Prometheus specialists for your dedicated team.

Where Prometheus fits in a long-term product team.

The pull model suits dynamic infrastructure well. Prometheus discovers targets through service discovery and scrapes them, so a pod that appears is monitored without anything being configured, and one that disappears simply stops being scraped.

Cardinality is the constraint that decides whether a Prometheus deployment stays healthy. Every distinct label combination is a separate time series, so a label carrying user IDs or request paths produces millions of series and exhausts memory. It is the single most common way teams take their own monitoring down.

What your dedicated team does with Prometheus.

Metrics accumulate. Every team adds instrumentation, little is ever removed, and a year later the system stores a lot of data that goes unqueried while the alerts that matter are buried in it.

Periodic review of what is collected and what is alerted on is ongoing work, agreed as part of a committed monthly capacity for platform.

Common Prometheus use cases.

• Monitoring that follows dynamic workloads Service discovery, so new instances are observed without configuration.
• Cardinality kept under control Label discipline, so high-cardinality values never reach the metric names.
• Alerts on symptoms, with causes kept for diagnosis Paging on what users experience, with metrics available for the diagnosis afterwards.

Adding Prometheus skills to your team.

Metrics and alerting work sits with your dedicated cloud and DevOps team, with cardinality treated as a design constraint from the start.

Every Prometheus specialist we assign works remotely inside your tools as a dedicated member of your team, with the management on our side. It is how companies hire remote developers without opening an offshore office of their own.