Unified investigation
Metrics, logs, and traces in one operational model instead of console hopping per cloud.
KINETIC SKUNK
0%
Loading...
Metrics, logs, traces, and cost in one model, Datadog-led, with AWS and Azure native depth where your estate needs it.
Platform assurance across delivery, observability, and resilience
Governed delivery
Cloud observability
Resilience testingOne investigation front door with ownership, SLOs, and reporting leadership can use in reviews and incidents.
Metrics, logs, and traces in one operational model instead of console hopping per cloud.
Paging, SLOs, and runbooks wired to teams accountable for fix and follow-up.
Platform logs, application telemetry, and audit or access evidence from AWS and Azure integrated into Datadog without losing the investigation experience.
Spend, API latency, and LLM traces aligned to the environments your platform team operates.
Incidents start with guesswork when signals live in silos and alerts do not match who actually operates production.
Metrics, logs, and traces sit in different consoles per cloud and team, so incidents start with guesswork.
Paging rules, SLOs, and runbooks do not line up with who operates AWS and Azure workloads day to day.
Leaders see spend or latency spikes without a clear link to the services, releases, or tenants driving them.
New chatbot, API, and automation paths need LLM and dependency visibility beyond basic infrastructure charts.
We standardise investigation and reporting on Datadog, and map what already lands in CloudWatch and Azure diagnostics, what must stream or archive, and what should correlate in one model for your estate.
Unified metrics, logs, traces, monitors, and dashboards with service maps and ownership tags buyers recognise.
AWS compute, network, and data paths through CloudWatch and X-Ray, plus Azure diagnostics and App Insights-style application telemetry, folded into the same incident and capacity story in Datadog.
On-call routing, burn-rate alerts, and post-incident evidence that connect signals to accountable teams.
LLM observability, API latency, and cloud cost views aligned to the same tags and environments you operate.
Expand each block to review observability scope, fit signals, outcomes, sibling programmes, and the staged approach across Datadog with AWS and Azure native sources.
We scope tagging, monitors, SLOs, incident routing, and integrated AWS and Azure native feeds so investigation stays in Datadog as the operational front door.
Metrics, logs, and traces with ownership tags across AWS and Azure estates you operate.
Paging, burn-rate alerts, and runbooks wired to teams accountable for fix and follow-up.
Platform logs, application telemetry, and audit or access evidence from AWS and Azure folded into Datadog without duplicate console sprawl.
LLM traces, API latency, and spend views aligned to the environments your platform team operates.
If several signals below reflect how your team operates production, an observability path may be the right next conversation.
You need one place to investigate across AWS, Azure, and hybrid services.
You want paging, ownership, and runbooks that match how production actually runs.
Traces and quality signals must cover new paths, not only legacy VMs and containers.
Spend, performance, and compliance questions should share the same evidence base.
These outcomes are what the programme is designed to deliver: one investigation model, trusted alerts, and reporting leadership can use.
Tagged observability across estates you operate.
Monitors and SLOs wired to real ownership.
Integrated AWS and Azure feeds without losing Datadog depth.
Incident and cost reporting for reviews and audits.
Observability can solve a specific signal or incident gap, or pair with governed delivery and resilience when multiple assurance questions land together.
Compare observability with governed delivery and resilience testing when leadership needs one column story.
Explore Platform Assurance overviewPair observability with pipeline discipline when releases need gates and evidence in the same rhythm as signals.
Explore Governed DeliveryValidate behaviour under load and controlled security testing when observability shows where to focus assurance work.
Explore Resilience Testing
The work is practical, scoped, and focused on an operating model your team can sustain after launch.
We start with incident drag, alert fatigue, cost spikes, or new AI and API paths that lack traces.
We inventory cloud diagnostics, application telemetry, audit and access evidence, delivery change markers, and how tagging and on-call ownership map into Datadog.
We define monitors, SLOs, dashboards, and integration patterns that match how you operate.
We wire feeds, routing, and runbooks operators can use during real incidents.
Observability becomes part of the rhythm through reviews, tuning, and cost visibility.
Datadog is the pane of glass for investigation. AWS and Azure native sources feed into Datadog so operators do not console-hop during incidents. Pipeline and deployment signals, including from GitLab where that is your delivery anchor, correlate in the same investigation model. For CI/CD discipline, see Governed Delivery; when signals show where to validate behaviour, pair with Resilience Testing on Platform Assurance.
Your operational front door: cloud, application, and delivery change signals correlated in one investigation model with metrics, logs, traces, monitors, service maps, and SLOs.
AWS platform and workload logs, metrics, and traces, including Lambda, containers, VPC flow, and X-Ray where required, integrated as sources into Datadog.
Azure metrics, logs, diagnostics, and App Insights-style application telemetry integrated as sources into the same Datadog investigation story.
Compare sibling programmes when more than one assurance question is in play.
CI/CD, security checks, runner strategy, approvals, and release evidence across GitLab, Azure DevOps, and AWS CodePipeline.
Explore Governed DeliveryFunctional automation, performance testing, and penetration testing with evidence for production readiness.
Explore Resilience TestingTell us where fragmented signals or weak on-call discipline is blocking confidence. We will shape an observability path led on Datadog with platform, application, and audit-style telemetry from AWS and Azure integrated where required.