The Ultimate Guide for 2024

This is the ultimate guide to microservices in 2024.

In this new guide you’ll learn:

  • Microservices fundamentals
  • How to optimize & scale
  • Why and how of microservices
  • And lots more...

Let’s get started.

Microservices : Your Comprehensive Guide to Success

by Rajeev Bera

Updated  February 11, 2024


Microservices Introduction

Let’s start with the basics.

In this chapter, I’m going to cover what EXACTLY is a microservice. And why it’s SUPER important in 2024.

I’ll also show you what is (and isn’t) considered a “microservice”.

Let’s dive in.

Microservices introduction

What are Microservices?

Microservices (or Microservices architecture) is an approach. 

It is an architectural style that can guide you in designing and structuring your overall system. 

(Microservices, not a framework or implementation)

Microservices are not a framework or implementation
  • Microservice is a small component of a large application.
  • Each microservice can operate independently.
  • They communicate with each other via simple, lightweight methods.
  • A small team manages one microservice, making them around business needs.
  • They can be deployed independently. (for faster and easier updates)

Let me repeat one important statement.

Microservice is an architectural style. It guides you on how to design and structure your system.

defination of microservices

And about Implementation - You can use any language to create microservices like C#, Java, Python, or others.

You can use any cloud platform you like. It can be AWS, Google, Azure, or something else. 

Easy, right?

Evolution of Microservices

You can say -  Microservices started with Service-Oriented Architecture (SOA). 

In the early 2000s, Service-Oriented Architecture (SOA) was a big thing. It splits applications into separate services. 

SOA - Evolution from SOA to Microservices

But SOA had two main problems

  • Complexity (It was quite complex)
  • Flexible (It wasn’t flexible enough)

Big companies like Amazon, Netflix, and Spotify need to handle loads of data. And in around 2010, they started breaking their big applications into smaller ones.

Each piece focused on a single task. (This is what we now call "microservices") 

Software expert Martin Fowler wrote about microservices in 2014. This made microservices and their use clear to everyone.

Microservices keep evolving to make building software better and faster.

Microservices and Service-Oriented Architecture (SOA)

Microservices and Service-Oriented Architecture (SOA) are two blueprints for building software. 

They both are architectural styles. But they’re not twins. 

And here is how they are different -

Evolution from SOA to Microservices
  • Task Orientation: Think of microservices like expert tradespeople. Each one’s got a specific job that it does really well, focused on a unique part of your business.

    Now, SOA?

    That’s more like a jack-of-all-trades. SOA deals with lots of different parts of your business all at once.

  • Data Management: When it comes to data, microservices like their own space. Each service comes with its own database.

    But with SOA, it’s a bit different. Many services can all dip into the same shared database.

  • Operational Autonomy: You can deploy each service independently.

    If you opt for SOA, remember that shared resources may limit your operational flexibility.
Microservices provide more flexibility and scalability

Microservices provide more flexibility and scalability. However, they may add complexity. On the flip side, SOA can offer sturdy, reusable business components. 

Every system has strengths and challenges, so it’s all about finding what fits best for you!

Monolithic vs. Microservices Architecture

Monolithic and Microservices architectures represent two unique strategies in software development.

Each has a unique set of characteristics and use cases.

Monolithic Architecture

Monolithic architecture is like a single, massive, do-it-all unit.

Imagine it as a large machine responsible for executing every task in your application. Building and using it is relatively simple. However, the entire system could be in danger if one component malfunctions. 

When it comes to scaling, it’s a case of all-or-nothing. You must expand the entire unit, which can be complicated and expensive.

Developing, testing, and deploying a monolithic architecture is relatively straightforward. Key features of the Monolithic architecture include:

Monolithic Application
  1. 1
    Single Codebase: The entire application logic exists within a single codebase.
  2. 2
    Single Build System: The entire application is built and deployed at once.
  3. 3
    Single Database: Typically, a monolithic application communicates with a single database.
  4. 4
    Single Point of Failure: If any part of the application fails, it can affect the entire system.
  5. 5
    Scalability Issues: When traffic increases, the entire application needs to be scaled. (even if only one functionality requires more resources)

Microservices Architecture

Think about taking a huge, complex machine and splitting it into tiny, efficient parts.

That's the essence of microservices architecture.

Every part is a self-sufficient unit. It can evolve, upgrade, or even stumble, all without causing a hiccup in the rest of the system. This gives it flexibility and resilience, though it does make things a tad more complex to handle.


There are many advantages of microservices. And here are the main features of a Microservices architecture:

  1. 1
    Decoupled Services: The application breaks down into several small services. Each is capable of independent updates without affecting the others.
  2. 2
    Independent Deployment: Each service can be built and deployed independently.
  3. 3
    Polyglot Persistence: Every service can pick its own database that suits its style and needs.
  4. 4
    Fault Isolation: If a service fails, it does not necessarily bring down the whole system.
  5. 5
    Scaling: Each service can be scaled independently based on its needs.

