DEV Community: An Architect

The First Principles of Scalable Software Design

An Architect — Mon, 14 Jul 2025 07:13:17 +0000

Think like an engineer. Design like a physicist.

The problem is never the system. The problem is the assumptions.

When we talk about scalable software, we often rush into Kubernetes clusters, load balancers or microservices. But scalability is not a checklist of tools — it is a mental model. And one of the sharpest mental models in our toolkit is First Principles Thinking.

In this article we will not talk about infrastructure but how to think when designing systems that don't collapse under success.

What Are First Principles in Software Design?

In physics, a "first principle" is a fundamental truth — one that cannot be deduced further.

In software, first principles are the non-negotiables — truths that remain constant regardless of frameworks, tech stacks or company-level(scale).

Let's decode some of them.

Principle #1: Complexity is a Cost — Not a Feature

Every abstraction leaks. Every extra layer introduces mental overhead. If you're not paying in compute, you're paying in cognitive load.

When designing systems, we are often tempted to make things "future-proof" — but complexity rarely scales well. The most scalable systems are clear, not clever and most simple. Have worked on many software some got rewrite within first 100 days while some worked for more than 8 years without major rewrites. These all coached me one thing that simple slays longer.

New lens to adopt:
Don't ask, "Can we build it this way?"
Ask, "Can someone else maintain this six months from now?"

Principle #2: Latency Compounds Faster Than You Think

Imagine a function call takes 200ms. You add a few service boundaries. Suddenly your user is waiting 2 seconds. That's not scale — that's sludge.

First principle: Every network hop is a cost center.
Design approach: Minimise the number of decisions and dependencies in the critical path.

Bonus Thought: Think of every added dependency as a liability on your performance balance sheet.

Principle #3: Scalability Begins at the Interface

Your internal APIs aren't just contracts. They're commitments to the future.

Will they gracefully handle increased load?
Will they evolve without breaking consumers?
Can they be understood without tribal knowledge?

Here's a trick from Amazon's internal playbook: Design every service interface as if it will be public one day. It forces clarity and resilience by default.

Principle #4: Load Isn't the Enemy — Unpredictability Is

Scaling isn't about handling more — it's about handling unpredictable spikes with predictable behavior.

That's why idempotency, graceful degradation and circuit breakers aren't just implementation details — they're architectural mindset shifts.

A truly scalable system doesn't fail dramatically.
It fails softly — and recovers fast.

Principle #5: Local Decisions Must Align with Global Goals

A team optimises their service with aggressive caching. Another team, unaware, writes a dependent service that expects real-time data. Congrats — you've scaled chaos.

Scalability doesn't live in silos.
Every micro-decision should map back to macro-outcomes: latency goals, fault tolerance, observability, etc.

Pro Tip: When in doubt, align every design decision to SLAs, not just business logic.

So… What Does This All Mean?

We often approach scalability as a reaction to growth. But first principles thinking flips the script:

Don't chase best practices. Define timeless truths.
Don't design for scale. Design to make scaling trivial.
Don't abstract problems. Understand them.

Wrapping Up!

The best software designs aren't scalable because they're complex.
They're scalable because they're built from unshakable foundations.

If you're designing systems today, take a moment to strip away everything that's optional. What you're left with — that's your first principle.

Now, scale from there.

How to Design a Write-Heavy System: A Beginner-Friendly Guide You’ll Want to Bookmark

An Architect — Tue, 29 Apr 2025 17:13:26 +0000

When designing a system that handles a lot of incoming data—like transactions, logs, messages or orders—your priority is not reading that data, but writing it fast and efficiently. These systems are called write-heavy systems.

This guide breaks down the process in a way that anyone can understand, with an analogy that sticks. Whether you're a beginner building your first backend or a seasoned engineer setting up a scalable pipeline, this is your go-to checklist.

Imagine Your System is an Ice Cream Shop

In our analogy:
Customers = users
Orders = write operations (inserts/updates)
Menu views = read operations (queries)

In a write-heavy system, people are mostly placing orders—not just browsing the menu.

Let's walk through how to set up a system that can take those orders quickly and reliably.

Step 1: Understand What You're Handling

Before choosing databases or tech stacks, ask yourself:

What kind of data is being written? (e.g., chat messages, transactions, logs)

How frequently is data written?

Do you need to store it forever or just for a short time?

This helps you define the structure and volume of your database.

Step 2: Use Bins, Not Drawers

Imagine throwing order slips into a big bin, rather than neatly organising them right away.

Choose databases that handle high write throughput:

✅ PostgreSQL with partitioning
✅ MongoDB for flexible schemas
✅ Cassandra or DynamoDB for large-scale writes

✅ ClickHouse or InfluxDB for time-series or logs

Avoid too much normalisation or constraints—they slow down writes.

Step 3: Add a Queue at the Counter

If users come in waves, you don't want to turn them away.

Use message queues like:
Kafka
RabbitMQ
Amazon SQS

These act like waiting lines, temporarily holding data before it hits the database. Queues absorb spikes and make sure nothing gets lost.

Step 4: Delay the Clean-Up

Don't try to organise everything while you're slammed with orders.

Instead:
Write now
Clean up later (during off-peak times)
Use batch jobs or stream processing (e.g., Apache Spark, AWS Lambda) to:

Summarise
Archive
Transform

This keeps the system responsive during busy hours.

Step 5: Add More Counters (Scale Horizontally)

If one counter isn't enough, open more.

That means:
Sharding your database (split data across servers)
Replicating writes to multiple nodes
Using load balancers

Scaling horizontally helps maintain performance as load increases.

Step 6: Prefer Logs Over Rewrites

Instead of updating the same data repeatedly, log every change.

Benefits:
Faster writes
Easy rollback or reprocessing
Clear audit trail

Log-based architectures (event sourcing, write-ahead logs) are great for write-heavy use cases.

Step 7: Always Save a Timestamp

Add a created_at or written_at field to every piece of data.

It helps you:
Order events
Debug issues
Run analytics later

Timestamps are simple but powerful.

