglot Persistence (e vedremo cosa significa) nel rispetto di una corretta gestione delle risorse IT e delle pratiche di DevOps.
The slides were presented @ Kubernetes Meetup Bangalore held on 26th May - 2018 by Sathyam Zode - An OpenEBS Contributor and Software Engineer at MayaData .
AWS to Bare Metal: Motivation, Pitfalls, and ResultsMongoDB
Like many startups, Wish grew up on AWS. As our cluster grew and the price of SSDs fell, we started exploring bare metal. Fast-forward 2 years and we have hundreds of MongoDB instances on bare metal fully integrated with our AWS infrastructure. It wasn't all smooth sailing, but the performance & cost improvements were worth it! Hear the story of how we did it and gain a framework for thinking about how to make the leap from cloud-centric architecture to a hybrid model.
Icinga Director and vSphereDB - how they play together - Icinga Camp Zurich 2019Icinga
Talk by: Thomas Gelf
While the Icinga Director is the main configuration tool for Icinga, vSphereDB is a completely different beast. Icinga models everything around Hosts and Services, vSphereDB instead discovers your whole VMware infrastructure and builds a huge and deep inventory.
This talk wants to explain the reasoning behind this, shows what’s possible right now and where those powerful Icinga components are heading to in the near future.
The slides were presented @ Kubernetes Meetup Bangalore held on 26th May - 2018 by Sathyam Zode - An OpenEBS Contributor and Software Engineer at MayaData .
AWS to Bare Metal: Motivation, Pitfalls, and ResultsMongoDB
Like many startups, Wish grew up on AWS. As our cluster grew and the price of SSDs fell, we started exploring bare metal. Fast-forward 2 years and we have hundreds of MongoDB instances on bare metal fully integrated with our AWS infrastructure. It wasn't all smooth sailing, but the performance & cost improvements were worth it! Hear the story of how we did it and gain a framework for thinking about how to make the leap from cloud-centric architecture to a hybrid model.
Icinga Director and vSphereDB - how they play together - Icinga Camp Zurich 2019Icinga
Talk by: Thomas Gelf
While the Icinga Director is the main configuration tool for Icinga, vSphereDB is a completely different beast. Icinga models everything around Hosts and Services, vSphereDB instead discovers your whole VMware infrastructure and builds a huge and deep inventory.
This talk wants to explain the reasoning behind this, shows what’s possible right now and where those powerful Icinga components are heading to in the near future.
Event driven workloads on Kubernetes with KEDANilesh Gule
Slide deck of the presentation done at the Pune User Group on 27th February 2021. Demonstrate how Kubernetes based event driven autoscaling (KEDA) can be used with RabbitMQ as the event source.
Kubernetes Forum Seoul 2019: Re-architecting Data Platform with KubernetesSeungYong Oh
Session Video: https://youtu.be/7MPH1mknIxE
In this talk, we share Devsisters' journey of migrating its internal data platform including Spark to Kubernetes, with its benefits and issues.
데브시스터즈에서 데이터플랫폼 컴포넌트를 쿠버네티스로 옮기면서 얻은 장점들과 이슈들에 대해 공유합니다.
Conference session page:
- English: https://sched.co/WIRK
- Korean: https://sched.co/WYRc
Serverless real use cases and best practices: Asavari Tayal, Microsoft, Serve...iguazio
Let's take a look at real cases from Microsoft customers worldwide to learn how they solved their problems with the Azure serverless platform, as well as best practices (and some caveats) from the architectures used developing these solutions.
Our Application development is nearing completion. It's time to prepare our cluster for production, but are we sure the system is capable of handing the load? Have we achieved high availability? What preflight checks should we be running. Learn how Dev & Ops work together to achieve production readiness and plan for scale, availability, monitoring.
Building a Real-Time IoT monitoring application with AzureDavide Mauri
Being able to analyze data in real-time is a very hot topic already and it will be more and more in. From product recommendations to fraud detection alarms a lot of stuff would be perfect if it could happen in real time. In this session a sample solution using the serverless capabilities of Azure will be developed, right from the ingestion of sensor data to their analysis and recommendation using AI in real time. Come to see how you could do the same in your environment, moving your application capabilities to the next level.