When dealing with heavier, more complex tasks, microservices could be your go-to. 

Evolution from Monolithic to Microservices

For sure, in Microservice, it’s more to manage, but the results could be worth it.

Is REST API a Microservice?

A REST API is not a microservice.

REST API is a set of principles for building web services, often using HTTP methods (like GET, POST, PUT, DELETE, etc.)

REST API and Microservice

Microservices are an architectural pattern where an application is composed of small, independent services.

Microservice is not just an API. it’s a small and independent service. And it performs a specific function within a larger system. A REST API can be used to facilitate communication between microservices, but they are separate concepts.

Why are Microservices Important?

Microservices are really changing the game in software development.

  • As folks are surfing the web more on phones and tablets. The software is shifting towards microservices.
  • The need for scalability is another push toward using them.
  • Plus, the race to develop software faster is also making microservices a go-to choice.

In a nutshell, the internet is our go-to, and we all love things quick and simple. 

According to the stats on Statista

Microservices are the choice for 81.5 pc of companies
  • Microservices are the choice for 81.5% of companies.
  • Another 17.5% of firms are getting ready to jump on the Microservices bandwagon.

You know what’s cool?

Microservices aren’t just for the big companies. Even start-ups and small businesses are jumping on the bandwagon.


It’s simple. Businesses can grow more quickly and turn new ideas into something tangible in no time at all. Thanks to the benefits of microservices.

But you’re probably wondering:

“How many different types of microservices are there? What are their key principles?”.

Well, that’s what our next chapter is all about…

Microservices 101

This chapter is all about microservices 101. And this chapter will make SUPER easy to understand microservices.

So, hold tight! 

In this chapter, I’ll show you 

- Key principles of microservices. 
- What is database per service.
- How to handle databases efficiently. 

And more…

Microservices 101

Microservices Anatomy: Understanding Services and Components

What is the heart of microservices architecture? 

Two parts -  services and components. 

To use microservices, you need to know their structure.

The Heart of Microservices Architecture

The Role of Services

Understanding microservices starts with understanding services. 

A service is a software piece. It wraps up a specific business task. Services can be developed and scaled independently. This independence boosts scalability and fault isolation.

However, splitting an application into services isn’t easy. It needs a deep understanding of the task at hand. It also requires careful planning to avoid unwanted dependencies.

Breaking Down Components

A microservice has several components:

Microservices components
  1. 1
    Business Logic: This is where the work happens. Here, you implement the business functionality.
  2. 2
    Data Access Layer: This connects the service to its database. It hides the database’s specifics from the service.
  3. 3
    API Endpoints: Other services interact with the service through this interface. Services often use RESTful APIs over HTTP/HTTPS.
  4. 4
    Infrastructure Layer: This houses necessary running components. These include logging, error handling, security, and communication libraries.
  5. 5
    Configuration: This holds the settings and parameters that govern the service. It dictates how the service behaves, typically externalized from the code.

Microservices Communication

Services talk to each other through protocols. They usually use HTTP/HTTPS for synchronous talks or messaging queues for asynchronous ones. 

Effectively applying the right communication patterns in microservices is important. 

And In the next chapter I will dive deep in the microservices communication.

Microservices Orchestration

Microservices orchestration is the coordinated management of individual services in a microservices architecture.

It automates the workflows and interactions between microservices, handling tasks like sequencing, scaling, and failure recovery, often using tools like Kubernetes or Docker.

Microservices and Databases

Getting a microservices setup right means figuring out the best way to deal with data storage. It’s a different game when you compare it to old-school monolithic apps.

Here’the deal: each microservice gets its own personal database. This setup guarantees a relaxed coupling and keeps data tidy and consistent.

Techies often call this the "Database per Service" pattern.

Microservices breakdown

Database per Service

In the world of microservices, each service has its own dedicated database - it's a one-database-per-service deal. Other services can’t just barge in and access this database. If they need some data, they need to knock on the door or, in tech-speak, use the owning service’s API.

It boosts the decoupling and encapsulation of each service. It’s a bit like building separate rooms in a house - each room is independent and has its own privacy. That’s how each microservice keeps its independence.


  • Technology Flexibility: Every microservice gets its own database, so teams can cherry-pick the perfect database type for their service. It could be a relational database, NoSQL, graph, or anything else that fits.
  • Fault Isolation: By keeping databases separate, if a service fails, it won’t directly impact the data of other services. This isolation improves the system’s overall resilience.
  • Data Consistency: Each microservice looks after its own data. It uses transactions, checks, and rules to keep data correct and consistent.


No doubt, there are many perks, but it’s not all sunshine and rainbows.

