Observability · 2026 Guide

Dynatrace Alternatives for SRE Teams: The Complete 2026 Guide

By Ayush M.Published on: Nov 14, 202613 min read
The seven alternatives
Sherlocks AIDatadogNew RelicGrafana CloudSigNozOpenObserveHoneycomb
TL;DR

Teams leave Dynatrace for one of four reasons: memory-hour billing, the annual commitment, OneAgent versus OpenTelemetry, or platform weight. For the broadest SaaS replacement pick Datadog; for a familiar APM with simpler pricing, New Relic; for OpenTelemetry-native managed observability, Grafana Cloud; to self-host, SigNoz; for the lowest cost at high log volume, OpenObserve; for high-cardinality debugging, Honeycomb. None of them gives you Davis-style automated root cause out of the box, so decide where investigation lives before you decide where data lives. Sherlocks AI is that investigation layer, on top of whichever stack you pick.

Dynatrace is still one of the strongest observability platforms on the market. For enterprises with the budget to match, OneAgent's single-install coverage and Davis AI's automated root cause analysis remain genuinely useful. But the questions SRE teams are asking in 2026 are not about product strength. They are about the renewal quote, the commitment model, the OpenTelemetry story, and whether the platform's complexity still fits a team that has grown leaner since the contract was signed.

This guide compares seven Dynatrace alternatives on the things that actually matter when you are evaluating a switch: pricing model, deployment options, integration surface, and what each tool is genuinely best at replacing. Every price below is from the vendor's pricing page as of November 2026.

Why teams look past Dynatrace in 2026

Dynatrace is not a weak product. OneAgent instruments a host once and maps every process, service, and dependency into Smartscape, and Davis AI (now part of Dynatrace Intelligence) walks that map to rank a probable root cause when an alert fires. For a large enterprise estate, that is still a defensible position.

Teams leave for four reasons, and the alternative you should pick depends on which one is yours.

1

The bill tracks memory and hours, not value

Dynatrace Platform Subscription (DPS) prices Full-Stack Monitoring at $58 per month per 8 GiB host, metered at $0.01 per memory-GiB-hour. Infrastructure Monitoring is $29 per host per month. Kubernetes Platform Monitoring is $1.40 per pod per month, included on Full-Stack hosts. Log costs arrive in three parts: $0.20 per GiB ingested, $0.0007 per GiB-day retained, and $0.0035 per GiB scanned.

Each number looks small in isolation. Multiplied across a production fleet, a noisy incident window, and six months of historical retention, the monthly figure is not small at all. Teams moving to consumption-based observability without a capacity-planning muscle are the ones who get the worst surprises.

2

The annual commitment model

DPS is one annual spend commitment that you draw from across every Dynatrace capability. Dynatrace does not charge penalty overages, which is genuinely a good design. But unused commitment is money spent, and the renewal quote starts from last year's peak usage, not your average. Teams with seasonal or event-driven workloads routinely over-commit the first year and under-negotiate the second.

3

OneAgent versus OpenTelemetry

OpenTelemetry has become the de facto standard for instrumenting modern applications. Dynatrace supports OpenTelemetry, but the platform's deepest features (Smartscape mapping, PurePath distributed traces, some Davis AI inputs) still get the richest data from OneAgent. Teams that have invested in OpenTelemetry end up either running two agents in parallel or accepting that they are not getting the full Dynatrace experience.

4

Weight

DQL, Smartscape, Grail, and the DPS rate card are each a learning curve in their own right. A platform engineering team of five does not always want a platform that assumes a platform engineering team of fifty. The sticker-shock conversation is usually a weight conversation in disguise.

What you are not leaving behind

The idea of automated root cause analysis. Davis AI set the expectation that an observability platform tells you why, not just what. Dynatrace now meters that explicitly: autonomous investigations are billed under "Agentic Operations" at $0.10 per AI unit, with Dynatrace's own example suggesting around 30 units per multi-step investigation, or roughly $3 per run. For a limited time Dynatrace is not billing these inside Dynatrace Assist, only when they run through workflows, MCP, or the API.

Whichever alternative you choose, you need a plan for where the investigation step will live. The cheapest observability stack with no investigation layer still leaves the on-call engineer doing the dashboard-hopping at 3 a.m.