Bonus: What to Avoid in Write-Heavy Systems

❌ Heavy indexing on every field (slows down inserts)
❌ Complex joins on write paths
❌ Overuse of transactions
❌ Writing and reading from the same table at the same time without planning

TL;DR – Your Write-Heavy System Design Checklist

Step Action
1️⃣ Understand your data types and write frequency
2️⃣ Choose a write-optimized database
3️⃣ Add message queues to absorb spikes
4️⃣ Delay processing with batch jobs
5️⃣ Scale horizontally (shards, replicas)
6️⃣ Log all writes instead of overwriting
7️⃣ Add timestamps to every write

Building a system that handles tons of data?
Save this post NOW and share it with your team—because your next app deserves to scale from Day 1.
💬 Got questions? Drop them below and let's design it right together!

For SEO not to read
write-heavy system design
database design for high write load
scalable backend for write-intensive apps
write-optimized database architecture
backend system design checklist

The Great Microservice Delusion: How We Broke the Monolith and Our Will to Live

An Architect — Fri, 04 Apr 2025 07:22:39 +0000

It started, as most tech disasters do, with a meeting.

Somewhere in a glass-walled room full of sticky notes and ambition, someone declared, "Let's break up the monolith!" Cue the slow clap. Champagne may or may not have been popped. Diagrams were drawn. Visions of Netflix-scale greatness danced in our heads.

Six months later, we had 42 microservices, three of which were mysteriously called auth-service, none of which agreed on what a user was, and our deployment pipeline looked like a Rube Goldberg machine built during a nervous breakdown.

Congratulations. We had achieved "distributed hell".

This article is for every brave soul who has ever uttered the words "We should go microservices" without first updating their life insurance policy. It's also for those who've been burned and are now huddled in the glow of a monolithic comeback. Let's talk architecture—real talk.

The Monolith: Villain or Misunderstood Introvert?

Let's start with the punching bag of modern architecture: the monolith. It's big, it's old and it's probably written in Java 8 or another decade old version of any language. Like that one drawer in your kitchen that has batteries, duct tape and a mysterious key to a forgotten door—it holds everything.

But you know what? That drawer works. It's reliable. It has character.

The monolith gets a bad rap because of its size, but size isn't the enemy—complexity, without boundaries is. A well-structured monolith can outperform a poorly planned microservice mess every single day, and you won't need a PhD in Kubernetes just to run tests.

Lesson: If your monolith is a mess, splitting it into smaller messes won't help. That's just distributing dysfunction.

Microservices: Now with More Opportunities to Fail!

Ah, microservices. The siren song of scalability. The dream of team autonomy. The promise of being "cloud-native", whatever that means this week.

And then reality hits.

That one service that only runs on Tuesdays for no discernible reason.

The "cascading failure" where one service times out, causing another to retry until everything catches fire.

CI/CD pipelines so complex they require a wiki, a sherpa and emotional support.

We promised agility and we got fragility.

Microservices can work, but they demand:

Discipline.
Monitoring.
Observability.
Contracts between services.
Governance. (Yes, I know that word makes developers itchy, but suck it up.)

Analogy Time: Microservices are like kids. Everyone wants one until they realise you have to feed them, teach them and make sure they don't punch each other over shared toys (databases).

Service Boundaries: Or, How to Play API Jenga with Your Sanity

Here's a fun game: Ask your team to define the boundaries of the user-service. Watch as the room descends into philosophical debate about the nature of identity, ownership and whether storing profile pictures counts as a "core concern".

One of the greatest sins in microservices is drawing boundaries based on your org chart. Just because there's a "Payments Team" doesn't mean "payments" deserves its own service or ten services.

Boundaries should be based on domain, not on team silos. If you need a refresher, look into Domain-Driven Design. Or just remember this rule: If two services keep shouting across the fence to talk to each other, maybe they shouldn't be neighbours.

The Infrastructure Hangover

So after a month long debate if you've got your shiny microservices. Now enjoy managing:

Network latency
API gateways
Circuit breakers
Load balancers
TLS certificates
Secrets management
Logging across services
Distributed tracing
Versioning
Retry storms
Orchestration
Service discovery
And the occasional DNS issues will keep popping-up just to keep you humble.

If that list made your eye twitch, you're not alone. Welcome to the microservices tax. It's the price you pay for freedom. Like moving out of your parents' house only to realise rent is due and laundry doesn't do itself.

Reality Check: You don't need Kubernetes if you only deploy once a month. Sometimes an EC2 instance and some bash scripts are all you need to sleep at night.

Conway's Law: The Puppet Master of Your Architecture

Every architecture is a reflection of the team that built it. If your teams don't talk to each other, guess what? Your services won't either. Or worse - they'll miscommunicate, creating a distributed gossip chain of outdated data and failed expectations.

Want better architecture? Build better teams.

Cross-functional teams.
Shared context.
Engineers who understand that backend is not a kingdom and frontend is not a dumping ground.

And for heaven's sake, get your PMs to stop promising features that need five services to handshake like secret agents at a Cold War summit.

Wrapping Up: A Monolith by Any Other Name...

At the end of the day, architecture is about trade-offs. There are no silver bullets — only silver shrapnel flying in different directions.

Monoliths aren't evil. Microservices aren't magical. What matters is why you're building what you're building — and whether your team can actually operate it without sacrificing their evenings, their mental health or their will to write code ever again.

So before you reach for that service splitter, ask yourself:

Are we solving a problem or running from one?
Are our teams mature enough to handle the complexity?
Is this architecture helping us deliver faster or just feel fancier?

Because remember: Software architecture is like parenting. If you can't manage one, you're probably not ready for twins.

Call to Action:

If this article made you laugh, nod or throw your coffee across the room in recognition — good. Now go take a walk, grab a marker and erase half the services from your architecture diagram. Your future self will thank you.

And if you've got battle stories from your own architecture war zone, drop them in the comments. Misery loves company — and sometimes that company knows how to fix your deployment pipeline.