  • Harmony Across Services: Keeping things in sync across services gets a bit tricky. To navigate this, developers often employ distributed transaction tactics, such as the Saga pattern.
  • Data Duplication: Sometimes, data needs to be present in more than one service. This leads to duplicated data and can stir up issues with syncing and maintaining consistency.
  • Complex Queries: Running complex queries or joins that spread across multiple services becomes a hard nut to crack. A common way to handle this is by dedicating a separate service to carry out such queries. Command Query Responsibility Segregation (CQRS) is a common tool for this.

Yes, there are challenges with the Database per Service pattern. But, it’s still seen as a best practice in microservices. 


Because it champions the independence of each service.

And that’s key in a microservices setup. It allows each microservice to evolve at its own pace. This offers room for flexibility, which is vital when managing complex, distributed systems.

Key Principles of Microservices

Microservices follow specific principles that enhance their potential in software architecture.

The principles of microservices shape their structure. They enhance scalability, flexibility, and resilience in application development.

Below are the eight core principles that are fundamental to microservices:

  1. 1
    Single Responsibility Principle: In the microservices world, each service has a single job. This keeps things neat and easy to handle. Plus, it brings clarity to what each service is there for.
  2. 2
    Independence: Each microservice should stand on its own. It should be able to change, grow, and operate without messing with the others. This lone-wolf attitude is the backbone of continuous delivery and deployment.
  3. 3

    Domain-Driven Design (DDD): It is a key concept in microservices. It’s a methodology that organizes microservices based on business needs. Each microservice focuses on one specific business function. So, the whole setup mirrors the business and its operations.

  4. 4

    Decentralization: Microservices love decentralization. It’s crucial for managing data and processes. Each service gets its own database, keeping them loosely linked yet in order. Teams also get to enjoy this freedom, choosing the best tech for their service without any central dictation.

8 Key Principles of Microservices
  1. 5
    Failure Isolation: Microservices should be built to survive alone. If one goes down, the others shouldn’t. By keeping each service independent, one hiccup doesn’t bring down the whole operation.
  2. 6
    Automated Deployment: Automated processes are key in microservices. They’re used in testing, integration, and deployment. They help with scaling too. This leads to a steady and smooth delivery process. Often, this involves practices like CI/CD.
  3. 7
    Continuous Delivery: Microservices are all about quick, reliable delivery. Helping businesses get new features to users fast.
  4. 8
    Evolutionary Design: Microservices should be designed to accommodate changes over time. The services should be small and loosely coupled. So they can be updated, replaced, or removed as the system and its requirements evolve.

These principles are key. They guide you when you design, develop, and manage a system based on microservices.

These eight core principles provided are widely recognized in the context of microservices. 

There are additional principles and best practices that can be applied depending on the specifics of the system being built. However, they may not be as universally agreed upon as "core."

Here are three more ...

Bonus Key Principles of Microservices
  1. 9
    Service Granularity: A careful consideration of service size is vital in a microservices architecture. They should be small enough to handle a single function but large enough to add real value to the business.
  2. 10
     Stateless Services: Services should be stateless. They shouldn’t depend on data from previous interactions. This boosts scalability, as any service instance can handle any request.
  3. 11
    API-First Design: In the world of microservices, API-First Design is a must. A well-designed API ensures smooth communication between services. Starting with the API before getting into implementation helps keep services decoupled and able to evolve on their own.

Remember to keep your project’s unique needs in mind when deciding which principles to focus on.

Deeply understanding and thoughtfully applying the principles is more important than attempting to implement all of them simultaneously.

Types of Microservices

In the world of application architecture, microservices come in various forms. Each type brings a unique approach to tackling challenges, offering solutions based on business needs. 

Here’s a breakdown of the most common types, as well as other forms used in specific scenarios.

Most Commonly Used Microservices

  1. 1
    Domain-Driven Microservices: These are arguably the most common form of microservices. Each corresponds to a distinct business domain, and they handle specific business operations. Domain-driven microservices focus on core business needs and functions.
  2. 2
    API Gateway: This type acts as a single entry point into a system. (Think of this type as the reception desk of a hotel.) It receives API calls, routes them to the appropriate microservice, and then aggregates the responses to send back to the client. It provides a level of abstraction between the client and the microservices.
  3. 3
    Data-Centric Microservices: These microservices handle a specific data type in a particular business functionality. This type is common in applications where each service needs its own database to ensure loose coupling.
  4. 4
    Event-Driven Microservices: These microservices trigger when a specific event occurs. These are the quick responders. They are commonly used in systems where certain actions are driven by event occurrence.

Other Types of Microservices

  1. 1
    Composite Microservices: These are the team players. They work by combining inputs from various services to deliver one unified response. They make sure the entire application works in harmony.
  2. 2
    Integration Microservices: These are the communicators. They ensure all microservices effectively talk to each other, bridging communication gaps.
  3. 3
    Unit-of-Work Microservices: These are the specialists. They focus on a specific task (unit of work) or a transaction, like managing an order or a customer request.
  4. 4
    Proxy Microservices: These act as intermediaries between your microservices and external clients. (You can think of them as security guards)They provide an additional layer of security and abstraction.
  5. 5
    Chain Microservices: These are like an assembly line. Each one follows a set order, passing outputs from one to the next in the chain.
  6. 6
    Branch Microservices: These work like a family tree, with one parent microservice directing tasks to various child services.

