Grafana Cloud vs Sentry: A Complete Comparison for 2026

For most of the last decade, these two products sat side by side in the same stack without competing. Sentry caught the exceptions in your code. Grafana showed you what the servers were doing. Teams paid for both and connected them with a data source plugin.

That division is wearing thin. Sentry's structured logs reached general availability in September 2025, and it now sells tracing, continuous profiling, session replay, uptime and cron monitoring, and an AI debugger called Seer that opens pull requests. Grafana Cloud, meanwhile, has added Frontend Observability for browser errors and sessions, Application Observability for services, an incident and on-call product, and AI that investigates across its data. Both are reaching into the other's territory, which raises a question many teams have not had to ask before: do you still need both?

The answer depends on where each one starts. Sentry is a developer debugging platform organized around the issue, the grouped error that links a stack trace to the commit, logs, trace, and replay behind it. Grafana Cloud comes from the other direction. Grafana Cloud is a managed observability platform built on open-source backends, pairing Mimir, Loki, Tempo, and Pyroscope for metrics, logs, traces, and profiles, all viewed through Grafana dashboards.

This comparison covers each product's starting point, error tracking, logs, metrics and infrastructure, tracing and profiling, frontend monitoring, AI, alerting and incidents, pricing, deployment, and whether running both still makes sense.

Quick comparison

The table covers the basics. Several rows show overlap that did not exist a few years ago.

Where each one starts

The products feel different from the first screen, because they are organized around different objects.

Sentry starts from SDKs in your application. Each exception arrives with its stack, the events leading up to it, and request details, and Sentry folds repeats of the same problem into one issue. Everything else it has added attaches to that issue, so one page shows the error, the logs around it, the trace it belonged to, and often a replay of what the user did.

Grafana Cloud starts from signals. Agents and OpenTelemetry collectors send metrics, logs, traces, and profiles into separate managed backends, and Grafana dashboards, Explore, and alert rules sit on top. You can begin anywhere, with a CPU graph, a log query, or a slow trace, and move between signals that share labels.

The practical difference: Sentry answers "what broke in my code and why" with very little setup. Grafana answers "what is the system doing" across far more of the stack, with more configuration.

Error tracking

Sentry's home ground, and still its strongest feature.

Sentry's grouping model deduplicates similar errors into issues, suspect commits point to the change that likely caused a new error, ownership rules send issues to the right engineer, and release health reports the share of sessions that crashed in each version, so a broken release becomes visible early. If you evaluate error tracking alone, Sentry's depth is hard to match.

Grafana Cloud handles errors differently. Frontend Observability, built on the open-source Faro SDK, captures browser errors and groups them alongside web vitals and sessions. On the backend, errors show up as log lines in Loki, failed spans in Tempo, and error-rate metrics in Application Observability. That works well for spotting that error rates rose, but it lacks Sentry's issue workflow: no suspect commits, no ownership routing, no per-issue resolution tracking for backend exceptions.

If you are deciding how Sentry fits against other full platforms, our Datadog vs Sentry comparison covers the same question with a different observability vendor.

Logs

Both now sell logs, for different jobs.

Grafana Cloud Logs runs on Loki, which indexes labels rather than full log content and queries with LogQL. It accepts logs from anywhere, including infrastructure, Kubernetes, and applications, and keeps them for 30 days on Pro with extra retention available. Pricing is split into process, write, and retain charges, about $0.45 per GB ingested above the 50 GB included each month.

Sentry Logs attaches trace and span IDs to every entry automatically, so moving from a log line to the request waterfall is a single click, and structured attributes are searchable without parser setup. Most of those logs arrive through the Sentry SDKs or a few supported drains. They cost $0.50 per GB beyond the 5 GB included, and Sentry itself positions them as a debugging aid rather than a replacement for log management.

Metrics and infrastructure

This is where the two products differ most, and Grafana wins outright.

Grafana Cloud Metrics, built on Mimir, is Prometheus-compatible and keeps metrics for 13 months on Pro. Kubernetes Monitoring, prebuilt integrations, and Application Observability turn that data into ready-made views of clusters, nodes, pods, and services. Pricing is $6.50 per 1,000 billable series above the 10,000 included, which makes cardinality the main cost to manage.

Sentry has no host metrics, container metrics, or infrastructure view. If an error traces back to an overloaded database server or an unhealthy node, Sentry can show you the exception but not the machine behind it. Teams that run Sentry alone almost always add another tool for infrastructure. For a look at how Grafana Cloud's metrics compare with another full platform, see our Datadog vs Grafana Cloud comparison.

Tracing and profiling

Both trace requests and profile code, in different ways.

Grafana Cloud Traces runs on Tempo, accepts OpenTelemetry natively, and queries with TraceQL. Pyroscope adds continuous profiling across languages, and both share Grafana's process, write, and retain pricing, with 50 GB of each included per month.

Sentry's tracing is SDK-instrumented, which means spans exist wherever an SDK is installed and link back to the related errors and replays. Its continuous profiling is a real strength, showing which function on which line is making an endpoint slow. Uninstrumented services and infrastructure hops do not appear in Sentry traces. Sentry includes 5 million spans on paid plans, with pay-as-you-go pricing after that.

Frontend monitoring and session replay

Sentry's Session Replay reconstructs the DOM rather than recording pixels, prioritizes sessions that hit errors, masks sensitive data by default, and can summarize a session in text so nobody has to sit through the recording. It covers web and mobile.

Grafana Cloud Frontend Observability tracks web vitals, browser errors, sessions, and user journeys, and links frontend requests to backend traces in Tempo. It is aimed at understanding frontend performance across many users more than at reproducing one user's bug.