Want more salty wisdom, spicy rants and architecture truths wrapped in wit? Subscribe to the newsletter. It's cheaper than therapy and twice as fun.

My Main Learnings Architecting a Digital Payments Banking Platform

An Architect — Fri, 24 Jan 2025 11:19:43 +0000

Building a digital payments banking platform wasn’t just another engineering milestone; it’s a test of resilience, innovation and the ability to marry technical excellence with user-centric design. I thank God for providing me the opportunity to architect such a platform that powers seamless account management, bill payments, FasTag management and money transfers while meeting stringent regulatory requirements.

Here, I’ll share my main learnings from this journey, which taught me invaluable lessons in engineering, leadership and collaboration.

1. Start with Security by Design

In the banking and payments sector, trust is non-negotiable. People can pardon you for anything but not if their penny moved from one account to another without their permission. Thus one of our first priorities was embedding security into every layer of the system "from architecture to code".

Here are a few steps I found essential:

Data Encryption: Every data flow was secured using end-to-end encryption, ensuring sensitive information was protected both in transit and at rest.

Authentication Protocols: We adopted JWT with mobile OTP validation.

Threat Modeling: Anticipating attack vectors through rigorous threat modeling saved us from potential vulnerabilities later in production.

Key Takeaway: Security isn’t a feature you add later. It must be an inherent part of your design process.

2. Scalability and High Availability are the Backbone

When you’re dealing with financial transactions, downtime is unacceptable. From the outset, our architecture needed to handle millions of transactions per second (TPS) with zero compromise on reliability. Achieving this required:

Distributed Systems: We designed for distributed databases and replicated services across multiple geographic regions to minimise latency.

Failover Mechanisms: Active-active clustering ensured that even if one data center failed, another could seamlessly take over.

Auto-Scaling: By leveraging Kubernetes for container orchestration, we could dynamically scale resources up or down based on transaction load.

Key Takeaway: Plan for scale from day one. Assume your traffic will multiply exponentially and design systems that can handle it without flinching.

3. Compliance is a First-Class Citizen

Navigating the labyrinth of regulatory requirements was one of the most challenging aspects. From PCI DSS for payment processing to RBI guidelines (specific to India), every decision had to align with compliance mandates. This wasn’t just about ticking boxes it was about:

Data Residency Rules: Ensuring that sensitive data was stored within the prescribed jurisdiction and should always be saved in encrypted format.

Audit Trails: Building transparent logging systems that recorded every action for traceability.

Continuous Monitoring: Implementing tools to monitor for compliance violations in real-time.

Key Takeaway: Compliance is not a roadblock; it’s a safeguard for both the business and its users. Integrate it early and iterate often.

4. User Experience Drives Adoption

The best technical solutions mean little if they’re frustrating to use. We invested heavily in understanding user behavior and crafting a platform that delivered on simplicity and speed. Some strategies included:

Seamless Onboarding: Using minimal input fields and leveraging e-KYC (electronic Know Your Customer) processes reduced onboarding time by 70% and allowed the most remote customer to create their bank account with us.

Real-Time Feedback: Users were informed of errors instantly, improving trust and reducing frustration.

Mobile-First Design: Given the growing dominance of mobile users, we optimised every interaction for small screens without compromising functionality.

Key Takeaway: A digital platform succeeds only if it solves real user problems in a frictionless way.

5. Collaboration Between Cross-Functional Teams is Essential

Building this platform wasn’t a solo act; it required collaboration between product managers, legal teams, UX designers and of course, engineers. Here’s what worked:

Daily Syncs: Daily stand ups helped us to keep track of the work progress, though we hated it a lot when first implemented.

Weekly Syncs: A clear cadence of cross team meetings kept everyone aligned on priorities.

Transparent Roadmaps: Engineering, product and compliance teams co-created roadmaps to ensure realistic timelines.

Rapid Prototyping: Testing ideas early through mockups or proof-of-concepts reduced back-and-forth and ensured stakeholder buy-in. I thank the strategy and tag-line of our new CEO, “New feature release, everyday!”.

Key Takeaway: Engineering excellence thrives in a culture of open communication and cross-functional collaboration.

6. Monitoring and Observability Cannot Be Afterthoughts

Even the most robust systems can fail, but the key is to detect and fix issues before they impact users. Observability was a cornerstone of our platform and we achieved this through -

Real-Time Dashboards: Tools like Grafana and Prometheus provided live insights into transaction speeds, error rates and system health. Displaying these graphs on large screens helped us to track even a tiny dip and fix them fast.

Automated Alerts: Proactive notifications for anomalies allowed us to resolve issues before they escalated.

Post-Mortem Culture: Every incident was treated as a learning opportunity, with detailed root cause analyses and actionable improvements.

Key Takeaway: Building a resilient system means preparing for the worst-case scenario and learning from failures.

7. Technical Debt Management is Crucial for Long-Term Success

As with any large-scale project, trade-offs were inevitable. However, consciously managing technical debt helped us avoid future bottlenecks. For example:

Debt Registers: We maintained a backlog of known trade-offs and reviewed them regularly to decide when they needed resolution.

Refactoring Cycles: Allocating dedicated sprints for refactoring ensured we didn’t compromise long-term maintainability.

Modular Architecture: Designing for modularity allowed us to replace or upgrade individual components without reworking the entire system.

Key Takeaway: Accept that technical debt will exist but never let it pile up unchecked.

8. Investing in the Team is the Best ROI

Finally, none of this would have been possible without the incredible team I had the privilege to work with. As a leader, I focused on -

Up-skilling Engineers: Organising regular training sessions on security, cloud architecture and performance optimisation.

Encouraging Ownership: Empowering team members to make decisions and take accountability fostered innovation and motivation.

Recognising Contributions: Celebrating wins big or small kept morale high and built a culture of appreciation.

Key Takeaway: The success of any system is directly proportional to the passion and skill of the team behind it.

Conclusion

Architecting a digital payments banking platform was a journey that tested every facet of my experience as a software architect. It reinforced the importance of security, scalability, user-centric design, compliance and collaboration. Most importantly, it taught me that no challenge is insurmountable with the right mindset and team.

