New Maple Local: one binary, no account.

Open-source observability. Built on OpenTelemetry. Your agent reads it too.

Query your traces, logs, metrics, and session replay in under a second. $39/month includes 100 GB of each signal. No per-host or per-seat fees.

  • Self-host the whole thing

    Every line of Maple's source is on GitHub under FSL-1.1, and each release becomes Apache 2.0 after two years. Run it on your own infrastructure with no license call.

    Read the source
  • No proprietary agent

    Maple speaks plain OpenTelemetry. Point an OTLP exporter at it and keep the instrumentation you already wrote. If you leave, there is nothing to rip out.

    See instrumentation
  • Hosted in the US or the EU us eu

    Choose the EU when you sign up and your telemetry is stored and processed in Frankfurt. Same plan and price in both regions.

    About EU hosting
  • $39/month, 14-day free trial

    A card is required to start the trial and nothing is charged until it ends. No per-seat, per-host or per-query fees at any volume.

    See what it costs
Health, latency and errors across your system.

01 · Signals

Read the trace.

Every request as a span tree, attributes intact. Click a span and see what it carried.

An 18-span API trace waterfall with nested application and SQL operations

Search the logs.

Structured logs straight from OTLP. Filter by severity, service, or any attribute, then jump to the trace.

Structured log search with severity facets and attribute filters

Replay the session.

Every click, route, console line, and failed request. Replay and spans share one session id.

A browser session replay showing the recorded page and captured network requests

02 · Incident

From a 3 AM page to the line that caused it.

Four surfaces, one trace id. Every step below opens from the one before it.

  1. alert trace 4f9ac21e…8b7d40f2

    The alert arrives with context.

    Error rate on api-gateway crosses 5%. The alert carries the service, the threshold it broke and the spans that failed. Route it to Slack, Discord, Telegram, PagerDuty, email, or any webhook.

    An alert rule with its threshold, evaluation window and firing history
  2. trace trace 4f9ac21e…8b7d40f2

    The trace opens on the failing span.

    The failing request is a span tree with every attribute intact. Three Stripe retries sit at the bottom, red, each timing out at exactly 1.75 seconds.

    A span selected in the waterfall with its full attribute set open alongside
  3. logs trace 4f9ac21e…8b7d40f2

    The logs are already correlated.

    Jump from the failing span to its logs on the trace id. Retry exhaustion, connection pool at 20/20. The confirmation is on the same screen.

    A log detail with linked trace and span IDs, correlated events and full resource attributes
  4. agent trace 4f9ac21e…8b7d40f2

    Or hand it to an agent.

    Point Claude, Cursor, or any MCP client at Maple. It lists services, searches traces, reads the source, and proposes the fix.

    An MCP client walking the same incident: five tool calls from list_services to propose_fix, ending in a patch

03 · Local

Maple on your laptop, as one binary.

One maple executable runs OTLP ingest, an embedded database, the query API and the dashboard on 127.0.0.1. No account and no cloud.

$ brew install Makisuo/tap/maple

or curl -fsSL https://maple.dev/cli/install | sh

local · 127.0.0.1:4318 LIVE
maple start
🍁 maple · local mode
listening on http://127.0.0.1:4318
OTLP/HTTP POST /v1/{traces,logs,metrics}
query POST /local/query
dashboard https://local.maple.dev
· bundled UI: pass --offline
data ~/.maple/data
pid 48213 · stop with maple stop
one binary · one port nothing leaves 127.0.0.1

04 · Platform

Everything else you'd have bought separately.

Metrics, service maps, error grouping, alerting, and an MCP server, all on the instrumentation you already send.

01

Metrics & dashboards

Request rate, error rate, latency percentiles. Build the board yourself, or ask the agent to build it.

The metric explorer listing every metric with its type and cardinality
Metrics & Dashboards →
02

Service map

Live request flow across your services. The cascade you'd otherwise reconstruct from a postmortem, in the foreground.

A focused service neighborhood showing API, database, and cache dependencies with live request flow
Service Catalog & Map →
03

Error tracking

Errors grouped by type across every service, with trends over time, affected services, and sample traces attached.

