Kafka summit SF 2019 - the art of the event-streaming appNeil Avery
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database.
In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.
The art of the event streaming application: streams, stream processors and sc...confluent
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.
Kafka summit SF 2019 - the art of the event-streaming appNeil Avery
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database.
In this talk, I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.
The art of the event streaming application: streams, stream processors and sc...confluent
Have you ever imagined what it would be like to build a massively scalable streaming application on Kafka, the challenges, the patterns and the thought process involved? How much of the application can be reused? What patterns will you discover? How does it all fit together? Depending upon your use case and business, this can mean many things. Starting out with a data pipeline is one thing, but evolving into a company-wide real-time application that is business critical and entirely dependent upon a streaming platform is a giant leap. Large-scale streaming applications are also called event streaming applications. They are classically different from other data systems; event streaming applications are viewed as a series of interconnected streams that are topologically defined using stream processors; they hold state that models your use case as events. Almost like a deconstructed realtime database. In this talk I step through the origins of event streaming systems, understanding how they are developed from raw events to evolve into something that can be adopted at an organizational scale. I start with event-first thinking, Domain Driven Design to build data models that work with the fundamentals of Streams, Kafka Streams, KSQL and Serverless (FaaS). Building upon this, I explain how to build common business functionality by stepping through patterns for Scalable payment processing Run it on rails: Instrumentation and monitoring Control flow patterns (start, stop, pause) Finally, all of these concepts are combined in a solution architecture that can be used at enterprise scale. I will introduce enterprise patterns such as events-as-a-backbone, events as APIs and methods for governance and self-service. You will leave talk with an understanding of how to model events with event-first thinking, how to work towards reusable streaming patterns and most importantly, how it all fits together at scale.
Pre-Con Education: What Is CA Unified Infrastructure Management and what's ne...CA Technologies
If you are new to CA Unified Infrastructure Management (formerly known as CA Nimsoft Monitor), learn more about this comprehensive monitoring solution here. This presentation covers the “basics” of CA Unified Infrastructure Management (CA UIM) to help you build your knowledge on the general concepts, components and features that CA UIM offers. We will also cover the major features that are now available within our recent 8.0 release, including new analytics (“time to threshold” and “time over threshold”), reporting improvements (TopN and “At A Glance” reports) and more.
For more information on DevOps solutions from CA Technologies, please visit: http://bit.ly/1wbjjqX
Hello Sir
We are a premier academic writing agency with industry partners in UK, Australia and Middle East and over 15 years of experience. We are looking to establish long-term relationships with industry partners and would love to discuss this opportunity further with you.
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8 Key Elements to Modern IT Operations Management with a Digital Operations C...OpsRamp
Struggling to control the chaos of your IT infrastructure? Here are the 8 Key Elements to Modern IT Operations Management with a Digital Operations Command Center.
Getting Started with Nastel AutoPilot Business Views and Policies - a TutorialSam Garforth
A tutorial presentation introducing the concepts of business views and policies for monitoring IBM MQ and any other middleware or technology for middleware-centric application performance management.
Proposed pricing model for cloud computingAdeel Javaid
Cloud computing is an emerging technology of business computing and it is becoming a development trend. The process of entering into the cloud is generally in the form of queue, so that each user needs to wait until the current user is being served. In the system, each Cloud Computing User (CCU) requests Cloud Computing Service Provider (CCSP) to use the resources, if CCU(cloud computing user) finds that the server is busy then the user has to wait till the current user completes the job which leads to more queue length and increased waiting time. So to solve this problem, it is the work of CCSP’s to provide service to users with less waiting time otherwise there is a chance that the user might be leaving from queue. CCSP’s can use multiple servers for reducing queue length and waiting time. In this paper, we have shown how the multiple servers can reduce the mean queue length and waiting time. Our approach is to treat a multiserver system as an M/M/m queuing model, such that a profit maximization model could be worked out.
In this presentation we look at the use of the Hortonworks Data Flow (HDF) platform application in the finance sector operations. We define the process of deployment and use of the distribution as part of the operations and how the different components are integrated to support real-time payments and banking functionality. Documenting the challenges faced to allow a high performance system that promotes data integrity and real-time visualisation using the Hortonworks Data Platform (HDP). Focusing specially on the use of Apache Zeppelin workbooks across the business as they main information management tool. Our specific approach focus on creating a flexible system that allows fast prototyping and integrated visualisation, monitoring and audit. Demonstrating the use of the HDF distribution on the creation of business domain abstractions to in a real life application of a Domain Driven Design. We implement a cross platform use of Avro, as future prof model and language that is understood by the business and IT areas. Due to the scalability of the platform we can execute payments operations at high rate even across countries at the same time reusing the same architecture to monitor the business operations.
