Now TV — flagship streaming platform,
delivering entertainment to millions across the globe.
"Millions of viewers, zero tolerance for downtime." — The reality of streaming at scale.
The Platform
Now TV's flagship streaming services deliver live and on-demand content to tens of millions of viewers. Working at this scale means every decision — from architecture to caching strategies — directly impacts the experience of a massive, real-time audience.
My Role
As a Senior Software Developer, I design and implement core platform services that power the streaming experience. From content discovery and personalization pipelines to real-time playback orchestration, I focus on building systems that are resilient, performant, and ready to scale.
Key Contributions
- Core backend services for content delivery and metadata management
- High-throughput APIs serving real-time viewer requests
- Event-driven architectures for personalization and recommendations
- Cross-platform feature development across streaming services
Tech Stack
Java · Kotlin · Spring Boot · Kafka · AWS · DynamoDB · Kubernetes · GraphQL
Working at Scale
Streaming at this level isn't just about serving video — it's about orchestrating dozens of microservices, each handling millions of events per minute, while keeping latency low and availability high. A single misconfigured cache policy can mean the difference between a seamless experience and a buffering spinner for millions of households during prime time.
I've learned to think in terms of blast radius: every change, every deploy, every feature flag carries risk proportional to the audience size. That discipline — building for failure, testing for edge cases most people never encounter, and treating observability as a first-class citizen — has shaped how I approach every system since.
The Personalization Challenge
One of the most interesting problems in streaming is surfacing the right content to the right viewer at the right time. It's not just recommendation algorithms — it's real-time context: what device they're on, what time of day it is, what they watched last, and what's trending in their region. Building the data pipelines and serving infrastructure to make those decisions in milliseconds is a challenge I've spent significant time on.
Live Events
Live streaming brings its own set of pressures. When millions of viewers tune in simultaneously for a Premier League match or a live concert, traffic patterns spike in ways that normal load testing can't fully predict. I've worked on the autoscaling and traffic management strategies that keep the platform stable under those extreme conditions.
"The best streaming experience is the one you never notice." — When infrastructure disappears, the content shines.
What I Learned
- Design for degradation — graceful fallbacks beat hard failures
- Observability is non-negotiable — you can't fix what you can't see
- Deploy small, deploy often — incremental changes reduce blast radius
- Cache strategically — the right TTL on the right data is worth more than any optimization
Cross-Platform Complexity
Building shared services that respect market differences, content rights, device ecosystems, and regulatory requirements without duplicating logic is an ongoing architectural challenge — and one that keeps the work genuinely interesting.
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Streaming is one of the few industries where software quality is directly experienced by consumers. A slow API doesn't just log an error — it ruins movie night. That direct line between code and human experience is what makes this work meaningful, and it's why I care so deeply about getting the details right.