Virtualizing Apache Spark with Justin MurrayDatabricks
This talk explains the reasons why virtualizing Spark, in-house or elsewhere, is a requirement in today’s fast-moving and experimental world of data science and data engineering. Different teams want to spin up a Spark cluster “on the fly” to carry out some research and quickly answer business questions. They are not concerned with the availability of the server hardware – or with what any other team might be doing on it at the time. Virtualization provides the means of working within your own sandbox to try out the new query or Machine Learning algorithm. Deep performance test results will be shown that demonstrate that Spark and ML programs perform equally well on virtual machines just like native implementations do. An early introduction is given to the best practices you should adhere to when you do this. If time allows, a short demo will be given of creating an ephemeral, single-purpose Spark cluster, running an ML application test program on that cluster, and bringing it down when finished.
Dok Talks #111 - Scheduled Scaling with Dask and Argo WorkflowsDoKC
https://go.dok.community/slack
https://dok.community/
ABSTRACT OF THE TALK
Complex computational workloads in Python are a common sight these days, especially in the context of processing large and complex datasets. Battle-hardened modules such as Numpy, Pandas, and Scikit-Learn can perform low-level tasks, while tools like Dask makes it easy to parallelize these workloads across distributed computational environments. Meanwhile, Argo Workflows offers a Kubernetes-native solution to provisioning cloud resources in Kubernetes and triggering workflows on a regular schedule. Being Kubernetes-native, Argo Workflows also meshes nicely with other Kubernetes tools. This talk discusses the combination of these two worlds by showcasing a set-up for Argo-managed workflows which schedule and automatically scale-out Dask-powered data pipelines in Python.
BIO
Former academic in the field of renewable energy simulation and energy systems analysis. Currently responsible for architecting and maintaining the cloud- and data strategy at ACCURE Battery Intelligence
KEY TAKE-AWAYS FROM THE TALK
Argo Workflows + Dask is a nice combination for data-processing pipelines. There are a a few "gotchyas" to be on the look-out for, but in nevertheless this is still a generally-applicable and powerful combination.
https://github.com/sevberg
There’s a plethora of Container-related services available in Azure: Azure Container Instance, Azure Container Service, managed Kubernetes and managed container registry to name a few. I will cover the most useful container and container orchestration related services in this talk, explain their differences and help you figure out which scenarios they fit best.
As presented by Karl Ots, Azure MVP at CNCF & Kubernetes Finland meetup. on February 22, 2018.
The Azure service fabric mesh is a fully managed cluster in Microsoft cloud to run containerized applications. Any application that runs in the container can he run in service fabric mesh cluster.
Hyper-C is OpenStack on Windows Server 2016, based on Nano Server, Hyper-V, Storage Spaces Direct (S2D) and Open vSwitch for Windows. Bare metal deployment features Cloudbase Solutions Juju charms and MAAS.
The slide deck was used during the Azure user group meet up on 16th August 2018. It is part of Hands on Lab for learning Azure Kubernetes Service. The talk demonstrated usage of Minikube to test Kubernetes manifest files using a single node cluster. The features covered as part of hands on demo included Namespaces, Pods, Deployment, Service, StatefulSets.
Sql Start! 2020 - SQL Server Lift & Shift su AzureMarco Obinu
Slide of the session delivered during SQL Start! 2020, where I illustrate different approaches to determine the best landing zone for you SQL Server workloads.
Video (ITA): https://youtu.be/1hqT_xHs0Qs
SQL Server Lift & Shift on Azure - SQL Saturday 921Marco Obinu
Slides presented at SQL Saturday 921, while talking about how to plan a Lift & Shift migration for SQL Server workloads, depicting the pros & cons of using different Azure services as landing zones.
Event driven workloads on Kubernetes with KEDANilesh Gule
Slide deck of the presentation done at the Pune User Group on 27th February 2021. Demonstrate how Kubernetes based event driven autoscaling (KEDA) can be used with RabbitMQ as the event source.
Kubernetes Forum Seoul 2019: Re-architecting Data Platform with KubernetesSeungYong Oh
Session Video: https://youtu.be/7MPH1mknIxE
In this talk, we share Devsisters' journey of migrating its internal data platform including Spark to Kubernetes, with its benefits and issues.
데브시스터즈에서 데이터플랫폼 컴포넌트를 쿠버네티스로 옮기면서 얻은 장점들과 이슈들에 대해 공유합니다.
Conference session page:
- English: https://sched.co/WIRK
- Korean: https://sched.co/WYRc
Serverless real use cases and best practices: Asavari Tayal, Microsoft, Serve...iguazio
Let's take a look at real cases from Microsoft customers worldwide to learn how they solved their problems with the Azure serverless platform, as well as best practices (and some caveats) from the architectures used developing these solutions.
