Who this is for
The right fit
- Platforms whose week-over-week growth is breaking the system
- E-commerce sites preparing for Black Friday and product drops
- SaaS companies graduating into the enterprise tier
- Media platforms with unpredictable viral spikes
What you can expect
Outcomes that matter
10x
Traffic headroom
peak without re-architecting
<200ms
P99 latency
under sustained load
-40%
Cost per request
after caching and right-sizing
Want a deeper benchmark? See real numbers in client work or read engineering insights.
Anatomy
Challenges, approach, outcomes
The core shape of every engagement.
Challenges Addressed
- •Systems showing strain at current scale
- •Unclear where the next bottleneck will be
- •Cost growing faster than revenue
- •Reliability issues during peak traffic
Approach
- 1.Load test and profile to find real bottlenecks
- 2.Design for horizontal scaling where possible
- 3.Implement caching and CDN strategies
- 4.Build observability for proactive scaling
Outcomes
- Handle 10x traffic without architecture changes
- Predictable costs that scale sublinearly
- 99.9%+ reliability during peak events
- Clear playbook for next scaling phase
How we work
Engagement phases
A predictable rhythm from kickoff to handoff. Phases overlap when it makes sense.
Bottleneck Hunt
Load test, profile, and find the next 3 bottlenecks before they find you.
- Load test report
- Profile flame graphs
- Capacity model
Foundations
Add caching, CDN, autoscaling, and async paths for the obvious wins.
- Cache layer
- CDN config
- Autoscaling policies
Re-Architect Hot Paths
Decompose the hottest paths so they scale horizontally with low coupling.
- Service decomposition
- Read replicas
- Sharding plan
Game Days
Run quarterly load tests and game days to prove the system holds.
- Game day runbooks
- Capacity dashboards
- On-call playbooks
Curious how this maps to your context? Walk through the engagement process or jump straight to scoping a project.
Services
Services that deliver this solution
The capabilities Sri brings to bear on this engagement.
Stack
Technologies in play
The tools Sri reaches for when delivering this solution.
Industries
Best fit for
Sectors where this solution delivers the most value.
Proof
Recent work
Where this solution has delivered for real teams.
E-commerce Speed Optimization
Black Friday at 12x normal load
Media Streaming Redesign
10M concurrent viewers
Real-Time Analytics Platform
Sub-200ms at 50k QPS
Browse the full case study library or see who Sri has worked with.
Dig deeper
Further reading
Playbooks, blueprints, and writings that go deeper on this solution.
FAQ
Common questions
What founders and engineering leaders ask before kicking off.
When should I split my monolith?
Later than people think. First exhaust caching, async, and read replicas. Split only the parts that actually scale or fail differently from the rest.
How do you avoid over-engineering?
Tie every change to a measured bottleneck and a business event (deal size, traffic forecast, peak campaign). No speculative complexity.
More questions? Check pricing and engagement models or ask Sri directly.
Adjacent
Related solutions
Often paired with or sequenced after this engagement.
Ready to implement this solution?
Let's discuss how this approach can be tailored to your specific needs.