You can also add documentation and example code to the operations with Razor views, which is covered in Chapter 5, Documentation and Versioning. Consistency Keep old versions of your API as long as they are needed to ensure that there is no break in the usages. Be consistent with the naming of properties also take naming practices of the technologies used by clients into account , endpoints, and formats and ultimately push a changelog to ease migration of changes.
The usage of versions is covered in Chapter 5, Documentation and Versioning. Robustness One of the main benefits of using ServiceStack for your service is that you can deal with various input and output formats: You can use QueryString, POST-payload, form-data and even extend this by adding your own format for inputting data. ServiceStack also bundles different output formats and can be enhanced with customized content types.
Attach validation to your requests as well to provide comprehensible reasons for a failed communication, which is covered in Chapter 5, Documentation and Versioning. Authentication, authorization, and security Before any other point on the checklist, there's the encryption of the transport layer with the incorporation of SSL for external services.
Processing a request should always capture the following aspects:. Authentication can also serve as a base to limit resources for a consumer as well as a common starting point to troubleshoot issues.
ServiceStack also provides several ways to implement authentication and authorization to your service with various providers, which is covered in Chapter 2, ServiceStack as Your Unique Point of Access. Problems with distributed systems The design approach of distributed systems is by no means a silver-bullet and introduces new problems or magnifies existing ones. I am going to discuss some higher level problems and leave out the low level issues, such as transportation issues package loss, network latency , to focus on the stack of a typical software engineer.
Complexity in design As such systems consist of many endpoints, we have new challenges to worry about. A broader set of skills Bringing a distributed system to life requires extensive skills within the development team, as well as the operational team. Adding new dependencies to single services also needs a distributed understanding of the components involved, to keep the system vital and to be able to respond to requests in a reasonable time.
Testing Before you ship a system it needs to be tested. Testing does not stop with a single service, but is done for the complete environment, which becomes challenging when you need to ensure the consistency of the environment for manual and automated testing. Differences between staging systems and live systems, such as different framework versions, can also be a problem.
A pragmatic approach in the long run is to incorporate monitoring to easily spot anomalies in the flow of operations, as bugs can have amplified repercussions on the system.
Rollout The rollout of such a dynamic environment should be done by a fully automated deployment process, leaving as little room as possible for manual faults. Operating overhead Splitting a monolith into multiple processes may start with a certain number of service instances.
When applying a failover protection or load balancing and messaging, it becomes a really challenging task to keep such a system running, as the number of instances can easily increase. Tracing In a distributed system, one can not simply solve an issue by inspecting a process. You will have multiple places for log files that need a correlative identifier to track down a request and its problems. There are many solutions out there to help you to manage and centralize logging.
Contracts To ensure valid communication between two services, you need a contract for a message format and a basic understanding of it. Any one-sided change to this contract will result in a break, therefore we need a coordinated way of releasing it. A basic solution to this problem is the introduction of versions to the messages, which is basically a method to introduce backward compatibility to the system.
As we all know, business sometimes calls for partial rollouts that render components out of sync and "versions" are no longer the magic bullet in such a case. Issues at runtime We might come across many issues while running our system that we need to learn from their huddles and perfect our system.
Here are some of the problems we might face:. Un atomicity of operations An operation in a distributed system is by no means guaranteed to be atomic, as it might be split into several subtasks that can be executed in parallel or sequentially across service borders.
This calls for a certain mechanism of distributed transactions, to revoke preceding actions when an essential subtask failed. This can also be achieved by queuing entities in a staged pool and releasing them to the live system when all the operations are successfully applied, or otherwise invalidate the changes. A shared register When multiple components share the same entity, such as credentials, there is a need to synchronize the register to have the same data available in multiple processes and to minimize hard faults, which fall back to a common database.
Another issue originates in the asynchronous behavior of such systems, making it vulnerable to lost updates, which happens when component A and component B are updating the same entity. If the components do not have a shared register but rather solve this issue by implementing synchronization, there is a need to introduce a notification upon changes.
Performance Besides the performance of a single service, there's a natural overhead in the communication when you have to marshal the request and response instead of just working on a reference in the same process. It is important to not base this process on blindfolded guessing when trying to resolve a bottleneck, which is wrong most of the time. It's better to base it on investigation even if it is hard to apply in a distributed system.
