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Top New Relic Alternatives Worth Evaluating in 2026

A Practical Guide for Teams Outgrowing New Relic

New Relic remains one of the strongest observability platforms on the market. It delivers full-stack monitoring, AI-powered capabilities, and fast root-cause analysis across metrics, events, logs, and traces. But in 2026, three structural issues are driving teams to evaluate alternatives:

  • Billing that punishes growth: New Relic’s per-seat “full platform” fee – $49 to $349/month for full platform access – compounds fast. For a 20-person team, the seat bill alone exceeds $6,980/month before a single byte of data is ingested. The newer Compute Capacity Unit (CCU) model removes seats but introduces billing opacity that is even harder to forecast.
  • NRQL lock-in: New Relic Query Language is proprietary. Every dashboard, alert, and custom query your team builds is non-portable. Switching platforms means rebuilding your entire query library from scratch.
  • SaaS-only architecture: For teams with HIPAA, GDPR, or data residency requirements, New Relic’s cloud-only model is not a preference issue – it is a compliance blocker.

This guide evaluates seven alternatives across pricing, OpenTelemetry support, deployment model, and real-world migration feasibility. Each tool is assessed against what New Relic actually costs at your scale – including the cloud egress fees most comparison guides ignore.

*Estimates based on 30TB/month ingestion, 100 hosts, 20 users, 30-day retention. Full methodology at end of article.*

Why Teams Are Looking for New Relic Alternatives

The Seat Tax: Per-User Pricing That Punishes Collaboration

New Relic’s Standard plan charges $99/month per full platform user (maximum five). Pro costs $349/user/month. This creates a dynamic where engineering leads ration access – deciding which developers are senior enough to deserve a login. When junior developers, support engineers, and product managers are locked out, incident response slows and knowledge concentrates in a few hands.

The CCU Model: Billing Opacity Disguised as Flexibility

New Relic’s Core Compute model removes seat limits but introduces Compute Capacity Units (CCUs) – a billing dimension that charges for queries, alerts, and data processing in ways that are genuinely difficult to forecast. Unlike GB-based pricing (pay per gigabyte ingested), CCU consumption can spike during incidents – precisely when engineers are running the most queries.

NRQL Lock-In: The Hidden Cost of Leaving

Every dashboard, alert, and custom query built in New Relic is non-portable. Teams that have spent years building operational knowledge in NRQL discover that switching platforms requires rebuilding their entire query library. Modern alternatives built on OpenTelemetry and SQL-compatible query engines avoid this problem – your queries and skills remain vendor-neutral.

SaaS-Only Architecture and Compliance Risk

New Relic supports regional data centers, but for teams with HIPAA, GDPR Article 44, DPDP Act, or FedRAMP requirements, the SaaS-first model may not satisfy data residency obligations. Self-hosted platforms that run inside your own VPC are structurally different – and for regulated industries, often the only viable option.

How We Evaluated the Best New Relic Alternatives

Most observability tools can collect logs, metrics, and traces. The biggest differences show up in pricing, OpenTelemetry support, deployment model, operational effort, and long-term fit.

  • Pricing model and cost predictability: How pricing behaves as telemetry volume grows, more users need access, and more features are used. We model GB-based, seat-based, and host-based pricing at consistent data volumes.
  • OpenTelemetry support – native vs bolt-on: OTel-native platforms ingest OTLP data without transformation – no context loss, no “OTel tax” on custom metrics. Platforms that added OTel as a layer on top of proprietary agents often require workarounds.
  • Deployment model: SaaS-only, self-hosted, or hybrid. For regulated industries, this is the deciding factor before any other evaluation begins.
  • Observability depth (MELT coverage): Metrics, Events, Logs, and Traces – the four pillars. We evaluate whether each platform covers all four and how well signals are correlated for investigation.
  • Kubernetes and cloud-native support: Where observability complexity grows fastest.
  • The hidden egress cost: When you send telemetry to any external SaaS platform, your cloud provider charges ~$0.10/GB for data leaving your VPC. At 30TB/month, that is $3,000/month, which does not appear on your observability invoice.
  • Ease of migration from New Relic: Can existing instrumentation be reused? How long does the transition take?

