01
APM distributed tracing
Tracing requests across frontend, microservices and databases to pinpoint where latency comes from.
Technologies — Cloud, DevOps & AI
Datadog observability, APM & cost control
We set up end-to-end Datadog observability across your stack, with metric and log pipelines that keep the bill under control.
Core capabilities
Why we build with Datadog
02
Log pipelines & exclusion rules
Filtering debug noise before it is indexed, so you stop paying to store logs nobody reads.
03
Actionable SLOs & monitors
Error-budget alerts that fire on real user impact rather than transient noise.
Use cases
Where Datadog fits
Mission-critical SaaS observability
Real-time visibility into checkout funnels and API latency with automated PagerDuty escalation.
Datadog bill remediation
Auditing and pruning custom metric cardinality spikes that cause surprise overages.
How we staff it
Datadog engineers you interview first
Seniority and experience are agreed in the proposal, and you interview every engineer before they start.
Working-hours overlap is agreed for each engagement and written into the statement of work — the shared window, who shifts hours, and how handoffs work outside it.
Technical FAQs
Frequently asked engineering questions
Usually caused by unindexed log volume, untamed custom metric tag cardinality, or full APM sampling. We implement ingestion controls.
We deploy the Datadog Agent as a Kubernetes DaemonSet and attach OpenTelemetry instrumentation to Next.js server runtimes.
Ecosystem
Related technologies
Planning a Datadog project?
Tell us about your architecture, backlog and team. We'll reply within one business day with an honest read on whether we can help.