For Teams Scaling Fast Without Scaling Costs
Fast-growing engineering teams hit a familiar wall with application performance monitoring: the tool that felt affordable at launch starts billing per host, per seat, and per data dimension, so the invoice climbs faster than traffic does. As services multiply and on-call rotations grow, observability becomes one of the least predictable lines in the engineering budget, exactly when teams can least afford a surprise.
This guide compares seven APM platforms – CubeAPM, Datadog, New Relic, Grafana Cloud, Elastic APM, Honeycomb, and Sentry – on pricing, deployment, OpenTelemetry support, and full-stack coverage, so you can pick a platform that scales with your data instead of your headcount.
All cost estimates assume a mid-scale reference scenario: 30TB/month ingestion (~20TB logs, 7TB traces, 3TB metrics), 100 hosts, 20 full-platform users, 500,000 active metric series, and 30-day retention across all signal types, with core observability only. Estimates are directional, based on public rate cards as of early 2026; negotiated discounts can reduce SaaS costs significantly.
What to Look For in an APM Tool
- Predictable pricing: prefer a single, forecastable billing dimension over models that meter hosts, seats, custom metrics, and indexed data separately, where costs spike during the incidents when you query most.
- Data residency and ownership: for most SaaS vendors keeping telemetry in your own region is a paid add-on or not available at all; for self-hosted platforms like CubeAPM it is guaranteed by architecture.
- OpenTelemetry-native support: OTel instrumentation keeps your data portable and avoids proprietary agent lock-in as you change tools.
- Full-stack coverage and retention: APM, logs, infrastructure, and tracing in one place, with retention that does not force a costly trade-off as volume grows.
1. CubeAPM
Best for: DevOps and platform teams that want full-stack observability inside their own cloud without SaaS data egress, pricing sprawl, or DIY self-hosting overhead
CubeAPM is a self-hosted, OpenTelemetry-native, full-stack observability platform that runs inside your own AWS, GCP, or Azure VPC, so telemetry data stays inside your infrastructure while CubeAPM monitors the setup remotely. Pricing is a single meter – data ingested – so hosts, users, and custom metrics never add line items, which makes the bill scale with data rather than team size.
Used by Delhivery, Mamaearth, and the world’s largest bus aggregator – redBus (part of MakeMyTrip Limited (NASDAQ: MMYT), 8+ countries), among others. SOC 2 Type II and ISO 27001 certified, rated 5/5 on Capterra and G2, and a High Performer in the Spring 2026 APM Grid Report.
Key Features
- OpenTelemetry-native: compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents for incremental migration
- Self-hosted, vendor-managed: runs in your VPC with zero cloud egress cost, and your monitoring stays up even if the internet doesn’t
- Full MELT coverage, AI-based Smart Sampling, unlimited retention, and an MCP server that customers can use to query CubeAPM in natural language
- 800+ integrations: APM, logs, infrastructure, Kubernetes, Kafka monitoring, synthetic monitoring, RUM, and error tracking
Pricing
Ingestion-based pricing of $0.15/GB, with no per-user, per-host, or custom metric fees and unlimited users and retention included. At 30TB/month: ~$5,100/month all-in. Delhivery saw a 75% cost reduction after replacing three separate monitoring tools, and Mamaearth saved ~70% and migrated in under an hour.
- Pro: predictable single-dimension pricing, data never leaves your VPC, and direct engineering support via WhatsApp and Slack, which responds in minutes during incidents
- Con: requires self-hosted deployment in cloud or on-prem; may not suit teams looking for a SaaS-only model.
- Con: AI/ML anomaly detection is growing but not as mature as Dynatrace Davis AI
2. Datadog
Best for: Teams that want one mature SaaS platform across observability and security, and where cost is not a constraint
Datadog is the category leader, with 1000+ integrations and unified coverage across infrastructure, APM, logs, RUM, and synthetics, plus Watchdog AI for anomaly detection. The trade-off for fast-growing teams is its pricing model: hosts, custom metrics, log ingestion ($0.10/GB), log indexing, APM spans, and RUM sessions are each metered separately, and custom metrics alone can reach 30-52% of the bill at scale.
- Strengths: the deepest integration ecosystem and a mature, all-in-one SaaS platform.
- Watch-outs: multi-dimensional billing is hard to forecast, OTel metrics are often billed as custom metrics, and data leaves your infrastructure for analysis, so for teams where in-region data residency is a hard requirement, self-hosted platforms like CubeAPM are worth evaluating before committing.
