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APM & Tracing
Secure the front door. Email is where most attacks arrive — APM is Datadog’s application performance monitoring & distributed tracing — trace every request end-to-end across your services to find exactly why it’s slow or failing (down to the code). The app-level view — correlated with infra, logs & user sessions, one click.
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How it’s rated
Full scoreboard ↓Quick answer
The Datadog platform family
This page covers APM & Tracing — the app-level view. The rest of the Datadog platform:
Quick facts
30-second orientation- Product
- APM & Distributed Tracing
- Vendor
- Datadog (founded 2010 · NASDAQ: DDOG)
- The category
- Application performance monitoring
- What it does
- Trace every request end-to-end; find the bottleneck
- The view
- How your CODE & SERVICES perform (not just servers)
- Includes
- Distributed tracing, Continuous Profiler, service maps, USM
- The edge
- Trace → infra metric → log → session, one click
- Strong for
- Microservices & cloud-native apps
- Vs
- Dynatrace, New Relic, Grafana Tempo, Honeycomb
- In India via
- TechBag — scoping, cost mgmt, GST (Datadog bills USD)
Understand APM & distributed tracing before you buy it
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
What is Datadog APM?
Datadog’s application performance monitoring & distributed tracing — trace every request end-to-end across your services to find exactly why it’s slow or failing, down to the code. The app-level view, correlated with infra, logs & sessions.
Guessing at app performance vs Datadog APM — the honest table
What consolidation actually replaces, dimension by dimension.
| Dimension | Unprotected / signature email | APM & Tracing (Datadog) |
|---|---|---|
| The view | Servers only (infra) | + code & services (APM) |
| Microservices | Guess which is slow | Trace the request, pinpoint it |
| Errors | Scattered | Tracked & grouped, in context |
| Code detail | None | Continuous Profiler (line-level) |
| Architecture | Unclear | Service maps & dependencies |
| Root cause | Jump between tools | Trace→infra→log→session, 1 click |
| DB queries | Hidden | Visible in the trace |
| Cost | (varies) | Per-host (public) — manage the bill |
Datadog APM traces every request across your microservices to find the bottleneck — correlated with infra, logs & sessions (one click), down to the code (Continuous Profiler). Honest caveat: it's per-host, ON TOP of infra monitoring — the bill compounds. Cheaper? New Relic. Deepest AI RCA? Dynatrace. TechBag manages cost + GST.
The five pieces of the platform
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Distributed Tracing
Trace requests end-to-end as they flow through your services — following each request's full journey across microservices, showing which services it touched, how long each took, and where errors occurred. So you see exactly how each request behaves, not just aggregate stats. Follow the request, find the problem.
Service Performance
Detailed performance metrics for every service, endpoint and database query — latency, throughput, error rates — so you know how each part of your application performs, and can spot which is slow or failing. Granular, per-component performance visibility. Know exactly what's slow.
Service Maps & USM
Service maps visualise how your services connect and depend on each other, and Universal Service Monitoring gives visibility even for un-instrumented services — so you understand your application's architecture and dependencies. See how it all fits together. The map of your app.
Continuous Profiler
The Continuous Profiler profiles your running code (CPU, memory, I/O) in production — so you can find the exact inefficient functions or lines consuming resources, going beyond traces to code-level detail. Profiling finds the code causing the problem. Down to the line of code.
One Unified Platform
Because it's part of ONE platform, an APM trace is one click from the underlying infrastructure metrics (is the host overloaded?), logs (what error?), and affected user sessions (RUM) — so you go from a slow request to its full root cause seamlessly. The unified-platform edge, applied to app performance.
One agent on every machine, one console over all of them — modules attach without a second operational world.
Twelve capabilities. Trace, analyse, connect.
APM traces every request across your services to pinpoint the bottleneck — correlated with infra, logs & sessions — part of portfolio, and paired with the human firewall.
