Looking to migrate from ReportPortal? Compare ReportPortal vs TestDino. TestDino sets up in five minutes, embeds Playwright traces inline, and runs AI triage.
ReportPortal is an open-source test reporting and analysis platform built to aggregate results across frameworks and CI systems. It ships an ML-based auto-analyzer that clusters failures and links them to known defects, and it can be self-hosted on Docker Compose with Elasticsearch and RabbitMQ, or purchased as a SaaS plan. For Playwright teams evaluating ReportPortal vs TestDino, the trade-off is infrastructure versus focus. TestDino is a Playwright-native test intelligence platform that plugs into playwright.config.ts as a single reporter. Runs stream in real time, every failure opens an inline trace viewer with DOM snapshots, network calls, and console logs, and AI triage classifies each result the moment it lands.
Beyond reporting, TestDino ships built-in test management designed for how engineering works in 2026: test cases live alongside run history, manual runs and exploratory sessions roll up under date-bound releases, and the full test record is queryable by Claude Code, Cursor, or any MCP-compatible agent.
Here's how ReportPortal vs TestDino breaks down for Playwright teams. Where TestDino helps and where ReportPortal doesn't reach.
Five-minute setup, no infrastructure
The TestDino reporter installs with one npm package and two environment variables. Runs stream into the dashboard on the first CI push. No Docker Compose, no Elasticsearch, no RabbitMQ, no ops team required.
Inline failure context on every test
Every failed test opens with an embedded trace viewer showing DOM snapshots, network calls, and console logs, plus screenshots, video, and per-attempt error groups by message, stack trace, and location. Failure investigation happens where the result is.
Built for Playwright, not adapted to it
TestDino treats project structure, browser channels, retries, and annotations as first-class concepts. There's no JUnit-style abstraction between the reporter and the data.
Predictable pricing, no support packages
$39/month billed annually for up to 3 users with 10,000 executions, AI failure classification, MCP Server, and SSO included. The free tier covers 5,000 executions and every core feature.
Heavyweight infrastructure to run
Self-hosted ReportPortal requires Docker Compose with five microservices: the API service, UI service, analyzer service, Elasticsearch, and RabbitMQ. Teams that can't run that infrastructure use the SaaS plan starting at $599/month.
Trace viewer is external
ReportPortal does not embed the Playwright trace viewer. Inspecting a trace means downloading the trace.zip attachment and opening it at trace.playwright.dev or in a local Playwright viewer.
JUnit-style abstraction for Playwright
Playwright integrates through a JUnit XML reporter. Project structure, browser channels, retries, and annotations don't surface as native concepts. Teams lose the depth that makes Playwright results useful.
Add-on costs for production support
ReportPortal's service packages run $10,000 to $50,000 per year for dedicated support, onboarding, and customization. Standalone Playwright teams adopting the tool for reporting pay well beyond what reporting should cost.
| | |
|---|---|---|
| Pricing (starts at) | $39/month (billed annually) | $599/month (SaaS) |
| Best for | Playwright test intelligence & management | Reporting with history and clustering |
| Playwright integration | Native (trace viewer, error grouping, MCP) | Via agents |
| Ease of use |  |  |
Getting Started | ||
| One-step CI setup | One reporter line, streams live | Docker Compose setup |
Dashboards & Reporting | ||
| Unified Playwright dashboard | Custom widgets | |
| Multi-tab test run detail view | Summary, History, AI Insights & more | Launch-level view |
| Pull request insights (per-PR history) | ||
| Test ExplorerBrowse tests as a hierarchy, a flat list, or by tag. | Launch tree | |
| Real-time streaming of results | Per-shard/worker | |
| Scheduled PDF reports (email) | Daily/Weekly/Monthly | |
Test Analytics | ||
| Analytics: trends & patterns | Widget-based | |
| Code coverage, per-file | Istanbul, run-level | |
| Environment analytics | Pass-rate/flaky by env | Via attributes |
Debugging & Evidence | ||
| Built-in Playwright trace viewer | ||
| Screenshots & video replay | ||
| Console logs (per test) | Node + browser | If attached |
| Visual diff comparison | ||
| Smart error grouping | Message/stack/location | Pattern matching |
