Secure the front door. Email is where most attacks arrive — Sentry Performance Monitoring is developer-first APM & distributed tracing — following a request end-to-end as a span waterfall, and profiling down to the exact slow function, all tied to your errors. See exactly where the time went, and why.
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This page covers Sentry Performance Monitoring (APM — tracing + profiling). The rest of the Sentry platform:
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
Developer-first APM & distributed tracing — follow a request end-to-end as a span waterfall, and profile down to the exact slow function, all tied to your errors.
What consolidation actually replaces, dimension by dimension.
| Dimension | Unprotected / signature email | Performance Monitoring (Sentry) |
|---|---|---|
| The diagnosis | ‘It feels slow’ | The exact slow span, located |
| How deep | Server-level metrics | Line-by-line code profiling |
| Slow DB queries | Hard to find | Slow-query & N+1 detection |
| Real user perf | Guessed | Web vitals (LCP, CLS, INP) |
| Slow + broken | Two separate tools | Performance tied to errors |
| Regressions | Found by users | Tied to release, alerted |
| Optimisation | Guess & hope | Target the real hotspot |
| Best fit | (varies) | Developer-first APM & tracing |
Sentry Performance Monitoring is developer-first APM — distributed tracing (end-to-end span waterfalls), code-level profiling (the exact slow function) and web vitals, all tied to your errors. Honest: it’s application-focused, not a full-stack infra platform — need infra/logs/RUM? Datadog/New Relic/Dynatrace (TechBag sells Datadog); many run both. TechBag scopes it & adds GST.
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Sentry follows a single request end-to-end — from the browser page load, through your backend services, to the database query and third-party API calls — capturing it as one connected TRACE across your whole system. See the whole request, not one service. End to end.
Each trace is broken into a waterfall of SPANS — each operation (a DB query, an HTTP call, a render) with its own timing — so you see exactly where the time went: the slow query, the N+1 loop, the blocking call. Where did the time go? Span by span, you can see.
Profiling goes a level deeper than the span: code-level, line-by-line profiles show the exact FUNCTION burning CPU or wall-clock time inside a slow operation — so you know not just which endpoint is slow but which line makes it slow. Down to the line of code. Why it’s slow, exactly.
Because it’s Sentry, a slow trace links directly to the related ERRORS — and an error links to its trace — so a performance problem and the exception it caused are one connected story, not two separate tools. Slow AND broken, in one view. The whole problem.
Sentry surfaces the slowest, most-impactful endpoints and web-vitals, flags performance regressions, and alerts you when a transaction degrades — so you fix the performance issue that hurts the most users first. Fix the worst first. Alerted before they complain.
One agent on every machine, one console over all of them — modules attach without a second operational world.
Sentry traces every request span-by-span and profiles down to the slow line — tied to your errors — the developer-first APM of portfolio, and paired with the human firewall.
Follow a single request across every service — frontend, backend, database, third-party — as one connected trace, so you see the whole journey, not one isolated hop. The whole request, end to end. See where it really goes.
Each trace breaks into a waterfall of spans with individual timings — DB query, HTTP call, render, cache — so the slow step is obvious at a glance. Where did the time go? The waterfall shows you.
Sentry surfaces slow database queries and classic N+1 problems (the same query fired hundreds of times in a loop) — with the exact query and where it’s called from. Catch the slow query. Kill the N+1.
Track Core Web Vitals (LCP, CLS, INP), slow page loads and slow frontend interactions — so you see the performance your real users actually feel. The performance users feel. Vitals that matter.
Profiling goes deeper than the span — line-by-line, function-level profiles show the exact code burning CPU or wall-clock time, in production, so you know which LINE to optimise. Down to the line of code. The slow function, named.
Visualise where time is spent as a flame graph — the call stack, the hotspots, the functions that dominate — so optimisation targets the code that actually matters. See the hotspot. Optimise what counts.
A slow trace links directly to the related errors, and an error to its trace — so a performance problem and the exception it caused are one connected story, all in Sentry. Slow and broken, one view. Not two tools.
See your slowest and most-impactful endpoints and transactions, ranked by duration, throughput and user impact — so you fix the performance problem that hurts the most users first. Fix the worst first. Ranked by impact.
Sentry flags when an endpoint or transaction gets slower — tied to the release — so you catch a performance regression before users complain, not after. Catch the slowdown early. Before they notice.
Get alerted when a transaction degrades, a web-vital breaches threshold, or throughput/latency spikes — to Slack, PagerDuty, Teams or email — with the trace to act on. Alerted on the slowdown. With the context to fix it.
The same tracing SDKs cover JavaScript, Python, Java, Go, .NET, mobile and more — with OpenTelemetry support — so you trace across your whole polyglot stack in one place. Every language you ship. One trace.