The best Dynatrace alternative depends on why you are leaving

Davis-style automated root cause without the Dynatrace footprint
Keep the observability stack you move to and add Sherlocks AI as the investigation layer
The broadest single SaaS platform
Datadog
A familiar APM with simpler pricing
New Relic
OpenTelemetry-native and managed
Grafana Cloud
Self-hosted and open source
SigNoz
Lowest cost at high log volume
OpenObserve
High-cardinality debugging for a product team
Honeycomb

The seven alternatives in detail

#1AI investigation layer

Sherlocks AI

sherlocks.aiPricing
Best for

Keeping Davis-style automated root cause when you leave Dynatrace

When to pick

You are moving to a different observability platform (or stitching several together) and do not want to lose the "platform tells you why" experience in the process.

Sherlocks AI is an AI SRE platform that runs read-only against whatever observability stack you keep. The Watson agent correlates logs, metrics, traces, and recent deploys when an alert fires and posts a drafted root cause to Slack within minutes, with the evidence and the ruled-out hypotheses attached.

Two things make it different from Davis AI as an investigation layer:

  • It reads across whatever tools you keep. The investigation survives the migration. You can run it on top of Datadog today, migrate to Grafana Cloud next year, and Sherlocks keeps working through the change.
  • Pricing is not metered per AI unit. The free tier includes 30 investigations per month, which is enough for most teams to validate value before paying, and Enterprise has unlimited investigations.
Pricing
Free tier of 30 investigations per month. Enterprise is custom pricing with unlimited investigations.
Deployment
SaaS, in-VPC, air-gapped (Enterprise).
Watch out
Sherlocks AI is an investigation layer. It does not collect telemetry on its own. You still need one or more platforms below it (Datadog, Grafana Cloud, New Relic, SigNoz, Prometheus, and so on).
Go deeper:Real investigations, step by stepSherlocks AI vs Datadog Bits AI
#2Full observability platform

Datadog

datadoghq.comPricing
Best for

The broadest like-for-like replacement

When to pick

Your reason for leaving Dynatrace is OneAgent weight and the DQL learning curve, not cost. You want a single SaaS pane with APM, logs, metrics, synthetics, and RUM in one bill.

Datadog's product surface is the closest to Dynatrace's in terms of breadth. APM starts at $31 per host per month (billed annually, with Infrastructure Monitoring), and the bill per host climbs well past that once logs, synthetics, and additional products are added. A 14-day free trial is available. Bits Investigation, Datadog's own investigation agent, is priced through AI Credits, and Datadog reports an average cost of about $4 per investigation.

Pricing
APM from $31 per host per month (annual, with Infrastructure Monitoring), log ingestion from $0.10 per GB.
Deployment
SaaS.
Watch out
Per-product SKUs multiply quickly. The headline price per host is not what you will pay at full deployment.
Go deeper:Datadog alternatives (2026)Sherlocks AI on Datadog
#3Full observability platform (APM-first)

New Relic

newrelic.comPricing
Best for

A familiar APM experience with simpler, usage-based pricing

When to pick

You want a forecastable bill based on data volume and user headcount, and your team already knows how to work with New Relic-style APM.

New Relic moved to a unified pricing model with 100 GB of data ingest free per month, then $0.40 per GB ingested, plus per-user pricing for full platform users. The free tier includes one full platform user.

Pricing
100 GB free, $0.40 per GB after, plus per-user pricing for full platform users.
Deployment
SaaS.
Watch out
Per-user pricing becomes meaningful at 20+ engineers. Model the user count honestly in your estimate.
Go deeper:New Relic alternatives (2026)
#4OpenTelemetry-native managed observability

Grafana Cloud

grafana.comPricing
Best for

Teams standardizing on open standards with a managed backend

When to pick

You run Prometheus, Loki, and Tempo (or want to), prefer OpenTelemetry over proprietary agents, and want someone else to run the storage layer.

Grafana Cloud's free tier includes 10,000 active metrics series, 50 GB each of logs, traces, and profiles, and 3 active users. Paid plans start at $19 per month plus usage, and the Pro tier moves to active-user pricing rather than per-seat.

Pricing
Free tier available, Pro from $19 per month plus usage.
Deployment
SaaS, with managed Grafana Enterprise options.
Watch out
Root cause analysis stays manual unless you add an investigation layer. [Grafana Assistant](https://grafana.com/docs/grafana-cloud/machine-learning/assistant/) is generally available, priced per active AI user, but its investigation features only reached general availability in July 2026.
Go deeper:Sherlocks AI on Prometheus and Grafana
#5Open-source observability

SigNoz

signoz.ioPricing
Best for

Teams who want to self-host and have the engineering time

When to pick

You are OpenTelemetry-native, have at least one engineer who can own the stack, and your cost reason is more about avoiding SaaS multipliers than about the licensing model.

