AI visibility report
Sentry ranks #1 in Error Tracking & Crash Reporting AI search.
Outside the top three on 2 of the 25 prompts buyers actually ask.
Rollbar is cited on 2 of those losses.
Free trial. Setup comes pre-filled for Sentry.
Also benchmarked
Sentry appears in another vertical
Track Sentry across these prompts daily.
Start free trialBest among 11 vendors · still absent from 64.7% of tracked prompt responses
Top-3 citations across 150 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Grok
Gemini Search
Perplexity
Google AI Mode
ChatGPT
Bing CopilotLeader, with room to expand. Sentry leads this category on presence and share of voice, but appears in only 35.3% of tracked prompt responses. The priority is defending current wins while expanding absolute coverage.
Where Sentry is losing
Prompts where competitors are visible and Sentry is not.
These prompt-level losses are the first prompts to track and repair.
Where Sentry is winning5
What event volume limits should I expect from error tracking platforms at scale — and which ones have the most predictable pricing as volume grows?
Avg # 1.0 · 1 platform
Which error tracking platforms handle source map uploads well so you see original TypeScript line numbers instead of minified bundle references?
Avg # 1.0 · 3 platforms
Which error tracking platforms buffer events locally during outages and replay them when connectivity is restored, rather than dropping events?
Avg # 1.0 · 2 platforms
Which error tracking platforms handle background job errors as well as request-response errors from a web server?
Avg # 1.0 · 2 platforms
Which error tracking platforms handle error storms gracefully when a bad deploy suddenly generates millions of events per minute?
Avg # 1.0 · 3 platforms
Where Sentry is losing2
Which error tracking platforms offer the best sampling rate controls to manage cost and noise in production without missing critical low-frequency errors?
Competitors on 2 platforms
Track this promptWhich platforms offer both error tracking and full session replay in one tool — and when does a team actually need both together?
Competitors on 1 platform
Track this prompt
Track Sentry daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Sentry is a San Francisco-based developer observability platform founded in 2012, widely recognized as the category-defining open-source error tracking tool. The platform captures, groups, and contextualizes errors, crashes, and performance issues in real time across web, mobile, game, and AI-powered applications. Sentry's unified approach connects error events, distributed traces, session replays, structured logs, and code profiling under a single correlated data model. Its Seer AI engine performs automated root-cause analysis and generates code patches directly from production context. Operating a self-serve SaaS model with SDKs for 100+ languages, Sentry serves over 150,000 organizations and 4 million developers globally, including Microsoft, Disney+, Anthropic, GitHub, Cloudflare, and Instacart.
Sentry is an application monitoring and error tracking platform that helps developers identify, reproduce, and fix software defects and performance regressions in production. It combines error monitoring, distributed tracing, session replay, structured logs, profiling, and AI-assisted debugging in one SDK-integrated platform, enabling engineering teams to go from alert to root cause to code fix without switching tools.
Key Facts
- Founded
- 2012
- HQ
- San Francisco, CA, USA
- Founders
- David Cramer, Chris Jennings
- Employees
- 400-500
- Funding
- $217M
- ARR
- ~$128M
- Customers
- 150K organizations
- Valuation
- ~$3B
- Status
- Private
Target users
Key Capabilities10
- Real-time error monitoring with automatic issue grouping, deduplication, and full stack traces
- Distributed tracing across microservices, serverless, and third-party APIs
- Session replay with user-interaction recording, network capture, and privacy controls
- Seer AI debugger: automated root-cause analysis and merge-ready patch generation
- AI code review (Seer) that flags regressions in pull requests before merge
- Continuous and UI performance profiling
- Structured log capture correlated with errors and traces in a unified view
- Cron and uptime monitoring
- AI/LLM and AI-agent observability for prompts, tool calls, and token usage
- Mobile and game crash reporting via native SDKs for iOS, Android, Flutter, and React Native
Key Use Cases8
- Production error detection and triage for web, mobile, and backend applications
- Distributed system performance monitoring and slow query / N+1 diagnosis
- Reproducing user-reported bugs via session replay without manual repro steps
- AI-assisted automated fix generation for production incidents
- Mobile crash reporting and release health tracking
- LLM and AI-agent observability for AI-powered products
- Release quality tracking linking errors to specific commits, PRs, and code owners
- On-call alerting and incident response via Slack, PagerDuty, and Linear
Sentry customer outcomes
Anthropic's systems team uses Sentry to debug hardware-related production incidents; the systems lead credited Sentry as essential to the company's ability to scale, stating the team debugs most incidents entirely within the platform.
Disney+ relies on Sentry to maintain service quality for its tens of millions of global subscribers, with a director of Disney Streaming Services citing Sentry's tooling as a key factor in service reliability.