1. CubeAPM

Best for: Cost control, data sovereignty, and teams that want managed self-hosted observability

Overview

CubeAPM is a self-hosted, OpenTelemetry-native, full-stack observability platform built for teams that want unified visibility across metrics, events, logs, and traces without the cost sprawl common in SaaS observability tools. It runs inside your own AWS, GCP, or Azure VPC – traces, logs, and metrics never leave your infrastructure boundary. CubeAPM handles upgrades, patches, and platform operations; you provide the infrastructure.

Ranked in the top 10 APM platforms in G2’s Spring 2026 APM Grid Report. Capterra 5/5, G2 5/5, and #4 easiest-to-use APM tools on G2. Used by Policybazaar (insurance), Delhivery ($3.5B logistics – 75% savings after replacing three separate monitoring tools), Mamaearth ($1.2B), world’s largest bus aggregator – redBus (part of MakeMyTrip Limited (NASDAQ: MMYT), 8+ countries), Ola, and Practo (healthcare). SOC 2 Type II and ISO 27001 certified.

Key Features

  • Full MELT observability: Metrics, events, logs, and traces in one platform with a single investigation workflow
  • OpenTelemetry-native: Built from the ground up on OTel. No proprietary agent required. Compatible with OpenTelemetry, Datadog, New Relic, Elastic, and Prometheus agents for incremental migration
  • Self-hosted, vendor-managed: Deploys in your VPC. Zero cloud egress cost (saves ~$3,000/month at 30TB vs any external SaaS)
  • AI-based Smart Sampling: Reduces low-value telemetry volume while preserving high-value traces
  • Unlimited retention: Included in pricing – no separate retention charges
  • MCP server: Customers can query CubeAPM in natural language
  • 800+ integrations: Kubernetes, synthetic monitoring, RUM, and error tracking included

Pricing

Ingestion-based, predictable pricing of $0.15/GB. No per-user fees. No per-host charges. Unlimited users and unlimited data retention included.

At 30TB/month: ~$5,100/month all-in ($4,500 license + ~$600 infra)

Delhivery: 75% savings after replacing three separate monitoring tools. Mamaearth: ~70% savings, migrated in under an hour. redBus: 4x faster dashboards, 50% faster MTTR.

“Dashboards are astonishingly fast compared to New Relic – the migration process was also super smooth.”

Direct engineering support via WhatsApp and Slack channels – response in minutes during incidents.

Pros

  • 70-75% lower cost than enterprise APM at scale
  • Complete data ownership – telemetry never leaves your VPC
  • Predictable pricing with no hidden billing dimensions
  • Zero cloud egress cost
  • Fast migration – multiple customers report under an hour setup

Cons

  • Requires self-hosted deployment in cloud or on-prem; may not suit teams looking for a SaaS-only model.
  • AI/ML anomaly detection is growing, but not as mature as Dynatrace Davis AI
  • SSO/RBAC less mature than enterprise SaaS incumbents

2. Honeycomb

Best for: High-cardinality event debugging and OpenTelemetry-first distributed tracing

Overview

Honeycomb takes a fundamentally different approach to observability: it stores wide events and derives trace, log, and metric views from a single data model. This makes it exceptionally powerful for debugging high-cardinality distributed systems where traditional APM sampling loses the signal. Honeycomb is OpenTelemetry-first, with OTel as the primary instrumentation standard. A private cloud option was announced in November 2025 for teams with data residency requirements.

Key Features

  • OpenTelemetry-first: OTel is the primary and recommended instrumentation standard
  • Wide events data model: Stores rich, high-cardinality events and derives all views
  • Unified telemetry: Traces, logs, and metrics navigated in one workflow
  • BubbleUp: Automated outlier detection across telemetry dimensions
  • Log Analytics: Correlated with traces for richer debugging context

Pricing

Usage-based, starts at $0.10/GB ingested. Cost scales with telemetry volume.

At 30TB/month: ~$5,600/month (can range $5K-$24K depending on event volume and plan)

Pros

  • Strong OpenTelemetry-first product direction
  • Exceptional for distributed tracing and high-cardinality debugging
  • Unified navigation across traces, logs, and metrics
  • Good support for structured logs and telemetry pipelines

Cons

  • Primarily a tracing and debugging platform – infrastructure monitoring is not the core strength
  • SaaS-only (private cloud option announced November 2025 but still early)
  • Teams looking for a dashboard-first experience may find Honeycomb’s workflow different
  • Actual spend scales with telemetry volume even with clear ingest pricing

3. Dynatrace

Best for: Large enterprises that need AI-automated root cause analysis

Overview

Dynatrace differentiates with its Davis AI engine, which automatically maps service dependencies and performs causal root-cause analysis. Gartner ranks Dynatrace highest in “Ability to Execute” among observability vendors. The platform targets large enterprises with complex, fast-moving microservice estates.

