production · eu-west-2 · 1.2M metric points/sec

Observability that answers before the page fires.

TraceLoop unifies application performance, infrastructure metrics, logs, distributed traces, alerts and incident analysis in one dark-fast platform — built in Britain, engineered for teams who carry the pager.

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telemetry ingested: 48 PB/mo
median query latency: 210ms
services observed: 140k+
platform availability: 99.99%

Live System Overview

A production dashboard, streaming right now

This is not a screenshot. It is the shape of a real TraceLoop workspace — live metrics, event stream and system health, updating in your browser.

live system overview

production · eu-west-2 · streaming telemetry

ALL SYSTEMS OPERATIONAL

requests / sec

8,412rps

p99 latency

142ms

error rate

0.12%

cluster cpu

46.8%

event stream

The Platform

Every signal. One timeline. Zero tool-hopping.

Eight capabilities that used to mean eight vendors, eight bills and eight different clocks. TraceLoop correlates all of them on one monotonic timeline.

Application Performance

Golden signals for every service — latency, traffic, errors and saturation — with RED dashboards that build themselves from your traces.

Infrastructure Monitoring

Hosts, containers, Kubernetes and serverless in one topology. Utilisation, saturation and cost per workload, refreshed every 10 seconds.

Logs

Schema-on-read log search at petabyte scale. Jump from any log line to the exact trace and span that produced it in one click.

Distributed Tracing

Tail-based sampling keeps every interesting trace. Waterfall, flamegraph and service-map views across 40+ runtime integrations.

Alerts

SLO burn-rate alerts, anomaly detection and static thresholds — routed to the right engineer with the right context attached.

Incident Investigation

Auto-assembled incident timelines: deploys, alerts, traces and logs merged into one story you can hand to the incident commander.

Integrations

OpenTelemetry-native, plus 120+ first-party connectors. If it emits telemetry, TraceLoop already speaks its language.

Case Studies

See how logistics, finance and healthcare teams cut MTTR, survive audits and keep p99 latency under budget with TraceLoop.

Inside TraceLoop

Dashboards your on-call team will actually like

Fictional workspace: checkout-platform, production, eu-west-2 — logs, traces, metrics, service topology and incident review, correlated on one clock.

requests / sec

8,412

▲ 4.2%

p99 latency

142ms

▼ 8ms

error rate

0.12%

stable

cluster cpu

46.8%

▲ 2.1%

log stream

service=checkout-platform · level>=debug · live tail

LIVE

14:32:07.441 INFO [api-gateway] route=POST /v1/checkout status=201 dur=42ms region=eu-west-2

14:32:07.502 DEBUG [auth-svc] token verified sub=usr_88f21 scope="checkout:write" cache=hit

14:32:07.688 INFO [payments-svc] auth captured txn=pay_5521c amount=£148.00 psp=stripe latency=38ms

14:32:07.940 WARN [checkout-svc] inventory hold retrying attempt=2/5 sku=LDN-4417 lock_timeout=250ms

14:32:08.115 INFO [kafka-events] produced topic=order.created partition=3 offset=9918422 lag=0

14:32:08.233 ERROR [postgres-01] deadlock detected txn=88412 victim=checkout-svc resolved=rollback

14:32:08.401 INFO [checkout-svc] txn retried txn=88412 status=committed dur=118ms trace=7c1f·9a2b

14:32:08.620 INFO [edge-lb] upstream healthy pool=api-gateway active=12/12 rps=8,412

trace waterfall

trace_id=7c1f9a2b · POST /v1/checkout · 412ms · 9 spans

1 ERROR

POST /v1/checkout

edge-lb

412ms

route.request

api-gateway

386ms

verify_token

auth-svc

37ms

create_order

checkout-svc

239ms

hold_inventory

checkout-svc

124ms

INSERT orders

postgres-01

49ms

INSERT orders (retry)

postgres-01

33ms

capture_payment

payments-svc

58ms

publish order.created

kafka-events

21ms

service map

checkout-platform · dependency topology · 8 services

2 DEGRADED

incident board

active and recent incidents · auto-linked to traces & deploys

4 OPEN

SEV1

Elevated 5xx on checkout-svc (eu-west-2)

INC-4417 · checkout-svc · opened 14:28 UTC · IC: A. Sharma

Investigating
SEV2

Kafka consumer lag > 50k on order.created

INC-4412 · kafka-events · opened 12:51 UTC · IC: P. Whelan

Identified
SEV2

Redis cache eviction rate above baseline

INC-4409 · redis-cache · opened 09:17 UTC · IC: D. Okonjo

Monitoring
SEV3

TLS cert expiring in 7 days — edge-lb

INC-4401 · edge-lb · opened yesterday · IC: E. Vance

Resolved

throughput by hour

requests · last 24h · aggregated 1h

0006121824

slo burn rate

checkout-availability · 99.95% · 30-day window

HEALTHY

error budget remaining71%

1h burn rate0.42×

6h burn rate0.68×

At current burn, the budget lasts 19 more days. No paging alert is expected this window.

Case Studies

Teams who stopped guessing

Fictional customers, real patterns: what happens when logs, metrics, traces and incidents finally share one timeline.

Harbourline Logistics

Freight & supply chain · 2,400 engineers-hours saved/yr

Cut mean time to resolution from 47 minutes to 6

Harbourline runs a 300-service fleet orchestration platform across three UK regions. Before TraceLoop, on-call engineers stitched together four tools to answer a single question: which container dropped the consignment scan? Correlated traces, logs and metrics in one timeline removed the guesswork.

faster MTTR: 87%
services observed: 300+
tools in the stack: 4 → 1

“We went from "which tool has the answer?" to "here is the answer". TraceLoop correlated a Kafka consumer lag spike to a single bad deployment in under a minute.”

Priya Whelan — Head of Platform Engineering, Harbourline Logistics

Meridian Capital Markets

Financial services · SEV1-free for 14 months

Sub-millisecond alerting for latency-sensitive trading

Meridian’s order-routing gateway must stay under a 5 ms p99. TraceLoop’s metrics pipeline ingests 1.2M points per second from the trading floor, and its anomaly alerts fire before human-visible symptoms appear — 31 early warnings in the last quarter alone.

metric points ingested: 1.2M/s
p99 gateway latency: <5 ms
early warnings last quarter: 31

“The anomaly detection caught a NIC firmware regression eleven minutes before it would have breached our latency SLO. That is the whole product in one story.”

Daniel Okonjo — SRE Lead, Meridian Capital Markets

Northgate Health

Healthcare · GDPR & DCB0129 compliant

Observability that passes clinical safety review

Northgate’s patient scheduling platform serves 1.8 million appointments a year. TraceLoop’s UK-region data residency, field-level log redaction and immutable audit trails let them add deep observability without slowing down clinical safety governance.

appointments/yr observed: 1.8M
platform availability: 99.99%
UK data residency: 100%

“Log redaction alone saved us a full engineering sprint per quarter. Our safety reviewers now get audit trails they actually trust.”

Dr. Eleanor Vance — Director of Digital Services, Northgate Health

Integrations

Speaks fluent OpenTelemetry — and 120+ other dialects

Agents, SDKs, collectors and webhook receivers for the stack you already run.

View all integrations

Kubernetes

Docker

AWS EC2

Azure VMs

GCP Compute

Terraform

Ansible

Nomad

PostgreSQL

MySQL

MongoDB

Redis

DynamoDB

Elasticsearch

ClickHouse

See every request. Solve every incident.

Start streaming telemetry into TraceLoop in under five minutes. No agents to babysit, no dashboards to build by hand.

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