Our Application development is nearing completion. It's time to prepare our cluster for production, but are we sure the system is capable of handing the load? Have we achieved high availability? What preflight checks should we be running. Learn how Dev & Ops work together to achieve production readiness and plan for scale, availability, monitoring.
Building a Real-Time IoT monitoring application with AzureDavide Mauri
Being able to analyze data in real-time is a very hot topic already and it will be more and more in. From product recommendations to fraud detection alarms a lot of stuff would be perfect if it could happen in real time. In this session a sample solution using the serverless capabilities of Azure will be developed, right from the ingestion of sensor data to their analysis and recommendation using AI in real time. Come to see how you could do the same in your environment, moving your application capabilities to the next level.
Virtualizing Apache Spark with Justin MurrayDatabricks
This talk explains the reasons why virtualizing Spark, in-house or elsewhere, is a requirement in today’s fast-moving and experimental world of data science and data engineering. Different teams want to spin up a Spark cluster “on the fly” to carry out some research and quickly answer business questions. They are not concerned with the availability of the server hardware – or with what any other team might be doing on it at the time. Virtualization provides the means of working within your own sandbox to try out the new query or Machine Learning algorithm. Deep performance test results will be shown that demonstrate that Spark and ML programs perform equally well on virtual machines just like native implementations do. An early introduction is given to the best practices you should adhere to when you do this. If time allows, a short demo will be given of creating an ephemeral, single-purpose Spark cluster, running an ML application test program on that cluster, and bringing it down when finished.
Dok Talks #111 - Scheduled Scaling with Dask and Argo WorkflowsDoKC
https://go.dok.community/slack
https://dok.community/
ABSTRACT OF THE TALK
Complex computational workloads in Python are a common sight these days, especially in the context of processing large and complex datasets. Battle-hardened modules such as Numpy, Pandas, and Scikit-Learn can perform low-level tasks, while tools like Dask makes it easy to parallelize these workloads across distributed computational environments. Meanwhile, Argo Workflows offers a Kubernetes-native solution to provisioning cloud resources in Kubernetes and triggering workflows on a regular schedule. Being Kubernetes-native, Argo Workflows also meshes nicely with other Kubernetes tools. This talk discusses the combination of these two worlds by showcasing a set-up for Argo-managed workflows which schedule and automatically scale-out Dask-powered data pipelines in Python.
BIO
Former academic in the field of renewable energy simulation and energy systems analysis. Currently responsible for architecting and maintaining the cloud- and data strategy at ACCURE Battery Intelligence
KEY TAKE-AWAYS FROM THE TALK
Argo Workflows + Dask is a nice combination for data-processing pipelines. There are a a few "gotchyas" to be on the look-out for, but in nevertheless this is still a generally-applicable and powerful combination.
https://github.com/sevberg
There’s a plethora of Container-related services available in Azure: Azure Container Instance, Azure Container Service, managed Kubernetes and managed container registry to name a few. I will cover the most useful container and container orchestration related services in this talk, explain their differences and help you figure out which scenarios they fit best.
As presented by Karl Ots, Azure MVP at CNCF & Kubernetes Finland meetup. on February 22, 2018.
The Azure service fabric mesh is a fully managed cluster in Microsoft cloud to run containerized applications. Any application that runs in the container can he run in service fabric mesh cluster.
Hyper-C is OpenStack on Windows Server 2016, based on Nano Server, Hyper-V, Storage Spaces Direct (S2D) and Open vSwitch for Windows. Bare metal deployment features Cloudbase Solutions Juju charms and MAAS.
The slide deck was used during the Azure user group meet up on 16th August 2018. It is part of Hands on Lab for learning Azure Kubernetes Service. The talk demonstrated usage of Minikube to test Kubernetes manifest files using a single node cluster. The features covered as part of hands on demo included Namespaces, Pods, Deployment, Service, StatefulSets.
Sql Start! 2020 - SQL Server Lift & Shift su AzureMarco Obinu
Slide of the session delivered during SQL Start! 2020, where I illustrate different approaches to determine the best landing zone for you SQL Server workloads.
Video (ITA): https://youtu.be/1hqT_xHs0Qs
SQL Server Lift & Shift on Azure - SQL Saturday 921Marco Obinu
Slides presented at SQL Saturday 921, while talking about how to plan a Lift & Shift migration for SQL Server workloads, depicting the pros & cons of using different Azure services as landing zones.
