Microservice Developers | Find Expertise with Ahex

Understanding gRPC and Protocol Buffers—A Modern Approach to Service Communication

ajay hooda — Mon, 06 Oct 2025 11:51:06 +0000

What is gRPC?

gRPC, or Google Remote Procedure Call, is a high-performance framework that allows applications to communicate with each other efficiently over a network. Instead of building one massive application, developers often break down their projects into smaller services. These services need a way to talk to each other, and that’s where gRPC comes in.

How does gRPC work?

Imagine two friends trying to talk on a walkie-talkie. REST APIs are like having to say “over” after every message, it gets the job done but is a bit slow and can waste time. gRPC, on the other hand, is like a seamless, continuous conversation. gRPC uses Protocol Buffers for data, which are incredibly lightweight and fast. This makes gRPC a much more efficient “translator” for services, leading to faster data transfer and less bandwidth usage. It also has built-in support for features like streaming, which allows a constant flow of data without having to open and close connections repeatedly.

gRPC vs REST

Definitions

Procedure : A procedure is just another word for a function or method in programming.

Procedure call : When you use/invoke a procedure (function), that’s a procedure call.

Remote Procedure Call: It means calling a function/procedure that exists on another computer (remote server) as if it were local.

gRPC : gRPC stands for Google Remote Procedure Call, an open-source, modern, AND high-performance framework for the implementation of RPC using HTTP/2 for fast communication and Protocol Buffers (Protobuf) for efficient data transfer.

Serializing : Converting an object into a format (binary or text) so it can be stored or sent over the network.

Deserializing: Taking the received data and converting it back to an object that the program can use.

Proto Buffer: Protocol buffers are language-neutral and platform-neutral data serialization formats developed by Google. It can be transmitted over a wire or be stored in the files.

Understanding gRPC Core Concepts: HTTP/2, Protobuf & RPC Model

WHAT IS PROTOCOL BUFFERS?

Protocol Buffers (Protobuf) as its interface definition language (IDL), which is one of its primary enhancements of RPC. Protobuf is a flexible and efficient method for serializing structured data into a binary format. Data that is encoded in a binary form is more space-efficient and faster to serialize and deserialize than text-based formats like JSON or XML.

Json or XML are also serializing the data. But they aren’t fully optimized for the scenarios where the data is to be transmitted between multiple microservices in a platform-neutral way. That’s why developers prefer protocol buffers over them. Think of it like packing your belongings into a small, neat suitcase so they take up less space and are easier to carry. Key Benefits:- Smaller and Faster: Much more efficient than JSON or XML.

PROTO BUFFER VS JSON

GRPC:

gRPC stands for Google Remote Procedure Call. gRPC is an open-source, modern, high-performance framework created by Google that allows applications to communicate with each other as if they were calling local functions. But over the network, instead of sending plain text like REST (JSON over HTTP), gRPC uses Protocol Buffers. gRPC is a modern, open-source framework for building Remote Procedure Call (RPC) APIs.

PROTO:

A .proto file is like a contract that explains what services exist, what functions they provide, and what data they use. It’s written before any code, and from it, you can automatically create client and server code in many programming languages, like Java, Python, Go, C++, and more.

PROTOC:

protoc is the Protocol Buffers compiler. It takes your .proto file (the contract) and converts it into real code (classes and methods) in your chosen programming language. This way, both client and server can use the same generated code to talk to each other easily and consistently.

HTTP/2:

HTTP/2 protocol allows multiple requests under a single connection. It introduces multiplexing, header compression, server push, and binary framing, which makes it much faster and more efficient than HTTP/1.1.

MULTIPLEXING:

Multiple requests can be sent over a single TCP connection simultaneously, eliminating head-of-line blocking and reducing latency.

GRPC WORKFLOW:

When building a gRPC service, the process usually follows three key steps. Let’s understand them with a simple example of a User Service (where a client asks for user details).