AI and MCP

Each vendor's AI reflects its starting point.

Seer pulls together everything Sentry knows about an issue, from the stack and surrounding logs to replays, recent commits, and the source itself, then proposes a fix, often as a pull request ready for review. Seer Agent extends that to open-ended questions, and Sentry's MCP server gives Claude Code and Cursor the issue context. Seer costs $40 per month for each active contributor, meaning anyone with at least two pull requests in a connected repository, on top of your plan.

Grafana's AI works across telemetry. Grafana Assistant writes PromQL, LogQL, and TraceQL, builds dashboards, and carries out multi-step investigations, and Sift runs automated checks for error spikes, latency changes, and resource contention during incidents. Grafana Cloud includes 3 active Assistant users, with additional users starting at $20 each. Grafana's open-source MCP server exposes dashboards, data sources, and alerting to AI clients.

The split is clean. Seer fixes bugs in your code and cannot see your hosts. Grafana's AI investigates systems and does not write code fixes.

Alerting, incidents, and status pages

Sentry detects problems. Grafana can also run the response.

Sentry sends alerts by email or through chat integrations, and its uptime and cron monitors catch outages and missed jobs. It has no on-call schedules, phone escalation, incident timelines, or post-mortems, so teams running Sentry usually add PagerDuty or a similar tool.

Grafana Cloud includes Grafana IRM, which combines on-call scheduling, escalation chains, phone and SMS paging, and incident management, with incidents declared straight from a dashboard panel. IRM is free for 3 active users and $20 per active user after that. Our incident.io vs Grafana IRM comparison covers how it compares with a dedicated response tool.

Neither product includes customer-facing status pages, so you will need a separate tool for that with either one.

Pricing

The two price very different things, which makes a direct total misleading. Here is what each meter looks like.

Grafana Cloud

The Free tier includes 10,000 active metric series, 50 GB each of logs, traces, and profiles, 3 active users, and 14 days of retention. Pro costs $19 a month plus usage above those allowances:

1. Metrics: $6.50 per 1,000 billable series, with 13 months of retention
2. Logs, traces, and profiles: $0.05 per GB processed plus $0.40 per GB written, with 30 days of retention and $0.10 per GB for each additional 30 days
3. Visualization users: $8 per active user beyond 3
4. IRM users: $20 per active user beyond 3
5. Grafana Assistant: 3 active AI users included, additional users from $20

Enterprise brings volume discounts, with metrics as low as $3 per 1,000 series.

Sentry

Team costs $26 a month and Business $80 a month, both with unlimited users. Included quotas cover 50,000 errors, 5 GB of logs, 5 million spans, and 50 replays, with pay-as-you-go rates beyond that. Error pricing is tiered from $0.0003625 down to $0.00015 per error at volume. Seer adds $40 per active contributor per month, and uptime monitors beyond the first cost $1 each.

A 15-engineer example

Take a team of 15 engineers with 50,000 active metric series, 300 GB of logs, 100 GB of traces, 5 million errors, and 10 active contributors.

These totals are not like for like. Grafana's number buys metrics, logs, and traces across the whole stack but no Sentry-style issue tracking. Sentry's number buys deep error tracking and Seer but no infrastructure monitoring. Most teams that run both pay something close to the two numbers added together.

Self-hosting and enterprise

Both offer an open-source path. Grafana's LGTM stack, Loki, Grafana, Tempo, and Mimir, can run on your own infrastructure, though operating it at scale is a real engineering commitment. Sentry's self-hosted edition remains popular with teams that have strict data requirements.

On the managed side, Grafana Cloud covers SOC 2 Type II and GDPR, with FedRAMP and PCI DSS options for regulated buyers. Sentry provides SOC 2 on paid plans, a HIPAA BAA, SAML and SCIM on Business and above, and ISO 27001 and data residency options on Enterprise.

Running both

Many teams will keep both, and that is a reasonable choice. Grafana has a Sentry data source, so Sentry issues can appear on Grafana dashboards, and Sentry's trace IDs can be followed into Tempo if both receive OpenTelemetry context. The cost is two contracts, two query models, and an investigation that still crosses products whenever an error has an infrastructure cause.

The overlap is now large enough to revisit that habit. If your backend errors are well covered by structured logs and traces, Grafana alone may be enough. If your team spends most incident time in stack traces and rarely looks at host metrics, Sentry plus a lightweight uptime and on-call tool may cover you. If you want to replace both, our Better Stack vs Sentry comparison looks at a platform that accepts Sentry SDKs and covers the infrastructure side too.

Which one fits your team

Choose Grafana Cloud if you need visibility across infrastructure, Kubernetes, and services, already use Prometheus or OpenTelemetry, and want on-call and incident management in the same platform. It suits platform and SRE teams comfortable with PromQL and LogQL, and teams that value an open-source path. Watch active series counts closely.

Choose Sentry if your main problem is bugs in application code and you want the fastest route from an exception to a fix. It suits product engineering teams, frontend and mobile developers, and organizations that want Seer to propose fixes as pull requests. Plan for a separate tool for infrastructure, on-call, and status pages.

Final thoughts

These products have spent years as neighbors, and they are now drifting into each other's space. Sentry is still the better debugger, and Grafana Cloud is still the better view of the system.

So the question for 2026 is less which one to buy and more whether you still need both. Look at your last ten incidents. If most ended in a stack trace, Sentry is earning its place. If most ended on a host or a queue that Sentry cannot see, you are paying for a debugger to watch problems it was never built to find.

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