Azure SQL Database (SQL DB) is a database-as-a-service (DBaaS) that provides nearly full T-SQL compatibility so you can gain tons of benefits for new databases or by moving your existing databases to the cloud. Those benefits include provisioning in minutes, built-in high availability and disaster recovery, predictable performance levels, instant scaling, and reduced overhead. And gone will be the days of getting a call at 3am because of a hardware failure. If you want to make your life easier, this is the presentation for you.
Azure Day Rome Reloaded 2019 - Reactive Systems with Event Gridazuredayit
Event Grid Può essere usato in modo estremamente pervasivo e versatile per costruire architetture serverless reattive, ad esempio nel mondo IoT delle Smart Things, a costo “quasi zero”. Con Event GRid è possibile creare sistemi potenzialmente giganteschi (e impossibili da ricreare on premises), che si autogovernano, espandono (e cambiano!!!) sulla base delle logiche di campo.
AWS re:Invent 2016: Born in the Cloud; Built Like a Startup (ARC205)Amazon Web Services
This presentation provides a comparison of three modern architecture patterns that startups are building their business around. It includes a realistic analysis of cost, team management, and security implications of each approach. It covers Elastic Beanstalk, Amazon ECS, Docker, Amazon API Gateway, AWS Lambda, Amazon DynamoDB, and Amazon CloudFront, as well as Docker.
The slides I used for my "Securing an Azure Functions REST API with Azure Active Directory" session (SAFwAD for short) at Intelligent Cloud Conference in Copenhagen.
AWS re:Invent 2016 Recap: What Happened, What It MeansRightScale
Get behind the hype and headlines from AWS re:Invent 2016 and find out what it all means to you. We’ll share what’s working for AWS users and highlight which new features and services you’ll want to look at. Whether or not you attended re:Invent, this wrap-up will help you develop your 2017 cloud to-do list.
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartoriwalk2talk srl
In questa sessione analizzeremo le opportunità e le sfide che ci aspettano nella migrazione di database in Microsoft Azure.
Vedremo le possibili soluzioni proposte dalla piattaforma Azure e cercheremo di capire quali si adattano meglio ai differenti scenari di utilizzo, massimizzando i vantaggi e riducendo il più possibile i rischi.
Per richiedere accesso al canale contenente le registrazioni audio/video delle sessioni tecniche di Cloud Conference Italia 2017 compila il seguente form:
https://goo.gl/Fq6DQE
This presentation provides overview of Windows Azure, comparing with AWS, and introduces many Azure services such as web role, storage services, Sql Azure, and much more.
AWS provides a range of Compute Services – Amazon EC2, Amazon ECS and AWS Lambda. We will provide an intro level overview of these services and highlight suitable use cases. Amazon Elastic Compute Cloud (Amazon EC2) itself provides a broad selection of instance types to accommodate a diverse mix of workloads. Going a bit deeper on EC2 we will provide background on the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current-generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances, both from a performance and cost perspective.
Building a SaaS based product in Azure - Challenges and decisions madeBizTalk360
In this session, founder/CTO of BizTalk360 - Saravana Kumar shares his experiences, challenges, and lessons that he and his team learnt when they built their first SaaS based product(s) - BizTalk360 Cloud and ServiceBus360.
Industrial IoT from the Ground up with Azure and Open Source
IIoT leverages the power of machines and realtime analytics to pick up on industrial inefficiencies and problems sooner, and save time and money in addition to supporting BI efforts. In a myriad of reference architectures it is up to experience and trial-error to find out what really works in a real life scenario.
We will review the challenges and solutions in building an IIoT platform from the ground up on the edge between Azure and open source in order to have the best from both worlds. Technical focus will be on IoT Edge, TS Insights, Stream Analytics, IoT Hub, App Insights, Event Grid, Service Bus, ARM templates, Influx DB, Grafana and more - all neatly glued together by Azure Functions.
Cost Effective Rendering in the Cloud with Spot InstancesAmazon Web Services
Usman Shakeel from Amazon Web Services, explains to us how to use AWS Spot Instances to implement low cost video rendering applications and workflows.