Step 1 Define:
- Write a .proto file using Protocol Buffers.
- This file acts like a contract between client and server.
- Example: Define a service GetUser that takes a user ID as input and returns the user’s details (name, email, etc.).
Step 2: Compile:
- Use the protoc compiler to convert the .proto file into real source code.
- Code can be generated in multiple languages like Go, Java, Python, or C#.
- Example: The same GetUser service definition can be turned into client and server code in any language.
Step 3: Implement:
- On the server side, write the logic.
- e.g., when GetUser is called, fetch details from a database and return them
- On the client side, simply call GetUser as if it were a local function, and the server responds with the user info.
- Example: The client requests user ID = 1 → server returns Alice, alice@example.com.

WHAT IS SCHEMA?

syntax = “proto3”;
message Person {
string first_name = 1;
string last_name = 2;
optional int32 age = 3;
float weight = 4;
repeated string addresses = 5;
}

syntax = “proto3”; This tells protobuf which version you’re using. proto3 is the latest version (simpler, most commonly used). Without this line, protobuf might assume proto2, which has more complex rules.
message Person { … } : message defines a schema (like a class). Person is the name of the message, everything inside { … } are the fields that belong to Person.
Each field follows this pattern: = ;
Each field has: type (string, int32, float, etc.). name (first_name, last_name, etc.)
tag number (= 1, 2, 3…) → unique ID, Tag numbers must be unique within the message; these numbers are used in the binary format, not the names. It means it never writes “first_name” or “last_name” as text to disk. Which saves space. Instead, it only writes the tag number + value.

Ex: [ tag=1 ][ “Alice” ]

[ tag=2 ][ “Johnson” ]

[ tag=3 ][ 25 ]

repeated makes the field a list or array.
optional makes the field optional, which means Protobuf doesn’t write unused optional fields into the binary. Normal fields still carry default values (e.g., 0 for numbers, “” for strings). With optional, you don’t store that default unless it’s explicitly set. Saves bandwidth + storage when sending over the network.

Key Features of gRPC

High Performance with HTTP/2:

gRPC uses HTTP/2 for fast, low-latency communication with multiplexing and header compression, ideal for microservices.

Cross-Platform & Multi-Language Support

gRPC works across platforms and languages, using .proto files to generate compatible client/server code.

Strongly Typed Contracts

gRPC’s .proto files define strict data and method contracts, preventing errors with strongly typed code.

Built-in Authentication & Security

gRPC ensures secure data exchange with SSL/TLS and supports flexible authentication like OAuth or JWT.

Efficient for Microservices

gRPC’s lightweight Protobuf and HTTP/2 streaming make it perfect for fast, reliable microservice communication.

Simple Request-Response

The client sends one request, and the server replies with one response, which is ideal for simple tasks like authentication.

Server Streaming

Client sends one request, server streams multiple responses, great for live updates like stock prices.

Client Streaming

Client streams multiple messages, server responds once, suitable for file uploads or batch data.

Bidirectional Streaming

Both client and server stream messages simultaneously, perfect for real-time apps like chat or gaming.

Advantages of gRPC

Performance Efficiency: gRPC’s use of HTTP/2 and binary serialization makes it faster and more efficient than traditional REST APIs, especially in high-performance environments.
Strong API Contracts: The use of protobuf provides a strict contract for API communication, reducing the likelihood of errors and improving compatibility across services.
Real-Time Communication: Support for bi-directional streaming allows for real-time communication, making gRPC ideal for applications requiring instant data exchange, like chat apps or live updates.
Built-In Code Generation: gRPC supports automatic code generation for client and server stubs in multiple languages, speeding up development and ensuring consistency.

Limitations of gRPC

Steeper Learning Curve: The use of Protocol Buffers and understanding HTTP/2 can require additional learning, especially for teams accustomed to REST and JSON.
Limited Browser Support: gRPC is not natively supported by browsers, which can limit its use in web applications without additional workarounds like gRPC-Web.
Complexity in Debugging: The binary nature of Protocol Buffers can make debugging more challenging compared to text-based formats like JSON, which are human-readable.

gRPC vs REST

Case study:

In my case study, I compared the latency, throughput, and resource usage of REST and gRPC APIs running on a Kubernetes cluster. With 90,000 requests handled per second as opposed to REST’s 66,000, gRPC performed better than REST. Additionally, it demonstrated a smaller memory footprint and reduced network bandwidth consumption, which made it perfect for microservices with demanding performance requirements.