Key Features

  • Davis AI: Automatic baselining, anomaly detection, and probable-cause analysis
  • Full-stack monitoring via OneAgent with automatic service discovery
  • OpenTelemetry support via OTLP API, OTel Collector, and Dynatrace Collector
  • Dedicated Kubernetes observability with flexible deployment via Dynatrace Operator
  • Log management with separate ingest, processing, and retention pricing

Pricing

Usage-based with separate rate-card units. Full-Stack Monitoring at $0.01/memory-GiB-hour, Log Management ingest/process at $0.20/GiB, retain at $0.0007/GiB-day.

At 30TB/month: ~$20,000-$35,000+/month

Breakdown: 100 hosts x $0.08/hr x 8 GiB x 730 hrs ~$4,700 + log ingest 20TB x $0.20/GiB ~$4,100 + log retention ~$430 + traces/metrics/APM + commitment overhead.

Pros

  • Best automated root cause analysis in the market
  • Automatic full-topology discovery – minimal manual configuration
  • Managed deployment option for data residency (Dynatrace Managed)
  • Strong compliance and enterprise security features

Cons

  • Proprietary OneAgent creates its own vendor lock-in
  • Memory-GiB-hour pricing is harder to estimate than flat per-GB models
  • Log retention billed separately from log ingestion
  • Davis AI requires a baselining period – new deployments do not get full value immediately

4. Grafana Cloud (LGTM Stack)

Best for: OTel-first teams that want flexible dashboards and open-source foundations

Overview

Grafana Labs assembled the LGTM stack – Loki (logs), Grafana (dashboards), Tempo (traces), Mimir (metrics) – into a coherent observability platform. Grafana Cloud is the managed version. Paired with Grafana Alloy (an OTel Collector distribution), it provides dedicated OTLP endpoints that auto-route signals to the right backend. Best for teams already running Prometheus who want to extend to full observability without a forklift migration.

Key Features

  • LGTM stack: Mimir for metrics, Loki for logs, Tempo for traces
  • Grafana Alloy: OTel Collector distribution with built-in Prometheus pipelines
  • Strongest dashboarding and visualization across multiple telemetry sources
  • k6 performance testing integrated into the observability ecosystem
  • Cost attribution features for metrics, logs, and traces

Pricing

Usage-based across telemetry types. Logs: $0.05/GB process + $0.40/GB write + $0.10/GB retain. Traces: same structure. Metrics: $6.50/1k active series. Platform fee: $19/month.

At 30TB/month (managed cloud): ~$15,000-$20,000+/month

Breakdown: 20TB logs ~$11,000 + 7TB traces ~$3,500 + 500K metric series ~$4,000 + base. Adaptive Metrics/Logs features can reduce this materially.

Pros

  • Fully OTel-native – no custom metrics penalty
  • Adaptive Metrics/Logs actively help reduce billing
  • Strong open-source community; highly customizable
  • Self-hosted path available for cost-driven teams with operational capacity

Cons

  • No native APM out-of-the-box – requires significant configuration
  • Self-hosting at scale requires dedicated SRE expertise
  • Usage-based pricing still grows with volume on managed cloud
  • LGTM stack has a steep learning curve for teams new to Grafana

5. Datadog

Best for: Broad SaaS ecosystem coverage with the budget to manage billing complexity

Overview

Datadog is the largest commercial observability platform and New Relic’s most direct competitor. Its integration catalog (900+) and feature breadth are unmatched – APM, logs, security, RUM, synthetics, and network monitoring under one roof. The trade-off is cost: host-based pricing compounds quickly at scale, and custom metrics charges are a persistent source of bill shock.