| Flaky detection (+ stability %) | Requires config | |
| Playwright Tags and AnnotationsAttach priority, owner, links, and metrics to tests. | Priority/owner/links/metrics | Custom attributes |
CI/CD Optimization | ||
| GitHub CI Checks quality gates | Per-env + mandatory tags | |
| Branch → environment mappingMatch each Git branch to the environment it runs against. | Exact/regex | |
| Sharded / parallel run support | Per-shard live view | Parallel launches |
| Native CI breadth | GitHub, GitLab, Azure DevOps, TeamCity, Bitbucket, CircleCI, Jenkins | Agents/plugins |
| Self-managed GitLab | ||
Test Management | ||
| Test case management (suites, ownership) | ||
| Bulk test case creation from PRDs / Jira / stories | via MCP | |
| Release tracking (releases/cycles/sprints) | ||
| Exploratory/manual sessions | ||
| Import/export test cases | JSON/CSV/ZIP | Via API |
AI & Automation | ||
| Local MCP (IDE agents) | Cursor/Claude Code/Copilot | |
| Remote MCP (web AI) | ||
| AI test run summary on GitHub PRs | ||
| AI test suite audit (audit score + report) | ||
| AI failure classification | ML-based auto-analysis | |
Integrations & Collaboration | ||
| Bug tracking breadth | Jira, Linear, Asana, monday | Jira, Rally |
| Slack notifications with run summaries | ||
Platform & Security | ||
| Public API & CLIs | REST + @testdino/playwright | REST API |
| Project-level AI controls | Per-feature toggles | |
| Compliance & certifications | ISO 27001, SOC 2 Type II, GDPR | Self-managed (your infra) |
Plans & Pricing | ||
| Plan tiers | Free · Pro $39 · Team $79 · Enterprise | OSS free (self-hosted) · SaaS $599 · Enterprise |
| Free executions | 5,000/mo | Unlimited (self-host) |
| Support | Chat + Slack Connect + Priority email | Community / Paid |
| Start for Free | ||
Feature-by-feature breakdown showing how each tool handles the areas that matter most to testing teams.
ReportPortal's dashboard is built from customizable widgets: launch statistics, investigated percentage, passing rate, and trend charts. Teams configure these manually. There's no PR view tied to commits and files changed, and scheduled PDF exports aren't available out of the box.
ReportPortal attaches screenshots and logs to failed tests and clusters errors via the ML auto-analyzer. Playwright trace files are downloadable as attachments, but the trace doesn't render inside ReportPortal. Inspecting one means opening trace.playwright.dev or a local viewer separately.
The ML auto-analyzer clusters failures based on error messages and stack traces, then links clusters to known defects when patterns match. Teams seed the analyzer by manually investigating past launches. There are no AI-generated summaries posted to GitHub or Slack, and no confidence scores on individual failures.
npx -y @testdino/mcp@latest. Agents in Cursor, Claude Code, and Claude Desktop query test runs by branch, environment, commit, time, or author through list_testruns, debug failures with full trace and artifact context through debug_testcase, and rank flaky tests across recent runs.ReportPortal doesn't ship an MCP Server. AI coding agents in Cursor, Claude Code, or Claude Desktop can't query Playwright failures, pull trace context, or create test cases through agent workflows. Community-built integrations exist for launch management and analyzer operations, but they don't expose Playwright failure context.
Quality Gates is a Premium feature available across all SaaS tiers. Branch-regex environment mapping and merge-blocking GitHub status checks aren't part of the platform. Environment context is added through Launch attributes that teams maintain manually.
ReportPortal isn't a test management tool, so there are no test cases, suites, plans, or manual testing workflows.
Purpose-built capabilities that help Playwright teams ship faster and debug smarter.
Where each platform leads, and where it falls short.
ReportPortal is an open-source test reporting platform designed to aggregate results across frameworks and CI systems.
ML-Based Auto-Analyzer
Clusters failures by error message and stack trace patterns, then links clusters to known defects using past investigation history as training data.
Open-Source and Self-Hostable
Apache 2.0 licensed with 14K+ GitHub stars. Teams with infrastructure resources can self-host and extend via REST API and plugin architecture.
Framework Breadth
Integrates with Java (TestNG, JUnit, Cucumber), Python (pytest, Robot), JavaScript (Jest, Cypress, WebdriverIO), and more via a JUnit XML or native agent.