End-to-End Distributed Tracing
Trace every request across your services end-to-end — following its full path through microservices, with timing and errors at each hop. So you see the complete journey of each request and where it goes wrong. Distributed tracing is essential for microservices. The full request, traced.
Per-Service Performance Metrics
Latency, throughput and error rates for every service and endpoint — so you know how each part of your app performs, and can spot the slow or failing one. Granular service metrics pinpoint where problems are. Performance, per service.
Database Query Insight
See how database queries within your traces perform — slow queries, N+1 problems — so you can find and fix database bottlenecks (a common cause of app slowness). Database performance in context of the request. Find the slow queries.
Error Tracking
Track and group errors across your services — so you see what's failing, how often, and where, and can prioritise fixes. Understanding errors (not just latency) is key to reliability. Know what's breaking, and why.
Service Maps & Dependencies
Visualise how your services connect and depend on each other — the topology of your application — so you understand the architecture and how a problem in one service affects others. Service maps make complex microservices comprehensible. See your app's shape.
Continuous Code Profiling
Profile your running code in production (CPU, memory, I/O) — finding the exact functions or lines consuming resources — so you can optimise inefficient code, going beyond traces to code-level detail. Profiling pinpoints the costly code. Down to the line.
Universal Service Monitoring
Get service-level visibility even for services you haven't fully instrumented — Universal Service Monitoring uses the platform to surface service performance broadly — so you have coverage without instrumenting everything upfront. Broad service visibility, less setup. Coverage, faster.
Easy Instrumentation
Instrument your apps with minimal code change (or auto-instrumentation for many languages/frameworks) — so getting tracing going is fast, not a big project. Easy instrumentation drives real adoption. Tracing, without the pain.
Trace → Infrastructure Metrics
From a slow trace, one click to the underlying infrastructure metrics — is the host overloaded, the container throttled? — so you know if the cause is the code or the infrastructure. Connecting app to infra is essential root-cause context. Code or infra? One click.
Trace → Logs
From a trace, one click to the related logs — the exact error messages and context for that request — so you see precisely what went wrong. Trace-to-log correlation is the fastest path to the error detail. The exact error, one click away.
Trace → User Session (RUM)
Connect a trace to the real user session (RUM) that triggered it — so you see the actual user experience behind a slow request, and can prioritise by user impact. Linking backend performance to real user experience closes the loop. From code to the user affected.
Watchdog AI + The Platform
Watchdog AI surfaces app-performance anomalies automatically, and APM is part of the one Datadog platform (with infra, logs, security, DEM) — so app performance is seen in full context, with AI help. AI-assisted APM on a unified platform. Smarter, connected app monitoring.
Watch Datadog APM in action
The overview, getting started, and protecting M365 email.
Datadog Application Performance Monitoring (APM)
APM & distributed tracing.
Datadog APM Introduction
Getting started with tracing.
Datadog Overview: See Inside the Platform
The unified platform.
Want a live, India-context walkthrough on your own fleet?
Book a guided demo →The endpoint catches what arrives. Email stops it arriving.
Here’s what genuinely sets Datadog APM apart (and where to watch cost).