Whether you’re embarking on a similar project or simply looking for inspiration in solving complex problems, I hope these learnings resonate and guide you in your endeavours. After all, in software architecture, the true measure of success isn’t just the system you build, it's the value it delivers to the people who use it.

React Rookie to Rockstar: My 10x Proficiency Hack (You Won't Believe #5!)

An Architect — Thu, 14 Dec 2023 11:53:05 +0000

Level Up Your React Skills: 10 Tips to Become a Pro

Tired of feeling like a React rookie? Well, fear not! This guide unlocks the secrets to 10x-ing your React proficiency and becoming a coding champion.

1. Stay Updated, Be the Update Master:

React JS evolves faster than your weekend plans, so staying ahead of the curve is crucial. Dive into the official React blog and social media for the latest scoops on new features, security updates, and upcoming changes. Bonus points for joining online communities like Stack Overflow and Reddit's r/reactjs, where you can connect with fellow developers and decode the mysteries of each update.

2. Master the Fundamentals:

Building a solid foundation is key to React mastery. Don't just dabble, deep-dive into core concepts like components, state management, props, and the virtual DOM. The official React documentation is your best friend, filled with tutorials, examples, and everything you need to build your React fortress. To solidify your knowledge, consider online courses, workshops, and practical projects – think of it as React boot camp!

3. Practice Makes Perfect (and Powerful):

Just like your biceps, your React skills need regular workouts. Take on real-world projects that put your newly acquired knowledge to the test. Websites like LeetCode, HackerRank, and Codewars offer a buffet of React-specific challenges to keep your coding muscles toned.

4. The React Docs: Your BFF:

This comprehensive guide is your React bible. From basic concepts to advanced techniques, it's packed with explanations, code samples, and real-world applications. Bookmark it, refer to it constantly, and let it be your guiding light throughout your React journey.

5. Join the React Tribe:

The React community is a vibrant hub of knowledge and support. Dive into forums like Stack Overflow and Reddit's r/reactjs to connect with other developers, share experiences, and pick up valuable tips from the pros. Remember, knowledge shared is knowledge multiplied!

6. Design Patterns: Your Secret Weapons:

Design patterns are like pre-built blueprints for solving common programming problems. Mastering React design patterns like compound components, render props, and higher-order components (HOCs) will help you write cleaner, more maintainable code, and build better applications faster.

7. State Management: Master the Flow:

Understanding state management is like learning the secret language of React. By mastering libraries like React Context API, MobX, and Redux, you'll build more efficient, scalable, and maintainable applications. Think of it as unlocking the full potential of your React code.

8. Embrace the Ecosystem:

The React universe is vast and bursting with tools, libraries, and frameworks to empower you. Explore the React ecosystem to discover tools that boost your productivity and optimize your workflow. It's like finding the perfect power-ups for your React journey!

9. Code Cleanliness: The Developer's Mantra:

Writing clean, maintainable code is the mark of a true coding ninja. Follow best practices like descriptive variable names, modular code, and clear comments to make your React code easy to read, understand, and improve even years down the line.

10. Debug Like a Boss:

Bugs are inevitable, but fearing them is a rookie mistake. Hone your debugging skills with tools like Redux DevTools, Chrome DevTools, and React Developer Tools. Remember, debugging is a superpower – use it wisely to conquer those pesky bugs!

So, there you have it! These 10 tips are your roadmap to React mastery. Grab your coding sword, embrace the learning journey, and watch your React skills soar!

Bonus Tip: Don't forget to have fun! Learning React should be an enjoyable journey, so celebrate your progress, experiment, and don't be afraid to make mistakes. Remember, the best way to learn is by doing, and the React community is always there to support you.

Conclusion:

Mastering React is a journey, not a destination. Embrace continuous learning, leverage the vibrant community, and push your boundaries. The future of web development awaits, and you're ready to build it or probably the one to create a new one, who knows?

xx
Anks
JavaScript Rockstar

Auth2 Explained: The Essential Guide for Developers and Architects

An Architect — Fri, 08 Dec 2023 17:53:24 +0000

What is Auth2?

Auth2, also known as OAuth 2.0, is an industry-standard authorization system that allows a website or application (client) on behalf of a user to access resources hosted by another website or application (resource server). It provides secure delegated access without requiring the client to store or expose the user's credentials.

Brief History

Released: OAuth 2.0 was first released in 2010 as a replacement for OAuth 1.0.
Alternatives: Prior to Auth2, solutions such as SAML and Basic Authentication were used, but they had limitations like complexity, security issues, and a lack of flexibility.

Key Features:

Security: Securely grants access to resources without sharing user credentials.
Simplicity: Easier for developers to implement compared to other authorization protocols.
Flexibility: Supports various authorization flows for different applications and devices.
Widely adopted: Used by major websites and applications like Google, Facebook, and Twitter.

For any architect, most crucial thing is to decide the best alternatives for their solutions. So here is the basic idea when to use one over other -

SAML: This protocol is ideal for large organisations with complicated security needs and the need for SSO across several apps.

OpenID Connect: This is appropriate for online and mobile apps that require easy authentication and authorization as well as quicker integration.

Advantages of Auth2:

Improved security: No need to store or share user credentials directly.
Ease of Use: Simpler implementation for developers and a better user experience.
Wide Adoption: Most major online services and apps support widespread adoption.
Scalability: Easily handles huge amounts of authentication requests.

Limitations of Auth2:

Vulnerable to attacks: Auth2, like every protocol, is vulnerable to attacks if not implemented appropriately.
Limited control over user data: Clients have limited control over user data obtained through Auth2.
Complexity for certain scenarios: Certain use cases may necessitate further configuration or customisation.

We use various preventions to avoid Vulnerability assaults but that is quite long to mention here, I can write a whole blog on that if needed let me know.

Conclusion

Auth2 has evolved as the main online authorization standard, providing a combination of security, convenience, and flexibility. Its extensive use and simplicity of integration make it an invaluable tool for both developers and users. However, it is critical to understand its limits and put suitable security measures in place to prevent such risks.