TestDino is a Playwright-native AI test intelligence platform that brings inline trace viewing, AI classification, and failure analytics into one focused reporter.
TestDino MCP Server
Lets AI coding agents query Playwright test runs, debug failures with full retry and artifact context, detect flaky tests, and manage manual test cases and suites, all from the editor.
Inline Playwright Debugging
Trace viewer, screenshots, video, and console logs all open inline on the failed test. No downloading trace.zip, no external viewer.
Native Playwright Reporter
Plugs into playwright.config.ts with one npm package. Project structure, browser channels, retries, and traces all surface as first-class concepts.
Predictable, Standalone Pricing
$39/month billed annually for up to 3 users with SSO and MCP included. No infrastructure overhead, no service package multipliers.
Verified reviews from QA and engineering teams running Playwright in production.
Analyzing failed Playwright runs in CI used to eat up a lot of our time. TestDino solved that with a centralized dashboard that pulls in screenshots, logs, and failure trends in one place. What's been most useful is the automatic grouping of failures, since instead of checking each failing test individually, we can immediately see patterns and likely causes. It's made triaging failures, and identifying which tests are simply flaky, dramatically faster.
Lead Software Engineer
We inherited an existing test suite without much context on how it was built, and TestDino gave us a real way to take ownership of it. It shows us clearly which tests are the slowest, the flakiest, and the ones failing most often, which has been essential for knowing where to focus our effort. It's given us the visibility to understand the current state of the code and steadily improve its reliability.
Senior QA Engineer at Penpot by Kaleidos
I monitor everything my tests do, from the full list of tests to detailed error screenshots. The GitHub integration is smooth, so commit hashes, CI runs, and HTML reports open straight from the dashboard. I use TestDino almost every day, and it has improved the quality of our automation code.
Lead QA Automation Engineer
Before TestDino, we were manually digging through raw reports to catch flaky and failing tests, and it took a lot of time. Now everything is stored and analyzed automatically, with no extra setup layers needed. The installation itself was simple, and it's made spotting flaky tests a much faster, cleaner process for our team.
Test Automation Team Lead
TestDino gives us a clean dashboard and reporting setup that's genuinely easy to work with, packed with useful analytics. It's effectively replaced what used to be a custom Power BI dashboard for us, while being far simpler to set up and maintain. The platform makes it easy to centralize and visualize results, so tracking trends and understanding failures no longer takes extra effort.
QA Automation Engineer
Reviewing our Playwright test results used to mean sifting through raw output to figure out what actually broke. TestDino changed that by giving us a clear, structured view of every run. Failed tests are easy to spot right away, and debugging that used to take real effort now moves a lot faster.
Automation Engineer
Enterprise-grade security so your team can focus on shipping instead of worrying about data.
Secure authentication, role-based access control, and data encryption safeguard your test data in transit and at rest.
Persistent analytics with historical tracking deliver reliable insights about test performance, coverage, and release readiness.
Automated backups and retention policies maintain a complete history of test data. Project-scoped access prevents unauthorized changes.
ReportPortal is free to self-host but carries infrastructure and support costs. TestDino offers flat monthly pricing for Playwright-focused teams.
Multi-tenant SaaS project space. Self-hosted is free but requires Docker Compose with Elasticsearch and RabbitMQ.
Multi-tenant shared SaaS instance
ML auto-analyzer for failure clustering
Quality Gates (SaaS add-on)
Unlimited users
Up to 12 months data retention
REST API and plugin architecture
30-day free trial
For dev teams shipping to production. Flat pricing, no infrastructure, no per-user multiplier.
10,000 test executions per month
Up to 3 users
60-day data retention
AI failure classification with confidence scores
TestDino MCP Server with test case writes
PR view and CI/CD optimization
Embedded trace viewer and debugging features
Integrations with Jira, Linear, Asana, Slack
Stop wasting time on
flaky tests
Yes. The Playwright trace viewer renders directly on the failure detail panel with DOM snapshots, network calls, and console logs, alongside screenshots and video on every failed attempt. You don't download trace.zip or open an external viewer.
Side-by-side comparisons of features, pricing, and integrations to help you pick the right testing tool.