Speaker
Luis Caldeira, Chief Architect, Orwell Group
Gian Marco Cabiato, Head of Engineering, Orwell Group
Smart Services & Smart Clients - How Microservices Change the Way You Build a...Neil Mansilla
YAPC talk abstract: http://www.yapcna.org/yn2015/talk/5945
YAPC video: http://livestream.com/yapc/events/4112215/videos/89840147
I gave this talk on microservices architecture at YAPC (Yet Another Perl Conference) North America in Salt Lake City on June 10, 2015.
We took a deeper dive into the how and why Runscope implements a microservices architecture.
Survey on reliable sla based monitoring for billing scheme in cloud computingeSAT Journals
Abstract The facility to record and keep report of the usage of cloud resources in reliable and certifiable manner is a pioneer to both cloud service provider and to users too. Because usage information is potentially susceptible and must be verifiably correct. This is critical job because in an attempt to provide mutually integrated approach to the system, we come to know that computational overhead increase due to use of traditional asymmetric key operations which lead the system bottleneck. The success of any billing system depends upon factors like integrity, non repudiation. The traditional billing systems are restricted in the security capabilities. To overcome this drawback, paper introduces the billing system called THEMIS. This new billing system introduces some new attributes which provides security facilities to the billing transactions. This system brings new concept called Cloud Notary Authority (CNA) which administer the billing transactions and make it good enough to accept by users and cloud service provider. The Cloud Notary Authority generates the binding information which helps system to solve the future conflicts between users and cloud service provider. SLA (service level agreement) monitoring approach is introduced to provide forgery resistance which doesn’t allow to modify the information even by supervisor of the cloud service provider. The service level agreement monitoring approach is improved with TPM (Trusted Platform Module) which sort the information in very secure manner. Keywords - Cloud Notary Authority, Cloud server provider, verification, transaction processing, resource allotment.
“Program to an interface, not an implementation” they[1] say …
But when IMyInterface foo = new IMyInterface() is not valid code … how are you supposed to achieve that ? The answer is Dependency Injection.
In this talk, we’ll talk about Dependency injection, what it is and what it is not. We’ll see how it is a valuable set of practices and patterns that help design maintainable software built on top of the SOLID object-oriented principles.
We’ll see how, when used properly, it delivers many benefits such as extensibility and testability … We’ll also cover some anti-patterns, ways of using Dependency Injection that can lead to code that is painful to understand and maintain
This talk is not about DI/IOC containers per se, but focuses on the core concepts of Dependency Injection. Those concepts are essential to understand how to use those “magic-looking” tools (if they are needed at all …)
This talk is not only for .NET developers. It will contain code examples written in C#, but should be understandable by developers with knowledge in other statically-typed object-oriented languages such as Java, Vb.NET, C++ …
Scaling for Success: Lessons from handling peak loads on Azure with NServiceBusParticular Software
What happens when 200k users unexpectedly decide to use your platform simultaneously? We’re using autoscale on Azure PaaS so surely we can handle that, right? Wrong! Ask me how I found out… After going through a bit of trouble, I want to help you avoid the same mistakes I made.
Beyond simple benchmarks—a practical guide to optimizing code Particular Software
We know it’s vital that code executed at scale performs well. But how do we know if our performance optimizations actually make it faster? Fortunately, we have powerful tools which help—BenchmarkDotNet is a .NET library for benchmarking optimizations, with many simple examples to help get started.
In most systems, the code we need to optimize is rarely straightforward. It contains assumptions we need to discover before we even know what to improve. The code is hard to isolate. It has dependencies, which may or may not be relevant to optimization. And even when we’ve decided what to optimize, it’s hard to reliably benchmark the before and after. Only measurements can tell us if our changes actually make things faster. Without them, we could even make things slower, without realizing.
