Service Fabric is the foundational technology introduced by Microsoft Azure to empower the large-scale Azure service. In this session, you’ll get an overview of containers like Docker after an overview of Service Fabric, explain the difference between it and Kubernetes as a new way To Orchestrate Microservices. You’ll learn how to develop a Microservices application and how to deploy those services to Service Fabric clusters and the new serverless Service Fabric Mesh service. We’ll dive into the platform and programming model advantages including stateful services and actors for low-latency data processing and more. You will learn: Overview of containers Overview of Service Fabric Difference between Kubernetes and Service Fabric Setup Environment to start developing an application using Microservices with Service Fabric.
Shared as part of Cloud Community Days on 17th June 2020 - ccdays.konfhub.com
In this session, we will discuss a use case where we need to quickly develop web and mobile front end applications which are using several different frameworks, hosting options, and complex integrations between systems under the hood. Let’s see how we can leverage serverless technologies (Azure Functions and logic apps) and Low Code/No code platform to achieve the goal. During the session we will go though the code followed by a demonstration.
Here is a slidedeck for the training offerings from CodeOps Technologies. Interested in organizing a training in your organization? Contact us at: [email protected]
In this workshop, you will understand how Azure DevOps Services helps you scale DevOps adoption strategies in enterprise. We will explore various feature and services that can enable you to implement various DevOps practices starting from planning, version control, CI & CD , Dependency Management and Test planning.
It is difficult to deploy interloop Kubernetes development in current state. Know these open-source projects that can save us from the burden of various tools and help in deploying microservices on Kubernetes cluster without saving secrets in a file.
Accelerating Deployment With Azure DevOps - Murughan and Leena - CCDays CodeOps Technologies LLP
This talk helps you understand why DevOps and the power of Azure DevOps which helps in automating build & release process faster for multiple languages & framework.
Presented as part of Cloud Community Days on 19th June - ccdays.konfhub.com
In this session, we will understand how to create your first pipeline and build an environment to restore dependencies and how to run tests in Azure DevOps followed by building an image and pushing it to container registry.
Let’s dive into the world of serverless and give you real world examples of how to get started. We will focus on Azure Functions in Java and discuss how to provision, deploy and test them in a productive environment. In my demos we will see the ease of local development leveraging from the great integration in Visual Studio Code. Finally, let’s ship our samples and scale them in Azure. If you are tired of server maintenance and want to achieve more with your java functions , don’t miss this session.
In this talk, we will start with some introduction to Azure Functions, its triggers and bindings. Later we will build a serverless solution to solve a problem statement by using different triggers and bindings of Azure Functions.
Language to be used: C# and IDE - Visual Studio 2019 Community Edition"
In this session, we will explore how to deploy .net core web apps in azure Kubernetes service using azure DevOps starter and Azure DevOps.
Presented as part of Cloud Community Days on 19th June - ccdays.konfhub.com
Imagine a scenario, where you can launch a video call or chat with an advisor, agent, or clinician in just one-click. We will explore application patterns that will enable you to write event-driven, resilient and highly scalable applications with Functions that too with power of engaging communication experience at scale. During the session, we will go through the use case along with code walkthrough and demonstration.
Shift Remote AI: Build and deploy PyTorch Models with Azure Machine Learning ...Shift Conference
Take a deep look into Azure Machine Learning, a cloud service that helps you build, train, deploy, and manage models. Walk through the data science process and then have some fun creating a ML recognition model based on the Simpsons cartoon with PyTorch. You'll leave this session with a better grasp of the technological components of Azure Machine Learning services.
Tasos Moustakis, Infrastructure Technology Solutions Manager at Uni Systems, explains how Microsoft Azure migration runs smoothly through Ansible Automation platform. From Cloud Migration Through Automation: Next Level Flexibility virtual event, hosted on September 30, 2020
UK Azure User Group - Blazor and Azure (Tim Ebenezer)Richard Conway
This document summarizes a presentation on using Blazor and Azure in an enterprise environment. It begins with an introduction to Blazor, explaining that it is a front end framework that can run on the client or server using C# and interacts with Azure services. It then compares Blazor to JavaScript frameworks. An example high level Blazor and Azure architecture is shown. Key considerations for deploying Blazor at scale in an enterprise are discussed, including scaling the SignalR service, handling large file uploads, logging to Application Insights, and page lifecycles. A demonstration of SignalR scaling is provided. Follow up reading resources are listed at the end.