When you’re planning your application, consider the needs and layout before choosing your microservices. The right ones can make your software smoother and more effective.

Microservices Communication

This chapter is all about making it SUPER easy for microservices to communicate.

In this chapter, I’ll guide you on how to identify and resolve communication bottlenecks... and how to establish seamless data flow between the independent services.

Lets dive in.

Microservices Communication

Microservices Communication is like teamwork in a game of soccer.

Each part of a program, like each player, knows exactly how to pass the ball or, in this case, share info.

Many communication patterns exist. And in this chapter, I will share the three most widespread.

Request/Response Pattern

The Request/Response is a cornerstone communication pattern in a microservices architecture.

Clients send requests. Servers respond to them.

It provides a structure where requesters (clients) and responders (servers) are distinct.

They interact sequentially, with the client awaiting a response following a request.

This pattern ensures a predictable and straightforward data flow, wherein each request is met with a corresponding response.

Microservices Communication - Request Response Pattern

How it Works :

The hop of the Request/Response pattern begins with the client. The client constructs a query (or a request) and sends it to the server. 

And server takes action on the request ( when he receives it). It's essential to understand server does not need any other information about the client except the request.  

Once the server processes the request, it responds to the client. This is when the client, who has been patiently waiting, can continue its operations. 

(like a telephone call)

This waiting period is a characteristic feature of the Request/Response pattern, underlining its synchronous nature. 

Advantages :

  • Simple: The Request/Response pattern is straightforward. It’s like human interactions - ask a question, get an answer. 
  • Data Certainty: Since the client waits for the server’s response, it ensures the client has the information needed before taking the next step.
  • Compatibility: This pattern is widely used and supported, with HTTP/HTTPS being standard protocols supporting it, making it highly compatible with many systems.

Disadvantages :

  • Blocking Nature: In the Request/Response pattern, the client has to wait for the server's response before it can continue, potentially leading to inefficiencies or slowdowns in a system.
  • Error Propagation: Since the client is waiting for a response, any errors on the server side can directly impact the client, making error handling critical.

Example :

Here are examples of the Request/Response pattern.

  1. 1
    Google: You type a query. That’s a request. Google’s servers hear it and they find the right answers.
    Your search results come back to you.

  2. 2
    Amazon: You want to see a product. You send a request. Amazon’s servers catch it and find the product details.
    You get what you asked for.

  3. 3
    Netflix: You browse Netflix’s library. That’s your request. Netflix’s servers see it and find the show or movie you want.
    Your viewing choice is ready.

Event-Driven Pattern

The Event-Driven Pattern is a progressive communication pattern integral to modern microservices architecture.

Services generate events. Other services react to them.

It establishes a framework where events act as triggers, and different services within the system can act upon those triggers without direct coupling.

Events happen asynchronously, with subscribers listening to specific events and reacting when they occur.

This pattern encourages a lively and interactive data flow, where services can operate independently yet stay informed about changes within the system.

Microservices Communication - Event-Driven Pattern

How it Works :

The Event-Driven Pattern starts with a service known as the publisher. The publisher creates an event and pushes it to a common message broker or event bus.

(A common message broker or event bus is middleware. It enables asynchronous communication in a system.)

The event is a signal that something noteworthy has occurred within the system.

Meanwhile, other services, called subscribers, continuously listen to the event bus. They’re tuned to specific events that interest them.

When an event of interest occurs, the subscribers catch it and take action.

It’s like a city broadcaster disseminating news in a public square. Whoever is interested in the news will respond, but the broadcaster doesn’t know who that might be.

Advantages :

  • Flexibility: The Event-Driven Pattern allows services to operate independently. And they react to events as needed.
  • Scalability: Here, services can be added/removed without affecting the whole system.
  • Resiliency: It's asynchronous. It means a failure in one part of the system doesn’t immediately impact others. And it leads to robust error handling.

Disadvantages :

  • Complexity: Managing events can be complex, especially in an extensive system.
  • Ordering Issues: One of the challenges in the system is related to ordering issues. Ensuring that events are processed in the correct order can be challenging.
  • Potential Data Inconsistency: Handling data consistency across services can be challenging.

Example :

Here are examples of the Event-Driven Pattern in action

  1. 1
    Uber: An event is triggered when a ride is completed.
    Other services catch this event to process payments, rate drivers, and update ride statistics.
  2. 2
    LinkedIn: When you update your profile, that’s an event. 
    Other services within LinkedIn catch it to update your connections, recommend jobs, and more.

  3. 3
    Amazon: Add a product to your wish list, and that’s an event. 
    Amazon’s services catch it to make recommendations, alert you to price drops, or notify sellers.


