Last9 vs Dynatrace: In-Depth Comparison 2026

Last9 and Dynatrace serve different ends of the observability market. Last9 is a newer platform built around high-cardinality telemetry and predictable event-based pricing, targeting mid-market SaaS and DevOps teams that want cost control without vendor lock-in. Dynatrace is an enterprise observability incumbent known for its Davis AI engine, full-stack automation, and deep support for complex hybrid cloud environments.

According to the CNCF’s 2024 Annual Survey, 87% of organizations now use logs, 57% use traces, and the average enterprise runs eight observability technologies. That fragmentation explains why Dynatrace’s unified platform and AI-driven automation appeal to large organizations, while teams at smaller scale increasingly evaluate alternatives like Last9 that offer simpler pricing and OpenTelemetry-native architecture without enterprise overhead.

This guide compares both platforms across pricing models, deployment options, APM signal depth, AI capabilities, and total cost of ownership. CubeAPM appears in the comparison table as a third option for teams evaluating both Last9 and Dynatrace.

Quick Comparison: Last9 vs Dynatrace at a Glance

Feature	Last9	Dynatrace	CubeAPM
Best for	Mid-market SaaS teams, high-cardinality use cases	Enterprise IT with complex hybrid cloud stacks	On-prem teams, data-sovereign, cost-sensitive
Pricing model	Event-based, starts $0.01/event	Per GiB ingested, full-stack license required	$0.15/GB flat, unlimited users
Deployment	SaaS only	SaaS + Managed (on-prem option available)	Self-hosted in your VPC or data center
OTel support	Native	Partial (requires OneAgent for full feature set)	Native
AI automation	Limited (anomaly detection, not full AIOps)	Davis AI for root-cause analysis, auto-discovery	Smart sampling, anomaly detection
Trace fidelity	High-cardinality friendly	Full-stack, auto-instrumented via OneAgent	Full-fidelity, zero sampling
Log management	Integrated, event-based billing	Integrated with Grail data lakehouse	Integrated, same $0.15/GB rate
On-prem option	No	Yes (Dynatrace Managed)	Yes (default deployment model)
APM depth	Traces, metrics, logs, Kubernetes-native	Full-stack APM, RUM, synthetics, infra, security	APM, distributed tracing, logs, infra, RUM, synthetics
Monthly cost (13TB)	~$4,200 (estimated, event count dependent)	~$7,800–$10,400 (estimate, varies by license tier)	$1,950

Pricing estimates based on a standardized 13TB/month ingestion profile with 60 hosts and mixed signal types. Actual costs vary by retention, indexing, support tier, and enterprise discounts. Verify current rates at [Last9 pricing](https://last9.io/pricing/) and [Dynatrace pricing](https://www.dynatrace.com/pricing/).

Last9 Overview

Last9 is a newer observability platform launched to address cost unpredictability and vendor lock-in in traditional APM tools. It is built around event-based pricing and high-cardinality telemetry, designed for SaaS companies and DevOps teams running Kubernetes-heavy workloads.

Key strengths:

• Event-based pricing model — charges per event ingested, not per host or user, which can be more predictable for teams with stable cardinality profiles
• High-cardinality support — handles dimensional metrics and trace attributes without requiring pre-aggregation or sampling at the edge
• OpenTelemetry-native — no proprietary agents, full compatibility with OTel collector and SDK instrumentation
• Kubernetes-first monitoring — built-in support for pod labels, namespace filtering, and Kubernetes event correlation

Known limitations:

• SaaS-only deployment — no on-prem or BYOC option, which rules it out for regulated industries with data residency requirements
• Limited AI automation — offers anomaly detection but lacks the autonomous root-cause analysis and auto-remediation features found in Dynatrace’s Davis AI
• Smaller ecosystem — fewer pre-built integrations and dashboards compared to Datadog or Dynatrace
• Event pricing complexity — while event-based pricing can be predictable, it requires upfront estimation of event volume, and miscalculating cardinality can lead to surprise bills

Pricing:

Last9 pricing starts at $0.01 per event ingested. The total monthly cost depends on how many events your instrumentation generates, which varies by cardinality, sampling strategy, and workload type. A team ingesting 500 million events per month would pay approximately $5,000 per month before retention add-ons or support tiers.

Dynatrace Overview

Dynatrace is an enterprise observability platform that has been in the APM market since 2005 (originally as Compuware). It is known for its Davis AI engine, which automates anomaly detection, root-cause analysis, and dependency mapping across full-stack environments.

Key strengths:

• Davis AI automation — automatically detects anomalies, identifies root causes, and maps dependencies across distributed systems without manual configuration
• Full-stack coverage — infrastructure, APM, real user monitoring, synthetics, logs, security, and business analytics in one platform
• OneAgent auto-instrumentation — single agent auto-discovers services, instruments code, and injects distributed tracing without manual SDK instrumentation
• Hybrid cloud support — works across AWS, Azure, GCP, Kubernetes, OpenShift, and on-prem data centers with unified topology mapping

Known limitations:

• High cost — Dynatrace is consistently one of the most expensive APM platforms at scale, with per-GiB ingestion pricing compounded by full-stack license fees
• OpenTelemetry support is partial — while Dynatrace can ingest OTel data, full feature parity requires OneAgent, which is proprietary and creates vendor lock-in
• Complex pricing model — pricing varies by product (infrastructure, full-stack, logs, security), making cost estimation difficult without a sales call
• Steep learning curve — advanced features like Davis AI and custom metric ingestion require significant onboarding and expertise

According to user reports on Reddit, teams have documented Dynatrace bills jumping from $12,000 to $28,000 per month after log ingestion increased during a production incident, with no prior warning or throttling mechanism.