SigNoz is open source and self-hostable, with a managed cloud tier starting at $49 per month. The product covers APM, logs, metrics, and tracing in one stack, built on ClickHouse and OpenTelemetry.

Pricing
Self-host free, SigNoz Cloud from $49 per month.
Deployment
Self-hosted or SaaS.
Watch out
Budget the engineer time honestly. Self-hosted observability is cheaper per GB and more expensive per hour of operator time.
Go deeper:The best observability tools for SRE teams
#6Open-source logging and observability

OpenObserve

openobserve.aiPricing
Best for

High log volume at low storage cost

When to pick

Logs are the dominant cost center in your observability bill and you want object-storage economics rather than per-GB retention pricing.

OpenObserve stores logs on object storage (S3, GCS, Azure Blob), which fundamentally changes the retention cost model. Self-hostable and open source, with a managed cloud option at $0.50 per GB ingested.

Pricing
Self-host free, OpenObserve Cloud from $0.50 per GB ingested.
Deployment
Self-hosted, SaaS, and BYOC.
Watch out
Younger ecosystem than Grafana or SigNoz. Fewer out-of-the-box integrations and a smaller community.
Go deeper:How to choose an observability platform
#7High-cardinality debugging and tracing

Honeycomb

honeycomb.ioPricing
Best for

Product engineering teams who need to slice on unique request attributes

When to pick

You run a complex distributed system where the question you actually need to answer is "which user, which request, which endpoint, under which build." Honeycomb's query model is built for this.

Honeycomb's free tier includes 20 million events per month. Paid plans start at $150 per month with unlimited seats, which is a different pricing shape from everyone else on this list and often friendlier for larger teams.

Pricing
Free tier (20M events), Pro from $150 per month.
Deployment
SaaS.
Watch out
Honeycomb is tracing-first. You will likely pair it with a metrics tool (Prometheus, Grafana Cloud) for the full observability picture.
Go deeper:Metrics, logs, traces and events

Dynatrace alternatives at a glance

Dynatrace alternatives compared on category, pricing model, free tier, deployment and investigation layer
ToolCategoryPricing modelFree tierDeploymentInvestigation layer
Sherlocks AIAI investigationFree tier, then Enterprise30 investigations/monthSaaS, in-VPC, air-gappedYes, built-in
DatadogFull platformPer host + per product14-day trialSaaSBits Investigation (~$4/run)
New RelicFull platformPer GB + per user100 GB + 1 full platform userSaaSNew Relic AI (assistant)
Grafana CloudOTel-managedUsage-based10k series, 50 GB logs, 3 active usersSaaSGrafana Assistant
SigNozOpen sourceSelf-host free, cloud from $49Self-hostSelf-hosted, SaaSManual
OpenObserveOpen sourceSelf-host free, cloud from $0.50/GBSelf-hostSelf-hosted, SaaS, BYOCManual
HoneycombTracing-firstPer event20M events freeSaaSManual
DynatraceReferenceFull platformPer memory-GiB-hour + per host15-day trialSaaS, ManagedDavis AI / Dynatrace Intelligence (~$3/run)

Scroll the table sideways to see every column.

How to decide in a week

Observability migrations go wrong when teams decide on product feel instead of on consumption. A one-week evaluation that actually works:

  1. Day 1 to 2

    Pull your last month's actual Dynatrace consumption. How many hosts, how many GiB-hours, how many logs ingested, retained, scanned. This is your ground truth.

  2. Day 3

    Price that exact consumption through each candidate's rate card. The answers will not match the headline marketing numbers. Several candidates that look cheaper will not be cheaper at your actual volume.

  3. Day 4

    Decide where root cause analysis lives before deciding where data lives. If you want to keep "the platform tells me why," pick either a vendor with an investigation layer (Datadog Bits AI, Sherlocks AI on top of anything), or budget a separate line item for it. Do not assume it comes for free.

  4. Day 5 to 6

    Run OpenTelemetry in parallel. Any vendor you shortlist should accept OTel data. Instrument one service both ways and compare the depth of the resulting traces.

  5. Day 7

    Check the exit terms before you sign. What does the data look like in 12 months when you leave this one too?