This presentation is from the Integration Day event, a TechMeet360 Community Initiative, held on September 10, 2016 at Microsoft GSTC in Bangalore. In this slide, Microsoft's Escalation Engineers Tulika Chaudharie and Harikharan Krishnaraju explain using Azure Functions for Integration. The presentation starts with a general overview of Azure Functions and then it moves on to some of the common Integration Patterns and how Azure Functions fit into the scenarios.
Serverless compute with Azure Functions abstracts away infrastructure management and allows developers to focus on writing code for triggered operations. Azure Functions supports bindings to data sources and services that avoid writing boilerplate integration code, and can be deployed and managed via the Azure Functions runtime, CLI tools, templates and samples on GitHub.
Introduction to Azure Functions.
An event-based serverless compute experience to accelerate your development. Scale based on demand and pay only for the resources you consume.
CREATING REAL TIME DASHBOARD WITH BLAZOR, AZURE FUNCTION COSMOS DB AN AZURE S...CodeOps Technologies LLP
In this talk people will get to know how we can use change feed feature of Cosmos DB and use azure functions and signal or service to develop a real time dashboard system
Azure Functions allow for event-driven, serverless code execution in multiple languages like C#, Node.js, and Python. Functions can be triggered by events from various Azure services and external sources. They provide automatic scaling based on demand and sub-second billing. Functions make it easy to compose cloud applications from loosely coupled services and integrate with other Azure services like Logic Apps, Storage, SQL Database, and more.
Building Deploying and Managing Microservices-based Applications with Azure P...CodeOps Technologies LLP
This presentation covers:
* Setup AKS cluster on Azure
* Deploy a sample microservice-based highly available and scalable app to the cluster
* Set up Azure pipeline for CI and CD
* Automate deployment of the application on Git commit to AKS cluster
Presented as part of Cloud Community Days - 19 June - ccdays.konfhub.com
Azure Functions VS AWS Lambda: overview and comparisonAlex Zyl
The document compares serverless computing platforms Azure Functions and AWS Lambda. It provides an overview of key concepts like functions, triggers, bindings and event models. It also outlines some example use cases for functions. The document analyzes the architecture and infrastructure of Azure Functions and AWS Lambda and compares features between the two platforms. It concludes by listing relevant documentation and SDK repositories for further reference.
This document summarizes the design, development, deployment, and monitoring of serverless applications using Azure Functions. It outlines best practices for distributed architecture, cloud DevOps, and using Logic Apps for workflow orchestration. The development process involves using Azure Functions Core Tools and bindings to connect triggers and outputs. Deployment is done through Azure Resource Manager templates. Monitoring is done through Application Insights.
Prometheus is a popular open source metric monitoring solution and Azure Monitor provides a seamless onboarding experience to collect Prometheus metrics. Learn how to configure scraping of Prometheus metrics with Azure Monitor for containers running in AKS cluster.
This document provides an overview of Azure Logic Apps. It defines Logic Apps as a workflow engine that allows for easy scaling and integration of Azure services without code. Logic Apps use connectors, triggers, and workflows (conditions and actions) to automate tasks and business processes. Examples of Logic App use cases include processing files uploaded to FTP and importing data into SQL Server, processing RSS feeds and sending summary emails, and creating tickets in Dynamics CRM from incoming emails. The document demonstrates building Logic Apps with triggers like schedules and HTTP requests, and includes actions like outputting to Google Drive and sending emails. It also provides references for additional Logic App integration scenarios.
Join us for a deep dive into Windows Azure. We’ll start with a developer-focused overview of this brave new platform and the cloud computing services that can be used either together or independently to build amazing applications. As the day unfolds, we’ll explore data storage, SQL Azure™, and the basics of deployment with Windows Azure. Register today for these free, live sessions in your local area.
NWCloud Cloud Track - Overview of Cloud Computing and Windows Azure 101nwcloud
This document provides an overview of Microsoft's Windows Azure platform presented by Mithun Dhar, a Developer Evangelist at Microsoft. The key points covered include:
- What a Developer Evangelist is and Mithun Dhar's contact details.
