Comparison
Apselog vs Instatus
Instatus is a beautifully designed general-purpose status page company. Apselog is what happens when you take “status page” and rebuild it from scratch for products powered by LLMs. If your product is mostly traditional infrastructure, Instatus is a perfectly good choice. If your product IS an AI app, you want a tool that thinks like one.
The framing
Instatus has spent years polishing UI, subscriber flows, and multilingual support — all the polish you’d want for a non-AI SaaS. Apselog goes deep on the AI-specific signals: provider uptime across 10 LLMs, eval drift on your golden set, token-spend anomalies, AI-context incident summaries, tracing, and prompt versioning. We don’t try to be everything to every customer. We’re built specifically for the status page needs of LLM-powered products.
TL;DR
Same price tier — $0 free, $29/mo Pro. Same custom-domain story. End-user subscribers and embed badges are now at parity. The difference is everything else: Apselog ships 10 LLM provider probes preconfigured, nightly eval drift detection, token-spend anomaly alerts, AI-context incident summaries, tracing, prompt versioning, PII scrubbing, PagerDuty and Opsgenie integrations, multi-region probes, and custom theming. Instatus ships none of the AI-specific ones, because Instatus is a general-purpose status page. Pick by what your product actually is.
Feature comparison
| Feature | Apselog | Instatus |
|---|---|---|
Public status page with custom domain Both ship the table-stakes status page experience. | ||
Built-in probes for OpenAI / Anthropic / Gemini / Mistral / Groq / xAI / Replicate / Fireworks / Cohere / Together Apselog ships 10 provider probes preconfigured; Bedrock + Vertex get control-plane probes on Team. Instatus expects you to wire them up yourself. | ||
Golden-set eval drift detection (nightly accuracy tests) Catches silent model regressions a general-purpose tool can't see — the API returns 200 but accuracy dropped. | ||
Token-spend anomaly alerts (2.5x baseline → incident) Apselog turns a cost spike into a customer-visible incident before the invoice lands. | ||
AI-drafted incident summaries grounded in provider + eval + spend data AI-drafted, human-reviewed before publish. | ||
Distributed tracing across LLM calls Apselog ships request-level traces tied to incidents. Instatus doesn't model LLM calls at all. | ||
Prompt management with versioning Roll back a prompt the same way you roll back a deploy. | ||
PII scrubbing on ingested events Apselog scrubs PII at ingest. Out of scope for a generic status page. | ||
PagerDuty native integration Apselog: Events API v2 dispatch. Instatus: native connector. | ||
Opsgenie native integration Apselog: US + EU regions. Instatus: native connector. | ||
Scheduled maintenance windows Apselog: public-page banner. Both ship the standard workflow. | ||
Audit log Apselog: dashboard-action trail. Instatus: platform-level. | ||
Custom status-page theming (fonts, radius, colors) Apselog: sanitized tokens, no raw CSS. Instatus: full custom CSS. | ||
Multi-region probes Apselog: 3 regions (US + EU + APAC) on Team. Instatus: multi-region on paid tiers. | ~ | |
End-user subscriber notifications (email) Apselog ships email subscribers on every public page. Parity. | ||
Embeddable status badge for marketing / docs sites Drop-in badge with backlink. Parity. | ||
60-second probe cadence on Pro Pro tier runs probes every 60 seconds. Free tier is 2-minute. | ||
Multi-language / i18n status pages Instatus supports many languages out of the box. Apselog ships English only. | ||
Generic HTTP / port / TCP uptime monitors for any endpoint Instatus monitors any URL. Apselog is intentionally LLM-focused — that's the bet. | ||
Free tier with public status page Both offer $0 forever with a small attribution badge. | ||
Pro tier price (custom domain, no badge) Both at $29/mo. Same price, different AI feature surface. |
Where Apselog wins
The AI-specific surface Instatus structurally cannot cover
Six concrete advantages Apselog has today that a general-purpose status page — including a very good one like Instatus — cannot match without rebuilding around LLMs.
Ten provider probes that already know what to check
Setting up "is OpenAI up?" in a generic status page means writing a custom monitor against /v1/models, picking an endpoint that won't false-positive, and remembering to update it when the provider deprecates a route. Apselog ships 10 provider probes preconfigured — OpenAI, Anthropic, Gemini, Mistral, Groq, xAI, Replicate, Fireworks, Cohere, and Together — plus control-plane probes for Bedrock and Vertex on Team. New customer setup is closer to 5 minutes than an afternoon, and the probe code lives in lib/probes/providers.ts where it gets updated for everyone at once. Instatus expects you to read the provider docs and build the monitors yourself.
Eval drift catches what HTTP checks miss
When a provider silently ships a new weight, your endpoint still returns 200. Your monitors stay green. But your golden set scores drop 12% overnight and your support queue fills up Monday morning. Apselog replays a small set of representative prompts against your chosen model every night, scores them with an LLM-as-judge against a 7-day rolling baseline, and creates an Incident when the score drops 5% or more. This is the single feature on the matrix that no general-purpose status page — including Instatus — has. It is the reason this product exists.