Run performance monitoring as SaaS or self-host it — same ‘fair source’ FSL license (self-hostable, not OSI-open; converts to Apache 2.0 after two years). Your data, your choice of hosting. Cloud or your own infra.
The overview, getting started, and protecting M365 email.
Find why it’s slow.
Follow a request end to end.
Down to the slow function.
Want a live, India-context walkthrough on your own fleet?
Book a guided demo →Here’s what genuinely sets Sentry APM apart (and where it’s application-focused, not a full-stack platform).
The core reason developers use Sentry Performance Monitoring is DISTRIBUTED TRACING that shows, span by span, exactly where a request spends its time. The problem it solves: ‘the app feels slow’ is a symptom, not a diagnosis — the slowness could be a database query, an N+1 loop, a blocking third-party call, a slow render, or the network, and without tracing you’re guessing. What Sentry provides: it follows a single request end-to-end across your services — frontend page load, backend handlers, database queries, third-party API calls — and breaks it into a WATERFALL of spans, each with its own timing. So the slow step is obvious: you SEE that 800ms went to one query, or that the same query fired 200 times in a loop (an N+1), or that a third-party call blocked the response. Why it matters: you can’t fix what you can’t see. Tracing turns a vague performance complaint into a precise, located problem — the exact span, in the exact service — so optimisation is targeted, not guesswork. The value: Sentry’s distributed tracing follows a request end-to-end and breaks it into a span waterfall — so you see exactly where the time went, and fix the real bottleneck. For performance debugging, this matters. TechBag helps Indian teams adopt Sentry. TechBag helps you find the slow span, not guess.
A distinctive strength of Sentry APM is that PROFILING takes you a level deeper than the span — to the exact function and line of code burning the time. The problem it solves: tracing tells you WHICH span (which operation) is slow — but sometimes the slow span is your own code, and you need to know WHICH LINE inside it is the culprit before you can optimise. What Sentry provides: continuous, code-level profiling captures line-by-line, function-level profiles in production — visualised as flame graphs — showing the exact functions and call stacks consuming CPU or wall-clock time inside a slow operation. So you go from ‘this endpoint is slow’ to ‘this specific function on this line is the hotspot’. Why it matters: optimisation is only as good as your targeting. Profiling means you spend your effort on the code that actually dominates the time — not on a guess — so a small, precise change delivers the big win. Combined with tracing, you get the full picture: which span is slow (tracing) AND why (profiling). The value: Sentry profiling goes down to the exact function and line burning time — so optimisation is precise, targeting the real hotspot, not a guess. For code-level performance, this matters. TechBag helps Indian teams adopt Sentry. TechBag helps you fix the line, not the vibe.
A defining Sentry advantage is that performance data doesn’t live apart from errors — a slow TRACE links directly to the ERRORS it’s connected to, and vice versa. The problem it solves: in many stacks, your APM tool and your error tool are separate, so a real-world incident — which is usually slowness AND failures together — means correlating two systems by hand. What Sentry provides: because tracing and error monitoring are the same platform, a slow or failing trace shows you the related exceptions, and an error shows you the trace (and profile) around it. So when a page is both slow and throwing errors, you see the whole story in one place: the slow span, the failing call, the exception, the affected user. Why it matters: real performance problems and real errors are frequently the same incident — a slow, failing third-party call; a query that times out and errors. Having them CONNECTED means you understand and fix the whole problem fast, instead of stitching together an APM tool and an error tool. The value: in Sentry, performance is tied to errors — a slow trace and the exception it caused are one connected story, in one platform. For understanding real incidents, this matters. TechBag helps Indian teams adopt Sentry. TechBag helps you see slow-AND-broken as one problem.
A key strength of Sentry APM is that it’s DEVELOPER-FIRST and application-focused — it traces and profiles YOUR CODE, tied to your releases and your errors, rather than being an ops-centric infrastructure tool. The problem it solves: many APM/observability tools are built for ops teams watching infrastructure — great for server metrics, but they don’t take a DEVELOPER from ‘this transaction is slow’ to ‘this line of my code is why’. What Sentry provides: everything points at your application code — spans mapped to your operations, profiles down to your functions, traces tied to your releases (so you see which deploy regressed performance) and to your errors, all in the workflow developers already use for error monitoring. The same SDKs cover 100+ platforms, with OpenTelemetry support. Why it matters: because the person who fixes a slow endpoint is usually a developer, an APM built around the developer’s code and workflow removes friction — from detecting a slowdown to shipping the fix. It’s APM that engineers actually want to use, for the same reason they love Sentry’s error monitoring. The value: Sentry APM is developer-first — it traces and profiles your code, tied to releases and errors, in the developer’s workflow. For engineers optimising their own apps, this matters. TechBag helps Indian teams adopt Sentry. TechBag helps your developers make it fast.