Pricing:

Dynatrace pricing is consumption-based and varies by license tier. Infrastructure Monitoring starts at approximately $0.08 per GiB ingested. Full-Stack Monitoring, which includes APM, logs, and Davis AI, costs approximately $0.20 per GiB ingested with a minimum annual commitment. Enterprise contracts typically run $50,000 to $500,000+ annually depending on scale.

This estimate models a production observability setup with mixed signal types. Actual costs will vary based on retention period, feature usage, and negotiated enterprise discounts.

Feature-by-Feature Comparison

APM and Distributed Tracing

Last9:

Last9’s APM is built on OpenTelemetry spans and supports full distributed tracing across microservices. It retains high-cardinality trace attributes, making it well-suited for debugging distributed systems where context matters. Traces are searchable by any tag, and trace retention is unlimited at the standard pricing tier.

Trace instrumentation requires manual SDK or OTel collector configuration. There is no auto-instrumentation agent.

Dynatrace:

Dynatrace’s OneAgent automatically instruments applications at runtime, injecting distributed tracing without code changes. It captures full-fidelity traces across JVM, .NET, Node.js, Python, Go, and PHP. Traces are correlated with infrastructure metrics, logs, and real user sessions via the Davis AI topology map.

Dynatrace’s PurePath technology captures every transaction by default, then uses AI-driven sampling to retain the most relevant traces. This ensures full context during incidents without storing every trace indefinitely.

Verdict:

Dynatrace wins on automation and full-stack context. Last9 wins on cost and OTel compatibility for teams that prefer open standards over proprietary agents.

Log Management

Last9:

Last9 ingests logs as events and charges per event, making log costs predictable if your log volume is stable. Logs are indexed and searchable by default with no separate indexing fee. Retention is unlimited.

Last9 does not offer built-in log parsing or structured field extraction. Teams typically send pre-parsed JSON logs via the OTel collector.

Dynatrace:

Dynatrace’s Grail data lakehouse unifies logs, metrics, traces, and security events in a single queryable data store. Logs are auto-parsed, indexed, and correlated with APM traces and infrastructure metrics. Dynatrace Query Language (DQL) allows complex log queries across petabytes of data.

Log ingestion is charged at $0.08 per GiB for Infrastructure Monitoring or included in the Full-Stack Monitoring license at $0.20 per GiB.

Verdict:

Dynatrace wins on log correlation, auto-parsing, and query power. Last9 wins on cost if your log volume is high and you do not need advanced parsing.

Infrastructure Monitoring

Last9:

Last9 monitors infrastructure via Prometheus or OpenTelemetry metrics. It supports Kubernetes node metrics, pod health, and cluster-level resource utilization. Infrastructure metrics are billed as events, same as logs and traces.

There is no built-in agent for host-level monitoring. Teams must configure Prometheus exporters or OTel receivers.

Dynatrace:

Dynatrace’s OneAgent monitors hosts, containers, Kubernetes clusters, and cloud services automatically. It tracks CPU, memory, disk, network, and process-level metrics in real time. Infrastructure health is correlated with application performance via the Davis AI topology map.

Dynatrace also monitors AWS, Azure, and GCP services natively, ingesting cloud provider metrics without additional configuration.

Verdict:

Dynatrace wins on automation and cloud-native integrations. Last9 requires more manual configuration but offers cost advantages for teams already running Prometheus.

Kubernetes Monitoring

Last9:

Last9 is Kubernetes-native and supports filtering by namespace, pod label, and deployment. It surfaces Kubernetes events alongside metrics and traces, making it well-suited for cloud-native teams.

Kubernetes monitoring requires configuring the OTel collector with Kubernetes receivers.

Dynatrace:

Dynatrace’s OneAgent operator auto-discovers Kubernetes clusters, nodes, pods, and services. It monitors HPA scaling events, pod restarts, OOMKills, and control plane health. Dynatrace also correlates Kubernetes events with application traces and infrastructure metrics.

Verdict:

Dynatrace wins on automation and depth. Last9 wins on flexibility and cost for teams that prefer Kubernetes-native tooling over proprietary agents.

AI and Anomaly Detection

Last9:

Last9 offers basic anomaly detection on metrics and traces. Alerts are rule-based with threshold configuration. There is no autonomous root-cause analysis or auto-remediation.

Dynatrace:

Dynatrace’s Davis AI is the platform’s defining feature. It automatically detects anomalies, identifies root causes by analyzing dependencies across infrastructure, applications, and users, and prioritizes alerts by business impact.