The Publish/Subscribe, often known as Pub/Sub.

It is a messaging pattern in distributed systems.

Publishers send messages. Subscribers receive them. 

It provides a framework where senders (publishers) and receivers (subscribers) are separate.

They are decoupled and have no knowledge of each other.

Microservices Communication - Services generate events. Other services react to them.

How it Works :

In this pattern, a publisher creates messages and publishes them to a message broker or an event bus. The publisher does not send these messages directly to specific receivers. Instead, It sorts messages into classes (or categories). It does not know if there are subscribers for these messages.

On the other hand, subscribers express interest in one or more classes of messages. And only receive messages that are of interest.

 They don’t have to know anything about the publishers. The event bus or message broker manages the transmission of messages from publishers to subscribers.

Advantages :

  • Decoupling: Publishers and subscribers are separate. Changes in one don’t affect the other.
  • Scalability: You can add more publishers or subscribers to boost capacity. They don’t need to interact directly.
  • Resilience: If a subscriber fails, it won’t impact the publisher. The system can still publish messages.

Disadvantages :

  • Complex Error Handling: Because the system is asynchronous, handling errors can be complex.
  • Message Overhead: Each message needs metadata to identify its class (or category), adding overhead.

Example :

Here are examples of the Publish/Subscribe pattern:

  1. 1
    Twitter: You tweet something (publish). Your followers (subscribers) see the tweet. They’ve subscribed to you, so they get what you publish.
  2. 2
    Stock Market Updates: A stock exchange publishes updates about stock prices. Traders and brokers who have subscribed to updates about particular stocks receive these updates in real time.
  3. 3
    News Apps: Various news sections (like sports, politics, entertainment) are published by journalists. Readers subscribe to what they’re interested in, and only receive those specific updates in their feed.
microservices patterns

There are more patterns in microservices communication.


- Circuit Breaker Pattern
- API Gateway Pattern
- and more...

The idea is that microservices can communicate - smoothly.

And for a smooth system, automation is also essential. This is what the next chapter is - "Automation and Microservices."

So let's start the next chapter.

Automation and Microservices

In this chapter, I’II dive into details about Automation and Microservices. 

Here, you’ll discover how to 

  • Implement automation
  • Minimize redundancy
  • Smooth system and more...

This chapter is about less manual intervention and super smooth flow. 

Get ready to transform your workflow, Let’s start..

Automation and Microservices

The Importance of Automation in Microservices

Automation is critical to keeping efficiency and reliability in a microservices environment.

Before we dive deeper, let’s try to understand why automation matters. And here are a few key reasons.

The Importance of Automation in Microservices
  1. 1
    Speed: Automation expedites the development and deployment of services, allowing for quicker delivery.
  2. 2
    Consistency: Automated processes ensure uniformity, reducing variability in outputs and results.
  3. 3
    Reduced Errors: Minimizes the chances of human errors in routine tasks. And it increases overall reliability.
  4. 4
    Efficiency: By automating repetitive tasks, you can focus on high-value tasks. ( like writing code)
  5. 5
    Testing: Automated testing ensures each service operates as expected, preserving the system’s integrity.
  6. 6
    Reliability: Automated procedures guarantee that the services will function reliably and predictably
  7. 7
    Scalability: Automation facilitates the seamless scaling of services. As the demand fluctuates, it optimizes resource usage.

CI/CD Pipeline for Microservices

A CI/CD pipeline is a must-have tool in the microservices kingdom.

It standardizes the building, testing, and deploying of code. It makes software delivery quick and reliable.

In Continuous Integration, developers frequently merge code changes. The system then automatically builds the application. It runs a series of tests. This reduces the likelihood of integration-related bugs.

Continuous Integration

Continuous Deployment automates the release of validated code. It goes straight to a production environment. This means new updates reach users quickly. The entire process is consistent and reliable.

Continuous Deployment

By using a CI/CD pipeline, deployment errors get minimized. This ensures a smoother and more efficient workflow in a microservices architecture.

Automation Tools and Frameworks for Microservices

A variety of tools and frameworks support the automation of microservices.

Here are some key ones:

  • Docker: Docker is a tool for containerizing applications (Containerization is the encapsulation of an application and its dependencies into a standalone unit called a container).
  • Kubernetes: This is a tool for orchestrating containers. It aids in deploying, scaling, and managing applications packaged in containers.
  • Jenkins: Jenkins is an open-source automation server. It assists in automating the building, testing, and deployment of applications.
  • Istio: Istio is a service mesh framework. It simplifies managing, securing, and observing microservices.
  • Prometheus and Grafana: These tools focus on metrics. They help in monitoring microservices and visualizing the data.

These tools streamline microservices by easing development, deployment, and maintenance of complex applications.

Automation Tools and Frameworks for Microservices

Managing complexity is like juggling flaming swords in the high-stakes world of microservices. 