This presentation was delivered during the AWS Toronto Media and Entertainment Symposium
Microsoft released SQL Azure more than two years ago - that's enough time for testing (I hope!). So, are you ready to move your data to the Cloud? If you’re considering a business (i.e. a production environment) in the Cloud, you need to think about methods for backing up your data, a backup plan for your data and, eventually, restoring with Red Gate Cloud Services. In this session, you’ll see the differences, functionality, restrictions, and opportunities in SQL Azure and On-Premise SQL Server 2008/2008 R2/2012. We’ll consider topics such as how to be prepared for backup and restore, and which parts of a cloud environment are most important: keys, triggers, indexes, prices, security, service level agreements, etc.
Similar to Deploy Microsoft Azure Data Solutions (20)
Normalmente parliamo e presentiamo Azure IoT (Central) con un taglio un po' da "maker". In questa sessione, invece, vediamo di parlare allo SCADA engineer. Come si configura Azure IoT Central per il mondo industriale? Dov'è OPC/UA? Cosa c'entra IoT Plug & Play in tutto questo? E Azure IoT Central...quali vantaggi ci da? Cerchiamo di rispondere a queste e ad altre domande in questa sessione...
Allo sviluppatore Azure piacciono i servizi PaaS perchè sono "pronti all'uso". Ma quando proponiamo le nostre soluzioni alle aziende, ci scontriamo con l'IT che apprezza gli elementi infrastrutturali, IaaS. Perchè non (ri)scoprirli aggiungendo anche un pizzico di Hybrid che con il recente Azure Kubernetes Services Edge Essentials si può anche usare in un hardware che si può tenere anche in casa? Quindi scopriremo in questa sessione, tra gli altri, le VNET, le VPN S2S, Azure Arc, i Private Endpoints, e AKS EE.
Static abstract members nelle interfacce di C# 11 e dintorni di .NET 7.pptxMarco Parenzan
Did interfaces in C# need evolution? Maybe yes. Are they violating some fundamental principles? We see. Are we asking for some hoops? Let's see all this by telling a story (of code, of course)
Azure Synapse Analytics for your IoT SolutionsMarco Parenzan
Let's find out in this session how Azure Synapse Analytics, with its SQL Serverless Pool, ADX, Data Factory, Notebooks, Spark can be useful for managing data analysis in an IoT solution.
Power BI Streaming Data Flow e Azure IoT Central Marco Parenzan
Dal 2015 gli utilizzatori di Power BI hanno potuto analizzare dati in real-time grazie all'integrazione con altri prodotti e servizi Microsoft. Con streaming dataflow, si porterà l'analisi in tempo reale completamente all'interno di Power BI, rimuovendo la maggior parte delle restrizioni che avevamo, integrando al contempo funzionalità di analisi chiave come la preparazione dei dati in streaming e nessuna creazione di codice. Per vederlo in funzione, studieremo un caso specifico di streaming come l'IoT con Azure IoT Central.
Power BI Streaming Data Flow e Azure IoT CentralMarco Parenzan
Dal 2015 gli utilizzatori di Power BI hanno potuto analizzare dati in real-time grazie all'integrazione con altri prodotti e servizi Microsoft. Con streaming dataflow, si porterà l'analisi in tempo reale completamente all'interno di Power BI, rimuovendo la maggior parte delle restrizioni che avevamo, integrando al contempo funzionalità di analisi chiave come la preparazione dei dati in streaming e nessuna creazione di codice. Per vederlo in funzione, studieremo un caso specifico di streaming come l'IoT con Azure IoT Central.
Power BI Streaming Data Flow e Azure IoT CentralMarco Parenzan
Since 2015, Power BI users have been able to analyze data in real-time thanks to the integration with other Microsoft products and services. With streaming dataflow, you'll bring real-time analytics completely within Power BI, removing most of the restrictions we had, while integrating key analytics features like streaming data preparation and no coding. To see it in action, we will study a specific case of streaming such as IoT with Azure IoT Central.
What are the actors? What are they used for? And how can we develop them? And how are they published and used on Azure? Let's see how it's done in this session
Generic Math, funzionalità ora schedulata per .NET 7, e Azure IoT PnP mi hanno risvegliato un argomento che nel mio passato mi hanno portato a fare due/tre viaggi, grazie all'Università di Trieste, a Cambridge (2006/2007 circa) e a Seattle (2010, quando ho parlato pubblicamente per la prima volta di Azure :) e che mi ha fatto conoscere il mito Don Box!), a parlare di codice in .NET che aveva a che fare con la matematica e con la fisica: le unità di misura e le matrici. L'avvento dei Notebook nel mondo .NET e un vecchio sogno legato alla libreria ANTLR (e tutti i miei esercizi di Code Generation) mi portano a mettere in ordine 'sto minestrone di idee...o almeno ci provo (non so se sta tutto in piedi).