See how your CODE performs — not just your servers
The core reason Datadog APM matters is that it shows you how your APPLICATIONS and services are actually performing — at the code and request level — which is what most directly affects user experience, and which infrastructure monitoring alone can't tell you. Infrastructure isn't enough: infrastructure monitoring tells you how your servers, containers and cloud are doing (CPU, memory, etc.) — essential, but it doesn't tell you how your APPLICATION is performing from the user's perspective. Your servers can look healthy while your app is slow or failing — because the problem is in the CODE, a specific service, a slow database query, or how requests flow through your services. To understand and fix application performance (what users actually experience), you need the application-level view — which is APM. The application-level view: APM shows you how your applications and services perform: Request tracing — trace each request end-to-end as it flows through your services, seeing its full journey and where time is spent. Per-service/endpoint performance — latency, throughput and errors for each service, endpoint and database query. Code-level detail — with the Continuous Profiler, down to the functions and lines consuming resources. Errors — what's failing, where and how often. So you see how your CODE and SERVICES actually perform — the view that reflects user experience and that infrastructure metrics can't provide. Why it matters: application performance is what users experience — a slow or failing app hurts users, revenue and reputation, regardless of how healthy the servers look. To deliver good application performance, you must be able to SEE it (which parts are slow/failing) and understand WHY (which service, code or query) — and that's exactly what APM provides. It's the difference between knowing your infrastructure is up and knowing your application is fast and working. For any organisation whose applications matter to users (i.e. all), APM's application-level visibility is essential — and it complements infrastructure monitoring (together giving the full picture). The value: Datadog APM shows you how your CODE and services actually perform — tracing requests, measuring per-service performance, down to the code — the application-level view that reflects user experience and that infrastructure monitoring alone can't give. For application performance, this matters. TechBag helps organisations see and fix application performance with Datadog APM. TechBag helps you know how your apps really perform, not just your servers.
Distributed tracing — find the bottleneck in microservices
A defining strength of Datadog APM is distributed tracing — following each request end-to-end across your services — which matters because modern apps are often many microservices, and finding WHERE a request is slow or failing across them is otherwise extremely hard. The microservices problem: modern applications are increasingly built as microservices — many small services that call each other to handle a request. A single user request might touch a dozen services (front-end, auth, several back-end services, databases, caches, queues). This has benefits, but creates a hard problem: when a request is slow or fails, WHERE is the problem? Which of the many services is the bottleneck? With just aggregate metrics per service, you can't easily follow a specific request through the maze to find where it went wrong — the problem could be in any service, or in how they interact. Debugging distributed systems without tracing is guesswork. What distributed tracing provides: Datadog APM's distributed tracing follows each request through all the services it touches: A trace shows the request's FULL journey — every service it hit, in order, with how long each took and where errors occurred. So you see exactly WHERE the time went — which service or call is the bottleneck — and WHERE errors happened, for that specific request. You can find slow or failing services, slow database queries within the flow, and problematic dependencies. Service maps visualise how the services connect, giving the topology. So instead of guessing which of many microservices is the problem, you follow the actual request trace and pinpoint the culprit. Why it matters: for microservices/cloud-native applications (increasingly common), distributed tracing is essential — it's the only practical way to understand and debug performance across many interacting services. Without it, troubleshooting distributed systems is slow, painful guesswork; with it, you pinpoint the exact bottleneck or failure fast. This is a core reason APM is critical for modern apps, and Datadog's tracing (with easy instrumentation and great UX) is a leading implementation. It directly speeds resolution of the performance and reliability issues that most affect users. The value: Datadog APM's distributed tracing follows each request end-to-end across your microservices — so you pinpoint exactly which service, call or query is the bottleneck or failure, rather than guessing. For microservices/cloud-native apps, this is essential. TechBag helps organisations debug microservices with Datadog distributed tracing. TechBag helps you find the bottleneck in your distributed app.