Mastering Micro Frontends: Best Practices, Pitfalls to Avoid, Tools and Scaling Strategies

An Architect — Fri, 03 Nov 2023 15:33:04 +0000

Sorry guys, I was little busy in other things could not post for a while. Now those things are sorted so back here.

When we are talking about the series of designing software architecture, how can we miss the micro frontend. The term seems derived from the micro service architecture, which we had already discussed. Another reason of picking micro frontend architecture is I have started first time on this around 5 years back in late 2018 [Creating my small codes in vanilla JS to provide cross JS library and framework support; being little late to join the group].

Micro frontends have gain a good popularity as a solution to improve frontend application's modularity, maintainability and scalability. This architectural approach enables teams to work independently on distinct areas of a frontend application, making huge and complicated codebases easier to manage and faster to deploy. However, like with any technology, there are best practises, problems and tools to help you get the most out of micro frontends.

In this blog article, we will look at the DOs and DON'Ts of micro frontends, provide some tools for creating a repository of micro frontends and talk about techniques for scaling and monitoring your micro frontend architecture.

The DO's of Micro Frontends

Most of the DOs are common like other paradigms of programming still, I am mentioning them as a few of you might be setting up this as your first project.

1. Decompose Wisely

Divide your application into reasonable, self-contained chunks, but don't go overboard. Micro frontends should be narrow in scope and self-contained.

2. Consistent UI

Maintaining a consistent user interface and user experience across micro frontends is essential. To achieve visual harmony, use design systems and style guidelines.

3. Deployment Independence

Each micro frontend should be deployable separately, allowing for more frequent and quicker changes.

4. Cross-Team Collaboration

Encourage collaboration among teams working on various micro frontends. Encourage open dialogue and the sharing of excellent practises. I recommend at least 1 hour all dev meeting every week along with shared documentation with clear use case of components and utilities. Automating documentation will be bonus to and boon. [Drop in comment which tool do you use for auto documentation, I need this for my repo]

5. Version Control

Version control should be used for each micro frontend. This allows you to keep track of changes, roll them back if required, and assure the dependability of your programme.

6. Load on Demand

Load micro frontends on-demand, minimising user load time and enhancing performance.

7. Testing

Conduct thorough testing on each micro frontend to guarantee quality and compatibility.

8. Error Handling

Handle mistakes compassionately, and put a plan in place to manage failures that may arise in micro frontends. I would recommend proper error segregation like blocking error, non blocking error, network errors etc and handle them from a common place.

The DON'Ts of Micro Frontends

1. Over Engineering

Avoid creating an excessive number of micro frontends. It is critical to strike a balance between modularity and complexity.

2. Shared State Complexity

Avoid too complicated shared state management. Consider Redux, MobX, or shared state libraries as solutions. You can create your own pub sub or post message service. Implementation/state planning matters more than the tool to transfer states.

3. Inadequate Version Control

Failure to provide version control might result in compatibility concerns and code clashes amongst micro frontends.

4. Inconsistent UI

Inconsistent UI can mislead users and degrade the overall user experience. It will force developers to re create same thing multiple time, cause burden to your development cost.

5. Communication breakdown

Do not segregate teams working on various micro frontends. Encourage communication and teamwork. Missing communication might lead duplication of work.

6. Failure to Test

Failure to test your project will lead to a fail project, too bold but true. For those who want to read it in light tone - Failure to test might result in faulty micro frontends and compatibility concerns.

Tools for Micro Frontends

In last 5 years we have developed a lot in this domain and lot of open source tools are doing well.

1. Module Federation (Webpack 5+)

Module Federation in Webpack allows you to load micro frontends on demand and efficiently share dependencies.

2. Single-SPA

Single-SPA is a JavaScript framework that allows you to manage many micro frontends on a single page.

3. qiankun

A toolkit for developing dependable and maintainable micro frontend apps.

4. SystemJS

SystemJS is a dynamic ES module loader that may be used to dynamically load micro frontends.

5. Lerna

Lerna is a tool for organising multi-package JavaScript projects.

Scaling and Monitoring Micro Frontends

Scaling

Automation

To accommodate increased demand, use automated deployment and scaling solutions. Kubernetes and Docker are very useful tools for on demand scaling up.

Caching

To speedy delivery of your code and optimise the distribution of micro frontends to users, employ a content delivery network (CDN) or caching layer.

Load Balancing

It is must for balancing requests to separate micro frontends to guarantee balanced traffic distribution on all PODs.

Service Discovery

Implement service discovery techniques to assist micro frontends in locating and communicating with one another.

Monitoring

Monitoring is the critical part of software engineering as things are not visible physically so the data evidences are needed for debugging, managing and taking decisions. Here are a few important things to setup the system wide monitoring.

1. Centralised Logging

Collect logs from all micro frontends and store them in a centralised logging system to aid debugging and troubleshooting.

2. Error Tracking

Use error tracking software to track and analyse mistakes in real time. I am not going to name them here.

3. Performance Monitoring

Performance monitoring tools may be used to discover and fix performance bottlenecks.

4. User Analytics

Collect user analytics to obtain insights into user behaviour and improve user experiences.

5. Security Monitoring

Continuously monitor security-related issues in order to detect and remediate vulnerabilities.

Wrapping Up!

Micro frontends may significantly improve the scalability and maintainability of frontend apps, but they need careful planning and the proper tools. You may effectively develop and grow a micro frontend architecture by following best practises, avoiding common errors and using the correct technologies. Monitoring and scaling procedures guarantee that as your application expands, it stays performant and dependable.

Remember that the precise tools and tactics you use will be determined by the unique requirements and limits of your application. As your application matures, remain open to modifying and refining your strategy. If you feel stuck feel free to connect me for solution.

Thoughts or questions, are welcome in comment box...

Till the next time keep Learning-Coding-and-Growing.

Service-Oriented Architecture (SOA): A Comprehensive Guide

An Architect — Thu, 19 Oct 2023 08:42:22 +0000

Discussion of loose coupled architectures for scale is not complete without talking about Service-Oriented Architecture(SOA), so here is todays article on it.

