Mastering Microservices with Java - Third Edition

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By Sourabh Sharma
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  1. A Solution Approach

About this book

Microservices are key to designing scalable, easy-to-maintain applications. This latest edition of Mastering Microservices with Java, works on Java 11. It covers a wide range of exciting new developments in the world of microservices, including microservices patterns, interprocess communication with gRPC, and service orchestration.

This book will help you understand how to implement microservice-based systems from scratch. You'll start off by understanding the core concepts and framework, before focusing on the high-level design of large software projects. You'll then use Spring Security to secure microservices and test them effectively using REST Java clients and other tools. You will also gain experience of using the Netflix OSS suite, comprising the API Gateway, service discovery and registration, and Circuit Breaker. Additionally, you'll be introduced to the best patterns, practices, and common principles of microservice design that will help you to understand how to troubleshoot and debug the issues faced during development.

By the end of this book, you'll have learned how to build smaller, lighter, and faster services that can be implemented easily in a production environment.

Publication date:
February 2019
Publisher
Packt
Pages
446
ISBN
9781789530728

 

Chapter 1. A Solution Approach

As a prerequisite for proceeding with this book, you should have a basic understanding of microservices and different software architecture styles. Having a basic understanding of these will help you understand what we discuss in this book.

After reading this book, you will be able to implement microservices for on-premises or cloud production deployments and you will understand the complete life cycle, from design and development to testing and deployment, of continuous integration and deployment. This book is specifically written for practical use and to stimulate your mind as a solution architect. Your learning will help you to develop and ship products in any situation, including Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS) environments. We'll primarily use Java and Java-based framework tools, such as Spring Boot and Jetty, and we will use Docker for containerization.

In this chapter, you will learn about microservices and how they have evolved. This chapter highlights the problems that on-premises and cloud-based products face and how microservices architectures deal with them. It also explains the common problems encountered during the development of SaaS, enterprise, or large applications and their solutions.

In this chapter, we will explore the following topics:

  • Services and service-oriented architecture (SOA)
  • Microservices, nanoservices, teraservices, and serverless
  • Deployment and maintenance

 

 

Services and SOA


Martin Fowler explains the following:

The term microservice was discussed at a workshop of software architects near Venice in May 2011 to describe what the participants saw as a common architectural style that many of them had been recently exploring. In May 2012, the same group decided on µServices as the most appropriate name.

Let's get some background on the way microservices have evolved over the years. Enterprise architecture evolved from historic mainframe computing, through client-server architecture (two-tier to n-tier), to SOA.

The transformation from SOA to microservices is not a standard defined by an industry organization, but a practical approach practiced by many organizations. SOA eventually evolved to becomemicroservices.

Adrian Cockcroft, a former Netflix architect, describes a microservice-based architecture as follows:

Fine grain SOA. So microservice is SOA with emphasis on small ephemeral components.

Similarly, the following quote from Mike Gancarz, a member who designed the X Windows system, which defines one of the paramount precepts of Unix philosophy, describes the microservice paradigm as well:

Small is beautiful.

Microservice architectures share many common characteristics with SOAs, such as the focus on services and how one service decouples from another. SOA evolved around monolithic application integration by exposing APIs that were mostly Simple Object Access Protocol (SOAP)-based. Therefore, having middleware such as an enterprise service bus (ESB) is very important for SOA. Microservices are less complex than SOAs, and, even though they may use a message bus, it is only used for message transport and it does not contain any logic. It is simply based on smart endpoints.

Tony Pujals defined microservices beautifully:

In my mental model, I think of self-contained (as in containers) lightweight processes communicating over HTTP, created and deployed with relatively small effort and ceremony, providing narrowly-focused APIs to their consumers.

 

Though Tony only talks about HTTP, event-driven microservices may use a different protocol for communication. You can make use of Kafka to implement event-driven microservices. Kafka uses the wire protocol, a binary protocol over TCP.

