- When one dependency slows down, the entire system slows with it
- When something breaks, nobody knows where to look first
- Nobody knows in advance what will happen during peak periods
06
Reliability & Security
Site Reliability Engineering
We design for how the system behaves under pressure rather than under normal conditions: slow dependencies, traffic spikes and partial failure all included.
Scope
What we take on
We deal with reliability before the incident, not after it. We measure how the system behaves under pressure, separate what is critical from what is not, and point a limited budget at whatever causes the most business loss. Priority is set by measured risk, not by the risk people talk about most.
Workstreams
- Monitoring and alerting that warns before users are affected
- Immediate visibility into where a slowdown originates
- One component failing without bringing the whole system down
- Degrading to limited service instead of shutting down during an incident
- Knowing the system limits before a peak, not during one
- The same failure not happening a second time
When you need this
If these signs
look familiar.
Where we applied it
Retry, timeout and circuit breaker patterns, degraded-mode flows and root-cause isolation on the Obilet platform; low-latency 10K RPS services at KocDigital.
Results in production
Which platforms
have we applied this on?
%20lower cloud cost, same workload
Travel Distribution Platform
Multi-supplier inventory came together in one model, and the same volume is now served at 20% lower cloud cost.
Obilet’s bus, air and rail inventory was fed by suppliers that each had their own data model and their own failure behaviour, so every new integration put the search and booking flow at risk of regression. We normalised the inventory into a single internal model, solved station matching through geographic proximity and GIS, isolated supplier-side failures and reworked resource usage on AWS. The platform now runs independently of any one supplier, holds predictable performance through peak season, and serves the same workload at roughly 20% lower cloud cost.
Read the case study →
One screentrip, vehicle and field team planning
Passenger & Ground Operations
Airport passenger operations are planned and monitored from a single platform.
At TPort and Pegasus, trip planning, vehicle assignment and field team tasking ran in separate systems, so the operation could only assemble a picture of the day through manual coordination. We brought trip and vehicle planning, field task flow and operations screens onto one platform, integrated the API and SPA layer with enterprise systems and established role-based authorisation. Operations now plan and monitor the entire field from one screen.
Platform →Related platforms
Which platforms
does this discipline come into?
Let’s work together
Let’s look at a need you have around site reliability engineering.
Tell us where you are today and which constraints matter most; we will define a clear starting point together.