The tools we explore, from Docker to Kubernetes, along with essential Git commands, are the secret safety gloves you need

Let’s see the popular automation tools for microservices, both open-source and paid:

  • Docker: Docker is a leader in container technology. It packages applications for consistent deployment.
  • Kubernetes: Kubernetes automates container orchestration. It manages, scales, and deploys containers.
  • Jenkins: Jenkins is an open-source automation server. It facilitates building, testing, and deploying software.
  • Istio: Istio is an open-source service mesh. It controls and observes microservices.
  • Prometheus and Grafana: These open-source tools monitor and visualize metrics from your microservices.
  • AWS: Amazon Web Services offers a comprehensive suite of services. They range from container management to CI/CD.
  • Azure: A product from Microsoft. It gives you lots of tools to work with microservices. It's like a big toolbox for your projects.
  • GCP: Google Cloud Platform is another major cloud provider, includes services for managing & automating microservices.
  • OpenShift: It’s Red Hat’s enterprise-grade Kubernetes platform. It offers automated installation, updates, and more.
  • Helm: Helm is a package manager for Kubernetes. It simplifies the process of managing applications.
  • Spinnaker: Spinnaker is a multi-cloud continuous delivery platform. It enables fast and safe deployments.
  • Ansible: Ansible is an open-source tool. It can use for automating software provisioning, configuration management, and application deployment.

These tools handle everything about microservices. They help create, launch, and take care of them.

Many more tools are out there. But I mention just the popular ones.

Building Resilient Microservices

Only creating microservices doesn’t make a robust system.

Building resilient microservices is a the key.

In this chapter, I will cover essential parts of building reliable microservices. 

  • What is the need for resilience?
  • How to handle errors?
  • and more...

Let's start the journey to build stronger microservices!

Chapter Building Resilient Microservices

Importance of Resilience in Microservices

Before I dive deeper, let’s try to understand what resilience in microservices means. 

Resilience is the system’s ability to function under failure.

In a microservices architecture, many services work together. If one fails, others may be impacted. This can disrupt the whole system. Hence, resilience is key in microservices.

Here are key points that highlights importance of Resilience in Microservices.

  1. 1
    Stability: Resilience helps the system stay operational, even if individual services fails.
  2. 2
    Reliability: Resilient systems consistently perform their intended functions, ensuring trustworthiness
  3. 3
    Fault isolation: Resilience strategies help isolate faults within a single service without impacting the entire system.
  4. 4
    Service continuity: Resilience allows systems to keep running, avoiding user disruptions during failures.
  5. 5
    Handling external issues: Resilience allows microservices to manage issues beyond failures, like network latency. This adds robustness and reliability.

Strategies for Error Handling and Fault Tolerance

Achieving fault tolerance in a system is critical.

It ensures the system functions correctly, even if some parts fail. 

And here are some essential strategies for fault tolerance:

Retry and Timeout Policies - Recovering from Temporary Failures

Retry and timeout policies are critical for system availability and resilience. They help deal with transient failures effectively.

The Fault: Transient System Failures

Transient system failures are temporary faults. And these can be overcome by retrying the operation after a short period. These can include 

  • Temporary network glitches
  • Momentary database unavailability
  • or a brief overload of a service

Understanding Retry and Timeout Policies

Retry and timeout policies are techniques (or simply rules). It’s used in handling transient system failures.

A retry policy dictates how many times and how frequently an operation is reattempted. (if it fails initially due to a temporary glitch)

On the other hand, a timeout policy sets a limit on how long the system should wait for a response. And after that time, it is considered that the operation failed.

Together, these policies boost your system’s robustness. They make it more resistant to minor, temporary faults.

Retry and Timeout Policies in Practice:

Azure provides built-in support for these policies. With Azure’s SDKs, you can easily implement retry logic in your applications. This boosts resilience against transient faults.

AWS also supports these policies. The AWS SDKs come with a preconfigured set of retry policies. Developers have the flexibility to customize these policies based on their application’s needs.

Google Cloud is no different. It encourages the use of retry and timeout policies in its Cloud Endpoints. These policies prevent applications from hanging indefinitely due to a transient fault.

Circuit Breaker Pattern - Preventing System Overload

The circuit breaker pattern is key in preventing cascading failures in microservices. It acts like a shield, protecting your system.

The Problem: Persistent Service Failures

In a distributed system like microservices, certain components might exhibit persistent failures. It could happen because of various reasons, such as

  • Bugs
  • Resource saturation
  • Or network issues

These persistent failures can cause a cascading effect. It could bring down other dependent services and, ultimately, the entire system.

Defining the Circuit Breaker Pattern

The circuit breaker pattern is a design technique. It is used in microservices architecture to detect and manage recurring failures. 

This pattern functions similarly to an electrical circuit breaker. 

This prevents overloading the failing service with more requests. After the timeout, the circuit breaker allows a limited number of test requests to pass. If these succeed, the circuit breaker ’closes’, and regular traffic resumes. If they fail, the timeout period begins again.