Methods for inspecting performance is covered in Chapter 4, Analyzing and Tuning a Distributed System. Summary In this chapter the available components of ServiceStack were introduced, to give a crisp overview of the framework itself. In addition to this, we are now familiar with the basic concepts of ServiceStack, such as Code-First and the message pattern. We dove a little bit deeper into the processing chain and explored multiple hooks for injections. Finally, we spoke about design principles of an API and uncovered the problems with distributed systems.
In the next chapter we will introduce dependency injection, which lays the base for a hands-on scenario. Furthermore, we will cover sessions and caching, and add authentication and authorization to our working demo. Alternatively, you can buy the book from Amazon, BN. Click here for ordering and shipping details.
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Fr Mastering ServiceStack covers real-life problems that occur over the lifetime of a distributed system and how to solve them through developing an understanding of the tools of ServiceStack. What you will learn from this book Design a resilient API, following the RESTful The book starts with an introduction covering the essentials, but assumes you are just refreshing, are a very fast learner, or are an expert in building web services, by explaining the fundamental patterns of ServiceStack and how they differ from other methods of building web services.
NET developer who is rooted in the web fraction and still affiliated with it. Preface Chapter 5, Documentation and Versioning, shows you how to leverage built-in functionality to publish and modify the documentation of your API and introduces you to test clients, such as Swagger and Postman.
ServiceStack's adaptive nature makes the components of the framework fine-grained, which makes it crucial to understand the layout and its components: ServiceStack: Lets you create your own service endpoint. Text: In this namespace reside various serialization utilities ServiceStack.
Client: It contains the relevant clients to connect and ServiceStack. NET's leading client for Redis, an open source and advanced key-value store. Authentication: It provides various authentication ServiceStack. NET ServiceStack. Message Queue context The following MQ server implementations are available the packages are listed in brackets for easier searching on NuGet for your ServiceStack service: ServiceStack. RabbitMqServer ServiceStack. RabbitMq ServiceStack. RedisMqServer ServiceStack.
Server ServiceStack. Processing a request should always capture the following aspects: Validate the input Authenticate the consumer Check authorization to the operation Check authorization to the resource of the operation Authentication can also serve as a base to limit resources for a consumer as well as a common starting point to troubleshoot issues. Here are some of the problems we might face: Un atomicity of operations An operation in a distributed system is by no means guaranteed to be atomic, as it might be split into several subtasks that can be executed in parallel or sequentially across service borders.
You will also understand how to build and deploy Cloud-Native microservices with Spring Cloud. The advanced features of Spring Boot will be illustrated through powerful examples. We will be introduced to a JVM language that's quickly gaining popularity - Kotlin. Also, we will discuss how to set up a Kotlin project in Eclipse. By the end of the book, you will be equipped with the knowledge and best practices required to develop microservices with the Spring Framework.
Style and approach This book follows an end-to-end tutorial approach with lots of examples and sample applications, covering the major building blocks of the Spring framework.
Go beyond simply learning Kubernetes fundamentals and its deployment, and explore more advanced concepts, including serverless computing and service meshes with the latest updates Key Features Master Kubernetes architecture and design to build and deploy secure distributed applications Learn advanced concepts like autoscaling, cluster federation, serverless computing, and service mesh integration for observability Explore Kubernetes 1.
This book primarily concentrates on diving deeply into complex concepts and Kubernetes best practices to help you master the skills of designing and deploying large clusters on various cloud platforms. The book trains you to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend.
With the two new chapters, you will gain expertise in serverless computing and utilizing service meshes. As you proceed through the chapters, you will explore different options for network configuration and learn to set up, operate, and troubleshoot Kubernetes networking plugins through real-world use cases. Furthermore, you will understand the mechanisms of custom resource development and its utilization in automation and maintenance workflows.
By the end of this Kubernetes book, you will graduate from an intermediate to advanced Kubernetes professional. What you will learn Master the fundamentals of Kubernetes architecture and design Build and run stateful applications and complex microservices on Kubernetes Use tools like Kubectl, secrets, and Helm to manage resources and storage Master Kubernetes Networking with load balancing options like Ingress Achieve high-availability Kubernetes clusters Improve Kubernetes observability with tools like Prometheus, Grafana, and Jaeger Extend Kubernetes working with Kubernetes API, plugins, and webhooks Who this book is for If you are a system administrator or a cloud developer with working knowledge of Kubernetes and are keen to master its advanced features, along with learning everything from building microservices to utilizing service meshes, Mastering Kubernetes is for you.
