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Golang-Beego Framework and its Applications

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4 minutes read

There are usually some concerns when implementing a new technology such as what would happen if we get stuck somewhere and end up wasting our time and effort. It’s possible that we’ll have to go back to the original solution. We faced similar issues a year ago but after long and in-depth research, we found a solution that was more secure and safe-Golang and its frameworks. The way it is documented is really helpful. However, we were quite certain that we would not find all the answers online which was a challenge we accepted in the spirit of Lailah Gifty Akita’s renowned adage, “THERE IS ALWAYS A SOLUTION TO EVERY CHALLENGING SITUATION.”

This blog mainly talks about Golang-Beego framework and its applications. We’ll be discussing how Golang is used in Web Development and why most of the developers shift from Python, Node, or other languages to Go.

Let’s understand the Golang framework in order to know how it works.

What is Golang?

First appearing in 2009, Golang (popularly known as Go) quickly gained popularity among developers, becoming a preferred language for more than 90% of users. Its ancestor languages are C and C++ programming languages which is quite evident by looking into its syntax and compiling features. 

Primarily used for backend development, Go has 4 other use cases- 

  1. Cloud & Network Services
  2. Command-line Interfaces (CLIs) 
  3. Web Development
  4. Development Operations & Site Reliability Engineering. 

Here are some of the main features of Golang that make this framework the preferred choice for developers:

1. Simplicity 

Go syntax is straightforward as shown here and its compiler can smell trouble and raise errors during the build process — that is before the program is run.

Go Syntax in Golang-Beego Framework

The flexibility, usability, and incredibly cool concept behind Go (how it handles native concurrency, garbage collection, and safety+speed) are some of the features that are quite useful for developers.

2. Speed

Built-in concurrency ( Goroutines and Channels ) is one of the main reasons for its high performance. Analyzing this stack overflow will allow us to estimate its speed.

“I may have implemented this incorrectly because the results do not make sense. I have a Go program that counts to 1000000000; it finishes in less than a second. On the other hand, I have a Python script; it finishes in a few minutes. Why is the Go version so much faster? Are they both counting up to 1000000000 or am I missing something?” 

If you’re still unsure about the speed, here’s a comparison between Go, Node JS, Java, and Python that will help in gaining more clarity about its usage:

My Device Specification:

Device name- LAPTOP-Q8U9LM8P

Processor- Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz   2.10 GHz

Installed RAM- 16.0 GB (15.6 GB usable)

System type- 64-bit operating system, x64-based processor

N-body print:

Source Time To Count 

Go: 6.34   seconds

Python3: 545.25 seconds

GO

Output:

Factorial   Time To calculate factorial

10000       0.008 seconds

50000       0.506 seconds

100000      3.154 seconds

500000      82.394 seconds

1000000     284.445 seconds

NodeJS (Javascript )

Output:

Factorial   Time To calculate factorial

10000       0.113 seconds

50000       1.974 seconds

100000      22.730 seconds

500000      477.534 seconds 

1000000     1175.795 seconds 

Python

Output:

Factorial   Time To calculate factorial

10000       0.046 seconds

50000       1.187 seconds

100000      6.051 seconds

500000      388.607 seconds 

1000000     813.725 seconds 

JAVA

Output:

Factorial   Time To calculate factorial

10000       0.064 seconds

50000       1.607 seconds

100000      5.363 seconds

500000     141.076 seconds

1000000     585.868 seconds

3. Safety:

GARBAGE Collector:

Go prefers to allocate memory on the stack, so most memory allocations will end up there. This means that it has a stack per goroutine and when possible it will assign variables to this stack.

Golang mark and sweep garbage collector has two phases: Mark, and Sweep. First, it will mark all unused and used variables, then sweep unused ones.

The statistics and the description above suggest why one should work with Go. Golang framework that is best for creating APIs also accelerates and facilitates development.

Why do we use Beego Framework?

Be it Go or Beego, both are fantastic for developing high-performance REST APIs. 

Beego is a “battery included” framework, with built-in tools ( bee tool ), ORM, and libraries compared with other frameworks like Gin-gonic which is not a “battery included” type and contains most essential libraries and features not good for server-side features.

Beego uses a typical Model-View-Controller (MVC) framework which has turned out to be good for people (like us) who work on Python-Django before and Beego is quite similar.

Why do we use Beego Framework?

Conclusion: 

That’s how we started our application with Golang and Beego. We worked on PDF, Image handling with ImageMagick, AWS-SNS, AWS-SES SMTP, IVR calls, Fax, Digital signatures, Reports generation with ORM, and many more. And we haven’t found any blockage while working with third-party features like Twilio or AWS. It is really simple to write code on Golang as mentioned by their creators. There are certain challenges in using this framework but there are solutions as well. We really enjoyed it working on this framework. BEST OF LUCK for your upcoming Golang applications.