Key Features

  • Unified observability: metrics, logs, APM, RUM, synthetics, security, database monitoring
  • 900+ integrations – largest ecosystem in the category
  • Kubernetes Explorer with pod, deployment, and resource visibility
  • Synthetic monitoring across browser, API, and network-level tests
  • OpenTelemetry support via OTel Collector and Datadog Agent

Pricing

Multi-dimensional billing: hosts + custom metrics + log ingestion ($0.10/GB) + log indexing (~$1.70/million events) + APM spans + RUM sessions. OTel metrics are often billed as custom metrics.

At 30TB/month: ~$30,000-$45,000+/month

Breakdown (30% logs indexed): 100 hosts ~$2,400 + log ingest 20TB ~$2,000 + log indexing ~$30,000 + APM spans ~$3,000-5,000 + custom metrics ~$5,000+. Log indexing is the dominant cost driver.

Pros

  • Best-in-class integration ecosystem and product breadth
  • Strong Kubernetes, container, and cloud-native monitoring
  • Watchdog AI proactively surfaces anomalies
  • Mature CI/CD and deployment tracking

Cons

  • Billing complexity: host fees + custom metric overages + log indexing combine unpredictably
  • OTel metrics billed as custom metrics – adds cost for teams adopting open standards
  • SaaS-only – not suitable for teams with data residency requirements; self-hosted platforms are worth evaluating for those use cases
  • Total cost at scale significantly exceeds alternatives with simpler pricing models

6. Elastic APM

Best for: Teams already on the ELK stack who want to add APM without a new vendor

Overview

Elastic APM is the distributed tracing and application monitoring component of the Elastic Stack. For teams already indexing logs in Elasticsearch and visualizing in Kibana, adding APM is natural. It provides distributed tracing, service maps, error tracking, and MELT correlation. Note: Elastic APM’s OSS version reached end-of-service in September 2025 – evaluate managed options carefully for new deployments.

Key Features

  • Native Elasticsearch integration: APM data correlates directly with log indices
  • OpenTelemetry compatible across serverless, self-managed, and hybrid deployments
  • Machine learning-based anomaly detection via Elastic ML
  • RUM via JavaScript agent for frontend experience monitoring
  • Available self-hosted (SSPL license) or Elastic Cloud

Pricing

Self-hosted is free; you cover infrastructure. Elastic Cloud: consumption-based. Serverless Observability: Logs Essentials from $0.07/GB ingested + $0.017/GB retained/month.

At 30TB/month (Elastic Cloud): ~$8,000-$15,000/month

Pros

  • Zero incremental cost if already running Elastic for logs
  • Strong log + trace correlation in the same query interface
  • Self-hosted option keeps data on your infrastructure
  • ML-based anomaly detection included

Cons

  • Significant operational overhead to run self-hosted at scale
  • KQL (Kibana Query Language) is less developer-friendly than SQL
  • 2021 SSPL licensing change – review for open-source compliance
  • APM experience is less polished than purpose-built APM tools

7. Sentry

Best for: Developer-first teams that debug from code and user experience inward

Overview

Sentry is known for developer-first error monitoring that has grown into a broader application monitoring platform covering errors, tracing, logs, session replay, profiling, and cron monitoring. Best for developer-led teams that want fast issue triage without adopting a heavier infrastructure-first observability platform.

Key Features

  • Session Replay: Video-like reproductions of user sessions for web and mobile – a meaningful advantage for frontend debugging not available in most observability platforms
  • Error monitoring with stack traces, breadcrumbs, and context
  • Distributed tracing and performance monitoring
  • Profiling and cron monitoring
  • Self-hosted option available

Pricing

Event + usage-based. Team plan from $26/month base. Logs: $0.50/GB (Team PAYG). Spans: from $0.0000020/span above 5M.

At 30TB/month: ~$15,260/month

Pros

  • Best-in-class developer experience for error triage
  • Session Replay provides video-like debugging not found in traditional APM
  • Self-hosted option for data control
  • Strong frontend and mobile debugging capabilities

Cons

  • Primarily error and debugging focused – not full infrastructure observability
  • Teams needing deep infrastructure monitoring will need a complementary tool
  • Pricing at high volume can approach traditional APM costs
  • Less suited for infra-first or SRE-led observability workflows

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 ~$5K-$24K Usage-based Native Limited Limited
Dynatrace ~$20K-$35K+ GiB-hour + commit Partial Managed option Managed
Grafana Cloud ~$15K-$20K+ Usage-based Native If self-hosted Yes
Datadog ~$30K-$45K+ Host + feature-based Partial* SaaS only No
Elastic APM ~$8K-$15K Deployment-based Partial If self-hosted Yes
Sentry ~$15K-$32K Event + usage Partial If self-hosted Yes
New Relic (ref.) ~$20K-$25K+ Ingest + per-user Partial SaaS only No

* OTel metrics in Datadog are often billed as custom metrics. New Relic included as reference. All estimates use the methodology assumptions above. Vendor discounts and EDP commitments can significantly reduce SaaS costs.