Basic familiarity with networking concepts will be helpful. It is evolving just like the languages we use. You'll start by getting up to speed with architectural concepts, including established patterns and rising trends.
The book will then explain what software architecture is and help you explore its components. Next, you'll discover the design concepts involved in application architecture and the patterns in software development, before going on to learn how to build, package, integrate, and deploy your components. In the concluding chapters, you'll explore different architectural qualities, such as maintainability, reusability, testability, performance, scalability, and security.
Finally, you will get an overview of distributed systems, such as service-oriented architecture, microservices, and cloud-native, and understand how to apply them in application development. Learn how to build, test, secure, deploy, and efficiently consume services across distributed systems. Key Features - Explore the wealth of options provided by Spring Cloud for wiring service dependencies in microservice systems.
Book Description Developing, deploying, and operating cloud applications should be as easy as local applications. This should be the governing principle behind any cloud platform, library, or tool.
Spring Cloud—an open-source library—makes it easy to develop JVM applications for the cloud. In this book, you will be introduced to Spring Cloud and will master its features from the application developer's point of view. This book begins by introducing you to microservices for Spring and the available feature set in Spring Cloud. You will learn to configure the Spring Cloud server and run the Eureka server to enable service registration and discovery.
Then you will learn about techniques related to load balancing and circuit breaking and utilize all features of the Feign client.
The book now delves into advanced topics where you will learn to implement distributed tracing solutions for Spring Cloud and build message-driven microservice architectures.
Before running an application on Docker container s, you will master testing and securing techniques with Spring Cloud. Knowledge of Java and Spring Framework will be helpful, but no prior exposure to Spring Cloud is required. Spring Cloud-an open-source library-makes it easy to develop JVM applications for the cloud. Docker has been a game-changer when it comes to how modern applications are deployed and architectured. This book shows you how to leverage the power of Docker, you'll find new and innovative ways to use Docker Compose, Docker Swarm, and Kubernetes to help you take control of your containers in an efficient way.
Mastering Hyperledger Fabric. This book provides a comprehensive view of Solution Architecture, so it will be easy for architects to architect their solution. Managers to cope up with the latest trend. Faculty Professors in order to get industry insights.
Even Engineering Students who want to be ready with the latest technologies. Hyperledger Fabric is an open-source project that helps organizations create and maintain permissioned distributed Blockchain consortiums.
This book is for readers who are looking for Hyperledger offerings to build end-to-end projects with growing complexity and functionalities. There are many resources available regarding this issue, I will cover the most important thoughts, which are discussed further in this chapter.
Usually, you are defining an interface for an end user with limited technological knowledge. With services, the audience are programmers, which gives you a technical affine counterpart who may come up with every little flaw in your design. One of the main goals in the design process is to keep it simple, frictionless and understandable to the absolute maximum.
Verify the simplicity of the design by letting new people try your API, gather feedback and make the usage a straightforward scenario. Also, avoid the introduction of additional dependencies and unnatural bindings to use your service. Following a message based communication gives you a top-notch and solid base for solving the design process. This may only apply to external APIs, but should also be considered for internal ones. Provide example requests and responses, as well as documentation of the DTOs.
ServiceStack provides a metadata page to document the requests and responses that also serves as the base for Swagger. You can also add documentation and example code to the operations with Razor views, which is covered in Chapter 5 , Documentation and Versioning. Keep old versions of your API as long as they are needed to ensure that there is no break in the usages.
Be consistent with the naming of properties also take naming practices of the technologies used by clients into account , endpoints, and formats and ultimately push a changelog to ease migration of changes. The usage of versions is covered in Chapter 5 , Documentation and Versioning. One of the main benefits of using ServiceStack for your service is that you can deal with various input and output formats: You can use QueryString, POST-payload, form-data and even extend this by adding your own format for inputting data.
ServiceStack also bundles different output formats and can be enhanced with customized content types. If you want to implement your own format, you can do so by implementing your own format:. Attach validation to your requests as well to provide comprehensible reasons for a failed communication, which is covered in Chapter 5 , Documentation and Versioning.