About the Author

Piyush Raj graduated from IIT Kharagpur in Chemical Dept. He started his career with ML and AI, and now works at Mantra Labs as a software developer. In his free time, he likes to explore new paths in the real world or on paper through traveling and painting.

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Why Netflix Broke Itself: Was It Success Rewritten Through Platform Engineering?

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Let’s take a trip back in time—2008. Netflix was nothing like the media juggernaut it is today. Back then, they were a DVD-rental-by-mail service trying to go digital. But here’s the kicker: they hit a major pitfall. The internet was booming, and people were binge-watching shows like never before, but Netflix’s infrastructure couldn’t handle the load. Their single, massive system—what techies call a “monolith”—was creaking under pressure. Slow load times and buffering wheels plagued the experience, a nightmare for any platform or app development company trying to scale

That’s when Netflix decided to do something wild—they broke their monolith into smaller pieces. It was microservices, the tech equivalent of turning one giant pizza into bite-sized slices. Instead of one colossal system doing everything from streaming to recommendations, each piece of Netflix’s architecture became a specialist—one service handled streaming, another handled recommendations, another managed user data, and so on.

But microservices alone weren’t enough. What if one slice of pizza burns? Would the rest of the meal be ruined? Netflix wasn’t about to let a burnt crust take down the whole operation. That’s when they introduced the Circuit Breaker Pattern—just like a home electrical circuit that prevents a total blackout when one fuse blows. Their famous Hystrix tool allowed services to fail without taking down the entire platform. 

Fast-forward to today: Netflix isn’t just serving you movie marathons, it’s a digital powerhouse, an icon in platform engineering; it’s deploying new code thousands of times per day without breaking a sweat. They handle 208 million subscribers streaming over 1 billion hours of content every week. Trends in Platform engineering transformed Netflix into an application dev platform with self-service capabilities, supporting app developers and fostering a culture of continuous deployment.

Did Netflix bring order to chaos?

Netflix didn’t just solve its own problem. They blazed the trail for a movement: platform engineering. Now, every company wants a piece of that action. What Netflix did was essentially build an internal platform that developers could innovate without dealing with infrastructure headaches, a dream scenario for any application developer or app development company seeking seamless workflows.

And it’s not just for the big players like Netflix anymore. Across industries, companies are using platform engineering to create Internal Developer Platforms (IDPs)—one-stop shops for mobile application developers to create, test, and deploy apps without waiting on traditional IT. According to Gartner, 80% of organizations will adopt platform engineering by 2025 because it makes everything faster and more efficient, a game-changer for any mobile app developer or development software firm.

All anybody has to do is to make sure the tools are actually connected and working together. To make the most of it. That’s where modern trends like self-service platforms and composable architectures come in. You build, you scale, you innovate.achieving what mobile app dev and web-based development needs And all without breaking a sweat.

Source: getport.io

Is Mantra Labs Redefining Platform Engineering?

We didn’t just learn from Netflix’s playbook; we’re writing our own chapters in platform engineering. One example of this? Our work with one of India’s leading private-sector general insurance companies.

Their existing DevOps system was like Netflix’s old monolith: complex, clunky, and slowing them down. Multiple teams, diverse workflows, and a lack of standardization were crippling their ability to innovate. Worse yet, they were stuck in a ticket-driven approach, which led to reactive fixes rather than proactive growth. Observability gaps meant they were often solving the wrong problems, without any real insight into what was happening under the hood.

That’s where Mantra Labs stepped in. Mantra Labs brought in the pillars of platform engineering:

Standardization: We unified their workflows, creating a single source of truth for teams across the board.

Customization:  Our tailored platform engineering approach addressed the unique demands of their various application development teams.

Traceability: With better observability tools, they could now track their workflows, giving them real-time insights into system health and potential bottlenecks—an essential feature for web and app development and agile software development.

We didn’t just slap a band-aid on the problem; we overhauled their entire infrastructure. By centralizing infrastructure management and removing the ticket-driven chaos, we gave them a self-service platform—where teams could deploy new code without waiting in line. The results? Faster workflows, better adoption of tools, and an infrastructure ready for future growth.

But we didn’t stop there. We solved the critical observability gaps—providing real-time data that helped the insurance giant avoid potential pitfalls before they happened. With our approach, they no longer had to “hope” that things would go right. They could see it happening in real-time which is a major advantage in cross-platform mobile application development and cloud-based web hosting.

The Future of Platform Engineering: What’s Next?

As we look forward, platform engineering will continue to drive innovation, enabling companies to build scalable, resilient systems that adapt to future challenges—whether it’s AI-driven automation or self-healing platforms.

If you’re ready to make the leap into platform engineering, Mantra Labs is here to guide you. Whether you’re aiming for smoother workflows, enhanced observability, or scalable infrastructure, we’ve got the tools and expertise to get you there.

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