In this webinar you’ll learn how to:
- Identify areas of improvement which optimize the effort-to-value ratio
- Isolate code to make its performance measurable without extensive refactoring
- Apply the performance loop of measuring, changing and validating to ensure performance actually improves and nothing breaks
- Gradually become more “performance aware” without costing an arm and a leg
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Pre-Con Education: What Is CA Unified Infrastructure Management and what's ne...CA Technologies
If you are new to CA Unified Infrastructure Management (formerly known as CA Nimsoft Monitor), learn more about this comprehensive monitoring solution here. This presentation covers the “basics” of CA Unified Infrastructure Management (CA UIM) to help you build your knowledge on the general concepts, components and features that CA UIM offers. We will also cover the major features that are now available within our recent 8.0 release, including new analytics (“time to threshold” and “time over threshold”), reporting improvements (TopN and “At A Glance” reports) and more.
For more information on DevOps solutions from CA Technologies, please visit: http://bit.ly/1wbjjqX
Hello Sir
We are a premier academic writing agency with industry partners in UK, Australia and Middle East and over 15 years of experience. We are looking to establish long-term relationships with industry partners and would love to discuss this opportunity further with you.
Thanks & Regards
visit our website.
www.onlineassignmenthelp.com.au
www.freeassignmenthelp.com
www.btechndassignment.cheapassignmenthelp.co.uk
www.cheapassignmenthelp.com
www.cheapassignmenthelp.co.uk/
8 Key Elements to Modern IT Operations Management with a Digital Operations C...OpsRamp
Struggling to control the chaos of your IT infrastructure? Here are the 8 Key Elements to Modern IT Operations Management with a Digital Operations Command Center.
Getting Started with Nastel AutoPilot Business Views and Policies - a TutorialSam Garforth
A tutorial presentation introducing the concepts of business views and policies for monitoring IBM MQ and any other middleware or technology for middleware-centric application performance management.
Proposed pricing model for cloud computingAdeel Javaid
Cloud computing is an emerging technology of business computing and it is becoming a development trend. The process of entering into the cloud is generally in the form of queue, so that each user needs to wait until the current user is being served. In the system, each Cloud Computing User (CCU) requests Cloud Computing Service Provider (CCSP) to use the resources, if CCU(cloud computing user) finds that the server is busy then the user has to wait till the current user completes the job which leads to more queue length and increased waiting time. So to solve this problem, it is the work of CCSP’s to provide service to users with less waiting time otherwise there is a chance that the user might be leaving from queue. CCSP’s can use multiple servers for reducing queue length and waiting time. In this paper, we have shown how the multiple servers can reduce the mean queue length and waiting time. Our approach is to treat a multiserver system as an M/M/m queuing model, such that a profit maximization model could be worked out.
In this presentation we look at the use of the Hortonworks Data Flow (HDF) platform application in the finance sector operations. We define the process of deployment and use of the distribution as part of the operations and how the different components are integrated to support real-time payments and banking functionality. Documenting the challenges faced to allow a high performance system that promotes data integrity and real-time visualisation using the Hortonworks Data Platform (HDP). Focusing specially on the use of Apache Zeppelin workbooks across the business as they main information management tool. Our specific approach focus on creating a flexible system that allows fast prototyping and integrated visualisation, monitoring and audit. Demonstrating the use of the HDF distribution on the creation of business domain abstractions to in a real life application of a Domain Driven Design. We implement a cross platform use of Avro, as future prof model and language that is understood by the business and IT areas. Due to the scalability of the platform we can execute payments operations at high rate even across countries at the same time reusing the same architecture to monitor the business operations.
Speaker
Luis Caldeira, Chief Architect, Orwell Group
Gian Marco Cabiato, Head of Engineering, Orwell Group
Smart Services & Smart Clients - How Microservices Change the Way You Build a...Neil Mansilla
YAPC talk abstract: http://www.yapcna.org/yn2015/talk/5945
YAPC video: http://livestream.com/yapc/events/4112215/videos/89840147
I gave this talk on microservices architecture at YAPC (Yet Another Perl Conference) North America in Salt Lake City on June 10, 2015.
We took a deeper dive into the how and why Runscope implements a microservices architecture.