Before any other point on the checklist, there's the encryption of the transport layer with the incorporation of SSL for external services. Authentication can also serve as a base to limit resources for a consumer as well as a common starting point to troubleshoot issues. ServiceStack also provides several ways to implement authentication and authorization to your service with various providers, which is covered in Chapter 2 , ServiceStack as Your Unique Point of Access.
The design approach of distributed systems is by no means a silver-bullet and introduces new problems or magnifies existing ones. I am going to discuss some higher level problems and leave out the low level issues, such as transportation issues package loss, network latency , to focus on the stack of a typical software engineer.
As such systems consist of many endpoints, we have new challenges to worry about. Bringing a distributed system to life requires extensive skills within the development team, as well as the operational team. Adding new dependencies to single services also needs a distributed understanding of the components involved, to keep the system vital and to be able to respond to requests in a reasonable time. Before you ship a system it needs to be tested. Testing does not stop with a single service, but is done for the complete environment, which becomes challenging when you need to ensure the consistency of the environment for manual and automated testing.
Differences between staging systems and live systems, such as different framework versions, can also be a problem. A pragmatic approach in the long run is to incorporate monitoring to easily spot anomalies in the flow of operations, as bugs can have amplified repercussions on the system.
The rollout of such a dynamic environment should be done by a fully automated deployment process, leaving as little room as possible for manual faults. Splitting a monolith into multiple processes may start with a certain number of service instances. When applying a failover protection or load balancing and messaging, it becomes a really challenging task to keep such a system running, as the number of instances can easily increase.
In a distributed system, one can not simply solve an issue by inspecting a process. You will have multiple places for log files that need a correlative identifier to track down a request and its problems.
To ensure valid communication between two services, you need a contract for a message format and a basic understanding of it. Any one-sided change to this contract will result in a break, therefore we need a coordinated way of releasing it. A basic solution to this problem is the introduction of versions to the messages, which is basically a method to introduce backward compatibility to the system. As we all know, business sometimes calls for partial rollouts that render components out of sync and "versions" are no longer the magic bullet in such a case.
We might come across many issues while running our system that we need to learn from their huddles and perfect our system. Here are some of the problems we might face:. An operation in a distributed system is by no means guaranteed to be atomic, as it might be split into several subtasks that can be executed in parallel or sequentially across service borders.
This calls for a certain mechanism of distributed transactions, to revoke preceding actions when an essential subtask failed. This can also be achieved by queuing entities in a staged pool and releasing them to the live system when all the operations are successfully applied, or otherwise invalidate the changes. When multiple components share the same entity, such as credentials, there is a need to synchronize the register to have the same data available in multiple processes and to minimize hard faults, which fall back to a common database.
Another issue originates in the asynchronous behavior of such systems, making it vulnerable to lost updates, which happens when component A and component B are updating the same entity. If the components do not have a shared register but rather solve this issue by implementing synchronization, there is a need to introduce a notification upon changes.
Besides the performance of a single service, there's a natural overhead in the communication when you have to marshal the request and response instead of just working on a reference in the same process. It is important to not base this process on blindfolded guessing when trying to resolve a bottleneck, which is wrong most of the time. It's better to base it on investigation even if it is hard to apply in a distributed system.
Methods for inspecting performance is covered in Chapter 4 , Analyzing and Tuning a Distributed System. In this chapter the available components of ServiceStack were introduced, to give a crisp overview of the framework itself. In addition to this, we are now familiar with the basic concepts of ServiceStack, such as Code-First and the message pattern.
We dove a little bit deeper into the processing chain and explored multiple hooks for injections. Finally, we spoke about design principles of an API and uncovered the problems with distributed systems.
In the next chapter we will introduce dependency injection, which lays the base for a hands-on scenario. Furthermore, we will cover sessions and caching, and add authentication and authorization to our working demo. Andreas Niedermair is a. NET developer who is rooted in the web fraction and still affiliated with it. He has worked in numerous enterprise environments building leading industry solutions and has also contributed to the open source community.
He is always striving for a deeper understanding of technology to stay on the cutting edge. He contributed to the ServiceStack 4 Cookbook as a technical reviewer and has held lectures for non-profit associations.
About this book Mastering ServiceStack covers real-life problems that occur over the lifetime of a distributed system and how to solve them by deeply understanding the tools of ServiceStack.
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