Correlated with everything — from slow request to full root cause
A key strength of Datadog APM is that it's part of the ONE unified platform, so a trace is one click from the infrastructure metrics, logs and user sessions — letting you go from a slow request to its FULL root cause seamlessly, rather than jumping between tools. The root-cause context problem: when you find a slow or failing request (via APM), the next question is WHY — and the answer often lies OUTSIDE the trace itself: Is the underlying host or container overloaded (infrastructure)? What exact error occurred (logs)? Which real users were affected (user sessions/RUM)? To get the full root cause, you need to correlate the trace with infrastructure metrics, logs and user sessions. Traditionally, these are in SEPARATE tools — so you find a slow trace in your APM tool, then jump to your infrastructure tool, your logging tool and your RUM tool, manually correlating — slow and painful. Datadog's unified correlation: Because APM is part of Datadog's one platform, everything is connected: From a slow trace, ONE CLICK to the underlying infrastructure metrics — is the host/container the problem? From the trace, one click to the related LOGS — the exact error and context. From the trace, one click to the affected USER SESSIONS (RUM) — the real user experience behind it. All tied together by shared tags (service, host, environment). So from a slow request, you seamlessly get the full picture: the code (trace) + the infrastructure (metrics) + the error (logs) + the user impact (sessions) — in one platform, in clicks. So you go from 'this request is slow' to 'here's exactly why (this service, on this overloaded host, throwing this error, affecting these users)' — fast, without tool-jumping. Why it matters: getting to the FULL root cause quickly is what matters in troubleshooting — and the cause often spans app, infrastructure, logs and user experience. Datadog's unified correlation makes assembling this full picture seamless (one platform, one click), versus the slow tool-jumping of separate tools. This dramatically speeds resolution — which is Datadog's signature strength and a core reason APM is so effective within its platform. The value: Datadog APM is correlated with infrastructure, logs and user sessions on ONE platform — so from a slow request, you go to its full root cause (code + infra + error + user impact) in clicks, not tool-jumping. For fast, complete root-cause, this matters. TechBag helps organisations get from slow request to full root cause with Datadog. TechBag helps you find the complete why, fast.
Continuous profiling — down to the exact line of code
A powerful, deeper strength of Datadog APM is the Continuous Profiler — profiling your running code in production to find the exact functions or lines consuming resources — which matters because sometimes the answer to 'why is this slow or expensive' is in the code itself, and profiling finds it. Beyond traces — the code itself: distributed tracing tells you WHICH service or call is slow. But sometimes you need to go deeper — WITHIN a service, WHAT CODE is causing the slowness or consuming excessive CPU/memory? Which specific functions or lines are inefficient? Traces don't go to that code-level detail; for that, you need profiling. And code inefficiency is a real, common cause of performance problems and cost (inefficient code uses more CPU/memory, slowing things and increasing infrastructure/cloud cost). What the Continuous Profiler provides: Datadog's Continuous Profiler profiles your code in PRODUCTION, continuously and with low overhead: It shows which functions and lines of code consume the most CPU, memory and I/O — down to code-level detail. So you can find the exact inefficient code causing slowness or excessive resource use, and optimise it. It works in production (not just test), so you see real behaviour. It's correlated with traces — from a slow trace, dive into the profile of the code that ran. So you go beyond 'this service is slow' to 'this specific function is the problem', enabling precise code optimisation. Why it matters: finding and fixing inefficient code delivers real benefits: Better performance — optimise the actual code causing slowness. Lower cost — more efficient code uses less CPU/memory, reducing infrastructure/cloud cost (increasingly important given cloud costs). Precise fixes — target the exact code, not vague guesses. For performance-critical or cost-conscious applications, code-level profiling is a powerful capability — it finds optimisation opportunities that traces alone miss, improving both performance and efficiency. Combined with tracing, it means Datadog takes you all the way from a slow request to the exact line of code responsible. The value: Datadog APM's Continuous Profiler profiles your code in production — finding the exact functions and lines consuming resources — so you can optimise inefficient code for better performance AND lower cost. For deep performance optimisation, this matters. TechBag helps organisations optimise code with Datadog's Continuous Profiler. TechBag helps you find and fix the exact slow, costly code.