Monolithic architecture overview

Microservices are not new—they have been around for many years. For example, Stubby, a general purpose infrastructure based on RemoteProcedureCall (RPC), was used in Google data centers in the early 2000s to connect a number of services with and across data centers. Its recent rise is due to its popularity and visibility. Before microservices became popular, monolithic architectures were mainly being used for developing on-premises and cloud-based applications.

A monolithic architecture allows the development of different components such as presentation, application logic, business logic, and Data Access Objects (DAOs), and then you either bundle them together in an Enterprise Archive (EAR) or a Web Archive (WAR), or store them in a single directory hierarchy (such as Rails or Node.js).

Many famous applications, such as Netflix, have been developed using a microservices architecture. Moreover, eBay, Amazon, and Groupon have evolved from monolithic architectures to microservices architectures.

Now that you have had an insight into the background and history of microservices, let's discuss the limitations of a traditional approach—namely, monolithic application development—and see how microservices would address them.

Limitations of monolithic architectures versus its solution with microservices architectures

As we know, change is eternal. Humans always look for better solutions. This is how microservices became what it is today and it will evolve further in the future. Today, organizations are using agile methodologies to develop applications—it is a fast-paced development environment that has grown to a much larger scale after the invention of the cloud and distributed technologies. Many argue that monolithic architectures could also serve a similar purpose and be aligned with agile methodologies, but microservices still provide a better solution to many aspects of production-ready applications.

 

To understand the design differences between monolithic and microservices architectures, let's take an example of a restaurant table-booking application. This application may have many services to do with customers, bookings, analytics, and so on, as well as regular components, such as presentation and databases.

We'll explore three different designs here: the traditional monolithic design, the monolithic design with services, and the microservices design.

Traditional monolithic design

The following diagram explains the traditional monolithic application design. This design was widely used before SOA became popular:

Traditional monolithic application design

In a traditional monolithic design, everything is bundled in the same archive (all the presentation code is bundled in with the Presentation archive, the application logic goes into the Application Logic archive, and so on), regardless of how it all interacts with the database files or other sources.

 

 

Monolithic design with services

After SOA, applications started being developed based on services, where each component provides services to other components or external entities. The following diagram depicts a monolithic application with different services; here, services are being used with a Presentation component. All services, the Presentation component, or any other components are bundled together:

 

Microservices, nanoservices, teraservices, and serverless


The following diagram depicts the microservices design. Here each component is autonomous. Each component could be developed, built, tested, and deployed independently. Here, even the application User Interface (UI) component could also be a client and consume themicroservices. For the purpose of our example, the layer designed is used within the µService.

 

The API Gateway provides an interface where different clients can access the individual services and solve various problems, such as what to do when you want to send different responses to different clients for the same service. For example, a booking service could send different responses to a mobile client (minimal information) and a desktop client (detailed information), providing different details to each, before providing something different again to a third-party client.

A response may require the fetching of information from two or more services:

After observing all the sample design diagrams we've just gone through, which are very high-level designs, you might find that in a monolithic design, the components are bundled together and tightly coupled. All the services are part of the same bundle. Similarly, in the second design diagram, you can see a variant of the first diagram where all services could have their own layers and form different APIs, but, as shown in the diagram, these are also all bundled together.

 

 

Conversely, in the microservices design, the design components are not bundled together and have loose couplings. Each service has its own layers and database, and is bundled in a separate archive to all others. All these deployed services provide their specific APIs, such as Customers or Bookings. These APIs are ready to consume. Even the UI is also deployed separately and designed using µServices. For this reason, the microservices provides various advantages over its monolithic counterpart. I would, nevertheless, remind you that there are some exceptional cases where monolithic application development is highly successful, such as Etsy, and peer-to-peer e-commerce web applications.

Now let us discuss the limitations you'd face while working with Monolithic applications.

