Maple

Maple is an OpenTelemetry observability platform for teams working across distributed systems. It is best suited to developers who want traces, logs, metrics, and browser sessions connected in one workflow. Its flexible deployment options are a strong draw, but the Startup plan’s retention and usage caps call for careful planning.

Overview

Maple ingests traces, logs, and metrics and stores them in ClickHouse. The signals are linked for investigation: traces show request spans alongside logs and service data, while a structured log can lead directly to its trace. That makes Maple a practical fit for teams that need to follow failures across services rather than investigate each signal in isolation.

Browser session replay adds context from the user’s side. It records clicks, routes, console lines, and failed requests, linking sessions to traces through a shared session ID. Product events are unlimited and free during beta. Teams needing synthetic monitoring should look elsewhere; Maple does not provide it.

Key features

Telemetry, exploration, and alerts

Logs can be searched by severity, service, or attribute. Metrics have exploration, dashboards, service maps, and alerting, while alert rules can route to Slack, PagerDuty, Discord, Telegram, email, webhooks, and Hazel. These capabilities give engineering teams several ways to investigate and respond without separating their core telemetry workflows.

Integrations and automation

SDKs and guides cover Effect, Node.js, Next.js, Python, Go, Rust, Java, C#, Kotlin, and Laravel. Integrations also include Cloudflare, PlanetScale, GitHub, WarpStream, and Hazel. A hosted MCP server and documented REST API let agents and automation search telemetry, triage errors, build dashboards, and manage alert rules. That is useful for teams building automated operational workflows, though it does not replace the need to manage usage against plan limits.

Deployment and data control

Maple Cloud offers US and EU regions; EU telemetry is stored and processed in Frankfurt. The choice is permanent, so teams should settle residency requirements before creating a cloud setup. Self-hosting puts infrastructure and retention decisions in the customer’s hands. The source is released under FSL-1.1, with each release converting to Apache 2.0 after two years. For individual developers, Maple Local bundles ingestion, an embedded database, query API, and dashboard in one binary, without an account or cloud service.

Pricing

Maple has free self-hosted and local options, a 14-day trial, and paid plans from $39/mo. The free options suit different needs: Self-hosted costs nothing and leaves retention and residency to the operator, while Local costs nothing and runs on one machine without an account, cloud, or rate limits. Neither is a hosted cloud tier.

Startup costs $39 a month and includes 100 GB each of logs, traces, and metrics, plus 5,000 browser sessions. Beyond those allowances, each signal costs $0.30/GB and additional sessions cost $0.002/session. Product events remain unlimited and free during beta, but retention is 30 days. A private support channel is included. This plan is a reasonable starting point for teams whose volumes fit the quotas and whose investigations do not require longer retention; teams with sustained overages should account for the added charges.

Enterprise is custom pricing, from $2,000, and offers higher volume, custom retention, priority support, and the option to run in the customer’s own cloud account. It is the better fit for organizations that need more scale, longer or tailored retention, or that deployment arrangement. The 14-day trial gives prospective users a short period to assess the service before choosing a plan.

Platforms

Maple supports API, iOS, Linux, macOS, self-hosted, and web environments. The combination of cloud, customer-operated infrastructure, and local use gives teams room to choose a deployment model, while the fixed cloud-region selection is an important constraint for hosted deployments.

Who it's for

Maple suits engineering teams adopting OpenTelemetry that want traces, logs, and metrics together, especially when browser session context or automation through MCP and REST is useful. It also fits developers who want a standalone local tool, and organizations that need to self-host or run Enterprise in their own cloud account. It is less suitable for teams that need synthetic checks or cannot accept Startup’s 30-day retention and usage-based charges.

Pros and cons

• Pro: Traces, structured logs, metrics, and browser replay are connected, making it easier to move from a service signal to user-session context.
• Pro: Cloud, self-hosted, and local deployment cover distinct data-control needs, including a no-account local binary.
• Pro: MCP and REST support telemetry search and operational automation, with alert destinations spanning common team channels and webhooks.
• Con: Startup retention is limited to 30 days, which may not cover longer investigation or historical analysis needs.
• Con: Startup overages add per-GB and per-session charges, so costs rise when included quotas are exceeded.
• Con: A cloud region cannot be changed after selection, and synthetic monitoring is absent.

Alternatives

Observability Platforms is a useful category starting point for comparing tools. Choose Middleware if its free tier’s included 100GB of data, 1,000 RUM sessions, and 20,000 synthetic checks better match your monitoring needs. Dynatrace Kubernetes Monitoring is worth considering when Kubernetes-focused monitoring is the priority and its hourly per-pod billing fits better.

Grafana Cloud Application Observability may be the better choice for teams that prefer host-hour pricing, with a free tier that includes 2,232 host hours. New Relic Kubernetes Monitoring is an alternative for teams seeking a free option or an annual Pro commitment with unlimited full platform users and 100 GB of free data ingest. Uptrace may suit teams that want 50 GB free per month with unlimited users, services, and hosts.

Honeycomb is another freemium option, with its free plan allowing up to 20 million events per month, 100 million metrics data points per month, and two triggers. KloudMate may be a closer fit for teams whose volumes fit its free tier of 10 GB per month each for logs and traces, 15 million metric samples, and seven-day retention. Choose OpenSearch if an Apache 2.0 open-source option with no licensing fees is the priority.

Verdict

Maple is a strong choice for OpenTelemetry-oriented teams that want connected telemetry, browser replay, and a choice of hosted, self-managed, or local deployment. Its main advantage is the shared investigative context across signals and sessions. Look elsewhere if synthetic monitoring is essential, if 30-day Startup retention is too short, or if variable charges and an irreversible cloud-region choice do not suit your requirements.