Davis AI also provides automatic baselining, meaning it learns normal behavior for every service and metric without manual threshold configuration.

According to Dynatrace’s own case studies, BT (British Telecom) reduced IT tickets by 99% after deploying Dynatrace with Davis AI enabled.

Verdict:

Dynatrace wins decisively. Last9’s anomaly detection is functional but not autonomous.

Deployment Model

Last9:

Last9 is SaaS-only. Telemetry data is sent to Last9’s cloud, processed, and stored in their infrastructure. There is no on-prem or BYOC deployment option.

Dynatrace:

Dynatrace offers two deployment models:

1. Dynatrace SaaS — fully managed cloud service
2. Dynatrace Managed — runs in your own data center or private cloud, giving you full data residency and control

Dynatrace Managed is the same platform as SaaS but deployed on your infrastructure.

Verdict:

Dynatrace wins for regulated industries and teams with data residency requirements. Last9’s SaaS-only model rules it out for HIPAA, GDPR, or PCI-DSS use cases that prohibit external telemetry export.

CubeAPM also offers self-hosted deployment by default, making it an alternative for teams evaluating on-prem options.

Pricing Comparison

Dynatrace and Last9 use fundamentally different pricing models, making direct comparison difficult without modeling a specific workload.

Cost Scenario: Mid-Market SaaS Team

Assumptions:

• 60 hosts (Kubernetes nodes + database servers)
• 13TB/month ingestion (7TB logs, 4TB traces, 2TB metrics)
• 30-day retention, all signal types
• 15 engineering users with full access

Last9:

Last9 charges per event, not per GB. A 13TB workload typically generates 400–600 million events per month depending on cardinality. At $0.01/event, this scenario costs approximately $4,200–$6,000/month.

Dynatrace:

Dynatrace Full-Stack Monitoring at $0.20/GiB ingested costs approximately $2,600/month for 13TB. However, the full-stack license requires a minimum annual commitment, typically $50,000–$75,000 for mid-market deployments, bringing the effective monthly cost to $4,200–$6,250.

Infrastructure Monitoring alone (without APM or logs) costs less but does not include distributed tracing or Davis AI.

This estimate models a production-ready setup with full observability across logs, metrics, and traces. Actual costs will vary based on retention, enterprise discounts, and feature usage.

CubeAPM:

CubeAPM charges $0.15/GB flat for all signal types with unlimited retention and no per-user fees. The same 13TB workload costs $1,950/month.

Hidden Cost: Data Egress

Both Last9 and Dynatrace charge for data transfer when telemetry is sent from your cloud to their SaaS platform. AWS, Azure, and GCP charge approximately $0.08–$0.12 per GB for public internet egress.

For a 13TB/month workload, cloud egress fees add $1,040–$1,560/month to your total observability bill. This cost is often overlooked during evaluations but appears as a separate line item on your cloud provider invoice.

CubeAPM eliminates egress fees entirely by running inside your VPC.

Who Should Choose Each

Choose Last9 if:

• You are a mid-market SaaS or DevOps team running Kubernetes-heavy workloads
• You want high-cardinality telemetry support without sampling at the edge
• You prefer OpenTelemetry-native tools over proprietary agents
• You can accurately estimate your event volume upfront
• You do not have data residency or HIPAA/GDPR compliance requirements

Choose Dynatrace if:

• You are an enterprise IT organization managing complex hybrid cloud environments
• You need AI-driven root-cause analysis and automated dependency mapping
• You require full-stack observability across infrastructure, APM, RUM, synthetics, and security in one platform
• You have budget for enterprise-grade observability and prefer turnkey automation over manual configuration
• You need on-prem deployment for data sovereignty

Consider CubeAPM if:

• You need self-hosted deployment with managed support
• You want predictable $0.15/GB pricing with unlimited retention and no per-user fees
• You require full data residency and compliance by default
• You prefer OpenTelemetry-native tools with zero vendor lock-in

Verdict

Last9 and Dynatrace serve different segments of the observability market. Last9 is well-suited for mid-market teams that want high-cardinality telemetry and predictable event-based pricing without enterprise overhead. Dynatrace is built for large enterprises that need AI-driven automation, full-stack coverage, and hybrid cloud support, and are willing to pay premium prices for those capabilities.

If you are a regulated industry or require on-prem deployment, Last9 is not an option. Dynatrace Managed or CubeAPM become the primary alternatives.

If you are optimizing for cost and prefer open standards, Last9 or CubeAPM offer significant savings over Dynatrace. If you are optimizing for automation and full-stack depth, Dynatrace justifies its cost through reduced manual effort and faster incident resolution.

For teams evaluating both, the decision typically comes down to three factors: deployment model (SaaS vs on-prem), pricing predictability (event-based vs consumption-based vs flat-rate), and automation depth (rule-based alerts vs AI-driven root-cause analysis).

Disclaimer: The information in this article reflects the latest details available at the time of publication and may change as technologies and products evolve. Features, pricing, and plan limits can change over time. Always verify the latest information directly with the vendor before making purchasing or deployment decisions.

Frequently Asked Questions