- An agenda for the overview presentation covering Windows Azure, storage options, and deploying solutions.
- A brief introduction to Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
- An overview of the main components that make up the Windows Azure platform including cloud fabric, roles, storage, app fabric, and dev fabric.
Let’s dive into the world of serverless and give you real world examples of how to get started. We will focus on Azure Functions in Java and discuss how to provision, deploy and test them in a productive environment. In my demos we will see the ease of local development leveraging from the great integration in Visual Studio Code. Finally, let’s ship our samples and scale them in Azure. If you are tired of server maintenance and want to achieve more with your java functions , don’t miss this session.
In this talk, we will start with some introduction to Azure Functions, its triggers and bindings. Later we will build a serverless solution to solve a problem statement by using different triggers and bindings of Azure Functions.
Language to be used: C# and IDE - Visual Studio 2019 Community Edition"
In this session, we will explore how to deploy .net core web apps in azure Kubernetes service using azure DevOps starter and Azure DevOps.
Presented as part of Cloud Community Days on 19th June - ccdays.konfhub.com
Imagine a scenario, where you can launch a video call or chat with an advisor, agent, or clinician in just one-click. We will explore application patterns that will enable you to write event-driven, resilient and highly scalable applications with Functions that too with power of engaging communication experience at scale. During the session, we will go through the use case along with code walkthrough and demonstration.
Shift Remote AI: Build and deploy PyTorch Models with Azure Machine Learning ...Shift Conference
Take a deep look into Azure Machine Learning, a cloud service that helps you build, train, deploy, and manage models. Walk through the data science process and then have some fun creating a ML recognition model based on the Simpsons cartoon with PyTorch. You'll leave this session with a better grasp of the technological components of Azure Machine Learning services.
Tasos Moustakis, Infrastructure Technology Solutions Manager at Uni Systems, explains how Microsoft Azure migration runs smoothly through Ansible Automation platform. From Cloud Migration Through Automation: Next Level Flexibility virtual event, hosted on September 30, 2020
UK Azure User Group - Blazor and Azure (Tim Ebenezer)Richard Conway
This document summarizes a presentation on using Blazor and Azure in an enterprise environment. It begins with an introduction to Blazor, explaining that it is a front end framework that can run on the client or server using C# and interacts with Azure services. It then compares Blazor to JavaScript frameworks. An example high level Blazor and Azure architecture is shown. Key considerations for deploying Blazor at scale in an enterprise are discussed, including scaling the SignalR service, handling large file uploads, logging to Application Insights, and page lifecycles. A demonstration of SignalR scaling is provided. Follow up reading resources are listed at the end.
This presentation is from the Integration Day event, a TechMeet360 Community Initiative, held on September 10, 2016 at Microsoft GSTC in Bangalore. In this slide, Microsoft's Escalation Engineers Tulika Chaudharie and Harikharan Krishnaraju explain using Azure Functions for Integration. The presentation starts with a general overview of Azure Functions and then it moves on to some of the common Integration Patterns and how Azure Functions fit into the scenarios.
Serverless compute with Azure Functions abstracts away infrastructure management and allows developers to focus on writing code for triggered operations. Azure Functions supports bindings to data sources and services that avoid writing boilerplate integration code, and can be deployed and managed via the Azure Functions runtime, CLI tools, templates and samples on GitHub.
Introduction to Azure Functions.
An event-based serverless compute experience to accelerate your development. Scale based on demand and pay only for the resources you consume.
CREATING REAL TIME DASHBOARD WITH BLAZOR, AZURE FUNCTION COSMOS DB AN AZURE S...CodeOps Technologies LLP
In this talk people will get to know how we can use change feed feature of Cosmos DB and use azure functions and signal or service to develop a real time dashboard system
Azure Functions allow for event-driven, serverless code execution in multiple languages like C#, Node.js, and Python. Functions can be triggered by events from various Azure services and external sources. They provide automatic scaling based on demand and sub-second billing. Functions make it easy to compose cloud applications from loosely coupled services and integrate with other Azure services like Logic Apps, Storage, SQL Database, and more.