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.NET is better every year for a developer who still dreams of developing a video game. Without pretensions and without talking about Unity or any other framework, just "barebones" .NET code, we will try to write a game (or parts of it) in the 80's style (because I was a kid in those years). In Christmas style.
Building IoT infrastructure on edge with .net, Raspberry PI and ESP32 to conn...Marco Parenzan
IoT scenarios necessarily pass through the Edge component and the Raspberry PI is a great way to explore this world. If we need to receive IoT events from sensors, how do I implement an MQTT endpoint? Kafka is a clever way to do this. And how do I process the data? Kafka? Spark? Rabbit ?. How do we write custom code for these environments? .NET, now in version 6 is another clever way to do it! And maybe, we can also communicate with Azure. We'll see in this session if we can make it all work!
How can you handle defects? If you are in a factory, production can produce objects with defects. Or values from sensors can tell you over time that some values are not "normal". What can you do as a developer (not a Data Scientist) with .NET o Azure to detect these anomalies? Let's see how in this session.
C'è ancora diffidenza nei confronti dell'Internet of Things e il costo delle soluzioni custom non aiuta. Azure IoT Central è un servizio SaaS personalizzabile che rende accessibile a costi sostenibili. Vediamo quali sonole peculiarità di questo servizio.
Come puoi gestire i difetti? Se sei in una fabbrica, la produzione può produrre oggetti con difetti. Oppure i valori dei sensori possono dirti nel tempo che alcuni valori non sono "normali". Cosa puoi fare come sviluppatore (non come Data Scientist) con .NET o Azure per rilevare queste anomalie? Vediamo come in questa sessione.
It happens that we have to develop several services and deploy them in Azure. They are small, repetitive but different, often not very different. Why not use code generation techniques to simplify the development and implementation of these services? Let's see with .NET comes to meet us and helps us to deploy in Azure.
Running Kafka and Spark on Raspberry PI with Azure and some .net magicMarco Parenzan
IoT scenarios necessarily pass through the Edge component and the Raspberry PI is a great way to explore this world. If we need to receive IoT events from sensors, how do I implement an MQTT endpoint? Kafka is a clever way to do this. And how do I process the data in Kafka? Spark is another clever way of doing this. How do we write custom code for these environments? .NET, now in version 6 is another clever way to do it! And maybe, we also communicate with Azure. We'll see in this session if we can make it all work!
Time Series Anomaly Detection with Azure and .NETTMarco Parenzan
f you have any device or source that generates values over time (also a log from a service), you want to determine if in a time frame, the time serie is correct or you can detect some anomalies. What can you do as a developer (not a Data Scientist) with .NET o Azure? Let's see how in this session.
It happens that we have to develop several services and deploy them in Azure. They are small, repetitive but different, often not very different. Why not use code generation techniques to simplify the development and implementation of these services? Let's see with .NET comes to meet us and helps us to deploy in Azure.
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.
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/
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!
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/
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.
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
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Launch Your Streaming Platforms in MinutesRoshan Dwivedi
The claim of launching a streaming platform in minutes might be a bit of an exaggeration, but there are services that can significantly streamline the process. Here's a breakdown:
Pros of Speedy Streaming Platform Launch Services:
No coding required: These services often use drag-and-drop interfaces or pre-built templates, eliminating the need for programming knowledge.
Faster setup: Compared to building from scratch, these platforms can get you up and running much quicker.
All-in-one solutions: Many services offer features like content management systems (CMS), video players, and monetization tools, reducing the need for multiple integrations.
Things to Consider:
Limited customization: These platforms may offer less flexibility in design and functionality compared to custom-built solutions.
Scalability: As your audience grows, you might need to upgrade to a more robust platform or encounter limitations with the "quick launch" option.
Features: Carefully evaluate which features are included and if they meet your specific needs (e.g., live streaming, subscription options).
Examples of Services for Launching Streaming Platforms:
Muvi [muvi com]
Uscreen [usencreen tv]
Alternatives to Consider:
Existing Streaming platforms: Platforms like YouTube or Twitch might be suitable for basic streaming needs, though monetization options might be limited.
Custom Development: While more time-consuming, custom development offers the most control and flexibility for your platform.