Instacart adopted Sentry as its most reliable software issue signal across services regardless of language or framework, with an infrastructure software engineer noting it is used throughout the organization.
Recent Trend
How AI describes Sentry3
Sentry (with enterprise or integrated observability features): Primarily an error-tracking tool, but in enterprise contexts it can be combined with traces and logs in a unified view within the same platform, reducing the need to switch dashboards.
Which error tracking platforms integrate natively with observability stacks — metrics, tracing, and logs — so you don't need two separate dashboards?
Sentry * Datadog * New Relic * Splunk (Observability) * Dynatrace * Elastic Observability (Elastic APM) Notes on how they achieve correlation: * Propagation of trace context: The frontend app starts or parti...
Which error tracking platforms can correlate a frontend JS error with the backend API call that caused it across a distributed trace?
Sentry * Supports server-side errors (web requests) and background/job errors (e.g., workers, background queues) with unified dashboards, context, and error grouping.
Which error tracking platforms handle background job errors as well as request-response errors from a web server?
Most cited sources8
20Application Performance Monitoring & Error Tracking Software | Sentry
sentry.io·Landing Page
- B12
Next.js Observability Gaps & How to Close Them | Sentry Blog
blog.sentry.io·Blog Post
- D6
Loader Script | Sentry for JavaScript
docs.sentry.io·Documentation
- 5
NextJS Error and Performance Monitoring | Sentry
sentry.io·Landing Page
- 5
Sentry vs LogRocket | Sentry
sentry.io·Landing Page
- 4
Jira + Sentry Integration | Sentry
sentry.io·Landing Page
Alternatives in Error Tracking & Crash Reporting6
Sentry positions itself as the developer-first, open-source-rooted application monitoring platform differentiated by a unified data model that correlates errors, distributed traces, session replays, structured logs, and profiling in a single view.
- Its SDK-based onboarding (no agents, five lines of code) and self-serve model—accounting for roughly 70% of revenue—drive bottom-up viral adoption within enterprises.
- The Seer AI engine, which performs automated root-cause analysis and generates merge-ready code patches directly from production error context, is a key current differentiator versus narrower error trackers and broader APM suites alike.
Reviews
Praised
- Fast and easy SDK integration across languages and frameworks
- Rich error context including stack traces and suspect commits
- Session replay for bug reproduction without manual repro steps
- Reliable Slack alerting and notification routing
- Broad multi-language and multi-framework SDK support
- Distributed tracing across microservices
- Real-time issue detection and automatic grouping
- Seer AI root-cause analysis suggestions
Criticized
- Noisy alerts without careful SDK sampling and rule configuration
- Suboptimal automatic error grouping and fingerprinting
- Steep UI learning curve for new users
- Pricing escalates quickly at high event volumes
- Quota exhaustion and unexpected overage charges
- Seer AI features gated behind additional subscription cost
- Complex alert rule tuning required for clean production monitoring
Sentry earns strong ratings on G2 (4.5/5 from 516 reviews) and Gartner Peer Insights (4.4/5 from 44 reviews). Reviewers consistently highlight the ease of SDK integration, depth of error context (stack traces, suspect commits, session replay), and reliable Slack alerting as top strengths. Recurring criticisms include alert noise when misconfigured, suboptimal automatic error grouping, a steep UI learning curve for newcomers, and pricing that can escalate quickly at scale.
Pricing
Sentry offers four tiers. Developer (free): 1 user, 5K errors/month, 5M spans, 50 session replays, 30-day retention.
- Team
$26/month (billed annually), unlimited users, 50K errors, third-party integrations, Seer AI debugging available as add-on.
- Business
$80/month (billed annually), adds 90-day data retention, unlimited metric alerts with anomaly detection, advanced quota management, and SAML+SCIM.
- Enterprise
custom pricing with a dedicated technical account manager and premium support. Usage above included quotas is billed pay-as-you-go (e.g., $0.0003625 per error for 50K–100K errors on the Team plan). Seer AI autofix and code review features are an additional subscription on paid plans.
Limitations
- Users report that Sentry can produce excessive noise if SDK sampling and alert rules are not carefully configured.
- Automatic error grouping and fingerprinting logic is frequently cited as suboptimal, requiring manual adjustment.
- The UI is considered complex and overwhelming for new users.
- Pricing can escalate significantly at high event volumes, and quota management requires active monitoring to avoid unexpected overages.
- Seer AI features (autofix, AI code review) require a separate add-on subscription on top of base plan costs.