Building Deploying and Managing Microservices-based Applications with Azure P...CodeOps Technologies LLP
This presentation covers:
* Setup AKS cluster on Azure
* Deploy a sample microservice-based highly available and scalable app to the cluster
* Set up Azure pipeline for CI and CD
* Automate deployment of the application on Git commit to AKS cluster
Presented as part of Cloud Community Days - 19 June - ccdays.konfhub.com
Azure Functions VS AWS Lambda: overview and comparisonAlex Zyl
The document compares serverless computing platforms Azure Functions and AWS Lambda. It provides an overview of key concepts like functions, triggers, bindings and event models. It also outlines some example use cases for functions. The document analyzes the architecture and infrastructure of Azure Functions and AWS Lambda and compares features between the two platforms. It concludes by listing relevant documentation and SDK repositories for further reference.
This document summarizes the design, development, deployment, and monitoring of serverless applications using Azure Functions. It outlines best practices for distributed architecture, cloud DevOps, and using Logic Apps for workflow orchestration. The development process involves using Azure Functions Core Tools and bindings to connect triggers and outputs. Deployment is done through Azure Resource Manager templates. Monitoring is done through Application Insights.
Prometheus is a popular open source metric monitoring solution and Azure Monitor provides a seamless onboarding experience to collect Prometheus metrics. Learn how to configure scraping of Prometheus metrics with Azure Monitor for containers running in AKS cluster.
This document provides an overview of Azure Logic Apps. It defines Logic Apps as a workflow engine that allows for easy scaling and integration of Azure services without code. Logic Apps use connectors, triggers, and workflows (conditions and actions) to automate tasks and business processes. Examples of Logic App use cases include processing files uploaded to FTP and importing data into SQL Server, processing RSS feeds and sending summary emails, and creating tickets in Dynamics CRM from incoming emails. The document demonstrates building Logic Apps with triggers like schedules and HTTP requests, and includes actions like outputting to Google Drive and sending emails. It also provides references for additional Logic App integration scenarios.
Join us for a deep dive into Windows Azure. We’ll start with a developer-focused overview of this brave new platform and the cloud computing services that can be used either together or independently to build amazing applications. As the day unfolds, we’ll explore data storage, SQL Azure™, and the basics of deployment with Windows Azure. Register today for these free, live sessions in your local area.
NWCloud Cloud Track - Overview of Cloud Computing and Windows Azure 101nwcloud
This document provides an overview of Microsoft's Windows Azure platform presented by Mithun Dhar, a Developer Evangelist at Microsoft. The key points covered include:
- What a Developer Evangelist is and Mithun Dhar's contact details.
- An agenda for the overview presentation covering Windows Azure, storage options, and deploying solutions.
- A brief introduction to Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS).
- An overview of the main components that make up the Windows Azure platform including cloud fabric, roles, storage, app fabric, and dev fabric.
Introduction To Cloud Computing Winsows Azure101Mithun T. Dhar
The Windows Azure platform is a set of high-performance cloud computing services that can be used together or independently and enable developers to leverage existing skills and familiar tools to develop cloud applications. In this session, we’ll provide a developer-focused overview of this new online service computing platform. We’ll explore the components, key features and real day-to-day benefits of Windows Azure.
Highlights include:
· What is cloud computing?
· Running web and web service applications in the cloud
· Using the Windows Azure and local developer cloud fabric
· Getting started – tools, SDKs and accounts
· Writing applications for Windows Azure
Cloud computing and the Windows Azure Services Platform (KU Leuven)Maarten Balliauw
Maarten Balliauw gave a presentation on cloud computing and the Windows Azure Services Platform. He began with an overview of cloud computing and defined infrastructure as a service (IAAS), platform as a service (PAAS), and software as a service (SASS). He then discussed Windows Azure and its core services - Blob storage, Table storage, Queue storage, and SQL Azure. Balliauw also covered the Windows Azure AppFabric and its Service Bus and Access Control capabilities. He concluded with information on getting started with Azure and resources for learning more.
BizSpark Startup Night Windows Azure March 29, 2011Spiffy
This document provides an overview of Windows Azure and its core concepts. It discusses:
- Why cloud computing started and how Windows Azure came about to address challenges with managing machines.
- Key characteristics of cloud computing like elasticity, reduced costs, and new capabilities.
- Core Windows Azure services like Blob storage, Tables, Queues and AppFabric for identity management.
- How to plan application architecture, deploy to Windows Azure using tools like Visual Studio, and manage applications once deployed.