From the observability leader — with the honest cost caveat
Datadog APM comes from Datadog — the observability leader (NASDAQ: DDOG) — with the strengths (and the honest cost caveat) of the leading platform, and it's especially strong for microservices and cloud-native apps. The leading platform: Datadog is the leading cloud-observability platform, and its APM is a core, mature, well-regarded part — with excellent distributed tracing, easy instrumentation, great UX, the Continuous Profiler, and (crucially) deep correlation with the rest of the platform (infrastructure, logs, user sessions). For understanding application performance — essential for user experience — having APM from the observability leader, tightly correlated with everything else, is powerful. Especially strong for microservices: Datadog APM is particularly strong for microservices and cloud-native applications — exactly where distributed tracing is most needed and hardest to do without — fitting the modern architectures most organisations are moving to. Strong AI: Watchdog automatically surfaces app-performance anomalies, and Datadog's broader AI (Bits AI) assists investigation — so APM benefits from AI-driven detection and help. The honest cost caveat: as with all of Datadog, APM adds to the compounding, multi-module bill — APM is priced per host (public, transparent), but on top of infrastructure monitoring and other modules, so the total grows. Cost management (right-sizing, committed discounts) matters — which TechBag handles. Being upfront: Datadog is powerful and the correlation is best-in-class, but manage the bill. India relevance: for India's many cloud-native, microservices-building companies, Datadog APM is highly relevant. Via TechBag (Bengaluru-based), Indian organisations get it with local scoping, cost management and GST (Datadog bills USD). The value: Datadog APM — from the observability leader, with excellent distributed tracing, profiling, correlation and AI, especially strong for microservices — shows you exactly why your apps are slow, with the cost managed by TechBag. TechBag supplies it with local scoping and cost management. TechBag provides leading APM, with the bill managed.
The honest scope
Datadog APM (Application Performance Monitoring) with distributed tracing shows how your applications and services perform — tracing every request end-to-end across microservices, with per-service/endpoint/query metrics, error tracking, service maps, Universal Service Monitoring, and a Continuous Profiler (code-level) — all correlated on Datadog's one platform with infrastructure metrics, logs and user sessions (one click from a slow request to its full root cause). From the observability leader (NASDAQ: DDOG), especially strong for microservices. The honest framing — strengths, cost, and competition: APM's strengths are excellent distributed tracing, easy instrumentation, best-in-class correlation (the unified platform), the Continuous Profiler, and microservices/cloud-native fit. Its honest caveat (like all Datadog) is COST — priced per host (transparent), but adding to the compounding multi-module bill; manage it. The competitive landscape: Dynatrace is the enterprise, AI-first rival — its OneAgent auto-instruments and Davis AI gives deep automatic root-cause; for the deepest automatic RCA and enterprise auto-instrumentation, weigh Dynatrace. New Relic offers strong APM at a simpler, often cheaper price. Grafana Tempo (with the LGTM stack) is the cost-effective, open-source-leaning tracing option (more DIY). Honeycomb is a developer-loved, high-cardinality tracing/debugging tool (great for deep, exploratory debugging of complex systems). And open-source (OpenTelemetry + Jaeger/Tempo) is the DIY route. So the honest positioning: for the best correlated APM within the leading unified platform (cost managed), Datadog; for deepest automatic AI root-cause, Dynatrace; for strong APM at lower cost, New Relic; for cost-effective open-source tracing, Grafana Tempo; for deep exploratory debugging of complex systems, Honeycomb. Datadog APM is most compelling for organisations wanting excellent tracing correlated with full observability on the leading platform — especially microservices/cloud-native — with cost actively managed. TechBag scopes APM honestly — within the platform, managing cost, comparing vs Dynatrace/New Relic/Grafana/Honeycomb — and supports it (GST; Datadog bills USD).
The numbers behind the platform
What your Datadog APM journey looks like
APM scoping
Your apps (microservices? monolith?), your performance pains, which services to trace, and — crucially — the added cost (APM is per-host, on top of infra). TechBag scopes it and manages the bill honestly.
Instrument & trace
Instrument your apps (minimal code change / auto-instrumentation) and start distributed tracing — seeing requests flow across your services, with per-service performance and service maps.
Correlate & profile
Use the one-click correlation (trace → infra → log → session) for fast root cause, and the Continuous Profiler for code-level optimisation. From slow request to exact cause.