One-dimension scalability

Monolithic applications that are large when scaled, scale everything, as all the components are bundled together. For example, in the case of a restaurant table reservation application, even if you would like to scale only the table-booking service, you would scale the whole application; you cannot scale the table-booking service separately. This design does not utilize resources optimally.

In addition, this scaling is one-dimensional. Running more copies of the application provides the scale with increasing transaction volume. An operation team could adjust the number of application copies that were using a load balancer based on the load in a server farm or a cloud. Each of these copies would access the same data source, therefore increasing the memory consumption, and the resulting I/O operations make caching less effective.

Microservices architectures give the flexibility to scale only those services where scale is required and allow optimal utilization of resources. As mentioned previously, when needed, you can scale just the table-booking service without affecting any of the other components. It also allows two-dimensional scaling; here we can not only increase the transaction volume, but also the data volume using caching (platform scale). A development team can then focus on the delivery and shipping of new features, instead of worrying about the scaling issues (product scale).

Microservices could help you scale platforms, people, and product dimensions, as we have seen previously. People scaling here refers to an increase or decrease in team size depending on the microservices' specific development needs.

Microservice development using RESTful web service development provides scalability in the sense that the server-end of REST is stateless; this means that there is not much communication between servers, which makes the design horizontally scalable.

 

Release rollback in case of failure

Since monolithic applications are either bundled in the same archive or contained in a single directory, they prevent the deployment of code modularity. For example, many of you may have experienced the pain of delaying rolling out the whole release due to the failure of one feature.

To resolve these situations, microservices give us the flexibility to roll back only those features that have failed. It's a very flexible and productive approach. For example, let's assume you are the member of an online shopping portal development team and want to develop an application based on microservices. You can divide your application based on different domains such as products, payments, cart, and so on, and package all these components as separate packages. Once you have deployed all these packages separately, these would act as single components that can be developed, tested, and deployed independently, and called µService.

Now, let's see how that helps you. Let's say that after a production release launching new features, enhancements, and bug fixes, you find flaws in the payment service that need an immediate fix. Since the architecture you have used is based on microservices, you can roll back the payment service instead of rolling back the whole release, if your application architecture allows, or apply the fixes to the microservices payment service without affecting the other services. This not only allows you to handle failure properly, but it also helps to deliver the features/fixes swiftly to a customer.

Problems in adopting new technologies

Monolithic applications are mostly developed and enhanced based on the technologies primarily used during the initial development of a project or a product. This makes it very difficult to introduce new technology at a later stage of development or once the product is in a mature state (for example, after a few years). In addition, different modules in the same project that depend on different versions of the same library make this more challenging.

Technology is improving year on year. For example, your system might be designed in Java and then, a few years later, you may want to develop a new service in Ruby on Rails or Node.js because of a business need or to utilize the advantages of new technologies. It would be very difficult to utilize the new technology in an existing monolithic application.

 

It is not just about code-level integration, but also about testing and deployment. It is possible to adopt a new technology by rewriting the entire application, but it is a time-consuming and risky thing to do.

On the other hand, because of its component-based development and design, microservices architectures give us the flexibility to use any technology, new or old, for development. They do not restrict you to using specific technologies, and give you a new paradigm for your development and engineering activities. You can use Ruby on Rails, Node.js, or any other technology at any time.

So, how is this achieved? Well, it's very simple. Microservices-based application code does not bundle into a single archive and is not stored in a single directory. Each µService has its own archive and is deployed separately. A new service could be developed in an isolated environment and could be tested and deployed without any technical issues. As you know, microservices also own their own separate processes, serving their purpose without any conflicts to do with things such as shared resources with tight coupling, and processes remain independent.

Monolithic systems does not provide flexibility to introduce new technology. However, introduction of new technology comes as low risk features in microservices based system because by default these small and self contained components.

You can also make your microservice available as open source software so it can be used by others, and, if required, it may interoperate with a closed source, a proprietary one, which is not possible with monolithic applications.