Token spend as a first-class incident signal
A prompt injection that triggers a retry loop, a runaway agent, a customer accidentally setting max_tokens=10000 — these show up as a 10x cost spike before they show up as user complaints. Apselog ingests token-usage events, scans hourly against a 7-day baseline, and fires a HIGH-severity Incident at 2.5x and CRITICAL at 5x. The AI-drafted summary attempts to localize the cause from the data ('cost concentration in /chat endpoint suggests retry loop'). A generic uptime monitor never sees this signal — your bill arrives next month.
AI context for incident drafts
Better Stack ships AI postmortems and Checkly ships AI RCA, so the bar for 'AI-drafted status update' is rising fast across the category. The differentiator isn't the generation — it's the context the model gets. Apselog hands the drafting model the provider probe history, the affected golden set scores, and the relevant TokenUsageEvent window. The output reads like an engineer wrote it because the input is the same data an engineer would assemble. Instatus has no equivalent feature today, and even if they ship one tomorrow, they don't have the LLM-specific signal data to feed it.
Tracing, prompt versioning, and PII scrubbing — built in
Apselog now ships request-level tracing across LLM calls, prompt management with versioning, and PII scrubbing on every ingested event. None of these are theoretical roadmap items — they're shipped today. A general-purpose status page has no reason to model any of them, because it doesn't know what a prompt is. We treat them as table stakes.
Same price, radically different surface
Apselog Pro and Instatus Pro both land at $29/mo with a custom domain and no badge. For a non-AI SaaS, you get Instatus's polish for that $29 and that's a fair trade. For an AI app, the same $29 buys you eval drift, token anomalies, AI-context summaries, traces, prompt versions, PII scrubbing — none of which Instatus has. The price is the floor; the specialty is the ceiling.
Where Instatus wins (for general SaaS)
If you’re not building an AI app
Three places Instatus is genuinely the better tool — all of them outside the AI-app use case Apselog is built for.
Beautiful design and years of polish (for general SaaS)
Instatus is genuinely well-designed and has shipped status pages for a long time. If your product is a non-AI SaaS and the status page is mostly a marketing-adjacent artifact, Instatus is a defensible pick.
Generic uptime monitoring across any endpoint
Instatus monitors any HTTP / TCP / port target. If your product is a Postgres-backed Rails app with a Stripe dependency and an S3 dependency and one LLM call somewhere, Instatus covers all of those and Apselog covers exactly zero of the non-LLM ones. That is by design.
Multilingual subscriber pages
Instatus ships its status pages in many languages out of the box. Apselog is English-only with no near-term i18n plan. If you sell into multiple markets and need a Japanese or French status page on day one, that gap is real.
Decision
Which should you choose?
Pick Instatus if…
- · Your product is a non-AI SaaS — a Rails app, a Postgres-backed API, a B2B tool that touches one LLM endpoint as a side feature at most.
- · You need multilingual status pages on day one.
- · You value general-purpose design polish over LLM-specific signals.
Pick Apselog if…
- · Your product IS an AI app — if OpenAI, Anthropic, or any of the other 8 supported providers goes down, you have an outage.
- · You want to catch silent model regressions (the API returns 200, accuracy quietly drops 12%) before a support ticket finds them.
- · You want token-spend spikes to become incidents, not next month’s invoice surprise.
- · You want tracing, prompt versioning, and PII scrubbing in the same tool as your public status page — not stitched across three vendors.
- · You want AI-drafted incident summaries grounded in real provider and eval data, not generic templates.
- · You want end-user subscriber email and an embeddable badge — both shipped — and every AI-specific signal on top.
The honest framing
For non-AI SaaS, Instatus is a fine choice and we won’t pretend otherwise. For AI apps, the gap isn’t close — Instatus has none of the signals that matter when the failure mode is “OpenAI is up but our model is silently broken” or “a runaway agent just burned $4,000 in tokens overnight.” Same $29 price tier, completely different product. If you’re building anything where the letters “LLM” appear in your architecture diagram, the choice is Apselog.
Apselog v1 — what we don’t pretend
The honest small print
- Detection window is 2-5 minutes on Free, 60-second cadence on Pro. Cron interval plus revalidation. Honest about the floor; no synthetic sub-second checks we can’t back up.
- Ten providers, plus Bedrock and Vertex control-plane probes — OpenAI, Anthropic, Gemini, Mistral, Groq, xAI, Replicate, Fireworks, Cohere, and Together are fully supported. Bedrock and Vertex get control-plane probes (no token cost) on Team. If you need full inference probing for those two, that gap is real for now.
- Eval drift catches regressions on your test surface, not in the wild. If your golden set isn’t representative of real traffic, you’ll miss real degradations. The golden set is only as good as the prompts you put in it.
- Token-spend anomaly detection requires instrumentation. Your runtime has to POST usage events to our ingest API after each LLM call. It’s a real ask. We stay out-of-band so we never sit on your hot path.
- English-only status pages. No near-term i18n roadmap. If multilingual is a hard requirement, that’s an honest Instatus advantage.
Built for AI apps. Priced like an indie tool.
Free forever with the Apselog badge. $29/mo unlocks custom domain, 60-second probes, golden-set drift, token-spend anomalies, tracing, prompt versions, and subscribers.
See Apselog pricing →