Open-source alternatives to Dynatrace

Which open-source options replace Dynatrace, and why teams look for them

The short answer is OpenTelemetry for instrumentation, Prometheus and Grafana for metrics and alerting, and Jaeger or SigNoz for traces. Teams that replace Dynatrace usually keep the telemetry path and change only the backend, so the work starts with the agent layer rather than the dashboards. If your renewal is approaching, the decision is less about finding one product that does everything and more about which pieces you can own, operate and pay for on your own terms. That shift matters most when a contract is up for renewal, when a Managed deployment has to be kept in your own environment, or when data residency rules limit where telemetry may be processed. The pressure usually comes from the commercial terms. Dynatrace Platform Subscription (DPS) is consumption-based: customers sign an agreement of typically 1 to 3 years with a minimum annual commitment, and usage accrues against it on a per-capability rate card. Finance and platform teams often find that the commitment term, rather than the technology, sets the timetable. Before the next renewal, confirm with your Dynatrace account team the term length, the minimum commitment, which capabilities are on the rate card, and whether the same DPS can be shared across SaaS and Managed deployments. Dynatrace is offered as SaaS and as Dynatrace Managed, so an organization with a Managed footprint should also confirm which deployment model its current contract covers and what a move would involve. For the replacement itself, the practical first step is to check how much of your telemetry already arrives through OpenTelemetry. Dynatrace ingests OpenTelemetry traces, metrics and logs through its OTLP API, which means applications instrumented with the OpenTelemetry SDKs can be pointed at a self-hosted OpenTelemetry Collector during a parallel run. Teams that inventory their agent footprint, including any OneAgent-managed hosts and processes, can then decide where automatic discovery must be replaced by explicit instrumentation and where the existing gap is acceptable.

Which open-source option fits which part of Dynatrace

Dynatrace bundles collection, storage, analysis and AI-assisted diagnosis into one product, so a self-hosted replacement is a set of separate components. The cards below match each part of that stack to an open-source option and name the trade-off you accept by choosing it.

OpenTelemetry as the instrumentation layer

OpenTelemetry is an instrumentation standard and collection framework, not a backend, so it does not store or display anything on its own. It replaces the role OneAgent plays on the data-collection side only when you deploy SDKs, auto-instrumentation agents and a Collector in your environment. Because Dynatrace already ingests OpenTelemetry through its OTLP API, you can point the same telemetry at a self-hosted backend during a parallel run. The trade-off is that automatic discovery depth varies by language and framework, so confirm coverage for your runtimes before you retire any agent.

Prometheus for metrics and PromQL

Prometheus is an Apache-2.0 CNCF monitoring system that scrapes metrics over HTTP and queries them with PromQL. It can also receive OTLP metrics when started with the --web.enable-otlp-receiver flag, which lets OpenTelemetry Collectors write into it without a separate scrape configuration. The main trade-off is that Prometheus stores data on local disk and is designed for shorter retention, so you need a plan for long-term storage and for high-cardinality series. Your Dynatrace metric dashboards will need to be rebuilt as PromQL queries.

Grafana for dashboards and alerting

Grafana provides dashboards and alerting over Prometheus and other data sources, and it covers the visualization role that Dynatrace's built-in views fill. Grafana moved from Apache-2.0 to AGPL-3.0-only on April 20, 2021, with Grafana 8.0 as the first release under that license. Have counsel confirm that AGPL-3.0 terms are acceptable if you modify and offer Grafana to users over a network. Expect to rebuild service maps and alert rules by hand, since Dynatrace's topology views have no direct export equivalent.

Mimir for long-term metrics storage

Grafana Mimir is horizontally scalable long-term storage for Prometheus metrics, and it is licensed AGPL-3.0-only like Grafana. It addresses the retention and scale limits of a single Prometheus server, which is the usual gap when replacing a managed platform's metric history. Running Mimir means operating a distributed system with object storage, compactors and ingesters, so the cost is mostly staff time and infrastructure. Ask whether your team has capacity to run and upgrade that cluster before you commit to it.

Jaeger for distributed tracing

Jaeger is an Apache-2.0 distributed tracing backend and a graduated CNCF project, graduated in October 2019. Jaeger v2 is built on OpenTelemetry Collector components, so the ingest path from your OpenTelemetry pipeline stays consistent with the rest of the stack. Jaeger covers traces only, so metrics and logs need Prometheus and a log store alongside it. Confirm how much trace storage your sampling strategy requires, because trace volume drives storage cost more than service count does.

SigNoz as an all-in-one option

SigNoz is an OpenTelemetry-native platform that covers traces, metrics and logs in one product, which can reduce the number of components your team must run. It is open core: code outside the ee/ and cmd/enterprise/ directories is MIT, and code inside them falls under a separate enterprise license. Before adopting it, check which features you need sit inside the open part and which sit in the enterprise directories. The trade-off is a single system that you must operate and scale, with fewer independent projects to swap out if it stops fitting your needs.