Disclaimer - If you are decision maker then only go ahead, if your intention is you will be able to learn how to build your first SOA this article is not for you.

SOA refers to a software design paradigm that promotes the usage of loosely connected, reusable services. SOA services are software units that execute specified activities and communicate with one another via standard interfaces. SOA enables the construction of complex software applications by connecting these services like building bricks.

Key Components of SOA

Agility: SOA enables faster and easier development and deployment of software applications.

Flexibility: SOA applications are more adaptable and flexible to change.

Scalability: To accommodate changing demands, SOA applications can be scaled up or down.

Interoperability: Regardless of the underlying technology, SOA applications can communicate with other systems.

When to use SOA?

SOA is an excellent solution for a wide range of applications, including:

Complex applications that must be versatile and flexible.
Applications that must scale in order to fulfil large demand.
Applications that must communicate with other systems.

Core Principles of SOA

Modularity/ Reusability

SOA encourages the creation of smaller services, which are self contained and may be reused across several applications and systems, increasing efficiency and minimising redundancy.

Interoperability/ Service interfaces

Services in a SOA conform to established protocols and interfaces, allowing them to collaborate easily regardless of the underlying technologies.

Loose Coupling

SOA stresses loose connectivity between services, which means they can evolve independently of one another.

Design patterns for SOA

A variety of SOA design patterns can be utilised to create scalable and dependable SOA applications. Among the most common SOA design patterns are:

Service orchestration: It is a design paradigm for combining SOA services into complex workflows.
Service aggregation: It is a pattern that combines many SOA services into a single service.
Event-driven SOA: It is a method for developing SOA applications that are sensitive to events.

What an architect should consider while developing SOA for scale:

If you are an architect, a number of considerations should be made by you when designing a SOA for size, a few of them are:

Service granularity: SOA services should be designed to be granular, meaning that they should do a single task or a small collection of closely related tasks. This will make the services easy to reuse and maintain.

Service autonomy: SOA services should be intended to be autonomous, which means they should be able to function without relying on other services. This will make the system more scalable and resilient to failures.

Service scalability: SOA services should be built to 'be scalable', which means they should be able to accommodate increased traffic without sacrificing performance. This can be accomplished by employing strategies such as caching, load balancing, and replication.

Service monitoring: SOA services should be monitored to verify they are working as planned. This will aid in identifying and resolving issues before they affect users.

Conclusion

SOA is a strong software design paradigm that may be used to create applications that are scalable, adaptable, and interoperable. However, before determining whether or not to adopt SOA, it is critical to carefully analyse the application's requirements.

Furthermore, when developing SOA systems for scale, SOA architects should keep the principles of service granularity, autonomy, scalability, and monitoring in mind.

Till the next time keep Learning-Coding-and-Growing.

Architecting for Agility: Unleashing the Power of Event-Driven Architecture in Software Design

An Architect — Sun, 15 Oct 2023 10:42:38 +0000

In this series Design happens in mind first even for Softwares of software design articles, how can we move forward without discussing Event-Driven Architecture. When we talk about properties like high agility, responsiveness, scalability and adaptability, we can not stay away from discussing about Event-Driven Architecture (EDA). We will discuss about the fundamental concepts, benefits, and practical applications of EDA in software design.

Understanding Event-Driven Architecture

Event-Driven Architecture is a design paradigm, which enables the applications communicate with one another and respond to events. These events can be triggered by a variety of factors, including user interactions, sensors, or other software components. EDA is based on the concept of decoupling components by allowing them to interact via events, allowing for asynchronous, loosely coupled systems.

Two prime components of EDA

1. Event Producers:

Event producers are those entities which generate events. They could be IoT devices, databases, User input/interactions or any other software components. Basically you can compare it to any external action which will triggers for further process executions.

2. Event Consumers:

Event Consumers are those entities which react to events. They could be execution functionality, microservices, Database commit, or other software functions. Consider them like processing units of any manufacturing unit.

Key Concepts in Event-Driven Architecture

Events

The heart of EDA is events. An event is a major occurrence or change in the system's state. Events can be classified as follows:

Domain Events

They represent changes in domain such as a new order, a user registration, or a sensor reading.

Integration Events

They facilitate communication between several services, typically in a distributed system.

Event Broker

The Event Broker serves as a mediator, collecting and distributing events. Message brokers such as Apache Kafka and RabbitMQ, as well as cloud-based services such as AWS EventBridge and Azure Service Bus, are common implementations.

Event-Driven Microservices

Event-Driven Microservices are self-contained services that interact with one another through events. They are loosely connected, deployable separately, and may respond dynamically to changing conditions.

Benefits of Event-Driven Architecture

When we are talking about some design paradigm, it is useless without discussing their benefits, so here they are...

Scalability

By allowing event consumers to manage varying loads independently, EDA promotes dynamic scalability. This is critical for applications that have varying demands.

Loose Coupling

Because the components are loosely coupled, they can evolve separately. A component does not need to know who or what will consume an event when it generates it. They can simply move from one place to another in or out of the whole ecosystem, which saves time later.

Asynchronous Processing

EDA supports asynchronous communication, which is useful for handling time-consuming processes without causing the entire system to wait. In short, easy processing of long tasks in non-blocking manner.

Fault Tolerance

In EDA, a component failure does not always impact the entire system because events can be delayed or retried.

Real-Time Responsiveness

EDA is ideal for real-time and reactive systems, allowing for quick responses to events as they occur.

Practical Applications of Event-Driven Architecture

1. Microservices Communication

EDA is an ideal fit for microservices architecture, in which services communicate by events.

2. User Interfaces

EDA is frequently used in modern web applications for real-time updates and user interactions.

3. IoT and Sensors

EDA is useful for processing data from IoT devices and sensors, allowing for quick responses to environmental changes.

4. E-commerce and Order Processing

EDA is used in e-commerce systems to manage order processing and inventory adjustments.

