Observability
Observability is the ability to understand what is happening inside a system by looking at its external signals. It is the habit of seeing cause and effect before they turn into symptoms. It is the part of engineering practice that turns "something broke" into "we know exactly what broke and why". We build our own projects, and it matters to us to notice problems before users do. Ideally at the moment when the issue is still a small metric deviation, well before it becomes an incident with late-night calls.
What we consider good observability
Good observability answers the question "why and where exactly". It highlights the user journey, shows degradation, detects regressions after a rollout, gives you the confidence to roll back calmly. It stays quiet about trivia and speaks loudly when it truly matters. Poor observability looks like ten alerts no one reads, a dashboard with thirty graphs where nothing can be found, flat text logs that cannot be filtered. Good observability is three metrics that really describe the health of the system, together with structured logs where search takes seconds. We love the "three pillars" approach — metrics, logs, traces. Metrics answer "what is happening on average", logs answer "what happened at a specific moment", traces answer "how a request moved through the system". Each pillar is useful on its own. The magic begins when they are linked: from a metric alert you jump into logs, from logs into a trace, from the trace into code.
Private frontend monitoring
A separate love of ours is private frontend monitoring. You see real browser errors and performance, and the data stays inside your infrastructure. No shipping to third-party services, no extra dependency, no situation where your users become traffic for someone else's advertising model. We assemble a stack based on Grafana Faro, OpenTelemetry and our own backend for ingesting events. Such a solution costs more than wiring up a SaaS in five minutes. A year later you have infrastructure that works without external dependencies, with no event limits and with a predictable cost of ownership.
When backend and frontend signals live together, you stop stitching data by hand and start seeing the whole system at once.
Alerts as an engineering practice
Setting up an alert is easy. Tuning it to fire only when action is truly required is hard. We follow the rule: an alert that fires and demands nothing is a bad alert. Perhaps the threshold is off. Perhaps the metric is the wrong choice. Perhaps the problem has already been resolved automatically, and the human receives a notification for nothing. So every alert passes through a filter: what exactly is broken, why it matters, what action is expected, where to look. With clear answers to these questions, the alert stays. Such alerts fire rarely and always with purpose.
How this shows up in our projects
We collect signals so they help us make decisions: which experiments to run, what to optimize, where the bottleneck lives, how much an error costs. Where it helps, we add quick ways to tag events and experiments so we can replace belief with knowledge. In products with user traffic we ship a default panel with Core Web Vitals, breakdowns by country and device, a dedicated view of the distribution tail — because averages lie almost every time. In backend services we ship tracing through the whole chain, without which you cannot understand why a specific request took seven seconds. If you want to move from "it feels worse" to "here is the metric, here is the cause, here is the regression moment" — this is exactly our style.
Status
The competency is active and grows with our projects — because without observability any complex system quickly turns into wandering. We are ready to take projects from scratch (set up the stack, configure alerts, teach the team) and tasks that untangle an existing zoo of dashboards: what to keep, what to remove, what to replace. Orthodox tool for searching and studying scripture texts. Fast search, translation comparison, interpretations and children's mode.
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