Serialization caused gRPC to have a slightly higher initial latency, but it held steady under high loads. Web applications work well with REST because of its simplicity and reliability under moderate loads, even though it is less efficient.

However, for microservices, I recommend using gRPC, as it is more efficient and cost-effective in cloud environments. In my case study, I compared the latency, throughput, and resource usage of REST and gRPC APIs running on a Kubernetes cluster. With 90,000 requests handled per second as opposed to REST’s 66,000, gRPC performed better than REST.

Additionally, it demonstrated a smaller memory footprint and reduced network bandwidth consumption, which made it perfect for microservices with demanding performance requirements. Serialization caused gRPC to have a slightly higher initial latency, but it held steady under high loads. Web applications work well with REST because of its simplicity and reliability under moderate loads, even though it is less efficient. However, for microservices, I recommend using gRPC, as it is more efficient and cost-effective in cloud environments.

Comparison

Example

The image above showcases a JSON object for a user named Martin, with a size of approximately 96 bytes due to its text-based structure, including field names and values like “favoriteNumber”: 1337 it is taking almost 20 bytes. This overhead highlights JSON’s inefficiency, as the need to store verbose field names increases data size significantly.

The image above displays a proto file defined using Protocol Buffers, representing the same user data (username: “Martin”, favoriteNumber: 1337, interests: [“daydreaming”, “hacking”]) in a compact binary format. Unlike JSON’s 96-byte size, this proto file reduces the data to approximately 32-33 bytes by using numerical tags instead of text field names, as shown in the byte breakdown. This smaller size not only saves memory but also minimizes bandwidth usage, making it ideal for high-performance scenarios like microservices. Additionally, Protocol Buffers offer faster encoding/decoding and schema validation, ensuring data consistency and efficiency, which makes them a superior choice over JSON for optimized applications.

The chart shows how many tasks gRPC and REST can handle per second. For small tasks, gRPC manages 25,800, while REST handles 12,450, making gRPC 107% better. For large 1MB tasks, gRPC does 2,350 and REST does 1,250, with gRPC being 88% better. The blue bars for gRPC are taller, showing it works faster than REST.

This chart measures how long tasks take in milliseconds, with lower time being better. For small tasks, gRPC takes 12.8 ms on average, while REST takes 24.5 ms, making gRPC 48% faster. For large 1MB tasks, gRPC uses 98 ms compared to REST’s 175 ms, a 44% advantage. The blue gRPC bars are shorter, proving it finishes tasks quicker.

Real-World Use Cases

1. Video Streaming & Entertainment (Netflix, YouTube, Gaming)

When you search for content or start a multiplayer game, multiple systems communicate:

Content recommendation engines
User preference databases
Real-time player/viewer data
Video quality optimization systems
gRPC enables lightning-fast coordination between these services

2. Ride-sharing & Financial Services (Uber, Banking Apps)

When you book a ride or make a payment, critical systems must work together:

Location tracking and route calculation
Payment processing and security verification
Real-time updates and transaction databases
Driver matching and account balance systems
gRPC ensures secure, high-speed communication between all components

3. E-commerce & Social Platforms (Amazon, Instagram, Google Services)

When you shop online or share content, numerous backend services coordinate:

Product inventory and search systems
Social feeds and notification engines
File storage and user authentication
Recommendation algorithms and checkout processes
gRPC manages the complex communication between these interconnected systems

Each example shows how gRPC acts as the “nervous system” connecting different parts of modern applications to deliver the fast, reliable experiences users expect.

Conclusion

Understanding gRPC and Protocol Buffers—A Modern Approach to Service Communication,” it’s clear that gRPC, powered by Protocol Buffers and HTTP/2, revolutionizes how services communicate in today’s distributed systems. Its ability to handle high-performance, low-latency interactions makes it a game-changer for microservices, real-time applications, and large-scale platforms like Netflix, Uber, and Google services.