5. Financial Systems

In financial applications, EDA ensures that transactions and market events are processed in real-time.

Conclusion

In the field of software design, Event-Driven Architecture is a game changer. It is an appealing solution for modern applications due to its ability to develop flexible, responsive, and scalable systems. Architects and developers that embrace EDA may create systems that thrive in a dynamic, fast-paced digital ecosystem, ensuring that their applications are always in sync with the pulse of real-world events.

Navigating Microservices: Proven Strategies for Streamlined Development and Scalability

An Architect — Fri, 13 Oct 2023 17:13:09 +0000

This is continuation of previous article Mastering Microservices: Your Comprehensive Guide to Modern Software Design, which I had left in middle because of it's length. We will be talking about the proven strategies of using Microservices architecture, which worked for us. Definitely we did not introduced all from start of the project, but recommend you to use since start if you are going to start new development using this architecture.

1. Clear Service Boundaries:

You should define clear and well documented boundaries for your each microservice, consider it like a sellable service to another organisation. Do documentations like you see on paid APIs or services. This will avoid future ambiguity and streamline the process and team communications.

2. Use API Gateways:

Implement an API gateway as single entry point for all clients, this streamlines client interactions and guarantees a standard interface for all services. Apart of this major task of API gateway is to keep track of callee and maintaining ids in header, most important for request tracing. Which will later help us to easy and quick debugging.

3. Decentralised Data Management:

As discussed already consider each microservice is identity of unique organisation, we should make individual microservice responsible to manage its own decentralised data store to reduce dependency and avoid conflicts. To keep data synchronised, use event sourcing and publish-subscribe methods. Ultimately we have to move it towards observability so keep that in mind since start.

4. Service Discovery and Load Balancing:

Setting up an automatic service registration and load balancing is critical. This simplifies service management and assures even traffic distribution. You can use tools like Consul or Eureka. If you are in Java ecosystem Netflix Eureka or ZooKeeper(by Apache) would be your best companion.

5. Containerisation and Orchestration:

We use Docker for containerisation and Kubernetes (K8) as orchestration tools to manage microservices efficiently since start. These technologies simplified deployment and scaling processes, so did not tried or researches another. They helped us to develop and test environment specific, which is cool to use different versions of common library for different services when needed.

6. Monitoring and Logging:

Implementing comprehensive monitoring and logging solutions for each microservice is important. Prometheus and Grafana are two tools that can help you track performance, spot problems, and troubleshoot quickly.

7. Automated Testing and Continuous Integration:

How can someone missed automated test case in era of TDD, you can choose any framework of your choice. Continuous Integration helps a lot for fast deployments and re-deployment if needed any.

For new Architects

If you are an architect for your project I have few more gems for you next, keep focus on them too.

1. Scalability by Design:

Try to design your microservices stateless and horizontally scalable. This will help easy scaling by adding more instances of services whenever needed.

2. Versioning:

Plan for API versioning from the beginning to ensure backward compatibility. This helps clients to avoid disruptions when new versions are released.

3. Error Handling and re-try mechanism:

Implement robust error handling and resilience measures to architect for failure. To reduce service disruptions, use mechanisms such as circuit breakers and retries.

4. Security:

Prioritise security in the architecture, ensuring that sensitive data is safeguarded and services are properly verified and authorised. Only external APIs should exposed through gateway to public IP.

5. Microservices Governance:

Develop governance policies and procedures to guarantee that microservices principles are consistently applied throughout the organisation.

6. Continuous Health Check:

Maintain a mechanism for continuous health check and alert, to keep them up and working all time.

Apart of these team collaboration, documentation, DevOps practices, setting code quality rules are similar as other architectures.

Moreover microservices architecture is a philosophy, so implementation will always differ you just need to decide based on your own requirements and resources. Microservices architecture provides considerable benefits in terms of scalability and agility, but it also introduces new challenges. You might create easily maintainable and scalable
microservices environment with the help of following above mentioned best practices and considering crucial architectural criteria. Your carefully planned microservices architecture can enable your firm to survive in a dynamic and ever-changing technology landscape with minimal efforts.

Thoughts or questions, are welcome in comment box...

Till the next time keep Learning-Coding-and-Growing.

Mastering the Art of Software Design: A Deep Dive into SOLID Principles

An Architect — Thu, 12 Oct 2023 10:39:12 +0000

If you are coming after reading previous article titled as Mastering the Art of Software Design: Unveiling the Core Principles, I have already briefed about SOLID principles, You don't wanna go, I will write for you too. Let's jump into.

Writing maintainable, scalable, and reliable code is essential in the constantly changing world of software development. The SOLID principles are one set of design principles that software developers have developed over the years to accomplish this. Robert C. Martin's five guiding principles serve as a guide for creating readable, flexible, and maintainable software code. We will go into each SOLID principle in this blog article, examining what it implies and how it may be used to improve software design.

SOLID is an acronym of 5

Single Responsibility Principle (SRP)
Open/Closed Principle (OCP)
Liskov Substitution Principle (LSP)
Interface Segregation Principle (ISP)
Dependency Inversion Principle (DIP)

1. Single Responsibility Principle (SRP)

According to the single responsibility principle, a class should only have one cause for change. In other words, each class should be assigned only a single task. Maintaining, testing, and extending a class is more difficult when it has several duties. You may make your code more modular and understandable by following SRP.

It is preferable to divide a class that receives data from a file and conducts calculations into two independent classes—one for reading the data and the other for executing the computations—if you are designing such a class. In this manner, the computation logic won't be affected if you need to change how data is read.

2. Open/Closed Principle (OCP)

The Open/Closed Principle promotes openness for extension but closure for modification in software entities (classes, modules, and functions). In essence, it implies that you ought to be able to expand your code to include new features or behaviors without having to change the present codebase. This rule reduces the possibility of adding problems to previously functional code and encourages code reuse.

You can create adaptable and extensible systems by using methods like inheritance, interfaces, and abstract classes that comply to OCP. Instead of directly altering existing classes or modules in response to changing requirements, you can construct new classes or modules that extend them.

