Apliko
Problem we solve
My app went viral and the backend is on fire
From 1,000 to 50,000 users without rewriting the backend.
Cloud-native scaling, queue-based decoupling and the architecture you wish you had on day one.
Signs this is your problem
You will recognise yourself in at least one of these
- Sudden traffic spikes cause timeouts, 502s, or partial outages.
- Database CPU pegs at 100% during peak hours.
- Push notifications create thundering-herd effects on your API.
- Adding more servers does not help past a certain point.
Why it happens
The root cause, in plain language
The architecture was designed for the launch you had — not the launch you got. Synchronous calls, one database, and no queues mean every spike hits the same hot path.
Our approach
How we actually fix this
- 1
Profile the real production traffic to find the actual bottleneck (it is rarely what you think).
- 2
Move heavy or bursty work behind a queue so user-facing endpoints stay responsive.
- 3
Introduce read replicas, caching layers (Redis) or a dedicated read store where it pays off.
- 4
Set up autoscaling on the right signal (latency / queue depth, not just CPU).
- 5
Stress-test with realistic load profiles before the next campaign.
What you can expect
Outcomes our clients see
- Predictable latency under bursts that would previously crash the API.
- Server cost grows sub-linearly with users, not 1:1.
- Clear runbook for the next viral moment.
Case study
PayFlow Tracker — fintech app scaling
A personal-finance app syncing with 50+ European banks. We scaled the platform from 1k to 50k+ daily users while keeping zero downtime through major OS updates.
Related solutions
People with this problem usually also have these
Our API crashes when traffic spikes — should we rewrite in Go?
Identify the hottest microservices, rewrite only those in Go, and add a memory cache that absorbs spikes.
Refactor & performanceThe app is slow — but the database CPU is the one on fire
Most "the app is slow" problems are really database problems. We profile the queries, add the indexes, and restructure the tables.
Mobile appsLive location tracking that survives phones and scales to thousands
A location-tracking stack that handles both Android background kills and high-concurrency live updates — built on Go and a realtime channel designed for this exact problem.
Let's plan your growth
Initial consultation is completely free. We are looking for long-term partnerships.