Sentry APM comes from a developer-loved, widely-adopted platform — and for Indian teams TechBag adds the INR/GST billing, procurement, volume scoping and support that make adopting it straightforward. Sentry the company: founded in 2012 by David Cramer and Chris Jennings out of an open-source project, Sentry is used by 4M+ developers across 100k+ organisations (Disney, Cloudflare, GitHub, Slack, Atlassian). It’s developer-first and SELF-HOSTABLE under the FSL (‘fair source’: self-hostable, not OSI-open, converting to Apache 2.0 after two years). (Governance note: CEO is Milin Desai since 2020; co-founder David Cramer is now Chief Product Officer.) India relevance: India has huge developer adoption; the self-serve plans bill in USD with 18% GST under reverse-charge, complicating procurement. And because APM cost scales with the volume of SPANS (and profiles) you send, sampling and quotas matter. Where TechBag adds value: TechBag handles INR/GST invoicing and procurement, scopes your expected span/profile volume and sets sensible sampling (so the bill is predictable), and gives honest comparison vs Datadog / New Relic / Dynatrace (broader full-stack platforms — TechBag sells Datadog) where a full-stack tool fits better. The value: Sentry APM is developer-loved and self-hostable — and TechBag adds INR/GST billing, procurement, span-volume scoping and local support. TechBag supplies it, made local. TechBag provides Sentry APM, made local for India.
Sentry Performance Monitoring is Sentry’s APM — developer-first distributed tracing (end-to-end spans across your services), code-level profiling (down to the exact slow function), web vitals and endpoint insights, all tied to your errors. From Sentry (founded 2012; 4M+ developers; 100k+ organisations). The honest framing — strengths, and where it’s a code-level APM not a full-stack platform: Sentry’s strengths are best-in-class developer-first tracing and profiling of your APPLICATION, tied to releases and errors, in the developer’s workflow. But two honest caveats matter. (1) It is APPLICATION-focused, not full-stack infrastructure observability. Sentry brilliantly traces and profiles your code — but it is NOT a single platform for infrastructure metrics, log management at scale, network/cloud monitoring and real-user monitoring alongside APM. If you want one broad pane across your whole environment (infra + logs + APM + RUM), Datadog, New Relic and Dynatrace are broader (Datadog is a platform TechBag also sells). A very common setup is Sentry for developer error/trace/profile debugging AND a full-stack platform for infra observability. (2) COST scales with SPAN volume. Sentry APM prices on the volume of spans (and profiles) you send; a high-throughput app can get expensive, so SAMPLING (send a representative fraction of transactions rather than 100%) and quotas are essential — plan them up front. Other honest notes: the license is FSL (‘fair source’, self-hostable, not OSI-open); and some full-stack rivals go deeper on infrastructure and automated root-cause across the whole environment. So the honest positioning: for developer-first tracing and profiling of your application — tied to your errors, the thing developers want to use — Sentry is excellent; for a broad full-stack observability platform (infra + logs + APM + RUM), Datadog / New Relic / Dynatrace (TechBag sells Datadog); and many teams run both. TechBag scopes Sentry APM honestly — comparing vs Datadog, scoping your span volume with sampling to control cost, and billing INR/GST.
Your stack and services, your traffic/throughput (which drives span volume), and whether you also need full-stack infra observability. TechBag scopes it and compares honestly vs Datadog (which it also sells).
Enable performance in the Sentry SDK (or via OpenTelemetry), set a trace-sample rate, and traces start arriving — span waterfalls, slow queries, web vitals. Live in minutes.
Follow slow requests span by span, profile down to the slow function, tie performance to the related errors, and fix the highest-impact endpoints first. Optimise the hotspot.
Tune trace/profile sampling and quotas to control span volume cost, and combine with error monitoring, session replay and Seer AI. TechBag handles INR/GST and volume scoping.
Trusted across regulated industries in 100+ countries
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
“Distributed tracing showed us the 800ms was one N+1 query firing 200 times in a loop — something we’d have never found from server graphs. The span waterfall made it obvious.”
“Profiling took us from ‘this endpoint is slow’ to ‘this exact function is the hotspot’ — a two-line change cut the latency in half. That’s the difference precise targeting makes.”
“The killer bit is that performance is tied to our errors — when a page is both slow and throwing exceptions, we see the whole incident in one view instead of stitching two tools together.”
“Web vitals and endpoint insights told us which slow pages our real users actually feel — so we fixed the ones with real user impact first, not the ones that just looked bad on a dashboard.”
