Shyam Sundar - Cloud-Native Applications in Java
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- Book:Cloud-Native Applications in Java
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Highly available microservice-based web apps for Cloud with Java
About This Book
- Take advantage of the simplicity of Spring to build a full-fledged application
- Let your applications run faster while generating smaller cloud service bills
- Integrate your application with various tools such as Docker and ElasticSearch and use specific tools in Azure and AWS
Who This Book Is For
Java developers who want to build secure, resilient, robust and scalable applications that are targeted for cloud based deployment, will find this book helpful. Some knowledge of Java, Spring, web programming and public cloud providers (AWS, Azure) should be sufficient to get you through the book.
What You Will Learn
- See the benefits of the cloud environment when it comes to variability, provisioning, and tooling support
- Understand the architecture patterns and considerations when developing on the cloud
- Find out how to perform cloud-native techniques/patterns for request routing, RESTful service creation, Event Sourcing, and more
- Create Docker containers for microservices and set up continuous integration using Jenkins
- Monitor and troubleshoot an application deployed in the cloud environment
- Explore tools such as Docker and Kubernetes for containerization and the ELK stack for log aggregation and visualization
- Use AWS and Azure specific tools to design, develop, deploy, and manage applications
- Migrate from monolithic architectures to a cloud native deployment
In Detail
Businesses today are evolving so rapidly that they are resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This means developers now are faced with the challenge of building build applications that are native to the cloud. For this, they need to be aware of the environment, tools, and resources theyre coding against.
If youre a Java developer who wants to build secure, resilient, robust, and scalable applications that are targeted for cloud-based deployment, this is the book for you. It will be your one stop guide to building cloud-native applications in Java Spring that are hosted in On-prem or cloud providers - AWS and Azure
The book begins by explaining the driving factors for cloud adoption and shows you how cloud deployment is different from regular application deployment on a standard data centre. You will learn about design patterns specific to applications running in the cloud and find out how you can build a microservice in Java Spring using REST APIs
You will then take a deep dive into the lifecycle of building, testing, and deploying applications with maximum automation to reduce the deployment cycle time. Gradually, you will move on to configuring the AWS and Azure platforms and working with their APIs to deploy your application. Finally, youll take a look at API design concerns and their best practices. Youll also learn how to migrate an existing monolithic application into distributed cloud native applications.
By the end, you will understand how to build and monitor a scalable, resilient, and robust cloud native application that is always available and fault tolerant.
Style and approach
Filled with examples, this book will build you an entire cloud-native application through its course and will stop at each point and explain in depth the functioning and design considerations that will make a robust, highly available application
Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
Shyam Sundar: author's other books
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In this style, the fat JAR is deployed directly on the VM, as in the Service per process section. However, here there is only one service deployed per VM. This ensures a complete isolation of the service from the other services.
The deployment is automated through tools such as Chef and Puppet, that can take a base image (such as having Java installed) and then run through a series of steps to install the application JAR and other utilities on the VM:
Local cache is useful in limited use cases (such as non-changing static data) as the updates done in one service using Spring annotations such as @CachePut, @CacheEvict, and so on cannot be synchronized with a cache on the other instance of services if we are running more than one instance of a service for load balancing or resiliency purposes.
Java developers who want to build resilient, robust, and scalable applications that are targeted for cloud-based deployment will find this book helpful. Some knowledge of Java, Spring, web programming, and public cloud providers (AWS and Azure) should be sufficient to get you through the book.
In a deployment diagram, internet outside the firewall was depicted using the shape of a cloud. Not until I read Big Switch, Nicholas G. Carr, did I realize the full potential of cloud and what was to come. Fast forwarding 10 years, now we do not think twice before drawing the cloud shape around the complete system to depict how cloud is everywhere. Cloud Native comes naturally for start-ups, but for a lot of enterprises, this is still an uncharted territory. Just doing lift-and-shift is not the right use of cloud, though it may be the first thing most large corporations are doing to mitigate the currency of their data centers or to avoid extension of leases. The power of cloud is seen when we are able to build cloud-native architecture-based applications that are business critical and can drive transformational value. Hence, I have always encouraged my team to gain knowledge on designing and building smarter applications on cloud.