Optimise & manage cost
Optimise app performance and code (and cost), use Watchdog AI, and govern the APM spend (which hosts/services, committed discounts). TechBag manages cost and supports you (GST; Datadog bills USD).
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The review scoreboard
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
Quick poll — what’s driving your evaluation?
Talk to an advisor“Distributed tracing lets us follow a request across our dozen microservices and pinpoint exactly which one is the bottleneck — no more guessing. For a microservices app, APM is essential, and Datadog's tracing is excellent.”
“The one-click from a slow trace to the infrastructure metrics, the exact error logs, AND the affected user sessions is the killer feature — full root cause in seconds, all on one platform. That correlation is why we chose Datadog.”
“The Continuous Profiler took us down to the exact functions eating CPU — we optimised code that was both slow AND expensive (cloud cost). Beyond traces to the actual line of code. Powerful.”
“Instrumentation was easy — minimal code change, auto-instrumentation for our stack — so we got tracing going fast. And service maps made our complex microservices architecture finally comprehensible.”
“Honest note: APM adds per-host cost on top of infra monitoring and logs — the bill compounds. TechBag helped us right-size which services to trace and negotiate a committed discount. Managed, it's worth it.”
“We compared Dynatrace (deeper automatic AI root-cause) and New Relic (cheaper) — but for the best correlated APM within the unified platform, Datadog won, cost managed. TechBag gave an honest comparison.”
“Watchdog surfaced an app-performance regression we hadn't alerted on — AI-driven detection caught it early. APM plus AI plus the platform is a strong combination.”
“Seeing our slow database queries in the context of the request trace let us fix N+1 problems fast. Database performance in app context — exactly what we needed. TechBag handled India commercials and GST.”
Where everyone sits — the grids
Analyst firms bury this view behind paywalls, and G2 retired its Grid. So here’s TechBag’s synthesis of the APM & distributed tracing market — tap any vendor to see why it sits where it does.
TechBag Email-Security Grid
Execution strength vs product vision — the classic market map, minus the paywall.
Best correlated APM on the leading platform. This page's product.
Detection × Portfolio Integration
The grid nobody publishes — how strong the email detection is vs how integrated with the wider security portfolio.
Tracing + correlation + profiler.
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 vs the tracing/APM field
Dynatrace, New Relic, Grafana Tempo, Honeycomb and OpenTelemetry — honest lanes; the edge is best-in-class correlation on the leading platform (with a cost caveat). Deepest AI RCA? Dynatrace. Cheaper? New Relic. OSS? Grafana Tempo. We say so — and manage the bill.
| Dimension | Datadog APM | Dynatrace | New Relic | Grafana Tempo | Honeycomb | OpenTelemetry (DIY) |
|---|---|---|---|---|---|---|
| Position | Best correlated APM on the leading platform | Enterprise, AI/auto-instrument (Davis) | Strong APM, cheaper/simpler pricing | Cost-effective OSS tracing (LGTM) | Developer-loved high-cardinality debugging | Open standard + DIY backend |
| Distributed tracing | Excellent | Excellent (auto) | Strong | Good (Tempo) | Excellent (high-cardinality) | Standard (you run backend) |
| Correlation to infra/logs/sessions | Best-in-class (one platform) | Strong (AI-driven) | Good (unified) | Via Grafana (more DIY) | Tracing-focused | Assemble yourself |
| Continuous / code profiling | Yes (Continuous Profiler) | Yes | Some | Via Pyroscope | Limited | DIY |
| Ease of instrumentation | Easy (auto for many langs) | Auto (OneAgent) | Easy | OTel setup | OTel/SDK | You do it all |
| Automatic AI root-cause | Watchdog (good) | Davis AI (deepest) | Some | Some | Query-driven | None |
| Cost / predictability | Per-host; adds to compounding bill | Enterprise-priced | Simpler, often cheaper | Very cost-effective | Usage-based | Free (you run it) |
| Part of full observability platform | Yes — the whole platform | Yes | Yes | Yes (Grafana stack) | Tracing-focused | No (a standard) |
| Best fit | Correlated APM on the leading platform (cost managed) | Deepest automatic AI root-cause | Strong APM, lower cost | Cost-effective OSS tracing | Deep exploratory debugging | Open standard + DIY |
Which email-security approach fits you?