3. Liskov Substitution Principle (LSP)

According to the Liskov Substitution Principle, objects of a derived class must be interchangeable with those of the base class without impairing the program's ability to run correctly. To put it another way, it guarantees that derived classes can be used interchangeably with their base classes without leading to unexpected behavior.

Class hierarchies must be properly designed in order to achieve LSP compliance and must not violate the agreements made by base classes or interfaces. Small bugs and maintenance issues may result from violations of this principle.

4. Interface Segregation Principle (ISP)

The Interface Segregation Principle recommends against making clients rely on interfaces they do not use. In other words, it encourages the development of narrow, focused interfaces as opposed to broad, unified ones. Classes that implement interfaces need only supply implementations for the methods pertinent to their particular functionality in this fashion.

By adhering to ISP, you can avoid the "fat interfaces" issue, which occurs when classes are overloaded with methods they don't need to implement, resulting in code bloat and possible SRP breaches.

5. Dependency Inversion Principle (DIP)

High-level modules are encouraged not to depend on low-level modules by the Dependency Inversion Principle. They ought to both rely on abstractions. Additionally, it implies that abstractions should rely on details rather than the other way around.

DIP encourages loose connectivity between modules, which makes it simpler to upgrade or replace parts without harming the system as a whole. In actuality, this entails defining dependencies via interfaces or abstract classes, enabling dependency injection and inversion of control (IoC) containers.

Conclusion

The SOLID principles provide a framework for creating well-structured, maintainable, and extensible software designs. While applying these principles may necessitate additional effort and planning in the beginning, the long-term benefits in terms of code quality, flexibility, and simplicity of maintenance are well worth it. Software developers may create systems that stand the test of time and adapt to changing requirements by using SRP, OCP, LSP, ISP, and DIP. Understanding and using these principles is a crucial skill for any software developer who strives to build clean and efficient code.

Mastering Microservices: Your Comprehensive Guide to Modern Software Design

An Architect — Mon, 09 Oct 2023 13:30:02 +0000

// Edit 1 based on comments received

This article is written to help those who are taking design decisions, You can read through if you want insights on those. If you have reached here in search of how to write microservices? This article is not for you, there are plenty other available on internet.

// Edit 1 closed

Microservices architecture in a software design is an approach of breaking down the complex application into multiple smaller and loosely coupled services, which can operate independently and communicate clearly via APIs. Each service focuses on a specific function or feature, making individual components easier to design, deploy, and expand. This architecture encourages flexibility, agility, and the capacity to more effectively evolve and maintain software, particularly in big and frequently changing applications.

We are going to talk about benefits of using Microservices architecture, when to use them, when not. Along with challenges and best practices of Microservices architecture.

Benefits of using Microservices Architecture:

Scalability: It is Easy to scale individual services, based on traffic or usage without impacting others.
Agility: Faster development and updates/deployments, whatever tested can be deployed.
Flexibility: Smaller teams can choose diverse tech stacks for their services.
Fault Isolation: Isolate failures to service level, which could easily be found using separate logs identifier.
Team Autonomy: Empower small teams.
High Availability: Enhance fault tolerance, we just need to fix and redeploy the culprit service.
Incremental Updates: Release features independently, we need not to keep the ready features awaited because 2 features are not finished for monolithic bundle.
Hybrid Cloud and Multi-Cloud Environments: You can deploy your services in Hybrid Cloud and Multi-Cloud Environments.

When to use Microservices?

Microservices architecture are very well suited for below mentioned applications

1. Complex Applications:

Microservices architecture may help manage the complexity of large, complex applications with various features and capabilities by splitting the application down into smaller, more manageable services. You can single service for single functionality like login/register is one, managing dashboard is another service, and so on. Like SRP for functions, microservices for functionality.

2. Varying Scalability Needs:

If you anticipate varying workloads and need to scale particular services of your application independently, microservices enable you to scale/descale only the services that demand more/less resources respectively rather than the complete application.

3. Frequent Updates Needed:

Microservices are great for applications which require regular upgrades, new launches, or bug fixes since they facilitate rapid development and deployment cycles.

4. High Availability:

By separating failures to individual services, microservices can improve fault tolerance and offer high availability by lowering the danger of a single point of failure affecting the entire application.

5. A Team with Diverse Technology Stacks:

When you have a tech team with diverse stack and resilient in migrating their tech preference, choosing this could be a good option. You can distribute them into multiple teams and use their tech to the best part of your application and club the services for producing even better solution.

When not to use Microservices architecture?

As nothing fits all in software design so the microservices architecture, we have to refrain using it for following scenarios -

1. Simple Applications:

When the application is simple, we should avoid the network and configuration overhead of microservices architecture. Monolithic would be better option here.

2. Limited Resources:

The complexity offered by microservices may cause issues in terms of development, maintenance, and orchestration. If you have limited development resources or a small team, you should refrain using this architecture.

3. Data-Intensive Applications:

If your Application is highly based on complex data base transactions, you should avoid using microservices architecture because it makes hard to maintain data consistency. I am not saying maintaining data consistency will be impossible but that will need extra efforts and resources. We should follow the cost effective way ;)

Finally, the decision to employ microservices should be based on a thorough examination of your project's unique requirements, goals, and restrictions. When deciding whether microservices are the correct architectural approach, consider aspects such as team skills, project size, scalability needs, and the nature of the program.

Challenges:

I have been working with microservices architecture for more than 6 years now, I have found using microservices architecture comes with following caveats

Increased Complexity
Resources Overhead
Tooling Monitoring
Documentations and Communications
Cost Management
Learning Curve
Versioning
Service Coordination
Data Management

Best Practices:

After writing this long, I think the quality of blog is getting degraded and this is turning to a long post instead a bit size blog. I will write the best practices in details and link that article to this.

// Edit 2

I have got time to create the second part of this article Navigating Microservices: Proven Strategies for Streamlined Development and Scalability

// Edit 2 closed

Thoughts or questions, are welcome in comment box...

Till the next time keep Learning-Coding-and-Growing.