Survey on reliable sla based monitoring for billing scheme in cloud computingeSAT Journals
Abstract The facility to record and keep report of the usage of cloud resources in reliable and certifiable manner is a pioneer to both cloud service provider and to users too. Because usage information is potentially susceptible and must be verifiably correct. This is critical job because in an attempt to provide mutually integrated approach to the system, we come to know that computational overhead increase due to use of traditional asymmetric key operations which lead the system bottleneck. The success of any billing system depends upon factors like integrity, non repudiation. The traditional billing systems are restricted in the security capabilities. To overcome this drawback, paper introduces the billing system called THEMIS. This new billing system introduces some new attributes which provides security facilities to the billing transactions. This system brings new concept called Cloud Notary Authority (CNA) which administer the billing transactions and make it good enough to accept by users and cloud service provider. The Cloud Notary Authority generates the binding information which helps system to solve the future conflicts between users and cloud service provider. SLA (service level agreement) monitoring approach is introduced to provide forgery resistance which doesn’t allow to modify the information even by supervisor of the cloud service provider. The service level agreement monitoring approach is improved with TPM (Trusted Platform Module) which sort the information in very secure manner. Keywords - Cloud Notary Authority, Cloud server provider, verification, transaction processing, resource allotment.
“Program to an interface, not an implementation” they[1] say …
But when IMyInterface foo = new IMyInterface() is not valid code … how are you supposed to achieve that ? The answer is Dependency Injection.
In this talk, we’ll talk about Dependency injection, what it is and what it is not. We’ll see how it is a valuable set of practices and patterns that help design maintainable software built on top of the SOLID object-oriented principles.
We’ll see how, when used properly, it delivers many benefits such as extensibility and testability … We’ll also cover some anti-patterns, ways of using Dependency Injection that can lead to code that is painful to understand and maintain
This talk is not about DI/IOC containers per se, but focuses on the core concepts of Dependency Injection. Those concepts are essential to understand how to use those “magic-looking” tools (if they are needed at all …)
This talk is not only for .NET developers. It will contain code examples written in C#, but should be understandable by developers with knowledge in other statically-typed object-oriented languages such as Java, Vb.NET, C++ …
Scaling for Success: Lessons from handling peak loads on Azure with NServiceBusParticular Software
What happens when 200k users unexpectedly decide to use your platform simultaneously? We’re using autoscale on Azure PaaS so surely we can handle that, right? Wrong! Ask me how I found out… After going through a bit of trouble, I want to help you avoid the same mistakes I made.
Beyond simple benchmarks—a practical guide to optimizing code Particular Software
We know it’s vital that code executed at scale performs well. But how do we know if our performance optimizations actually make it faster? Fortunately, we have powerful tools which help—BenchmarkDotNet is a .NET library for benchmarking optimizations, with many simple examples to help get started.
In most systems, the code we need to optimize is rarely straightforward. It contains assumptions we need to discover before we even know what to improve. The code is hard to isolate. It has dependencies, which may or may not be relevant to optimization. And even when we’ve decided what to optimize, it’s hard to reliably benchmark the before and after. Only measurements can tell us if our changes actually make things faster. Without them, we could even make things slower, without realizing.
In this webinar you’ll learn how to:
- Identify areas of improvement which optimize the effort-to-value ratio
- Isolate code to make its performance measurable without extensive refactoring
- Apply the performance loop of measuring, changing and validating to ensure performance actually improves and nothing breaks
- Gradually become more “performance aware” without costing an arm and a leg
If there is one certainty in software, it's that things fail. It's not a matter of if but when. All too often, we throw the error at our users, who have no means of solving the problem except for trying again. Alternatively, we build custom code to address edge cases that can't easily be fixed, and we do so with a dangerous lack of insight into the problem at hand.
In this session, we'll discuss the importance of system resilience and how you can equip your software with the ability to recover from failure scenarios. After exploring different types of failures and considering different resilience strategies, we'll dig deeper into the retry pattern by rolling our own. We'll also see existing options, such as Polly and NServiceBus, that can handle this complexity for you.
Join me and embrace your system's failures.
“Have all my overdue invoices been paid?” Seems a simple enough question. But once you factor in the effects of time, even the simplest question can turn into a mess of edge cases and complicated batch jobs that never quite complete on time.
The NServiceBus Outbox gives you consistency between database and messaging operations, something that would be nontrivial to do on your own. So how does it work? And how can you prove that it works?
Serverless is the new hotness, but are Azure Functions right for your system?
Presented by Adam Jones, Chief Technology Officer for LHP Telematics, LLC based in Westfield, IN.
We know it's useful to split up complex systems. We've seen the benefits of modular deployment of microservices. Dealing with only one piece of code at a time eases our cognitive load. But how do we know where to draw the service boundaries? In complex business domains, it's often difficult to know where to start. When we get our boundaries wrong, the clocks starts ticking. Before long, we hear ourselves say "it would be easier to re-write it".