- Pricing: host + feature-based. At 30TB/month: ~$30,000-$45,000+/month.
3. New Relic
Best for: Teams that want a broad full-stack SaaS platform with a generous free tier to start
New Relic consolidates APM, infrastructure, browser, mobile, synthetics, and logs into the NRDB store, with OTLP ingest as its recommended data path and a free tier of 100GB per month plus one full-platform user. Its model has two cost axes – data ingested and per-user seats – so spend grows with both volume and team size as you scale.
- Strengths: broad full-stack coverage, OpenTelemetry support, and a free tier that lowers the barrier to start.
- Watch-outs: the dual cost axis of data plus users, an 8-day default retention, and NRQL lock-in that adds migration work later.
- Pricing: $0.40/GB ingest plus user fees ($49 Core; $99 to $349 per user per month for full platform access). At 30TB/month: ~$20,000-$25,000+/month.
4. Grafana Cloud (LGTM Stack)
Best for: OpenTelemetry-first teams that want flexible dashboards and open-source foundations
Grafana Cloud is the managed LGTM stack – Loki, Grafana, Tempo, and Mimir – with the strongest dashboarding in the category, Grafana Alloy for OTLP ingestion, and Adaptive Metrics and Logs to trim ingestion costs. It is fully OTel-native with no custom-metrics penalty, and a self-hosted OSS path exists for teams with the operational capacity to run it.
- Strengths: fully OTel-native, the most flexible dashboards in the category, and a free self-hosted option.
- Watch-outs: APM is less mature than dedicated tools; there is no built-in AI/ML anomaly detection, and self-hosted Grafana is prone to performance degradation at scale as query times and dashboard load grow.
- Pricing: usage-based, ~$0.55/GB logs effective, $0.50/GB traces, $8 per 1,000 metric series. At 30TB/month (managed): ~$15,000-$20,000+/month.
5. Elastic APM
Best for: Teams already on the Elastic Stack that want flexible deployment with search, logs, and APM together
Elastic APM extends Elasticsearch with distributed tracing, service maps, and ML-based anomaly detection, correlating traces with logs in one query interface. It can run as SaaS or fully self-managed, which keeps data in your environment, a natural fit for teams already running the ELK stack.
- Strengths: strong log and trace correlation and a self-hosted option that keeps data in your environment.
- Watch-outs: operational overhead at scale, a less polished APM UX, and the 2021 SSPL licensing change to review for open-source compliance.
- Pricing: deployment-based; self-hosted is free (you cover infrastructure), Elastic Cloud from $99/month. At 30TB/month (Elastic Cloud): ~$8,000-$15,000/month.
6. Honeycomb
Best for: Engineering teams that want OTel-first observability and high-cardinality debugging across distributed systems
Honeycomb is built around wide events and OpenTelemetry as its primary instrumentation standard, deriving trace, log, and metric views from a single data model. BubbleUp automates outlier detection across telemetry dimensions, and SLOs and service maps round out fast investigation workflows that scaling teams value during incidents.
- Strengths: OTel-first design, fast high-cardinality investigation, and BubbleUp outlier detection. Watch-outs: less infrastructure-first than full-stack platforms, largely SaaS-only (private cloud is early), and cost still scales with event volume.
- Pricing: event-volume-based; Free up to 20M events/month, Pro from $130/month. At 30TB/month: ~$5,600/month.
7. Sentry
Best for: Developer-led teams that want strong error monitoring, performance debugging, and session replay
Sentry is developer-first, covering errors, tracing, logs, session replay, profiling, and uptime monitoring, with AI debugging via Seer. Its session replay gives video-like reproductions of user sessions for web and mobile that most observability platforms do not offer, and its SDKs use OpenTelemetry under the hood for tracing.
- Strengths: best-in-class error and performance debugging, session replay, and code-level troubleshooting.
- Watch-outs: primarily error and debugging focused, rather than full infrastructure observability, so it is narrower than a platform-style APM.
- Pricing: event + usage-based; Team from $26/month, Business from $80/month, logs $0.50/GB. At 30TB/month: ~$15,260/month.