What New Relic Actually Costs at Your Team Size

Most comparison guides show pricing tiers. What they do not show is how those tiers combine – data ingest + user seats + synthetics + cloud egress – into a real monthly bill.

Team Profile Data / Users New Relic /mo CubeAPM /mo Annual Saving Saving %
Small team 500 GB, 3 users ~$458 ~$75 ~$4,596/yr ~84%
Growing team 5 TB, 10 users ~$4,955 ~$750 ~$50,460/yr ~85%
Mid-market 30 TB, 50 users ~$24,745 ~$4,500 ~$242,940/yr ~82%
Enterprise 200 TB, 150 users ~$97,750 ~$30,000 ~$813,000/yr ~69%

New Relic costs: Standard plan, Original data ($0.40/GB beyond 100GB free), full platform users at $99 to $349 per user per month for full platform access. CubeAPM: $0.15/GB, no user fees. Enterprise pricing may include negotiated discounts not reflected here.

If you want to model your current New Relic bill before committing to a switch, the New Relic pricing calculator breaks down every cost dimension: data ingest, user seats, synthetics, and cloud egress fees most teams overlook.

The Hidden Cost: Cloud Data-Out Egress

When you send telemetry to any external SaaS platform – New Relic, Datadog, or any cloud-hosted alternative – your cloud provider charges approximately $0.10/GB for data leaving your VPC. At 30TB/month, that is $3,000/month in AWS or GCP egress fees, which does not appear on your observability invoice. Self-hosted platforms running inside your VPC have zero data-out cost.

How to Migrate from New Relic to an OTel-Native Platform

Migration anxiety is real – you have built dashboards, tuned alerts, and accumulated operational knowledge in New Relic over months or years. The good news: switching to an OpenTelemetry-native platform is structurally less painful than previous APM migrations. Once your services emit OTLP data, you can point that data at any compatible backend with a configuration change rather than re-instrumentation.

Week Focus Key Actions Exit Criteria
1 Instrument inventory List every service using NR agents. Map data volumes per service. Choose target platform. Full inventory. Platform selected.
2 Parallel run Deploy OTel Collector alongside NR agents on 1-2 non-critical services. Dual-write telemetry. Compare dashboards. Traces/metrics parity confirmed on pilot services.
3 Dashboard migration Recreate top 10 critical dashboards and all active alerts. Validate alert accuracy. Remove NR agents from pilot services. Critical dashboards live. Alert parity verified.
4 Full cutover Roll OTel agents to remaining services. Cancel NR agents service-by-service. Run NR in read-only mode for 2 weeks. All services on new platform. NR agents decommissioned.

Practical note: Run both platforms simultaneously for at least two weeks before cancelling New Relic. Teams consistently discover dashboards they forgot existed, alerts that were silently firing, or integrations that depended on NR’s API. Document what each dashboard is measuring, not the NRQL syntax, before migrating.

Which New Relic Alternative Is Right for Your Use Case?

  • Choose CubeAPM if cost predictability and data sovereignty are priorities. Predictable $0.15/GB pricing, unlimited users, runs in-VPC with zero egress cost.
  • Choose Honeycomb if your team prioritizes distributed tracing and high-cardinality debugging with an OpenTelemetry-first workflow. Best for teams that think in events rather than dashboards.
  • Choose Dynatrace if enterprise AI automation and causal root-cause analysis are your primary need. Be prepared for the annual commitment.
  • Choose Grafana Cloud if you are OTel-first, want flexible dashboards, and are comfortable managing or funding the LGTM stack.
  • Choose Datadog if you need the broadest SaaS ecosystem and your budget supports host-based pricing at scale. Model custom metrics costs before committing.
  • Choose Elastic APM if your team already runs ELK and wants to add distributed tracing without introducing another vendor.
  • Choose Sentry if your team is developer-led, debugging from code inward, and needs session replay and error monitoring more than infrastructure-first observability.

