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Epok vs Grafana + Loki

Loki stores your logs cheaply. Grafana visualizes them. But neither tells you when something is wrong — that's on you. You write the alert rules, build the dashboards, tune the thresholds, and maintain it all as your services change. Epok does that part automatically.

Plan a controlled evaluationInspect the live incident →

Representative production boundary · shadow mode · no cutover · pre-agreed scorecard

THE 14-DAY EVALUATION

Keep Grafana + Loki. Make Epok prove what it adds.

01

Choose a representative boundary

Mirror a service group, ownership domain, environment, or critical user journey through OTel or an open shipper.

02

Keep every alert

Grafana + Loki remains the control while Epok watches the same production window.

03

Score the incident cohort

Classify correct, incorrect, abstained, and missed outcomes; measure alert fanout, time to verified cause, and responder effort.

Success is not “data arrived” or one anecdote. Expansion requires performance across the agreed incident cohort and operational gates.

AT A GLANCE
Epok vs Grafana + Loki at a glance — what each product is, how it bills, who operates it, how data gets in, and how detection is set up.
DimensionGrafana + LokiEpok
What it isA stack you assemble: Loki for logs, Prometheus or Mimir for metrics, Tempo for traces, Grafana for dashboards and alerting.A multi-signal detection engine. Logs, metrics, traces, infrastructure, RUM and session replay correlated on one incident canvas.
Billing basisOpen source — no license fee. Your cost is the compute, object storage and engineering time to run and scale it.Each plan includes one unified volume allowance. Paid-plan overage is $0.20/GB; there is no per-host, per-user, per-custom-metric, per-query or cardinality line.
Who runs itYou do. Self-hosting means capacity planning, upgrades, sharding and being on call for the observability stack itself.Hosted SaaS. Nothing for you to deploy, scale or upgrade.
Data collectionOpen standards: Grafana Alloy, Prometheus scrape, OpenTelemetry.No proprietary Epok server agent: send with OTLP or an open shipper such as Vector, Fluent Bit, Fluentd or the OpenTelemetry Collector. Browser RUM and replay require web instrumentation.
How detection is set upGrafana Alerting rules you author in LogQL and PromQL.Immediate rule packs begin matching supported signals as data arrives. Statistical detectors activate after they have the required history and signal coverage; threshold rules remain available when you want them.

Grafana + Loki facts checked against Grafana Loki (open source) on 2026-08-03. Vendors change packaging and pricing — tell us if anything here has gone out of date and we'll fix it.

SIDE BY SIDE
Capability
Grafana + Loki
Epok
Pricing model
Grafana + LokiOpen source (self-host + ops time) or Grafana Cloud (metered). You build and maintain the alerting and dashboards.
EpokFlat monthly. Detection and root cause come built — nothing to wire up.
Log storage
Grafana + LokiLoki stores logs in object storage (S3, GCS, MinIO) with a label-based index. Cost-efficient at scale.
EpokPurpose-built columnar log store on local SSD. Schemaless ingestion, automatic compression.
Search language
Grafana + LokiLogQL — label selectors plus pipeline stages. Familiar if you know PromQL.
EpokA purpose-built log search syntax. Full-text search, field filters, stats aggregation.
Dashboards
Grafana + LokiGrafana is best-in-class. Hundreds of panel types, templating, annotations, alerting integration.
EpokBasic. Service dashboards, volume charts, detector views. Not a general-purpose visualization platform.
Anomaly detection
Grafana + LokiManual alert rules only. You write LogQL/PromQL queries, set thresholds, and maintain rules per service.
EpokAutomatic across every signal — new failures, anomalies, silent services, regressions, and cascades.
Root cause analysis
Grafana + LokiNone. Investigation is manual: write queries, compare dashboards, trace through logs.
EpokAutomatic. What Changed analysis, dimension lift, causal ordering, cross-service cascade timeline, AI explanations.
Grouping repeated errors
Grafana + LokiNone built-in. Some community plugins exist for basic log pattern analysis.
EpokAutomatic. Errors that share a shape fold into one alert, so dozens of variants don't become dozens of pages.
A service going silent
Grafana + LokiManual. Requires absent()/absent_over_time() in PromQL, per metric, per service. Easy to miss.
EpokAutomatic, with awareness of expected quiet periods — catches a service that stops logging when it normally logs.
Setup effort
Grafana + LokiLoki: hours to stand up, weeks to make production-grade, then ongoing operator time to maintain.
EpokSend logs over HTTP. Detectors activate automatically. No dashboards to build, no alert rules to write.
Protocol support
Grafana + LokiLoki push API (Promtail, Grafana Alloy, FluentBit plugin). OTLP in newer versions.
EpokLoki push (native), Elasticsearch bulk, OTLP, FluentBit, Fluentd, syslog, CloudWatch, raw JSON. Same Promtail/Alloy config works.
Unified observability
Grafana + LokiYes. Grafana unifies Loki, Prometheus/Mimir, and Tempo in one UI — you wire up the sources and dashboards.
EpokYes. Logs, metrics, traces, RUM, and replay correlated on one canvas by shared trace ID — automatically.

Where Grafana + Loki wins

If you already run Prometheus + Tempo + Loki, Grafana gives you a unified view across all three telemetry types in one UI, and a vast library of community dashboards and plugins for slicing that data exactly how you want. Epok correlates signals automatically rather than handing you a canvas to build — if your team prefers fully custom, hand-built dashboards, Grafana is the deeper toolkit.

Loki's label-based architecture means storage costs scale with cardinality, not message size. And the Grafana ecosystem — community dashboards, 200+ plugins, and a massive user base — means you're never starting from scratch when you need a custom visualization.

CHOOSE EPOK WHEN
  • —You want automatic anomaly detection and root cause analysis without writing LogQL alert rules or maintaining dashboards.
  • —Your team is small and you don't have engineering hours to spend on observability infrastructure setup and maintenance.
  • —You want detection on day one, not after weeks of dashboard building and threshold tuning.
CHOOSE GRAFANA + LOKI WHEN
  • —You already run Prometheus and Tempo and want unified logs/metrics/traces in a single Grafana instance.
  • —You need extensive custom dashboards with templated variables, annotations, and cross-data-source correlations.
  • —You have platform engineers who can invest time in Loki operations, alert-rule authoring, and dashboard maintenance.
EVALUATION SETUP

Add Epok as a second destination first.

Epok accepts the Loki push protocol natively. If you run Promtail, Grafana Alloy, or any client that pushes to Loki's /loki/api/v1/push endpoint, point a copy at Epok. Same protocol, same config, same labels.

You can run both side by side. Keep Grafana for hand-built dashboards. Let Epok watch your logs, metrics, and traces for anomalies and draft the root cause. They complement each other.

Read the dual-shipping guide →

Keep Grafana + Loki. Make Epok prove the incident outcome.

Run a controlled shadow evaluation across a representative boundary. Compare both systems on the same incident cohort, then expand only after Epok clears the agreed quality, security, and operational gates.

Plan a controlled evaluationOpen the live demo →See pricing

* Capability comparisons, and any time or effort estimates, reflect our reading of publicly documented features and our own deployment experience as of August 3, 2026. They may not capture every plan, feature, or recent change — verify current capabilities directly with each vendor.

Datadog, New Relic, Splunk, Elastic, Grafana, Loki, Amazon CloudWatch, and other product and company names are trademarks of their respective owners. Epok is not affiliated with, endorsed by, or sponsored by them.