Cost Comparison at 30TB/Month Ingestion
| Tool | Est. Cost @ 30TB/mo | Pricing Model | OTel Native | Data Residency | Self-Hosted |
|---|---|---|---|---|---|
| CubeAPM | ~$5,100/mo all-in | $0.15/GB ingestion-based | Native | Always (in-VPC) | Yes (vendor-managed) |
| Honeycomb | ~$5,600/mo | Event-volume-based | Native | SaaS only | Private cloud (early) |
| Elastic APM | ~$8K-$15K | Deployment-based | Supported | If self-hosted | Yes |
| Sentry | ~$15,260/mo | Event + usage-based | Supported | SaaS only | Yes |
| Grafana Cloud | ~$15K-$20K+ | Usage-based | Native | If self-hosted | Yes |
| New Relic | ~$20K-$25K+ | Data + users | Supported | SaaS only | No |
| Datadog | ~$30K-$45K+ | Host + feature-based | Supported* | SaaS only | Logs only (preview) |
* OTel metrics in Datadog are often billed as custom metrics. New Relic shows full platform users at $99 to $349 per user per month for full platform access. Estimates are directional; vendor discounts and committed-use agreements can significantly reduce SaaS costs.
Feature Matrix
| Tool | OTel-Native | Full-Stack APM | Self-Hosted | Unlimited Retention | Predictable Pricing |
|---|---|---|---|---|---|
| CubeAPM | Native | Yes | Yes | Yes | Yes (single meter) |
| Datadog | Supported* | Yes | Logs only (preview) | Add-on cost | No |
| New Relic | Supported | Yes | No | No (8-day default) | No (data + users) |
| Grafana Cloud | Native | Partial | Yes (OSS) | Configurable | Usage-based |
| Elastic APM | Supported | Yes | Yes | Configurable | Deployment-based |
| Honeycomb | Native | Partial | Early | Event-based | No (event volume) |
| Sentry | Supported | Partial | Yes | Limited | No (event-based) |
How to Choose the Right APM for Your Team
- CubeAPM: choose it for cost predictability and data ownership; a single $0.15/GB meter and in-VPC deployment keep spend and telemetry under your control.
- Datadog: choose it for the broadest integration ecosystem and one mature SaaS platform, when budget is not the binding constraint.
- New Relic: choose it for broad full-stack coverage and a free tier that makes it easy to start small.
- Grafana Cloud: choose it for OTel-first teams that want maximum dashboard flexibility and open-source foundations.
- Elastic APM: choose it if you already run the Elastic Stack and want search, logs, and APM together.
- Honeycomb: choose it for OTel-first, high-cardinality debugging across distributed systems.
- Sentry: choose it for developer-led error monitoring, performance debugging, and session replay.
Final Thoughts
For fast-growing teams, the deciding factor is rarely a missing feature; it is whether observability spend stays predictable as traffic, services, and headcount climb. SaaS incumbents offer the broadest ecosystems and the fastest setup, open-source-rooted platforms offer the most flexibility, and newer self-hosted platforms make the strongest case for cost predictability and data ownership.
Before committing, model your real telemetry volume, retention needs, residency requirements, and OpenTelemetry usage against your top two options, then run a short proof of concept. Those numbers decide it more clearly than any feature checklist.
Frequently Asked Questions
Which APM tool is most cost-effective as we scale?
It depends on your billing exposure. Tools that meter hosts, seats, and custom metrics separately tend to grow fastest with team size, while single-dimension, ingestion-based pricing scales with data alone. At a 30TB/month reference scenario, self-hosted, ingestion-priced platforms such as CubeAPM and event-based tools like Honeycomb sit well below host- and seat-based SaaS incumbents.
Should a fast-growing team choose SaaS or self-hosted APM?
SaaS tools are faster to deploy and need less operational management, which suits small teams early on. Self-hosted platforms keep telemetry in your own cloud, remove cloud egress fees, and keep monitoring available even during external outages, which matters more as compliance and uptime requirements tighten.
Does OpenTelemetry support help avoid vendor lock-in?
Yes. Instrumenting with OpenTelemetry keeps your telemetry portable, so you can switch backends without re-instrumenting every service. Platforms that are OTel-native, or compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents, let you migrate incrementally rather than through a hard cutover.
Are free tiers enough for a scaling team?
Free tiers, such as 100GB per month on New Relic or 20M events per month on Honeycomb, are useful for early-stage projects and evaluation, but most growing teams outgrow them quickly. The more important question is how predictable the bill becomes once you cross the free threshold.
Can we start with one tool and add others later?
Yes, and many teams do, using OpenTelemetry as the common instrumentation layer so data can flow to more than one backend. Plan for sampling strategy and ingestion costs early, and standardize on OTel so adding or replacing a tool later does not mean re-instrumenting your stack.