It’s especially important for systems needing high uptime. The circuit breaker ensures that failing services don't hog resources. It prevents a drop in overall performance.

Circuit Breaker Pattern in Practice

Netflix’s Hystrix library is often used with Spring Cloud Netflix in the AWS ecosystem. It provides an implementation of the Circuit Breaker pattern. 

Azure provides a similar feature through Azure Service Fabric.

Google Cloud utilizes Cloud Armor to ensure system stability during service failures.

Bulkheads - Isolating Failures

As developers, you strive to build robust systems that withstand failures. One approach to achieving this resilience is through a strategy known as ’Bulkheads’.  This concept is derived from the shipping industry. 

The Problem: Cascading Failures

Cascading failures occur when a problem in one part of the system propagates, causing other parts to fail. This type of failure can lead to system-wide outages. And it makes it one of the most significant issues in distributed systems. (like microservices)

Understanding Bulkheads

Bulkheads are all about system isolation. This strategy aims to restrict failures within a specific part of your system. 

The idea takes its roots from the design of ships. Compartments within a ship’s hull are known as bulkheads. When there’s a breach, these bulkheads prevent water from flooding the entire vessel.

In the world of microservices, the concept works similarly. Each service is isolated, much like a ship’s compartments. If one service fails or gets overloaded, that issue stays confined. It doesn’t cascade or spread into other services.

Bulkheads in Practice

Bulkheads are present in popular cloud platforms. Azure, AWS, and Google Cloud all incorporate this concept. 

Take Azure as an example. Azure Service Fabric employs the Bulkhead pattern. This pattern isolates services. It helps maintain performance and stability. 

The situation is similar with AWS. AWS’s Well-Architected Framework suggests using bulkheads. The goal is to limit the blast radius of failures. 

Google Cloud also utilizes this strategy. Bulkheading is achievable with Google Cloud Endpoints. These endpoints isolate APIs. This ensures traffic spikes to one service don’t affect others. 

All these examples reflect the real-world significance of bulkheads. They show the value of this pattern in building resilient cloud-native applications.

Testing for Microservices Resilience

Testing for resilience is key in microservices. 

It’s about ensuring the system can handle and recover from failures. 

Here are a few key methods that add value:

Failure Injection Testing

Failure Injection Testing is a technique to fortify your system’s robustness. It involves deliberately introducing failures to test its recovery capabilities.

Understanding Failure Injection Testing

It’s a form of resilience testing where you inject failures intentionally. The goal is to assess how the system behaves and recovers from different types of faults. And making the systems more resilient. 

Performing Failure Injection Testing

You can inject failures at various levels, like. 

  • Network
  • Service level or 
  • At the application level.

These disruptions can simulate service unavailability, network latency, or data corruption. And then, you observe how the system responds.

Cloud Tools for Failure Injection Testing

Many cloud-based tools assist in this process. Azure’s "Fault Analysis Service" and AWS’s "Fault Injection Simulator" test system robustness. Google Cloud’s "Chaos Engineering" introduces controlled failures, allowing system response observations. 

In essence, Failure Injection Testing is a pre-emptive strike. It provides invaluable insights for fortifying your microservices architecture. It prepares your system for real-world scenarios. ensuring continued service delivery, even in unforeseen disruptive events.

Load Testing

Load Testing verifies system performance under a particular load, often beyond typical usage.

Defining Load Testing

 Load Testing assesses the system by gradually upping the load. This continues until the system reaches its limit. The goal is to pinpoint performance bottlenecks. This testing also identifies areas needing improvement.

Executing Load Testing

This usually involves using tools to simulate requests to the microservice. The focus is to observe how the system performs under heavy loads and where it starts to degrade. 

Cloud Tools for Load Testing

Various cloud platforms offer tools for Load Testing. 

  • Azure provides the "Load Testing Service."
  • AWS has the "AWS Load Testing Service."
  • Google Cloud offers the "Cloud Load Testing" service.

These tools help simulate load. They are also useful in analyzing system performance under stress. 

Disaster Recovery Testing

Disaster Recovery Testing is essential for ensuring system resilience against severe failures.

Understanding Disaster Recovery Testing

This testing aims to validate recovery tactics. It does so by mimicking severe failure scenarios. The ultimate goal is to ensure that the system can resume operations quickly. Minimizing downtime is key in this process.

Performing Disaster Recovery Testing

To carry out this testing, various procedures are necessary. 

- Firstly, backup procedures must be tested. This ensures that data restoration is efficient. 

- Secondly, failover processes are put to the test. The focus here is on the seamless switch to a backup system. 

- Lastly, data recovery strategies are assessed under disaster-like conditions. This helps confirm data safety and the ability to recover it effectively.