Errors grouped by type with counts, affected services and last-seen times
Error Tracking →
04

Alerting

Alert on error rate, latency, Apdex, throughput, any query-builder chart or raw SQL. Incidents open and resolve on their own. Routed to Slack, Discord, Telegram, PagerDuty, email, or any webhook.

Alert rules with severity, signal type and current state
Alerting →
05

AI & MCP

Any MCP-compatible client can list services, search traces, read the source, and propose a fix. Open protocol, no plugin.

The MCP server page with endpoint and client setup
AI & MCP Integration →
06

Cloud & Kubernetes

Kubernetes ships as a Helm chart. PlanetScale, Cloudflare, GitHub, and the rest connect with one OAuth grant.

Kubernetes Monitoring →
05 · Sovereignty

Your data, your instrumentation, your bill.

OpenTelemetry in, no proprietary agent, and the source on GitHub the whole time. You can leave with everything you brought.

01 · Open source
Source on GitHub under FSL-1.1. Each release becomes Apache 2.0 after two years. Read every line, fork it, or self-host on your own boxes if your security review needs that.
02 · OpenTelemetry native
OTLP straight in. No proprietary agent. The instrumentation you write today moves to anywhere OTel-compatible tomorrow.
03 · Your perimeter
Run Maple on your own infrastructure, against a ClickHouse you operate and scale yourself. Your telemetry never has to leave your network, and retention and residency are your call.
04 · Honest pricing
Pay $39/month for 100 GB per signal, then a flat $0.30/GB. No per-host fees. No per-seat fees. The pricing page and your invoice show the same numbers.

06 · Kubernetes

The pod behind the slow span

Install a Helm chart and cluster metrics start flowing. Opt a namespace in, and a slow request takes you straight to the pod that served it.

A simple Helm chart
A small chart you can read in full.
Pods linked to spans
Go from a slow trace to the pod and node that ran it.
Cluster-state metrics
Deployments, replicas and pod status, collected by the chart.
$ helm install maple-k8s-infra maple/k8s-infra
pod heatmap · 192 pods · cluster cpu 44% LIVE
PODS 192
RUNNING 184
DEGRADED 6
FAILING 2
HOT >78% 11
default default 72
observability obs 32
kube-system kube-sys 40
ingress-nginx ingress 24
data data 24
CPU
0% 100% degraded failing

07 · Web analytics

Web analytics from the sessions you already record.

Visitors, page views, referrers, countries, devices. No second script, no second vendor.

One SDK
MapleBrowser.init records the session. Analytics, replay, and the trace all read from it.
Bots excluded by default
Crawlers are filtered out and the excluded count is shown.
Every row is a filter
Click a referrer or a country and the page narrows to it. Every session links to its trace.
The Web Analytics page: unique visitors, sessions, page views and bounce rate over the last 7 days, with the live visitor badge and the visitors and page views chart

08 · Agents

The same incident, run by an agent.

Point Claude, Cursor, or any MCP client at Maple's server. The transcript is the exact sequence of tool calls it makes, from a service list to a proposed patch.

Reads the code behind the trace
The agent pulls the source file behind a span, so the fix it proposes cites your actual code.
Writes back
Claim an issue, set its severity, attach a fix. The agent changes state in Maple as well as reading it.
OAuth, no plugin
Point any MCP client at the endpoint and sign in. Open protocol, nothing to install.
mcp · agent session LIVE
> ask maple
list services that errored in the last 15m
→ list_services { window: "15m", filter: "errors > 0" }
← 3 services
paymentserrors142p992.4s recoserrors38p99840ms shippingerrors6p99320ms
> investigate payments
→ find_errors { service: "payments", window: "15m" }
← 1 issue
stripe.charge declined  ·  142 events  ·  98 users
→ error_detail { issue_id: "iss_8a91" }
← root cause: idempotency key collision
sample trace: trace_9f3c · order 8421
→ propose_fix { issue: "iss_8a91", fix: "scope idempotency_key by user_id" }
← fix attached. opened pr#412.
> 
4 tool calls · 4.2s https://api.maple.dev/mcp
09 · The bill

The bill, line by line.