Alignment with agile practices

There is no question that monolithic applications can be developed using agile practices, and these are being developed all the time. Continuous integration (CI) and continuous deployment (CD) could be used, but the question is—do they use agile practices effectively? Let's examine the following points:

  • When there is a highprobabilityof having stories dependent on each other, and there could be various scenarios, a story would not be taken up until the dependent story is complete.
  • The build takes more time as the code size increases.
  • The frequent deployment of a large monolithic application is a difficult task to achieve.
  • You would have to redeploy the whole application even if you updated a single component.
  • Redeployment may cause problems to already running components; for example, a job scheduler may change whether components impact it or not.
  • The risk of redeployment may increase if a single changed component does not work properly or if it needs more fixes.
  • UI developers always need more redeployment, which is quite risky and time-consuming for large monolithic applications.

The preceding issues can be tackled very easily by microservices. For example, UI developers may have their own UI component that can be developed, built, tested, and deployed separately. Similarly, other microservices might also be deployable independently and, because of their autonomous characteristics, the risk of system failure is reduced. Another advantage for development purposes is that UI developers can make use of JSON objects and mock Ajax calls to develop the UI, which can be taken up in an isolated manner. After development is finished, developers can consume the actual APIs and test the functionality. To summarize, you could say that microservices development is swift and it aligns well with the incremental needs of businesses.

Ease of development – could be done better

Generally, large monolithic application code is the toughest to understand for developers, and it takes time before a new developer can become productive. Even loading the large monolithic application into an integrated development environment (IDE) is troublesome, as it makes the IDE slower and the developer less productive.

A change in a large monolithic application is difficult to implement and takes more time due to the large code base, and there can also be a high risk of bugs if impact analysis is not done properly and thoroughly. Therefore, it becomes a prerequisite for developers to do a thorough impact analysis before implementing any changes.

In monolithic applications, dependencies build up over time as all components are bundled together. Therefore, the risk associated with code changes rises exponentially as the amount of modified lines of code grows.

When a code base is huge and more than 100 developers are working on it, it becomes very difficult to build products and implement new features because of the previously mentioned reason. You need to make sure that everything is in place, and that everything is coordinated. A well-designed and documented API helps a lot in such cases.

 

Netflix, the on-demand internet streaming provider, had problems getting their application developed, with around 100 people working on it. Then, they used a cloud service and broke up the application into separate pieces. These ended up being microservices. Microservices grew from the desire for speed and agility and to deploy teams independently.

Microcomponents are made loosely coupled thanks to their exposed APIs, which can be continuously integration tested. With microservices' continuous release cycle, changes are small and developers can rapidly exploit them with a regression test, then go over them and fix the defects found, reducing the risk of a flawed deployment. This results in higher velocity with a lower associated risk.

Owing to the separation of functionality and the single responsibility principle, microservices make teams very productive. You can find a number of examples online where large projects have been developed with very low team sizes, such as 8 to 10 developers.

Developers can have better focus with smaller code bases and better feature implementation, leading to a higher empathetic relationship with the users of the product. This conduces better motivation and clarity in feature implementation. An empathetic relationship with users allows for a shorter feedback loop and better and speedier prioritization of the feature pipeline. A shorter feedback loop also makes defect detection faster.

Each microservices team works independently and new features or ideas can be implemented without being coordinated with larger audiences. The implementation of endpoint failure handling is also easily achieved in the microservices design.

At a recent conference, a team demonstrated how they had developed a microservices-based transport-tracking application for iOS and Android, within 10 weeks, with Uber-type tracking features. A big consulting firm gave a seven-month estimation for this application to its client. This shows how the microservices design is aligned with agile methodologies and CI/CD.

So far, we have discussed only the microservices design—there are also nanoservices, teraservices, and serverless designs to explore.

 

Nanoservices

Microservices that are especially small or fine-grained are called nanoservices. A nanoservices pattern is really an anti-pattern.