Overall, launching a streaming platform in minutes might not be entirely realistic, but these services can significantly speed up the process compared to building from scratch. Carefully consider your needs and budget when choosing the best option for you.
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?
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
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."
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
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.
2. Senior Solution Architect @ beanTech
Microsoft Azure MVP
Community Lead 1nn0va // Pordenone
1nn0va After Hour
https://bit.ly/1nn0va-video
Linkedin: https://www.linkedin.com/in/marcoparenzan/
Marco Parenzan
3.
4. Da SQL Server a Azure SQL e oltre: le opportunità per i dati in
Azure
Dati relazionali in Azure
Dati non relazionali
Dati blob in Azure
Architetture a Messaggi, Comandi ed Eventi in Azure
Big Data in Azure
Gestire i dati dell'IoT in Azure
Servizi Cognitivi per i dati
Sicurezza
Agenda
5.
6. • Polyglot Persistence
• …non «spendere per spendere»…
• No more SQL...only!
• Microservizi
• Ogni servizio porta con sé uno storage
• «Next,Next,Next,Next,...»
• Operations & DevOps
• Quanto è «dato» e quanto è «servizio»?
• Un confine sempre più labile
• Questo è tutto ciò che è il cloud
Alcuni temi
22. • Azure love Blobs
• Developers love Blobs
• Developers love services that handles Blobs as first class citizens
• No relational
• No file system
Lesson learned
25. Column-family
Document
Graph
Turnkey global distribution
Elastic scale out
of storage & throughput
Guaranteed low latency at the 99th percentile
Comprehensive SLAs
Five well-defined consistency models
Table API
Key-value
Cosmos DB’s API for
MongoDB
Azure Cosmos Db
28. Multi-Master – Read/Write in any region
Benefits
• Write scalability around the world
• Low latency (<10ms P99 for 1kb document)
writes around the world
• 99.999% High Availability around the world
• Well-defined consistency models
• Automatic conflict management
30. Request Units
Each request consumes # of RU
Approx. 1 RU = 1 read of 1 KB document
Approx. 5 RU = 1 write of a 1KB document
Query: Depends on query & documents involved
GET
POST
PUT
Query
…
=
=
=
=
31. Operation Type # Requests per sec # RU's per Request RU's Needed
Write Single
Document 10,000 10 100,000
Top Query #1 700 100 70,000
Top Query #2 200 100 20,000
Top Query #3 100 100 10,000
Total RU/s 200,000 RU/s
Estimating Required RU’s
32. Storage Cost
Avg Record Size (KB) 1
Number of Records 100,000,000
Total Storage (GB) 100
Monthly Cost per GB $0.25
Expected Monthly Cost for Storage $25.00
Throughput Cost
Operation Type
Number of Requests per
sec Avg RU's per Request RU's Needed
Create 100 5 500
Read 400 1 400
Total RU/sec 900
Hourly Cost per 100 RU/sec $0.008
Monthly Cost per 100 RU/sec $6.00
Expected Monthly Cost for Throughput $54.00
Total Monthly Cost
[Total Monthly Cost] = [Monthly Cost for Storage] + [Monthly Cost for Throughput]
= $25 + $54
= $79 per month
* pricing may vary by region; for up-to-date pricing, see: https://azure.microsoft.com/pricing/details/cosmos-db/
Pricing Example
33. Service Bus
Architettura generica per User Story
• Microservizio responsabile del dominio
applicativo e della sua consistenza e
persistenza
• API di frontend per gestire le richieste
delle singole user stories specifiche verso
il microservizio
• Gestione in memory con Redis
• In caso di fail lettura da Cosmos
• In caso di update
• Aggiornamento di Redis
• Accodamento in serviceBus
• Batch aggiorna Cosmos per abbassare RU
API #1
Micro Service
Cosmos DB
REDIS
Caching
Update Batch
API #n
Read
Write
Command Read
Invoke
Invalidate Cache
Write
Invoke
Read
Command
35. • Azure love No SQL and Cosmos DB
• Developers love No SQL and Json
• Developer hates(?) Cosmos Db pricing?
• Developers loves (fuffa style ) microservices
• Everything has solution...
Lesson learned
36.
37. • È tutto Azure!
• Le dashboard, se si può, si fanno in Power BI (8€/utente/mese, ricordatevi,
anche solo per visualizzare)
• Governance dello sviluppo
• Premium Capacity
• Developers
• Deployment
BI? Power BI? Cosa c’entra con Azure?