When to keep Dynatrace

Keep Dynatrace if any of the following are true:

  • Your estate is large enough that the commitment buys a lower unit rate than list prices on the alternatives.
  • You run heavy enterprise Java or .NET workloads that OneAgent instruments better than open-source alternatives.
  • Your team is already fluent in DQL, Smartscape, and Davis AI, and the switching cost would be six-plus months of productivity.

If you are in this bucket, the better move is often to keep Dynatrace, negotiate the renewal from a stronger position, and add an independent investigation layer like Sherlocks AI alongside it. That way the next renewal conversation includes "we also have a vendor-neutral RCA system in place," which changes what Davis AI is worth.

Frequently asked questions

Grafana Cloud or SigNoz for pure Kubernetes observability, both OpenTelemetry-native. If you need Kubernetes incident investigation on top (automated RCA for pod crashes, HPA events, OOMKills), add Sherlocks AI as the investigation layer. Komodor, now an AI SRE platform built for Kubernetes, is also worth evaluating.

SigNoz and OpenObserve are both open source and self-hostable with no license fees. Grafana Cloud has a free tier that covers small deployments. None of these include Davis-style automated root cause out of the box, so budget for an investigation layer separately.

Not reliably. Datadog's per-host APM is $31 per month on an annual plan, versus Dynatrace Full-Stack at $58 per 8 GiB host, which looks cheaper at face value. But the Datadog bill per host climbs well past the APM price once logs, synthetics, RUM, and other SKUs are added. Price both against your actual consumption, not the marketing headline.

For large log volumes, OpenObserve has the lowest storage cost because it writes to object storage directly. For smaller teams with OpenTelemetry already in place, SigNoz self-hosted is usually the cheapest once you account for engineer time. For teams who want to stay on SaaS, Grafana Cloud's free tier plus usage pricing is often the lowest predictable spend.

SigNoz is the closest self-hosted equivalent for APM, logs, metrics, and traces in one stack. OpenObserve for logs-first workloads. Grafana + Prometheus + Loki + Tempo if you want to assemble the stack yourself. Dynatrace Managed also exists as a customer-hosted Dynatrace option if you want the Dynatrace product without the SaaS model.

Grafana Cloud replaces the dashboards, metrics, logs, and traces part of Dynatrace. What it does not replace out of the box is the Davis AI investigation layer. If you move from Dynatrace to Grafana Cloud, pair it with an investigation agent (Sherlocks AI, or Grafana's own Assistant) to close that gap.

Two different kinds of tool can replace Davis AI, depending on what you want:

  • An AI SRE agent that works across your stack: Sherlocks AI, Cleric, Resolve AI, Traversal, and OpsWorker all fit here. They read whatever observability stack you have and investigate when alerts fire.
  • An AI feature inside another observability platform: Datadog Bits AI, New Relic AI, Grafana Assistant. These are tied to a specific telemetry platform.

The first group is the right fit if you are leaving Dynatrace and do not want to be locked into another platform's AI. The second group is the right fit if you are already moving to a specific platform and want the AI feature bundled.

No. Sherlocks AI is an investigation layer, not an observability platform. It does not collect metrics, logs, or traces on its own. It reads from whatever observability stack you run and investigates incidents on top. Think of it as replacing the "Davis AI" part of Dynatrace while you pick a different stack for everything else.

The short version

Teams leaving Dynatrace in 2026 are usually solving for one of four things: consumption billing, annual commitment, OpenTelemetry fit, or platform weight. The right alternative depends on which one.

If you are optimizing for cost, model your actual consumption through each rate card, do not trust marketing headlines. If you are optimizing for OpenTelemetry, shortlist Grafana Cloud, SigNoz, and OpenObserve. If you are optimizing for keeping the "platform tells you why" experience, the investigation layer is a separate decision from the observability layer, and keeping it independent (Sherlocks AI on top of any stack) is usually cheaper and more flexible than buying another bundled solution.

Whatever you pick, build the migration around actual consumption numbers, decide where root cause lives before where data lives, and check the exit terms before you sign.

Related reading

Datadog Alternatives for Cost, Openness and AI SRE (2026)

New Relic Alternatives for SRE Teams: The Complete 2026 Guide

The Best Observability Tools for SRE Teams in 2026

Top 13 AI SRE Tools in 2026: The Complete Comparison

See an AI SRE work a real incident

Book 30 minutes with our team and watch an investigation run on your own stack.

Book a demo →

We use cookies

Only the strictly necessary ones are set when you arrive. Analytics and marketing cookies are set solely if you allow them, and you can change your mind at any time. See our Privacy Policy.