In the case of nanoservices, overheads such as communication and maintenance activities outweigh its utility. Nanoservices should be avoided. An example of a nanoservices (anti-) pattern would be creating a separate service for each database table and exposing its CRUD operation using events or a REST API.

Teraservices

Teraservices are the opposite of microservices. The teraservices design entails a sort of a monolithic service. Teraservices require two terabytes of memory, or more. These services could be used when services are required only to be in memory and have high usage.

These services are quite costly in cloud environments due to the memory needed, but the extra cost can be offset by changing from quad-core servers to dual-core servers.

Such a design is not popular.

Serverless

Serverless is another popular cloud architecture offered by cloud platforms such as AWS. There are servers, but they are managed and controlled by cloud platforms.

This architecture enables developers to simply focus on code and implementing functionality. Developers need not worry about scale or resources (for instance, OS distributions as with Linux, or message brokers such as RabbitMQ ) as they would with coded services.

A serverless architecture offers development teams the following features: zero administration, auto-scaling, pay-per-use schemes, and increased velocity. Because of these features, development teams just need to care about implementing functionality rather than the server and infrastructure.

 

 

Deployment and maintenance


CI and CD are important parts of today's development process. Therefore, having a proper pipeline for building, and for containerized delivery, is discussed in the following sub-sections.

Microservices build pipeline

Microservices can be built and tested using popular CI/CD tools, such as Jenkins and TeamCity. This is done very similarly to how a build is done in a monolithic application. In a microservices architecture, each microservice is treated like a small application.

For example, once you commit the code in the repository (SCM), CI/CD tools trigger the build process:

  1. Cleaning code
  2. Code compilation
  3. Unit test execution
  4. Contract/acceptance test execution
  5. Building the application archives/container images
  6. Publishing the archives/container images to repository management
  7. Deployment on various delivery environments such as development, quality assurance, and staging environments
  8. Integration and functional test execution
  9. Any other steps

Then, release-build triggers, which change the SNAPSHOT or RELEASE version in pom.xml (in the case of Maven), build the artifacts as described in the normal build trigger, publish the artifacts to the artifacts repository, and tag the version in the repository. If you use the container image, then build the container image as a part of the build.

Deployment using a containerization engine such as Docker

Because of the design of microservices, you need to have an environment that provides flexibility, agility, and smoothness for CI and CD as well as for shipment. Microservice deployments need speed, isolation management, and an agile life cycle.

Products and software can also be shipped using an intermodal-container model. An intermodal container is a large standardized container, designed for intermodal freight transport. It allows cargo to use different modes of transport—truck, rail, or ship—without unloading and reloading. This is an efficient and secure way of storing and transporting goods. It resolves the problem of shipping, which previously had been a time-consuming, labor-intensive process, and repeated handling often broke fragile goods.

Shipping containers encapsulate their content. Similarly, software containers are starting to be used to encapsulate their content (such as products, applications, and dependencies).

Previously, Virtual Machines (VMs) were used to create software images that could be deployed where needed. Later, containerization engines such as Docker became more popular as they were compatible with both traditional virtual stations systems and cloud environments. For example, it is not practical to deploy more than a couple of VMs on a developer's laptop. Building and booting a VM is usually I/O intensive and consequently slow.

Containers

A container provides a lightweight runtime environment consisting of the core features of VMs and the isolated services of OSes. This makes the packaging and execution of microservices easy and smooth.

As the following diagram shows, a container runs as an application (microservice) within the OS. The OS sits on top of the hardware and each OS could have multiple containers, with one container running the application.

