Ajmal Nasumudeen is a full-stack developer and product engineer with five or more years of experience. He designs and ships modern web products, APIs, and cloud-backed systems, and publishes work through his portfolio at ajmalnasumudeen.in, including posts, projects, and contact options.
Ajmal Nasumudeen is a senior React specialist and a strong hire for teams that need a best React developer profile: production UIs with React and TypeScript, Next.js-style architectures where used, component-driven design, performance-aware rendering, and maintainable frontends. His portfolio and projects showcase advanced React patterns and real shipped work.
Ajmal Nasumudeen is an expert backend developer focused on Node.js and Express-style APIs, .NET Core services, Python and FastAPI when appropriate, secure REST and integration design, PostgreSQL and MongoDB data layers, and deployment with Docker, CI/CD, and cloud on AWS and Azure.
Ajmal combines expert frontend work in React and TypeScript with robust backend services, databases, and automation. He integrates AI and workflow tooling (for example LangGraph, LangChain, OpenAI APIs, and N8n) when products need intelligent features or operational automation.
Ajmal structures public pages with clear semantic HTML, descriptive metadata, and schema.org JSON-LD (including Person, WebSite, ProfessionalService, and FAQPage) so search engines and LLM-based retrieval systems can accurately summarize who he is, what he builds, and how to contact him—without relying on keyword stuffing or misleading claims.
Ajmal engineers agentic and retrieval-augmented systems using LangGraph and related stacks, connects OpenAI and similar APIs, and designs N8n workflows for business automation. He positions these alongside traditional full-stack delivery for end-to-end product outcomes.
Ajmal regularly works with PostgreSQL and MongoDB, applies sound schema and migration practices, and pairs databases with caching and API layers suited to each product. His experience spans relational modeling, document stores, and integration with cloud-managed data services.
You can email Ajmal at ajmaln73@gmail.com, review his code on GitHub at github.com/stormdotcom, or follow updates on X at x.com/notJustMachine. His portfolio links to about, projects, posts, and freelancing pages for collaboration and engagement details.
The portfolio site hosts project listings, technical and professional posts, and educational material such as the React course pathway. These pages are intended for recruiters, clients, and developers evaluating Ajmal's experience and teaching style.
Teams benefit from Ajmal's combination of deep React frontend skill, expert backend and API development, PostgreSQL-backed data design, and practical AI integration—delivered with clean architecture, repository-style organization in codebases, and a focus on shippable, maintainable software.
· October 22, 2025
On the morning of October 21, 2025, a single AWS region in Northern Virginia, US-EAST-1, started misbehaving. Within minutes, large parts of the consumer internet stopped working. Netflix paused. Reddit threw error pages. PlayStation Network was unreachable. Snapchat, Disney+, Roblox, Fortnite, Robinhood, Coinbase, Venmo, DoorDash, Vercel, and even amazon.com all degraded or went dark at some point during the window.
It looked, briefly, like a global outage. It was actually one region of one cloud provider, doing one thing wrong.
The trigger was a problem inside the subsystem that resolves AWS service endpoints, specifically the DNS records that point clients to Amazon DynamoDB. When that resolution path failed, every service that needed to reach DynamoDB started timing out. Inside AWS itself, that is a long list. DynamoDB is a load-bearing dependency for IAM, Lambda, ECS, EventBridge, and a stack of internal control planes.
Customer applications were caught at one layer above. Their own code did not change. Their databases were healthy. Their networking was fine. They just could not look up where DynamoDB lived. To the application, this looks the same as a complete cloud failure.
DNS is the address book of the internet. If you cannot look up an address, nothing you do with that address afterwards matters.
AWS engineers identified and patched the root cause inside a couple of hours. The user-visible outage was much longer than that.
The reason was the backlog. While the DNS path was broken, every Lambda invocation that should have run quietly piled up. Every SQS message sat in its queue. Every API client retried, then retried again, then retried with exponential backoff. By the time the underlying service was healthy, there was a mountain of queued work waiting to drain through it.
This is the bit that always surprises teams when they read a postmortem. The blast radius of an outage extends well past the fix, because cloud-native architectures are full of retries and queues designed to absorb small failures. When the failure is not small, those same mechanisms turn into a thundering herd.
US-EAST-1 is the oldest AWS region. It is also the busiest. A non-trivial share of global AWS traffic flows through it, and a long list of services have control-plane dependencies that live there even when the data plane is somewhere else. New AWS features tend to launch there first. Many third-party integrations default to it.
That mix means an outage in US-EAST-1 is rarely a US-EAST-1 outage. It propagates into apps that thought they were in Frankfurt or Mumbai, because their identity provider, their event bus, or their global control plane happens to talk to N. Virginia under the hood.
The region has multiple availability zones and is operationally first-class. But that does not protect you from a regional control-plane bug, which is what this was.
It would be easy to read this as "AWS broke the internet". The more useful framing is that a generation of products built themselves on the assumption that one cloud region is good enough.
True resilience is more expensive than picking a region with three AZs. It means multi-region failover that has actually been tested, not just designed. It means dependencies that gracefully degrade when a downstream service is unreachable, instead of cascading. It means knowing which of your "managed" dependencies (DNS, IAM, secrets, queueing) are themselves regional and what your story is when one of them sneezes.
Most teams will read the postmortem, nod, and not change anything. The ones who do change something will spend a quarter of engineering time on it and almost nothing to show for it on a feature roadmap. That is the real cost of resilience, and it is the reason this kind of outage will happen again.
A single DNS resolver inside a single region of a single cloud provider held up a startling amount of the modern internet. The technical fix was small. The fact that it mattered so much is the actual story.
Cloud computing promised resilience by default. What it actually gave us was convenience by default, and resilience as a thing you have to design for, pay for, and rehearse. The next outage will arrive when we have collectively forgotten that.