Monitoring & alerts. Know before your customers do.
We set up uptime checks, error tracking, logs and alerts for your applications, integrations and AI features, routed to the right person.
For teams that hear about outages from customers, or whose automations fail silently.
Monitoring & alerts
We instrument your applications and workflows, define what healthy means for each, and route alerts to the people who can act, with enough context to fix the issue. AI features get their own checks: cost, latency, error rates and quality samples.
- (01)Uptime and error tracking
- (02)Alerts with context, to the right person
- (03)AI cost and quality checks
- (04)Dashboards for health and trends
Tools we use for this.
- Sentry
- OpenTelemetry
- Grafana
- Uptime checks
- Slack and email alerts
- Log management
We choose the stack that fits your requirements. Tool names describe our skills, not partnerships.
Setup.
1–2 weeks.
One clearly bounded piece of work, such as a system configured or a review completed, handed over ready to use.
Included
- (01)Health definitions for each system
- (02)Instrumentation and logging
- (03)Alert rules and routing
- (04)Dashboards
- (05)AI usage and cost tracking
- (06)Runbook for common alerts
Not included
- (01)Round-the-clock on-call response (available in Build & Support)
- (02)Monitoring tool subscriptions
- (03)Fixing the underlying issues (scoped separately)
How it runs
- (01) · Days 1–2
Define
What healthy looks like for each system.
- (02) · Week 1
Instrument
Logs, metrics, checks and alert routes.
- (03) · Week 2
Tune
Cut the noise so every alert matters.
Also available as: Build & Support (Staged, ongoing). Compare the formats.
Which tools do you use?
Common choices are Sentry, OpenTelemetry-based tools and Grafana, but we work with what you already have where possible.
How do you avoid alert fatigue?
Each alert needs an owner and an action. We tune thresholds in the second week and remove alerts nobody acts on.
Can you monitor AI quality?
Yes: cost, latency and error rates, plus regular samples of outputs checked against your criteria.