 

A container makes use of an OS' kernel interfaces, such as cnames and namespaces, which allow multiple containers to share the same kernel while running in complete isolation of one another. This gives the advantage of not having to complete an OS installation for each usage; the result is that the overhead is removed. This also makes optimal use of the hardware:

Layer diagram for containers

Docker

Container technology is one of the fastest growing technologies today, and Docker is leading it. Docker is an open source project and it was launched in 2013. 10,000 developers tried it after its interactive tutorial launched in August 2013. It was downloaded 2.75 million times by the time of the launch of its 1.0 release in June 2013. Many large companies have signed a partnership agreement with Docker, such as Microsoft, Red Hat, HP, OpenStack, and service providers such as AWS, IBM, and Google.

 

As we mentioned earlier, Docker also makes use of Linux kernel features, such as cgroups and namespaces, to ensure resource isolation and the packaging of the application with its dependencies. This packaging of dependencies enables an application to run as expected across different Linux OSes/distributions, supporting a level of portability. Furthermore, this portability allows developers to develop an application in any language and then easily deploy it from a laptop to a test or production server.

Note

Docker runs natively on Linux. However, you can also run Docker on Windows and macOS using VirtualBox and boot2docker.

Containers are comprised of just the application and its dependencies, including the basic OS. This makes the application lightweight and efficient in terms of resource utilization. Developers and system administrators are interested in a container's portability and efficient resource utilization.

Everything in a Docker container executes natively on the host and uses the host kernel directly. Each container has its own user namespace.

Docker's architecture

As specified on the Docker documentation, Docker architecture uses a client-server architecture. The Docker client is basically a user interface that is used by an end user; clients communicate back and forth with a Docker daemon. The Docker daemon does the heavy lifting of the building, running, and distributing of your Docker containers. The Docker client and the daemon can run on the same system or on different machines.

The Docker client and daemon communicate via sockets or through a RESTful API. Docker registers are public or private Docker image repositories from which you upload or download images; for example, Docker Hub (hub.docker.com) is a public Docker registry.

The primary components of Docker are the following:

  • Docker image: A Docker image is a read-only template. For example, an image could contain an Ubuntu OS with an Apache web server and your web application installed. Docker images are build components of Docker, and images are used to create Docker containers. Docker provides a simple way to build new images or update existing images. You can also use images created by others and/or extend them.
  • Docker container: A Docker container is created from a Docker image. Docker works so that the container can only see its own processes, and have its own filesystem layered onto a host filesystem and a networking stack, which pipes to the host-networking stack. Docker containers can be run, started, stopped, moved, or deleted.

For more information, you can take a look at the overview of Docker that is provided by Docker (https://docs.docker.com/engine/docker-overview/).

 

Deployment


Microservices deployment with Docker involves three things:

  • Application packaging, for example, JAR.
  • Building a Docker image with a JAR and dependencies using a Docker instruction file, a Dockerfile, and the docker build command. This allows you to repeatedly create images.
  • Docker container execution from this newly built image using docker run.

The preceding information will help you to understand the basics of Docker. You will learn more about Docker and its practical usage in Chapter 4, Implementing a Microservice. For more information, refer to https://docs.docker.com.

 

Summary


In this chapter, you have learned about or recapped the high-level design of large software projects, from traditional monolithic applications to microservices-based applications. You were also introduced to a brief history of microservices, the limitations of monolithic applications, and the benefits and flexibility that microservices offer. I hope this chapter helped you to understand the common problems faced in a production environment by monolithic applications and how microservices can resolve such problems. You were also introduced to lightweight and efficient Docker containers and saw how containerization is an excellent way to simplify microservices deployment.

In the next chapter, you will learn about setting up a development environment, looking at everything from your IDE and other development tools, to different libraries. We will deal with creating basic projects and setting up a Spring Boot configuration to build and develop our first microservice. We will be using Java 11 as the language and Spring Boot for our project.

About the Author

  • Sourabh Sharma

    Sourabh Sharma has over 16 years of experience in product/application development. His expertise lies in designing, developing, deploying, and testing N-tier web applications and leading teams. He loves to troubleshoot complex problems and develop innovative ways to solve problems. Sourabh believes in continuous learning and sharing your knowledge.

    Browse publications by this author

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