By offering smaller, faster data serialization, robust security, and flexible streaming options, gRPC not only enhances efficiency and reduces costs but also ensures reliable and scalable communication across diverse languages and platforms. In conclusion, gRPC stands as an invisible yet indispensable backbone, delivering smoother, quicker, and more secure digital experiences that shape the future of modern applications.

gRPC Frequently Asked Questions

Q1: What exactly is gRPC in simple words?

A: gRPC is like a super-fast messenger that helps different computer programs talk to each other. Imagine it as WhatsApp for software—but much faster and more reliable.

Q2: Do I need to know programming to understand gRPC?

A: Not at all! You just need to know that it’s the technology making your apps faster. Like how you don’t need to understand how a car engine works to drive a car.

Q3: When to use gRPC over REST?

A: It depends on the use case. gRPC is better for high-performance, low-latency requirements, while REST is preferred for simpler, web-based integrations.

Q4: What protocols do gRPC and REST use?

A: gRPC uses HTTP/2, while REST typically uses HTTP/1.1 or HTTP/2, depending on the implementation.

Q5: When not to use gRPC?

A: Avoid using gRPC when browser compatibility is a priority or when simplicity and human-readable formats like JSON are required.

Q6: Does gRPC make my internet faster?

A: Not your internet speed, but it makes apps respond faster because they can communicate more efficiently. It’s like having a direct phone line instead of sending letters.

Q7: Is gRPC safe for my personal data?

A: Yes! gRPC has built-in security features. It’s like having a secure, encrypted phone call instead of shouting across a crowded room.

Q8: Will I notice if an app uses gRPC?

A: You’ll notice the benefits: faster loading, quicker responses, and a smoother experience. But you won’t see gRPC itself—it works invisibly in the background.

Q9: Is gRPC expensive?

A: For users, it’s free. For companies, it actually saves money because it uses fewer server resources and less internet bandwidth.

Code Examples

Example 1: Ordering Food Online

syntax = “proto3”;
service OrderService { rpc GetOrderStatus (OrderRequest) returns (OrderResponse) {} }
message OrderRequest { string item = 1; int32 quantity = 2; }
message OrderResponse { bool available = 1; string price = 2; string delivery_time = 3; }

Contributors:

Team Nodejs. : Shubham, Thanay, Venu Gopal, Saniya, Akash, Jayasree, Arvindh, Kiran, Sai Meghana and Ajay Kumar.

The post Understanding gRPC and Protocol Buffers—A Modern Approach to Service Communication appeared first on Welcome to Ahex Technologies.

What are the essential skills for Microservices developers?

marketing ahex — Tue, 27 Jul 2021 09:49:59 +0000

Microservices have been gaining tremendous popularity, and many developers have been working on them lately. This is a trend that has been bringing many changes into the daily lives of people. Skills that were considered niche in the earlier times have now become the need of the hour.

If you are looking forward to working on microservices or seeking a job as a microservice developer, then the blog is for you.

Since there is much hype about microservices, we have mentioned a few critical skills that micro developers need to work on to become successful in this field.

Here are the essential skills which microservices developers need:

1. Architecture Knowledge:

In simple words, microservices are architectural patterns. Therefore, it is always a better idea for microservices developers to be familiar with the different languages. This is because most of the stuff in microservices happens in these high-end languages. Thus making it essential to know in and out about these languages.

For microservices developers, it is pretty essential to understand the typical patterns of microservices. The basic concept is that the developers should be well-versed with practices because if they are not, then they will choose the wrong solutions. Having proper knowledge of the practices simplifies the work and increases the quality by 10x times.

2. Domain Modelling:

Even if one understands their architecture and patterns quickly, it is undoubtedly quite hard to succeed in no time when it comes to Microservices. It can be pretty challenging to split responsibilities among various parts of the system. All one needs to do is be amazing at domain modeling and understand how to assign blame.