Join Adam for practical advice on discovering the hidden boundaries in your systems. Help tease out the natural separation of concerns in a sample business domain. During 20 years of developing complex systems, Adam has had plenty of time to get things wrong. Learn to avoid the common pitfalls that can lead us down the path to "the big re-write".
Webinar recording: https://particular.net/webinars/finding-your-service-boundaries-a-practical-guide
Monoliths are hard work. They're difficult to understand, brittle to change, time-consuming to test and risky to deploy. And you're stuck with the monolith's tech stack so you can't use any modern architectures or technologies.
Decomposing monoliths is easy if you take the right approach, and it results in a distributed solution with many small components. Those can be independently updated, tested and deployed, which means you release better software, more quickly.
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- The right approach to decomposition
- the feature-driven approach, powered by Docker and NServiceBus
- How to run your monolith in a container
- How to extract features into new components
- How to plug components together with NServiceBus and run the whole stack in Docker containers
Daniel Marbach shows the differences between theory and practice when building a reliable message pump that consumes and produces messages from queues.
Trygve Lorentzen shows how he designs systems that the developers, support team, and decision makers at ProTeria can easily understand with the help of ServiceInsight.
William Brander and Sean Farmar show how the monitoring game changes when a system becomes distributed and you start delving into the world of microservices.
Learn:
* Why monitoring changes in distributed systems
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Making communications across boundaries simple with NServiceBusParticular Software
There are times when you should consider setting up secure communications between your software components across network boundaries.
Here are just a few:
* Your application is enormous (e.g., the global deployment of a marketing site targeting billions of people)
* Remoteness (e.g., your company has branch office locations around the globe)
* Your network constraints prevent communication (e.g., your machines in Azure Cloud Services are unable to talk to each other directly)
* You don't know the network conditions (e.g., IoT or mobile devices)
Yves Goeleven and Sean Feldman show how to overcome such challenges using NServiceBus.
Making communication across boundaries simple with Azure Service BusParticular Software
There are times when you should consider setting up secure communications between your software components across network boundaries.
Here are just a few:
* Your application is enormous (e.g., the global deployment of a marketing site targeting billions of people)
* Remoteness (e.g., your company has branch office locations around the globe)
* Your network constraints prevent communication (e.g., your machines in Azure Cloud Services are unable to talk to each other directly)
* You don't know the network conditions (e.g., IoT or mobile devices)
Yves Goeleven and Sean Feldman show how to overcome such challenges using Azure Service Bus.
There are many resources out there that walk you through the process of setting up distributed systems, queuing and asynchronous processes — with and without NServiceBus.
Despite all the online education, teams continue to make the same common mistakes when designing and implementing microservices architecture. While the mistakes can have devastating consequences, they are easy to avoid when approached intentionally.
Jeffrey Palermo and Justin Self share their experiences in overcoming common microservices pitfalls and show how NServiceBus naturally encourages better architecture, such as easy adherence to SOLID principles.
Learn:
* What a microservice really is (and is not)
* What mistakes teams commonly make
* How to avoid the pitfalls and design more robust and scalable architecture
* How to equip your team for a microservices architecture
Connect front end to back end using SignalR and MessagingParticular Software
If you've ever worked on a message-based system, at some point you have probably asked the question: How can I connect my asynchronous back-end to the front-end?
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The cornerstone of the system we will study in this webinar is SignalR, a library that facilitates adding bi-directional communication between the server and the browser over the WebSocket protocol. We will also see how NServiceBus messaging framework can be used in combination with SignalR.
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* Use SignalR with message-based systems
* Use SignalR with NServiceBus
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A lot is changing in NServiceBus v6, especially with the changes required to support asynchronous message processing with Async/Await.
Daniel Marbach shows how the v6 API update helps to avoid common Async/Await pitfalls and makes your code ready for the asynchronous APIs in the cloud.
Learn how to:
* Leverage the new asynchronous APIs to avoid common Async/Await pitfalls
* Maximize the message throughput by using asynchronous APIs concurrently in your handlers
* Write synchronous code in the new asynchronous message handlers
* and last but not least, see how this relates to delicious Swiss Chocolate.
If you're an existing NServiceBus user and you want to be well prepared to migrate your solutions to the latest version of NServiceBus, or you're a complete newbie to NServiceBus and want to see how it can help you avoid common Async/Await pitfalls — don't miss this webinar!
Daniel Marbach showa how to combine Async/Await together with the Task Parallel Library to create a message pump for a service bus.