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Choose Datadog APM if…
- ✓You want to see how your CODE & services actually perform — trace every request, find the bottleneck
- ✓You run microservices/cloud-native apps — distributed tracing is essential and Datadog's is excellent
- ✓You want the best correlation — trace → infra → log → session in one click, on one platform
- ✓You want code-level profiling (Continuous Profiler) — with cost actively managed by TechBag
Dynatrace if…
- ✓You want the deepest automatic AI root-cause (Davis AI) and enterprise auto-instrumentation
New Relic if…
- ✓You want strong APM at a simpler, often cheaper price
Grafana Tempo if…
- ✓You want cost-effective, open-source-leaning tracing (with the LGTM stack)
Honeycomb if…
- ✓You want deep, high-cardinality exploratory debugging of complex systems
What do email threats cost you?
Drag the sliders (count services/hosts; engineer-hour cost as loaded rate). Estimates contrast flying blind on app performance (guessing which microservice is slow, slow debugging) vs Datadog APM (trace the request, pinpoint the bottleneck, one-click root cause) — the wins are faster resolution and better reliability. NB: APM is per-host, ON TOP of infra — TechBag manages the bill. Illustrative.
Loaded cost = salary + overheads per productive hour. Illustrative only — your TechBag quote models actual device counts and modules.
Three ways to consume it
Datadog APM has PUBLIC per-host pricing — transparent, but it ADDS to Datadog's compounding bill (on top of infra monitoring, logs…). Datadog bills in USD. TechBag scopes which services to trace, manages the added cost (sampling, committed discounts), and handles GST.
APM & Tracing (per host)
Best for application performance
- PUBLIC per-host pricing — transparent, but ADDS to the total
- Distributed tracing, service maps, Continuous Profiler
- Correlated: trace → infra → log → session, one click
+ Platform add-ons
Best for a broader rollout
- Scoped to your estate
- Add-on modules as needed
- Phased, right-sized deployment
+ The platform (managed cost)
Best value with TechBag
- Full observability (infra, logs, security, DEM) — correlated
- TechBag scopes which services to trace, manages the bill
- Datadog bills USD; TechBag handles cost mgmt + GST
Buy it for less — TechBag pricing beats list
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.
Get an India-ready quote
Tell us your device counts and current tools — we’ll model it against what you spend today.
The 8 questions to ask every vendor
Take this into your next vendor call — including ours.
Do you see how your CODE & services perform, not just servers? APM traces requests and measures per-service performance — the view infra monitoring can't give.
Do you run microservices? Distributed tracing follows each request across them to pinpoint the bottleneck — essential (and hard without).
Do you want fast, full root cause? Datadog's trace → infra → log → session correlation (one platform, one click) is the fastest path.
Need to find inefficient code (for performance AND cost)? The Continuous Profiler goes down to the exact functions/lines.
APM is per-host, ON TOP of infra monitoring — the bill compounds. Scope which services to trace; manage the cost. TechBag handles it.
Concerned about setup? Datadog APM has easy/auto-instrumentation for many languages — fast to adopt.
Deepest AI RCA? Dynatrace. Cheaper? New Relic. OSS tracing? Grafana Tempo. Deep debugging? Honeycomb. TechBag compares honestly.
Datadog bills in USD, per-host (public) — TechBag scopes, manages cost, and handles GST invoicing.
Questions buyers ask
Ready to see exactly why your apps are slow?
Scope Datadog APM (trace every request, pinpoint the bottleneck, down to the code) — and let a TechBag advisor scope which services to trace, manage the added cost, and handle GST. Or compare vs New Relic/Grafana if cost is your priority.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.