The document discusses Microsoft Azure cloud services for solution architects, providing an overview of Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) offerings, how to design for scalability and performance, and the importance of using proof of concepts to identify architectural risks early in the design process. It also emphasizes how the agility of Azure allows for rapidly prototyping solutions through a mix of PaaS and IaaS.
Sajeetharan Sinnathurai is a cloud solution architect with over 10 years of experience as a full stack developer specializing in Angular and Azure. He has made over 10,000 contributions to Stack Overflow and maintains 140 code repositories on StackBlitz. Sinnathurai regularly shares his expertise in developer communities and has received numerous Microsoft certifications and awards for his open source contributions.
This document provides an overview of Microsoft education and certification opportunities for IT professionals. It discusses databases like MySQL and Microsoft SQL, Azure SQL Database, Power BI, cloud application development, building bots, DevOps, Visual Studio 2019, and certification paths for data management and analytics, Azure DevOps, Azure apps and infrastructure, and new job roles. Key topics covered include what a database is, differences between MySQL and SQL, benefits of Azure SQL Database, what Power BI and bots are, what DevOps is, and Visual Studio workloads. It aims to help optimize skills and prepare attendees for new opportunities through Microsoft training and certifications.
This document discusses Azure Machine Learning services for data scientists. It provides an overview of Azure Machine Learning Studio for building and deploying machine learning models with over 100 modules. Numbers show hundreds of thousands of deployed models serving billions of requests. It also discusses Azure Batch AI for scalable machine learning training without managing infrastructure, and Azure Databricks for Apache Spark as a managed service on Azure. The document outlines the machine learning development lifecycle supported in Azure and tools for experimentation, model management, and operationalization of models.
Introduction to Microsoft Azure. Covers the change to a cloud development paradigm. Motivations for the change, Pricing structures, and an exercise in IT portfolio evaluation.
The document outlines an agenda for a workshop on application development with Azure cloud workloads. The agenda includes introductions to cloud computing, Azure services like App Service and Functions, event-based development, and Cognitive Services. It emphasizes that cloud skills are in high demand and learning them can provide opportunities to try services for free and improve one's resume.
When it comes to Large Scale data processing and Machine Learning, Apache Spark is no doubt one of the top battle-tested frameworks out there for handling batched or streaming workloads. The ease of use, built-in Machine Learning modules, and multi-language support makes it a very attractive choice for data wonks. However bootstrapping and getting off the ground could be difficult for most teams without leveraging a Spark cluster that is already pre-provisioned and provided as a managed service in the Cloud, while this is a very attractive choice to get going, in the long run, it could be a very expensive option if it’s not well managed.
As an alternative to this approach, our team has been exploring and working a lot with running Spark and all our Machine Learning workloads and pipelines as containerized Docker packages on Kubernetes. This provides an infrastructure-agnostic abstraction layer for us, and as a result, it improves our operational efficiency and reduces our overall compute cost. Most importantly, we can easily target our Spark workload deployment to run on any major Cloud or On-prem infrastructure (with Kubernetes as the common denominator) by just modifying a few configurations.
In this talk, we will walk you through the process our team follows to make it easy for us to run a production deployment of our Machine Learning workloads and pipelines on Kubernetes which seamlessly allows us to port our implementation from a local Kubernetes set up on the laptop during development to either an On-prem or Cloud Kubernetes environment
Building Cloud-Native Applications with Microsoft Windows AzureBill Wilder
Cloud computing is here to stay, and it is never too soon to begin understanding the impact it will have on application architecture. In this talk we will discuss the two most significant architectural mind-shifts, discussing the key patterns changes generally and seeing how these new cloud patterns map naturally into specific programming practices in Windows Azure. Specifically this relates to (a) Azure Roles and Queues and how to combine them using cloud-friendly design
patterns, and (b) the combination of relational data and non-relational data, how to decide among them, and how to combine them. The goal is for mere mortals to build highly reliable applications that scale economically. The concepts discussed in this talk are relevant for developers and architects building systems for the cloud today, or who want to be prepared to move to the cloud in the future.
This talk was delivered by Bill Wilder at the Vermont Code Camp 2 on 11-Sept-2010.