How each Dynatrace capability maps to self-hosted tools

This table maps the main Dynatrace capabilities to self-hosted open-source components and marks each as full, partial or to confirm. Read the coverage column first, then the notes on what your team must build or configure. The main takeaway is that OpenTelemetry instrumentation already sent to Dynatrace's OTLP API can usually be reused, while automatic discovery and AI-assisted root-cause analysis need more planning.

Capability	Self-hosted option	Coverage and what to plan
Distributed tracing	Jaeger v2 or SigNoz, fed by OpenTelemetry Collector	Full for trace collection and search. Confirm sampling strategy and storage sizing with the chosen backend before cutover.
Metrics collection	OpenTelemetry Collector with Prometheus, or Prometheus scraping directly	Full. Prometheus can receive OTLP metrics when started with the OTLP receiver flag, so existing exporters can keep working.
Metrics long-term storage	Grafana Mimir or Prometheus remote storage	Partial. Requires capacity planning and operational ownership that Dynatrace's managed storage otherwise handles.
Logs	Loki, OpenSearch or SigNoz logs, fed by OpenTelemetry	Partial. Confirm log volume, retention and query needs, since log pipelines differ most between options.
Service maps	SigNoz service map, Jaeger dependency view or Grafana Tempo service graphs	Partial. Service topology is derived from traces, so map quality depends on consistent span instrumentation.
Alerting	Prometheus Alertmanager and Grafana alerting	Full for threshold and rule-based alerts. Confirm notification routing and on-call integrations with your incident tool.
Dashboards	Grafana	Full for metrics and traces. Dashboards must be rebuilt, not imported, and Grafana is AGPL-3.0-only, which matters if you modify and distribute it.
Automatic discovery (OneAgent-style)	OpenTelemetry auto-instrumentation agents and Collector host metrics	Partial. Language auto-instrumentation covers common frameworks, but process discovery and dependency detection are less automatic. Test coverage per runtime.
AI-assisted root-cause analysis	No direct equivalent in the core stack	Gap. Expect manual correlation across traces, metrics and logs, or a separate tool. Confirm any AI features in candidate products.
Managed deployment in your environment	Self-hosted stack in your own cloud account or data center	Full in principle. You own installation, upgrades, backups, high availability and security hardening.
OTLP ingestion	OpenTelemetry Collector receiving OTLP over gRPC and HTTP	Full. Dynatrace documents OTLP ingestion of traces, metrics and logs, so existing OpenTelemetry instrumentation carries over with endpoint and token changes.

What replaces OneAgent-style automatic discovery

OneAgent-style automatic discovery has no single open-source drop-in. Dynatrace bundles host monitoring, process detection, code-level instrumentation and dependency mapping into one agent that the platform updates for you. Open source splits those jobs across several components, and each one needs an owner. The practical replacement is OpenTelemetry instrumentation for application traces and metrics, plus Prometheus service discovery or Zabbix for host and process inventory. Expect the coverage to be narrower and the setup to be more manual, particularly for older runtimes and third-party middleware.

Start with an inventory of runtimes, not with tools. List every language, framework and version in production (for example, Java, .NET, Node.js, Python, Go, or a legacy runtime), along with how each one is deployed. Then check the OpenTelemetry documentation for each runtime to see whether it offers automatic instrumentation, library instrumentation only, or manual instrumentation. Coverage differs by language and by library version, so confirm it against the exact framework versions you run. The Datadog Agent's user space code is Apache-2.0, so teams can read how a commercial agent collects host data, but it is a reference for design only and does not replace a Datadog subscription or a supported open-source collector.

For hosts and processes, Prometheus service discovery can find targets from cloud APIs, Kubernetes, DNS or static files, and exporters such as node_exporter collect host metrics. Zabbix covers host discovery and low-level checks, with its own agent and templates, and its license changed to AGPL-3.0 from version 7.0, so confirm that terms fit your distribution plans. Whatever you choose, plan for the manual work that remains: business transaction naming, custom spans around critical code paths, service dependency maps you must draw yourself, and sign-off from application owners who must maintain instrumentation as code changes.

What you give up, and the usual workarounds

Moving off Dynatrace is less about finding one replacement and more about rebuilding several things the platform bundles together. The cards below cover the capabilities teams most often miss after cutover, what they cost to rebuild, and what to confirm with each open-source project before committing.

Built-in AI root-cause analysis

Dynatrace correlates problems across topology, traces and logs with its own AI engine. None of the open-source components in this set provides an equivalent out of the box, so root-cause analysis becomes a team process. Replace it with written runbooks per service, anomaly-based alerts in Prometheus or Grafana, and correlation dashboards that link a metric spike to the trace and log views. Ask any vendor that claims automated root-cause analysis to show it working on your own telemetry before you rely on it.

Automatic topology mapping

OneAgent discovers processes, hosts and service dependencies without configuration. OpenTelemetry instrumentation only maps what each application emits, so service maps show gaps wherever a service is not instrumented. Plan an inventory of services and dependencies before cutover, add OpenTelemetry auto-instrumentation to each runtime, and check that trace context propagates across queues and third-party calls. Tracing backends such as Jaeger and SigNoz draw dependency graphs from the spans they receive, so their maps are only as complete as your instrumentation.

