Ops Pillar · TelemetryOps

See everything,
at petabyte scale.

TelemetryOps is the observability foundation of Ops Singularity. It collects OpenTelemetry signals from every service and stack, unifies logs, metrics and traces in one store built for petabyte scale, and lets any team build the dashboards and queries they need, then hands clean, correlated telemetry to Sentinel AI.

OpenTelemetry-native Logs, metrics & traces Petabyte scale Dashboard builder Collectors for any language
What is TelemetryOps

One observability layer for every signal you emit.

Most teams run observability across a pile of disconnected agents, formats and tools, and pay to keep data they cannot correlate. TelemetryOps unifies it on open standards: OpenTelemetry-native collectors gather logs, metrics and traces from most languages and stacks, a store built for petabyte scale keeps them queryable instead of sampled away, and a dashboard builder turns any signal into a view. The result is clean, correlated telemetry that people can explore and that Sentinel AI can reason over.

OpenTelemetry-native collection

Instrument once, in the language you already use.

TelemetryOps speaks OpenTelemetry end to end. Collectors and auto-instrumentation cover most languages and runtimes, and anything that emits OTLP is a first-class source, so you are not rewriting instrumentation to fit a vendor agent. Because it is OTel-native, the semantics travel with the data: resources, services and attributes stay intact from the SDK all the way to the query.

  • Collectors and auto-instrumentation for most languages
  • Any OTLP source is first-class, no proprietary agent
  • Resource and attribute semantics preserved end to end
CollectorsOTLP in
JVMjava auto-instrumentation reportinghealthy
GOotel-sdk traces + metricshealthy
NODEotlp/http exporter connectedlive
K8Scollector daemonset, node logslive
Unified logs, metrics & traces

Three signals, one correlated store.

Logs, metrics and traces land in one place and stay linked by the resources that produced them. A slow trace opens straight to the metrics around it and the exact logs its spans emitted, so an investigation is one path instead of three tools and a guess. Resources, whether a service, pod, container or cloud zone, sit at the centre, so context follows you as you pivot.

  • Logs, metrics and traces linked by resource
  • Pivot trace to log to metric without losing context
  • Resource-centric model across services and infra
Correlated viewOne path
Trace
Slow span Latency
Metric
Saturation Elevated
Log
Errors Spiking
Resource
payments-pod Pinned
Petabyte-scale storage & query

Keep the detail. Query it fast.

TelemetryOps is built for petabyte-scale telemetry, so high-cardinality data stays queryable rather than sampled down to fit a budget. Query in the language you know, PromQL for metrics and SQL for logs and traces, and get results fast enough to explore, not just to alert. Retention and tiering are yours to set, so cost tracks value instead of surprising you.

  • Petabyte-scale store, high cardinality kept queryable
  • PromQL and SQL over the same telemetry
  • Retention and tiering you control for predictable cost
Query enginePromQL / SQL
Hot tierFast
Warm tierReady
Cold / archiveCheap
Cardinality keptFull
Your retention policy decides what stays hot
Dashboard builder

A dashboard for every signal, built by anyone.

Turn any query into a panel and any set of panels into a dashboard, without waiting on a specialist. Build service views, team views and executive views over the same telemetry, and share them across the estate. Open dashboard standards mean the boards you build travel with you and are not trapped in one vendor's format.

  • Turn any query into a panel, any panels into a board
  • Service, team and executive views over one dataset
  • Open dashboard standards, portable and shareable
Dashboard builderLive panels
Latency
Throughput
Error rate
Saturation
Explore & investigate

Ask a new question without pre-building for it.

High-cardinality exploration lets you slice telemetry by any attribute after the fact, so you can chase an outlier you never predicted. Drill from a dashboard anomaly into the traces behind it, then the logs those spans emitted, and group by resource, endpoint or tenant to find where the pressure really sits. The workflow is built for the unknown-unknowns, not just the metrics you already chart.

  • Slice by any attribute, high-cardinality friendly
  • Drill from anomaly to trace to log in one flow
  • Group by resource, endpoint or tenant on the fly
ExploreGroup by
tenant: acmeHigh
endpoint: /payMed
region: eu-1Med
build: 4821Low
Outlier isolated to one tenant and endpoint
Open, portable & governed

Your telemetry, your standards, your perimeter.

TelemetryOps is built on open standards, OpenTelemetry for data and open formats for storage and dashboards, so nothing is trapped in a proprietary silo. It runs inside your perimeter, on-prem or air-gapped, and the same governance that covers the rest of Ops Singularity applies here: role-based access, data curation before any model, and full audit. That is what lets Sentinel AI reason over the telemetry safely.

  • Open standards for data, storage and dashboards
  • Runs in your perimeter, on-prem or air-gapped
  • RBAC, curation and audit, governed like every pillar
Open & governedNo lock-in
OTELOpenTelemetry data modelstandard
STOREopen format, your storageportable
RBACrole-based access, full auditgoverned
EDGEon-prem / air-gapped deployin perimeter
Powered by Sentinel AI

TelemetryOps sees it. Sentinel makes sense of it.

Collecting telemetry is only half the job. The unified logs, metrics and traces that TelemetryOps gathers feed Sentinel AI, the intelligence component at the core of Ops Singularity. Sentinel runs the OIAO loop over that telemetry, correlates signals into incidents, finds root cause across the estate graph, and resolves through governed, reversible Action Tickets.

Sherlock closes the root-cause loop and ProcBot executes the fix, every step explained with citations and fully audited.

1
Observe
TelemetryOps streams correlated logs, metrics and traces from every source.
2
Investigate
Sentinel AI slices high-cardinality telemetry to find root cause across the graph.
3
Act
ProcBot executes the approved MOP through a reversible, audited Action Ticket.
4
Optimize
Sherlock verifies the fix against the same telemetry before the incident clears.

See TelemetryOps on your stack.

Book a walkthrough and see OpenTelemetry-native collection, unified logs, metrics and traces at petabyte scale, and dashboards built over your own signals.