Side by side, at list price. The questions your finance team will ask, answered up front.

Line item Maple Datadog New Relic Grafana Cloud Dash0 SigNoz Axiom
Per-host fee None $15+ / host / mo None None None None None
Per-seat fee None None $10 first, then $99–349 / full-platform user / mo $8+ / active-user / mo None None None
Ingest pricing $0.30 / GB per signal $0.10 / GB + $1.70 / M indexed $0.40 / GB $0.55 / GB $0.60 / M spans or logs · $0.20 / M metric points $0.30 / GB · $0.10 / M samples $0.12 / GB + $0.20 / GB-hr
Default retention 30d default · custom 15d indexed logs (option shown) 30d logs · 8d traces 30d logs/traces · 13mo metrics 30d spans/logs · 13mo metrics 15d logs/traces · 1mo metrics Configurable · from $0.03 / GB stored
OpenTelemetry support Native Yes Yes Yes Native Native Native
License FSL-1.1 → Apache 2.0 Proprietary Proprietary AGPL components Proprietary MIT + commercial ee/ Proprietary
Self-host option Supported No No OSS components No Supported No
MCP / agent surface Hosted server Yes Yes Yes Yes Yes Yes

Competitor cells summarize public list prices, checked September 2026. Check each vendor's pricing page for current numbers. Maple's rate is the published per-GB rate, billed per signal. Use the calculator to project your monthly cost.

10 · Pricing

One plan, billed by the gigabyte.

One plan. 100 GB per signal included, then a flat rate. Nothing metered by host, seat, or query.

Startup 14-day trial
$39 /month

Everything is included.

$0
per host
$0
per seat
$0
per query
Start 14-day free trial

Free for 14 days · Cancel anytime · Card required to start

Hosted in the US or the EU (Frankfurt) at the same price. EU hosting

Included every month
Logs
100 GB
then $0.30 / GB
Traces
100 GB
then $0.30 / GB
Metrics
100 GB
then $0.30 / GB
Browser Sessions
5,000
then $0.002 / session
Product Events
Unlimited
free during beta

30-day retention · Private support channel · Unlimited dashboards · Advanced alerting · MCP server · AI chat · AI error triaging · Full API access

Estimate your bill →
Enterprise

Higher volume, custom retention, priority support.

Works with every language OpenTelemetry supports

FAQ

Common questions

What is Maple?
Maple is an observability platform for traces, logs, metrics and session replay, built on OpenTelemetry and backed by ClickHouse. It lets you collect, visualize, and query telemetry from distributed systems in real time, or let an AI agent do it for you over MCP.
Is Maple open source?
Maple's source is on GitHub under the Functional Source License (FSL-1.1). You can read every line, fork it, and self-host. Each release becomes Apache 2.0 two years after publication. You can run Maple yourself or use the hosted version.
Is Maple OpenTelemetry-native?
Yes. Maple is built on OpenTelemetry, the open, vendor-neutral standard for telemetry, so there are no proprietary agents. If you already emit OpenTelemetry data, you can point it at Maple without re-instrumenting your code.
How is Maple priced?
The Startup plan is $39/month with 100 GB of logs, traces, and metrics each included, then a flat $0.30 per GB. No per-host or per-seat fees. Enterprise plans add custom volume and retention.
Does Maple work with AI agents?
Yes. Maple runs an MCP (Model Context Protocol) server, so compatible AI agents can list services, search traces, find errors, and propose fixes directly against your telemetry.
Can I self-host Maple?
Yes. Run Maple on your own infrastructure against a ClickHouse you operate, using the Docker Compose setup in the repository. Maple Cloud is there for teams that would rather not operate it.
Where is my data stored?
Maple Cloud runs in two regions: the United States and the European Union (Frankfurt, Germany). You choose one when you create your organization, and all of its telemetry is stored and processed there. The region cannot be changed later. Pricing is the same in both. To keep the data inside your own network, self-host Maple.

Try it on your own traces.

14-day free trial, card required, no charge until it ends. Or self-host, or run maple start locally with no account at all.