Cloud Tools for Disaster Recovery Testing

Several cloud platforms offer disaster recovery tools. For instance, Azure provides "Azure Site Recovery" for swift system restoration. AWS offers "CloudEndure Disaster Recovery," which helps ensure continuous operation. Lastly, Google Cloud provides a comprehensive "Disaster Recovery Planning Guide." 

It’s not only about preparing for the worst-case scenario but also about ensuring business continuity in case of a severe system failure. 

Evolutionary Design in Practice

Refining your design can directly impact your project’s adaptability.

That’s not to say it will instantly make your system invincible to changes.

(You need solid foundations for that)

But enhancing your system design can make a significant improvement in its resilience.

And in this chapter, I'll show you strategies to level up your practice of evolutionary design.

Evolutionary Design in Practice

The Concept of Evolutionary Design

When I talk about Evolutionary Design in the context of microservices, it’s all about being agile and flexible.

It’s not about getting everything perfect on the first go. But It is about being able to grow and adapt as you learn more about the system and its needs.

If you're rigidly sticking to the initial design and hesitant to make changes, you're skating on thin ice.

Principles Guiding Evolutionary Design

Think of these principles as the compass that steers the ship of evolutionary design.

Incremental Changes: This is all about taking baby steps.

You don’t need to redesign the whole system in one go - that’s like trying to eat an elephant in one bite!

Make small, manageable changes, test them, learn from them, and then take the next step.

Microservices - Principles Guiding Evolutionary Design
  • Embrace Change: Change is the only constant in life.

    The same goes for evolutionary design. It’s not about rigidly sticking to a plan but about adapting to and learning from changes.
  • High Cohesion & Loose Coupling: In plain English, every microservice should stick to its job (high cohesion) and not meddle too much with others (loose coupling).

    It’s like the perfect workplace - everyone does their job and interacts with others only when necessary.

  • Feedback Loops: This is about learning from your actions.

    Make a change, observe the result, learn from it, and then make the next change. It’s like a conversation with your system - you talk (make changes), listen (observe), and then talk again (make more changes).

  • Automate, Automate, Automate: Automation is the secret sauce for evolutionary design.

    The more you can automate testing and deployment, the quicker you can make changes and get feedback.

    Next, I will explore the differences between evolutionary design and Big Design Upfront. Stay tuned because it's going to be a wild ride!

Evolutionary Design vs. Big Design Upfront (BDUF)

You may have heard of one more design approach - Big Design Upfront, often shortened to BDUF. 

You might be thinking, "What’s the deal with that?"

BDUF is like the grandfather of software design. In the BDUF approach, you have to get all your design decisions right at the very beginning.

It’s like planning a cross-country road trip where you map out every lunch break and gas refill before starting your car. 

Sounds pretty rigid, right?

Microservices - Evolutionary Design vs. Big Design Upfront (BDUF)

Evolutionary design sets a general direction but keeps options open for adaptation.

It's vital in microservices, where the architecture is always changing. The Big Design Up Front (BDUF) approach doesn't fit here.

Instead, evolutionary design lets your architecture flex and grow with your business, embracing change rather than resisting it.

Microservices Success Story - UBER

Let’s wrap up this guide with microservices case study.

Here, I’ll share transformations from monolith to microservices from a top-tier company like Uber.


  • Microservices architecture
  • Independent deployment
  • Decentralized data management
  • Fault isolation and more...

So, let’s dive in...

Microservices Case Studies

Uber is not just about cabs. 

It’s a technology powerhouse.

An thanks to Microservices.

Uber Logo

In the early days, Uber started as a monolith - A single, solid chunk of code. 

It did the job but had its limitations. 

  • Couldn’t scale. 
  • Couldn’t adapt.
Uber First app was without microservices

As Uber grew, this became a problem. The app needed to handle more. 

  • More rides. 
  • More users. 
  • More cities.

So, Uber decided to break down the monolith.

Uber monolithic to Microservice

They chose Microservices.

With Microservices, each function is a separate service.

Each service can be built, tested, and scaled independently.

This was a game-changer for Uber.

They were no more battling with one codebase.

Instead, they had a small, manageable service.

They could update one service without affecting others. They could scale up services in high demand. They could roll back services that had issues.

Uber with microservices

Uber’s move to Microservices was challenging. It was a journey filled with challenges. They had to rethink their entire infrastructure. They had to deal with service isolation, data consistency, and complex deployments. But they prevailed.

Today, Uber handles millions of rides a day. It operates in hundreds of cities around the world. 

Because of the scalability provided by Microservices.

Microservices - Journey is not over for Uber

The journey isn’t over, though.

Uber continues to evolve and adapt.

Continues to make the most of Microservices.

Because in this fast-paced world, standing still is falling behind.

Now It’s Your Turn

That’s it for my take on microservices.

Now I’d like to hear from you:

Which aspect of this guide captivates you the most?

Are you going to delve into the microservices architecture?

Or perhaps you’re interested in microservices automation?

Either way, I’m eager to hear your thoughts.

Please share in the comments.

Microservices Guide Now Your Turn

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