Munish, Ajay, and Shyam are part of the core team that has always researched and worked on emerging technologies, using them to solve business problems. They are among the leading experts and consultants on the enterprise digital transformation with a focus on distributed systems using microservices and emerging technologies such as reactive frameworks, open source, and container technology (Dockers and Kubernetes) to name a few. Hence, I encouraged them to work on this book so as to enable the next generation of developers to jump start their journey to cloud-native applications.
This book takes a step-by-step approach to understanding, designing, and writing applications for cloud. The authors take you on a learning journey that starts with the concepts, followed by building a small REST service, and then going through the incremental journey of enhancing the service to be cloud native. They cover various aspects of cloud-specific nuances, such as how to discover a service in a distributed architecture and the role played by service discovery tools. You will also learn how to migrate your application to public cloud providersAWS and Azure. The book covers serverless computing models such as AWS Lamda and Cloud Functions.
I encourage you to get the best out of this book to spearhead your application development journey on cloud.
Hari Kishan Burle
Vice President and Global Head Architecture Services
Wipro Limited
The benefits and trade-offs associated with the service per process style are as follows:
- This approach helps in separating the runtime processes on which the services run. Thus, it creates an isolation between the services, so that a memory leak or fat exception in one process does not affect the other services to some extent.
- This allows for selective scaling of service, by allowing more deployments of a service compared to other services on the existing hardware.
- It also gives the freedom to teams of using a different application server/web container based on specific use cases or the needs of the team.
- However, it cannot prevent any one service from hogging system resources (such as CPU, I/O, and memory) that can affect the performance of the other services.
- It also reduces the control over the runtime of the operations team, as there is no central web container or application server present in this model.
- This style requires good governance to limit variability in the deployment estate and having substantial use cases to support the divergence.
There are not many scenarios in which this is useful as it does not offer runtime isolation. However, it might be an intermediary step toward releasing the full separation.
To enable the adoption of the IaaS and PaaS services, a change in how the applications are designed and architected needs to be made.
The model of designing enterprise applications on a base platform (read: application server) meant that the heavy lifting of the application's scalability and availability was the responsibility of the platform. Enterprise developers would focus on using the standardized JEE patterns and developing components (Presentation, Business, Data, and Integration) to build fully functional and transactional applications. The extent to which the application could be scaled was limited by the abilities (node clustering and distributed caching) of the underlying platform:
A business application built as a monolithic application is typically characterized by the following factors:
- The entire application logic is packaged into a single EAR file
- The application reuse is derived by sharing JARs
- Application changes are planned months in advance, typically in a big push once a quarter
- There is one database that encompasses the entire schema for the application
- There are thousands of test cases that signify the amount of regression
- The application design, development, and deployment requires coordination among multiple teams and significant management
With the advent of social interactions and mobile users, the scale of application users and data started increasing exponentially. Enterprises soon found that the platform was becoming a bottleneck in terms of the following issues:
- Business agility: The operational cost of managing the application platform and making constant changes to the features/functionalities was getting hampered because of the monolithic nature of the application. Even for a small feature change, the entire cycle of regression tests and deployment across server clusters was eating into the overall speed of innovation.
The mobile revolution meant that the problem was not just at the channel layers, but also percolated down to the integration and systems of record layers. Unless enterprises fixed the problem across these layers, the ability to innovate and be competitive in the market would be under threat. - Cost: To handle the increased demand, the IT Operations team were adding new server instances to handle the load. However, with each new instance, the complexity was increasing along with license costs (that depended on the number of cores). Unlike the Facebooks of the world, enterprise cost per user was increasing with every user acquisition.
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