The cloud is all the rage. Does it live up to its hype? What are the benefits of the cloud? Join me as I discuss the reasons so many companies are moving to the cloud and demo how to get up and running with a VM (IaaS) and a database (PaaS) in Azure. See why the ability to scale easily, the quickness that you can create a VM, and the built-in redundancy are just some of the reasons that moving to the cloud a “no brainer”. And if you have an on-prem datacenter, learn how to get out of the air-conditioning business!
Il cloud è il presente e il futuro di moltissime soluzioni e infrastrutture aziendali. In questa sessione capiremo cos’è il cloud, che tipi di cloud ci sono e vedremo gli aspetti principali di Azure, dalle VM (IaaS) ai vari servizi di piattaforma (PaaS), facendo anche una piccola deviazione sulle API del Microsoft Graph e dei Cognitive Services (SaaS)
This document provides an overview of Windows Azure, Microsoft's cloud computing platform. It discusses key concepts like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The document outlines various Windows Azure services like compute, storage, SQL Azure, and AppFabric and how they can be used to build cloud applications. Pricing models for Windows Azure compute and SQL Azure are also presented.
Azure is the Latest technology and it is going to be the future, Katpro Technologies help you to Migrate your on-Premise Environment to Azure Cloud Solutions, and also help you to develop the Cloud solutions/Applications in the less span of time.
This document discusses using event-driven architectures and serverless computing with AWS services. It begins with defining event-driven architectures and how serverless architectures relate to them. It then outlines several AWS services like EventBridge, Step Functions, SQS, SNS, and Lambda that are well-suited for building event-driven applications. The document demonstrates using S3, DynamoDB, API Gateway and other services to build a serverless hotel data ingestion and shopping platform that scales independently for static and dynamic data. It shows how to upload, store, and stream hotel data and expose APIs using serverless AWS services in an event-driven manner.
This document provides an overview of the Azure Batch Service, including its core features, architecture, and monitoring capabilities. It discusses how Azure Batch allows uploading batch jobs to the cloud to be executed and managed, covering concepts like job scheduling, resource management, and process monitoring. The document also demonstrates Azure Batch usage through the Azure portal and Batch Explorer tool and reviews quotas and limits for Batch accounts, pools, jobs, and other resources.
In this session, we will take a deep-dive into the DevOps process that comes with Azure Machine Learning service, a cloud service that you can use to track as you build, train, deploy and manage models. We zoom into how the data science process can be made traceable and deploy the model with Azure DevOps to a Kubernetes cluster.
At the end of this session, you will have a good grasp of the technological building blocks of Azure machine learning services and can bring a machine learning project safely into production.
When it comes to microservice architecture, sometimes all you wanted is to perform cross cutting concerns ( logging, authentication , caching, CORS, Routing, load balancing , exception handling , tracing, resiliency etc..) and also there might be a scenario where you wanted to perform certain manipulations on your request payload before hitting into your actual handler. And this should not be a repetitive code in each of the services , so all you might need is a single place to orchestrate all these concerns and that is where Middleware comes into the picture. In the demo I will be covering how to orchestrate these cross cutting concerns by using Azure functions as a Serverless model.
We will walk through the exploration, training and serving of a machine learning model by leveraging Kubeflow's main components. We will use Jupyter notebooks on the cluster to train the model and then introduce Kubeflow Pipelines to chain all the steps together, to automate the entire process.
Must Know Azure Kubernetes Best Practices And Features For Better Resiliency ...CodeOps Technologies LLP
Running day-1 Ops on your Kubernetes is somewhat easy, but it is quite daunting to manage day two challenges. Learn about AKS best practices for your cloud-native applications so that you can avoid blow up your workloads.
What if you could combine Trello, GitLab, JIRA, Calendar, Slack, Confluence, and more - all together into one solution?
Yes, we are talking about Space - the latest tool from JetBrains famous for its developer productivity-enhancing tools (esp. IntelliJ IDEA).
Here we have explained about JetBrains' space and its functionalities.
This document provides an overview of functional programming concepts in Java 8 including lambdas and streams. It introduces lambda functions as anonymous functions without a name. Lambdas allow internal iteration over collections using forEach instead of external iteration with for loops. Method references provide a shorthand for lambda functions by "routing" function parameters. Streams in Java 8 enhance the library and allow processing data pipelines in a functional way.