One strategy is that one needs to draw more. Drawing with their team and other people involved in their project is a fantastic tool for fostering a better understanding of their domain. Being great at linking their domain and design is a valuable skill universally, especially for software developers.

3. DevOps and Containers

One of the unique ideas behind microservices is to work in the DevOps way. People need to take ownership of their service in almost all forms, be it writing code for use in production. Even if one is not planning to deploy in production, one should know how deployment is likely to look even if one is not deploying it.

There is no hiding here as one will have to become quite familiar with containers, Docker, Kubernetes, etc. the best part is that they can get Docker on their machine, and it is undoubtedly worth it. Besides containers, one needs to understand Queues, messaging, databases, some clouds, etc.

Even though it might seem like a lot of trouble, one doesn’t need to stress as several experienced colleagues in their team can help. Of course, no one is likely to become an expert overnight, but learning these technologies might be new to them if they weren’t exposed to the operation of any things.

4. Security:

As one might imagine, securing several things is way more challenging than securing one element. However, security concerns are in front of everyone’s minds when individuals work with monoliths with microservices.

When it comes to securing data at rest, the microservices have their way of securing configuration. But, above all, these are some elements where security cannot be compromised.

5. Testing:

Ideally, testing is one of the things that can be quite deficient in their productivity and success is undoubtedly having services that don’t fail regularly and don’t fulfill the contracts. People say that microservices are pretty tiny and look minor and less severe or business-like compared to substantial monolithic applications and some developers ignore the testing.

Above all, people shouldn’t miss it as they offer plenty of opportunities for creating amazingly tested and robust solutions, so one shouldn’t pass on it as it is way more than trivial, or unit tests aren’t likely to be the answer. One needs to include tests including:

Unit tests
Service / API test
End to End test of the integrated system

6. Continuous integration:

As mentioned earlier, end-to-end testing plays a crucial role. Still, with microservices, one needs to ensure that everything works perfectly, and they should also see microservices interact perfectly. One can go quite far when testing such challenging conditions in isolation.

One of the best ways to deal with the issue is to set up integration regularly whenever they merge with a problem; they need to set up the code to their master and deploy it to an integration environment where different tests tend to run.

7. Language

Ideally, the microservice architectural pattern isn’t likely to be associated with any programming language, but most tasks are done in Java. Above all, it is essential that anyone applying for any programming job needs to have skills in various languages; several staffing experts are specially trained and experienced to recognize a candidates’ Java skills by scanning their resume and deliverables they would have done in the past. If one’s past projects aren’t there for review or even if they are, then the hiring managers will likely use coding tests to verify these skills.

8. Back-End Development

As Microservices is most likely to be a distributed system, there are likely some challenges on the backend that would befuddle several developers. However, one’s familiarity with backend development will set them apart to solve software development challenges as they are experienced quickly.

DevOps is the newer way of working and is all set to shake up how we see the developers’ job. This is the perfect time for software developers to try their hands on something new and gain more significant insights.

With these essential skillsets, you can develop yourself as an advanced microservices developer.

The post What are the essential skills for Microservices developers? appeared first on Welcome to Ahex Technologies.

15 Best Practices for Building a Microservices Architecture

marketing ahex — Tue, 27 Jul 2021 09:49:48 +0000

Microservices Architecture is an evolving architectural pattern in which an application is designed and developed to collect small, autonomous, loosely connected services that communicate with one another.

In this thread, we will be grouping these best practices into categories that help in reflecting the progression of the different phases of SDLC (Software Development Life Cycle). These are some efficient tips, especially for the fresh adopters looking forward to transitioning integral to a microservice framework.