39. • PowerShell
• Azure DevOps
• Git non è pbix-friendly
• Ma è comunque un repo versionato
• E le pipeline sono un ottimo strumento di automation
Ops, Deployments
41. • DR of a DataWarehouse: big problem
• BIOps is not a practice
Lesson learned
42.
43. SQL virtual machines Managed instances
Azure SQL
Databases
• SQL Server surface area
(vast majority)
• Native virtual network
support
• Fully managed service
• SQL Server and OS server
access
• Expansive SQL and OS
version support
• Automated manageability
features for SQL Server
• Hyperscale storage (up to
100TB)
• Serverless compute
• Fully managed service
• Resource sharing between
multiple databases to
price optimize
• Simplified performance
management for multiple
databases
• Fully managed service
44. Azure SQL Database — Everything built-in
•Business continuity
High availability
Automated backups
Long term backup
retention
Geo-replication
•Scale
Advanced security
Automatic tuning
Built-in monitoring
Built-in intelligence
46. On-demand flexible scale
Operate at the true rhythm of
your business
Fully managed & intelligent
Focus on your applications, not
your infrastructure
Cost-effective
Pay for performance. Period.
Adapts compute resources to the
workload without sacrificing
performance
Automatically pauses and resumes
Fully-managed and intelligent
database service
Built-in 99.99% availability
Pay only for compute resources you
consume, on a per-second basis
Further optimize costs with configurable
compute thresholds
Best for unpredictable and intermittent
workloads on single databases, such as:
Dev/test E-commerce
Line of Business
Azure Cosmos DB offers the first globally distributed, multi-model database service for building planet scale apps. It’s been powering Microsoft’s internet-scale services for years, and now it’s ready to launch yours.
You can add Azure locations to your database anywhere across the world, at any time, with a single click. Cosmos DB will seamlessly replicate your data and make it highly available.
Cosmos DB allows you to scale throughput and storage elastically, and globally! You only pay for the throughput and storage you need – anywhere in the world, at any time.
27
The number of RU’s each operation consumes depends on many factors which include:
Document size
Number of indexed fields
Type of indexes
Consistency model choice
Not all queries will consume equal numbers of RU’s. Some operations are more computationally complex or require scans through more documents and therefore use more RU’s.
Business continuity enables your business to continue operating in the face of disruption, particularly to its computing infrastructure.
High availability of Azure SQL Database guarantees your databases are up and running 99.99% of the time, no need to worry about maintenance/downtimes.
2 read replicas - GP
3 replicas, 1 read-scale replica, zone-redundant HA - BC
Primary read/write replica + up to 4 read replicas - HS
Automated backups are created and use Azure read-access geo-redundant storage (RA-GRS) to provide geo-redundancy.
Also Point in Time restore
Long term backup retention enables you to store specific full databases for up to 10 years.
Geo-replication by creating readable replicas of your database in the same or different data center (region). You can manually failover to readable replicas
Also Auto-failover groups allows an application to recover in case of a data center outage
Scale by easily adding more resources (CPU, memory, storage) without long provisioning.
Advanced security detects threats and vulnerabilities in your databases and enables you to secure your data.
Automatic tuning analyzes your workload and provides you the recommendations that can optimize performance of your applications by adding indexes, removing unused indexes, and automatically fixing the query plan issues.
Built-in monitoring capabilities enable you to get the insights into performance of your databases and workload, and troubleshoot the performance issues.
Built-in intelligence automatically identifies the potential issues in your workload and provides you the recommendations that can help you to fix the problems.
Azure SQL Database serverless is our answer to cost-effectively resourcing these types of unpredictable and intermittent workloads. It is a dynamically scaling, on-demand version of Azure SQL Database that eliminates the complexity of resourcing and managing unpredictable workloads. Simply create a serverless database and connect your application, with no upfront resource configuration required. Serverless SQL databases automatically pause, resume and scale compute based upon your app’s requirements, making them particularly cost effective for variable or unpredictable workloads – or when you’re simply unsure of your requirements.
With resources available on-demand, serverless SQL databases optimize costs with pay per-second billing that aligns with the app’s performance, so you only pay for the compute resources you use .
Built upon the SQL Server architecture, serverless SQL databases are fully-managed, always up to date and highly available with a 99.99% uptime guarantee. Combined with built-in intelligence to optimize database performance and security, serverless SQL Databases help you be more productive so you can focus more on what you do best, building great apps faster and more cost effectively.