This talk will serve as a practical introduction to Distributed Tracing. We will see how we can make best use of open source distributed tracing platforms like Hypertrace with Azure and find the root cause of problems and predict issues in our critical business applications beforehand.
This talk serves as a practical introduction to Distributed Tracing. We will see how we can make best use of open source distributed tracing platforms like Hypertrace with Azure and find the root cause of problems and predict issues in our critical business applications beforehand.
Presentation part of Open Source Days on 30 Oct - ossdays.konfhub.com
Tailwind Traders recent internal employee survey showed their employees are frustrated with lengthy processes for simple actions, such as booking vacation and other company benefits. They want to reduce the friction of reviewing and booking vacation so it’s a simple, easy and pleasant process for their employees. In this session you will see how Tailwind Traders applied Conversational AI best practices to simplify the vacation process for their employees. Using the Bot Framework Composer tooling you can quickly build conversation flows, incorporate intelligence services such as Q&A maker and LUIS, test and deploy your virtual assistant to the cloud and embed it where your customers and employees spend their time.
Text analytics, sentiment detection etc. form a very important part of NLP. With huge data available today, making sense of the dara, detecting latent patterns, tagging documents etc. has become an important part of language modelling. Let us see how Azure Cognitive services enable us to detect document sentiments, Named entities, Key phrases, contextual information like geo spatial indices etc.
AI has become the most popular buzz word among tech and non-tech individuals and we talk about its applications in daily life. The applications are getting more and more complex, and classical computers are not able to handle most of the work. In this talk, I would like to demonstrate how a hybrid Quantum-Classical Machine Learning model will work and how it can benefit us in the longer run.
Slow applications are no fun. Application performance monitoring (APM) makes tracking down issues problems much easier. But which tools should you use? Join this session to know how to build a microservice using Java and containerize it to deploy it on Azure.
What Do Contribution Guidelines Say About Software Testing? (MSR 2025)Andre Hora
Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
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Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
Key improvements and features of Cinema 4D 2025 include:
Procedural Modeling: New tools and workflows for creating models procedurally, including fabric weave and constellation generators.
Procedural Animation: Field Driver tag for procedural animation.
Simulation Enhancements: Improved particle, Pyro, and rigid body simulations.
Spline Tools: Enhanced spline tools for motion graphics and animation, including spline modifiers from Rocket Lasso now included for all subscribers.
Unified Simulation & Particles: Refined physics-based effects and improved particle systems.
Boolean System: Modernized boolean system for precise 3D modeling.
Particle Node Modifier: New particle node modifier for creating particle scenes.
Learning Panel: Intuitive learning panel for new users.
Redshift Integration: Maxon now includes access to the full power of Redshift rendering for all new subscriptions.
In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov
Imagine if apps could think, plan, and team up like humans. Welcome to the world of AI agents and agentic user interfaces (UI)! In this session, we'll explore how AI agents make decisions, collaborate with each other, and create more natural and powerful experiences for users.
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
Why Orangescrum Is a Game Changer for Construction Companies in 2025Orangescrum
Orangescrum revolutionizes construction project management in 2025 with real-time collaboration, resource planning, task tracking, and workflow automation, boosting efficiency, transparency, and on-time project delivery.
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Landscape of Requirements Engineering for/by AI through Literature ReviewHironori Washizaki
Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
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Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
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Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
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Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
3. What is Azure Batch Service
Azure Batch Service – Core Services
Batch Hosting and Processing Architecture
Demo – Azure Batch Using Azure Portal
Agenda
4. What is Azure Batch Service
ABS allows you to upload batch jobs into the cloud and Azure Manage
the executions.
What is a Batch Job – a job that needs to be re-run multiple times on
may be different pieces of data or same sort of data, can be an example
of Batch Job.
17. Azure BatchResource Quotas
Resource Default Max
Batch accounts per region per subscription 1-3 50
Dedicated cores per Batchaccount 90-900 Unspecified
Low-priority cores per Batchaccount 10 – 100 Unspecified
Active jobs and job schedules per Batch account 100 - 300 1,000
Pools per Batchaccount 20 –100 500
19. Azure BatchOther Limits
Resource Limit
Concurrent tasks per computenode 4 x node cores
Applications per Batch account 20
Application packages per application 40
Maximum task lifetime 180 days
Compute nodes in inter-node communication enabled pool 100