“Honest: for infrastructure metrics, logs and cloud monitoring we run Datadog — Sentry APM is application-focused, not full-stack. But for tracing and profiling our own code, tied to errors, it’s superb. TechBag was clear on the split.”
“Span volume drives the bill — TechBag helped us set trace sampling so we get the tracing value at a predictable cost. That planning up front saved us a nasty surprise.”
“We self-host Sentry for data control and the same FSL license covers performance monitoring. TechBag scoped it and handled the GST and PO.”
“Sentry bills USD with GST reverse-charge — TechBag handled INR/GST invoicing and procurement. Developer-first APM, made buyable locally.”
Analyst firms bury this view behind paywalls, and G2 retired its Grid. So here’s TechBag’s synthesis of the APM & observability market — tap any vendor to see why it sits where it does.
Execution strength vs product vision — the classic market map, minus the paywall.
Developer-first APM, tied to errors. This page's product.
The grid nobody publishes — how strong the email detection is vs how integrated with the wider security portfolio.
Tracing + profiling tied to errors.
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Datadog APM, New Relic, Dynatrace, Grafana and Elastic APM — honest lanes; the edge is developer-first tracing & profiling tied to your errors. Need one full-stack platform (infra/logs/RUM)? Datadog (TechBag sells it) — many teams run both. We say so.
| Dimension | Sentry | Datadog APM | New Relic | Dynatrace | Grafana | Elastic APM |
|---|---|---|---|---|---|---|
| Position | Developer-first APM (tied to errors) | Full-stack observability platform | Full-stack observability | Full-stack + AI root-cause | Open dashboards / metrics | APM on the Elastic stack |
| Distributed tracing | Strong (dev-first, span waterfall) | Strong | Strong | Strong (auto) | Via Tempo | Good |
| Code-level profiling | Continuous, line-by-line | Continuous profiler | Some | Strong | Via Pyroscope | Some |
| Tied to errors (dev experience) | Errors + trace + replay, one platform | Error tracking module | Connected (platform) | Connected (platform) | Separate | Connected |
| Full-stack breadth (infra/logs/RUM) | Application-focused (narrower) | Broadest (one platform) | Broad | Broad (+ AI) | Broad (open, DIY) | Broad (Elastic stack) |
| Self-host option | Yes (FSL, fair source) | SaaS only | SaaS | SaaS + managed | Open-source / self-host | Self-host (Elastic) |
| Best fit | Developer-first tracing/profiling tied to errors | One full-stack platform (TechBag sells it) | Full-stack observability | Full-stack + AI root-cause (enterprise) | Open, DIY dashboards/metrics | APM on the Elastic stack |
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Drag the sliders (developers; slow endpoints / performance incidents per month; hour cost as loaded rate). Estimates contrast optimising without tracing (guessing from server metrics, no line-level insight, users find slowness) vs Sentry (span-level tracing, code-level profiling, performance tied to errors) — the wins are faster diagnosis, precise optimisation, and developer time saved. Illustrative — TechBag scopes your span volume & cost.
Loaded cost = salary + overheads per productive hour. Illustrative only — your TechBag quote models actual device counts and modules.
Sentry is volume-priced: Developer (free), Team ($26/mo annual; $29 monthly), Business ($80/mo annual; $89 monthly), and Enterprise (by quote) — APM cost scales by span/profile volume, so trace sampling matters. Sentry bills in USD with GST reverse-charge; TechBag handles INR/GST, procurement, and span-volume scoping (sampling & quotas) so the bill is predictable.
Best for developer-first tracing & profiling
Best for a broader rollout
Best value with TechBag
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Tell us your device counts and current tools — we’ll model it against what you spend today.
Take this into your next vendor call — including ours.
‘It feels slow’ with no diagnosis? Sentry distributed tracing shows span by span exactly where the time went.
Suspect the database? Sentry surfaces slow queries and N+1 problems with the exact query and call site.
Need to know which line is slow? Sentry profiling goes code-level — the exact function burning time, as a flame graph.
Incidents that are slowness plus errors? Sentry ties performance to errors — one connected story, one platform.
Need infra metrics, logs and RUM too? Sentry APM is application-focused — Datadog is the broad platform (TechBag sells both).
Care about what users feel? Sentry tracks Core Web Vitals (LCP, CLS, INP) and slow interactions.
Worried about span volume? APM cost scales with spans — TechBag helps set trace sampling and quotas up front.
Sentry bills USD with GST reverse-charge — TechBag handles INR/GST invoicing, POs and local support.
Scope Sentry Performance Monitoring (developer-first distributed tracing and code-level profiling, tied to your errors) — and let a TechBag advisor scope your span volume, set trace sampling for cost control, compare honestly vs Datadog, and add INR/GST and local support.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.