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* Achieve "graceful" shutdowns by applying cancellation to the asynchronous operations
* Achieve throttling with your concurrent operations without blocking unnecessarily
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* Avoid serious production bugs as a result of asynchronous methods returning void
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When many developers think of Command-Query Responsibility Segregation (CQRS), they envision separate datastores for reads and writes, linked together by some kind of event-based synchronization mechanism. The reality is that for many domains this is overkill, while for others it still doesn’t solve fundamental concurrency issues.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
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.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
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2. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
A workflow consists of an orchestrated and
repeatable pattern of business activity enabled by the
systematic organization of resources into processes that
transform materials, provide services, or process
information.[1]
It can be depicted as a sequence of operations,
declared as work of a person or group,[2] an organization
of staff, or one or more simple or complex mechanisms.
[Wikipedia]
3. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
A simple workflow: Invoicing
Issue
Payment
Ship
NotifyExpires IsPaid Collect
No
4. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
A simple workflow: Invoicing
Either a user or a scheduler fires code such as:
public void NotifyCustomersAboutPertainingExpiredInvoices()
{
var expiredInvoices = from i in db.OutgoingInvoices
where SomeClausesPointingToStillUnpaidExpiredInvoices
select i;
foreach(var invoice in expiredInvoices)
{
NotifyExpiredInvoiceToCustomer(invoice);
}
}
5. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
Enter CQRS
Presentation layer
Application layer
Infrastructure layer
Domain Model
Domain layer
Presentation layer
Infrastructure layer
CQRS
Queries
Data
access
Commands
Application
+
Domain
6. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
Why CQRS?
We faced a lot of complexity in modeling
We thought it was inherent domain complexity
Long story short: a single model caring about all aspects of the domain is
hard. Enter CQS
Command/Query Separation
(cit. Bertrand Meyer – 1980s)
Query
> Returns data
> Doesn’t alter state
Command
> Alter state
> Doesn’t return data
7. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
CQRS in action
As a business unit manager, I want to notify
customers about expired invoices
Database
.OutgoingInvoices.
.PerBusinessUnit(businessUnitId)
.ExpiredOnly()
.Select(i => new {InvoiceNumber = i.Number, CustomerId =
i.Customer.Id})
.AsParallel()
.ForAll(i => NotifyCustomer(i.InvoiceNumber, i.CustomerId));
8. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
The result
Pros:
• Easy to read
• Close to Ubiquitous Language
Cons:
• Synchronous (lower scalability)
• Either a scheduling engine or human interaction is
required
9. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
Commands: a different strategy
1. Application sends a command to the system
2. Commands are dispatched to workflow managers
(a.k.a. Sagas) which will execute them and then state
success/failure accordingly
3. Responses are notified to interested subscribers (a.k.a.
handlers) such as Denormalizers, which will
(eventually) update the read model’s database
Note: command/responses dispatch will be managed by a
Mediator
10. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
CQRS in action, part 2
As a business unit manager, I want to notify
customers about expired invoices
Database
.OutgoingInvoices.
.PerBusinessUnit(businessUnitId)
.ExpiredOnly()
.Select(i => new {InvoiceNumber = i.Number, CustomerId = i.Customer.Id})
.AsParallel()
.ForAll(i => mediator.Send(new NotifyPaymentDueCommand(i.InvoiceNumber,
i.CustomerId)));
11. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
The result, part 2
Pros:
• Easy to read
• Close to Ubiquitous Language
• Asynchronous
Cons:
• Either a scheduling engine or human interaction is
required
12. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
Queues or buses? That is the question (semi cit. )
Although both categories are viable options and support
common features (e.g.: message durability), a bus is generally
preferable due to advanced capabilities (e.g.: message
scheduling)
Mediator, who art thou?
13. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
Sagas 1-2-3
In a messaging system, a saga orchestrate a set of
messages. The main benefit of using a saga is that it
allows us to manage the interaction in a stateful manner
(easy to think and reason about) while actually working in a
distributed and asynchronous environment.
[Ayende]
Though Saga are not proper workflow/process manager,
they are effective at pretending to be
15. Introduction to ServiceInsight for NServiceBusMaking workflow implementation easy with CQRS
More resources:
• “Microsoft .NET: Architecting Applications for the Enterprise”
by Andrea Saltarello and Dino Esposito, Microsoft Press (2014)
• Merp (http://naa4e.codeplex.com)
Links