When New Relic Is Still the Better Choice

New Relic is still the right choice for teams that want a broad commercial observability platform with strong full-stack coverage in one SaaS environment.

  • If the free tier offering 100GB free per month is sufficient for your use case.
  • You want one vendor covering APM, infrastructure, browser, synthetics, Kubernetes, and incident workflows in one place.
  • You are already heavily invested in the New Relic ecosystem (dashboards, alerts, NRQL queries) and migration cost exceeds the pricing delta.
  • You need native OTLP ingest inside a commercial SaaS platform without moving to a self-managed stack.
  • You need mature synthetic monitoring with scripted browser/API tests and private locations.
  • You are comfortable actively managing telemetry volume, CCU consumption, and ingest governance.
  • You want AI-assisted observability (New Relic AI, alert-coverage analysis) built natively into the platform.

Final Thoughts

There is no single best New Relic alternative for every team. The right choice in 2026 depends on what matters most: pricing clarity, deployment model, OpenTelemetry fit, Kubernetes visibility, or day-two operational effort.

The practical decision tree is straightforward. If compliance or data residency is a hard requirement, self-hosted platforms are the only viable path – most SaaS alternatives do not solve this structurally. If cost is the primary driver, model your bill across data volume, user count, and cloud egress before committing – the gap between GB-based pricing and multi-dimensional billing models is often larger than teams expect. If enterprise automation is the priority, the AI-led platforms justify their premium for complex environments. If high-cardinality debugging and event-driven observability matter most, newer OTel-first platforms offer a fundamentally different investigation model.

Compare your top two options against your actual telemetry volume, deployment needs, and budget before making the switch. The numbers at your scale will make the decision clearer than any feature matrix.

Methodology

*Methodology: 30TB/month (~20TB logs, 7TB traces, 3TB metrics), 30% log indexing, 500K metric series, core observability only. Based on public rate cards, early 2026. Vendor discounts and EDP commitments can significantly reduce SaaS costs.*

Frequently Asked Questions

What is the best New Relic alternative in 2026?

There is no single best option for every team. For cost predictability and data sovereignty, self-hosted OTel-native platforms offer the strongest structural advantages. Datadog for the broadest SaaS ecosystem. Dynatrace for enterprise AI automation. Grafana for dashboards and OpenTelemetry flexibility. Honeycomb for high-cardinality distributed tracing. Sentry for developer-first error monitoring.

Which New Relic alternative is best for self-hosting?

Grafana (LGTM stack) and Elastic APM support fully self-managed deployment. For teams that want self-hosted observability without managing the backend themselves, vendor-managed self-hosted options exist that handle platform operations within your VPC.

Is Datadog better than New Relic?

Not across the board. Datadog has the largest integration ecosystem and strongest cloud-native monitoring breadth. New Relic remains strong for teams that want broad observability with OTLP ingest and a mature commercial platform. Both are significantly more expensive than OTel-native alternatives at the same data volume.

What is the cheapest New Relic alternative?

For teams below the free tier (1 user + 100GB/month), New Relic’s free tier is hard to beat. Beyond that, platforms with flat per-GB pricing and no per-user fees offer the lowest TCO at most team sizes – particularly when cloud egress savings are included in the calculation.

Can I use OpenTelemetry to replace New Relic agents?

Yes, and this is the recommended migration path. New Relic’s proprietary agents can be replaced with the OTel SDK for your language and the OTel Collector for batching and routing. New Relic itself accepts OTLP data, so you can migrate instrumentation to OTel without changing backends first – then point the Collector at your new platform when ready.

What happens to my data when I cancel New Relic?

New Relic retains your data according to your plan’s retention period after cancellation (8 days on Original plan, 90 days on Data Plus). After that, the data is deleted. This is why running your new platform in parallel for 2-4 weeks before cancelling is important.

What is Honeycomb best for compared to traditional APM?

Honeycomb excels at high-cardinality event debugging and distributed tracing. Unlike traditional APM platforms that aggregate metrics and sample traces, Honeycomb stores wide events and derives all views from them. This makes it exceptionally powerful for debugging complex microservice interactions where traditional sampling would lose the signal.

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