Here are 15 best practices for microservice success, which you should be aware of:

For organizing and arranging

Based on your requirements, determine if the microservices architecture is a good fit. Adopting a microservices architecture only because the big names are doing it is not a good reason. It would help if you examined your needs to determine where and how you might divide them into valuable functions. Make sure your application can be subdivided into microservices while still maintaining its basic functionality and operability.
Make sure everyone is on board with the plan. The transition from a monolithic architecture to microservices is a long and arduous process that affects more than just the development team. Therefore, stakeholders should examine the amount of time, money, and technical knowledge required to make the necessary infrastructure modifications.
Form microservices-focused teams. Teams should treat each microservice as though it were a separate application. Assign various microservices to various teams. This also necessitates that such teams possess the requisite skills and tools to create, deploy, and operate a service independently. Teams should be adaptable and large enough to conduct operations independently without wasting time talking.

When creating the microservice, keep the following in mind:

Make a clear distinction between your microservices and your business functions and services. You’ll be able to avoid creating microservices that are either too big or too little if you do this. If the former is the case, there are no advantages to employing the microservice architecture. The latter will result in a massive increase in operational costs that will outweigh any gains.
Create loosely linked services with excellent cohesion that cover a single constrained environment. A loosely connected service relies on other services as little as possible. To achieve high cohesiveness, the service’s design must adhere to the single responsibility principle, which states that it should fulfill only one primary purpose and execute it well. Finally, make your services domain-specific while still having internal domain details and domain-specific models. A Domain-Driven Design is achieved when a microservice supports a single-bounded context (DDD).
To communicate between services, use APIs and events. It is not a good idea for assistance to call each other directly. Instead, create an API gateway that manages authentication, requests, and answers for the services, as well as throttling. You may quickly redirect traffic from the API gateway to the updated version of your favor if you have an API gateway in place.
When designing a microservice architecture, keep security in mind. Adopt the DevSecOps approach as a recommended practice to provide a secure microservices framework. Because of their dispersed structure, microservices are more vulnerable to attack vectors in general. As a result, compared to a monolithic framework, provisioning security requires an entirely different approach—which is why DevSecOps is ideal.
Our Services are Laravel Developement | Mean Stack Development

When it came to creating the microservice

Each service should have its version control strategy. For simplicity of access provisioning and clean version control logs, each service should have its repository. This is especially useful if you are making a modification that could potentially break other services.
The development environment should be the same on all machines. Set up the service’s development environment as virtual machines to allow developers to adjust the framework and get started swiftly.
Make the service endpoints you are exposing backward compatible. You don’t want to annoy any of your callers. To do so, use stringent contract tests to guard against unexpected changes. Backward compatibility is also possible thanks to the API calls made in response to each user query. This allows your company to develop production-ready applications more quickly.

For the storage and administration of data

Each microservice should have its database or data storage. Choose a database that meets your microservice’s requirements, tailor the architecture and storage to the data it will hold, and utilize it only for that microservice. This is still one of the most critical aspects of developing a robust microservice framework. The maintainance of each service is separate while cooperating with other services via a service mesh.

For Deployment and Hosting

Separately deploy your microservices. This saves time when communicating with numerous teams during routine maintenance or upgrades projects. You also don’t want a single service to consume an excessive amount of resources, causing other services to suffer as a result. This helps with fault tolerance and avoids a full-blown outage by isolating each microservice from problems in other components.
Make your microservices containerized. Containers and microservices are frequently used together. Individual services can be deployed and managed individually with containerized microservices, without affecting services hosted on other containers. Containers also provide platform independence and interoperability, which are ideal for microservice architecture goals.
Create a separate build for your microservices and use automation to deploy them.
Enhancing efficiency through automation is an important part of implementing the DevOps methodology. You can automate DevOps workflows by enabling Constant Integration and Constant Delivery (CD/CI) with automation solutions like Jenkins.

For operations and maintenance:

Use an integrated system for monitoring and logging. An integrated logging system ensures that all microservices send logs in the same format while saving records separately for each of them. This, rather than a monolithic approach, allows for quicker error handling and root cause analysis.

Conclusion:

Microservices make it easier to maintain applications, but making the switch to a microservices design is complex. Although the methodology to adopt microservices varies depending on the use case, some basic best practices are constant.

The post 15 Best Practices for Building a Microservices Architecture appeared first on Welcome to Ahex Technologies.