Standardize on OpenTelemetry, without giving up data sovereignty or a single view.
Randoli is OpenTelemetry-native and built around platform engineering practices: an opinionated pipeline your teams can adopt in minutes, telemetry that stays in your environment, and one view across every cluster, cloud, and on-prem system.
Adopting OTel properly means assembling collectors, processors, and exporters from scratch, then maintaining that pipeline as your environment changes.
Randoli ships an opinionated pipeline with custom receivers so teams start fast, but it's standard OpenTelemetry underneath and works with any OTel-compatible setup you already run.
Most platforms require shipping raw logs, traces, and metrics out to a vendor cloud before you can query any of it.
Processing happens where the data is generated, so only derived signals reach the control plane and you set retention on your own storage at no extra cost.
Three questions about the same workload mean three dashboards, three data models, and manual work to line them up.
CVE and CIS posture, cost attribution, and application performance sit together in a single per-workload view, so the answer is one screen instead of three.
Every new cluster or cloud account adds another place to look, and nobody has a picture of the whole estate.
A single view spans every cluster, cloud, and on-prem environment you run, without stitching dashboards together by hand.
Generic AI assistants sit outside the cloud tooling your team actually operates, so their suggestions stop at the boundary of what they can see.
Raiya connects through cloud-specific MCP servers for AWS, Azure, and GCP, so root cause analysis and runbooks work natively with each provider's own tooling.
"The Randoli Observability platform has proved to be indispensable. The visibility and insights it provides enabled us to reduce spend, and helped our developers to troubleshoot faster while reducing the burden on our platform team."
Tarun Mistry, CTO, Rail, A Ripple Company
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