- Self-hosted deployment is available but may lack some cloud-only features.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Gemini Search | Perplexity | Google AI Mode | Bing Copilot | ChatGPT | Grok |
|---|---|---|---|---|---|---|
Capability5/5 cited (100%) | ||||||
Which error tracking platforms can correlate a frontend JS error with the backend API call that caused it across a distributed trace? | Your brand was cited | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking tools offer the best PII scrubbing and GDPR compliance features for stripping sensitive fields from payloads before they leave the browser? | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms handle background job errors as well as request-response errors from a web server? | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms handle error grouping best for flaky or non-deterministic errors with slightly different stack traces each time? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which platforms offer both error tracking and full session replay in one tool — and when does a team actually need both together? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Developer Experience5/5 cited (100%) | ||||||
What error tracking tools do teams typically use to manage the full workflow from alert to assignment to resolution in one place? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking tools handle deduplication and grouping best to reduce alert fatigue when a single bug triggers thousands of duplicate events? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms offer the best release tracking so teams can tell whether a new deploy made error rates better or worse? | Neither your brand nor a competitor was cited | A competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms integrate best into a developer's normal workflow — IDE plugins, chat notifications, or built-in triage dashboards? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms automatically capture the most useful context — breadcrumbs, user state, request data — so engineers can reproduce bugs without user help? | Your brand was cited | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Integrations & Ecosystem5/5 cited (100%) | ||||||
Which error tracking platforms offer the best webhook and event streaming support for building internal tooling on top of error data? | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms integrate natively with observability stacks — metrics, tracing, and logs — so you don't need two separate dashboards? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking tools integrate best with on-call and incident management systems to page the right person when a critical error spikes? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms have the best two-way sync with issue trackers so bugs automatically get created and closed in the right project board? | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
What tools help teams correlate error tracking data with feature flag releases to automatically flag which deployment introduced a regression? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Your brand and a competitor were cited |
Performance & Reliability5/5 cited (100%) | ||||||
What event volume limits should I expect from error tracking platforms at scale — and which ones have the most predictable pricing as volume grows? | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking SDKs have the lowest page load overhead and offer async or lazy-loading options to minimise impact? | Your brand was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Your brand was cited | Your brand and a competitor were cited | Your brand and a competitor were cited |
Which error tracking platforms offer the best sampling rate controls to manage cost and noise in production without missing critical low-frequency errors? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms buffer events locally during outages and replay them when connectivity is restored, rather than dropping events? | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms handle error storms gracefully when a bad deploy suddenly generates millions of events per minute? | Your brand and a competitor were cited | A competitor was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Setup & First Run5/5 cited (100%) | ||||||
What's the easiest error tracking and crash reporting platform to integrate into a React Native app for both iOS and Android from a single SDK? | Your brand was cited | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand and a competitor were cited |
What are the best error tracking tools for a Next.js app that handles both server-side and client-side rendering without doubling up on error events? | Your brand was cited | Your brand and a competitor were cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms handle source map uploads well so you see original TypeScript line numbers instead of minified bundle references? | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Your brand was cited | A competitor was cited | Your brand and a competitor were cited |
Which error tracking platforms are designed for microservices architectures where errors in one service can cascade into others? | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Your brand was cited | Neither your brand nor a competitor was cited | A competitor was cited | Your brand was cited |
I'm migrating error tracking to a new platform — which tools make it easiest to preserve historical data and recreate alert rules? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Your brand and a competitor were cited |
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Sentry | 35.3% | 39.3% | 20.7% | 9.3% | 90.7% | #26.5 | +0.51 |
| 2 | Rollbar | 33.3% | 22.9% | 13.3% | 19.3% | 64.7% | #37.1 | +0.36 |
| 3 | Bugsnag | 18.7% | 20.9% | 16.7% | 0.7% | 63.3% | #40.2 | +0.46 |
| 4 | Raygun | 15.3% | 6.2% | 1.3% | 14.7% | 19.3% | #28.5 | +0.40 |
| 5 | TrackJS | 11.3% | 4.8% | 0.7% | 2.7% | 4.7% | #29.5 | +0.38 |
| 6 | LogRocket | 8.7% | 3.1% | 0.7% | 2.0% | 14.7% | #35.3 | +0.46 |
| 7 | Highlight.io | 2.0% | 1.9% | 0.7% | 0.0% | 3.3% | #56.4 | +0.50 |
| 8 | Embrace | 1.3% | 0.6% | 0.0% | 1.3% | 0.7% | #16.7 | +0.68 |
| 9 | Airbrake | 1.3% | 0.4% | 0.7% | 0.0% | 6.7% | #52.5 | +0.30 |
| 10 | Jam.dev | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 11 | Luciq | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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