Out-of-the-box dashboards

Dynatrace ships host, service and Kubernetes views that appear as soon as an agent reports. Self-hosted Grafana starts empty, so every dashboard must be built or imported. Community dashboards for node, Kubernetes and common databases cover much of the infrastructure layer, but service-level views need to be written against your own metric names and labels. Budget time for dashboard ownership, version control of dashboard JSON, and review after each release of an exporter or collector, since metric names can change between versions.

Vendor support and response commitments

Dynatrace sells support under its commercial agreement, with response terms set in the contract. Most open-source projects in this set are community-supported, so no vendor is contractually accountable for a production incident unless you buy it. Zabbix sells technical support subscriptions, and some observability projects offer commercial support through their own companies. Ask each candidate for its support tiers, response commitments, and whether support covers the exact version you run. Compare those terms with the internal on-call model you already have.

Single-pane user experience

Dynatrace brings metrics, traces, logs, user sessions and alerts into one interface. A self-hosted stack usually splits these across Prometheus, Grafana, Jaeger or SigNoz, and a log store, so engineers switch tools during an incident. Reduce the friction by linking panels to traces through exemplars and trace identifiers, standardizing labels across all three signals, and building one entry dashboard per service. Test the workflow with the on-call team using a real incident drill before you retire the old tool.

What a self-hosted replacement costs over several years

This table sets the Dynatrace subscription side against the components you would pay for in a self-hosted stack, marking each line as one-time or recurring. Use it to decide which lines to request in quotes and which usage figures to model before you commit to a renewal or a self-hosted build.

Cost component	Who is paid or who carries it	One-time or recurring	What drives it
Dynatrace DPS commitment	Dynatrace, under a contract typically 1 to 3 years with a minimum annual commitment	Recurring for the term	Committed capacity, per-capability rate card, and whether SaaS and Managed usage share one DPS agreement
Dynatrace overage and renewal terms	Dynatrace, if usage exceeds the commitment or the term renews	Recurring	Telemetry growth, new capabilities enabled, and renewal pricing terms you negotiate in advance
Infrastructure for metrics and traces	Your cloud provider or data center team	Recurring	Active series count, trace volume, retention periods and storage tier for Prometheus, Mimir, and Jaeger or SigNoz
Grafana and alerting capacity	Your cloud provider or data center team	Recurring	Number of dashboards, query load, high availability design and whether you run Grafana Enterprise support
OpenTelemetry instrumentation work	Your engineers or DeployOpen under a fixed-scope engagement	One-time, with ongoing upkeep	Number of services, languages, auto-instrumentation coverage gaps and dual-shipping period length
Staff time to operate the stack	Your platform or SRE team	Recurring	Team skills in PromQL and OpenTelemetry Collector, on-call load, upgrade cadence and cardinality control
Migration of dashboards, alerts and runbooks	Your engineers or an implementation partner	One-time	Count of Dynatrace dashboards and alerting rules, plus the number of teams that rely on them
Support and upgrade contracts	Vendors or partners you select, such as a support subscription or a retainer	Recurring, optional	Whether you need vendor support SLAs, the agreed scope of upgrades and who runs security testing

How a Dynatrace to open-source migration runs

The sequence moves telemetry from OneAgent-based collection to OpenTelemetry and a self-hosted backend in stages, so each capability is proven before Dynatrace is switched off. Each step ends with a check that tells you whether the next one can start.

Inventory agents, services, dashboards and alerts
Start by listing every host and process where OneAgent runs, every monitored service, and every dashboard, alert, synthetic check and log query your teams rely on. Platform engineering leads this work with service owners, who confirm which alerts page someone and which are informational. The output is a single register that maps each Dynatrace feature to its owner and to the business process it supports. The step is done when service owners have signed off the list and no critical alert is left unassigned.
Roll out OpenTelemetry instrumentation
Application teams add OpenTelemetry SDKs or language-specific auto-instrumentation to the services in the register, and platform engineers deploy an OpenTelemetry Collector close to the workloads. Automatic discovery is not one-to-one with OneAgent, so teams should expect some manual spans and attributes for custom code paths and for runtime or host metrics that OneAgent collected by default. The step is done when each service emits traces, metrics and logs with consistent resource attributes and the Collector reports healthy exporters.
Map DPS-measured capabilities to backends
Dynatrace Platform Subscription bills by capability on a per-capability rate card, so the team should list which capabilities it actually consumes, such as infrastructure monitoring, application traces, log storage and synthetic checks. For each one, choose a self-hosted backend, for example Jaeger or SigNoz for traces and Prometheus with Grafana for metrics and alerting. Note where no open-source equivalent covers a capability, including Dynatrace's built-in AI root-cause analysis, and assign that gap to an owner. The output is a capability-to-backend table reviewed by architects and by the team that owns the Dynatrace contract.
Pilot the stack on one service
Choose one service with moderate traffic and a known failure history, and route its telemetry through the Collector to the self-hosted backend. Confirm that traces show the full request path, that PromQL queries return the metrics the on-call team needs, and that alert rules fire on a controlled test. Operations staff should work through a real incident or a scheduled fault injection during the pilot. The step is done when the pilot team agrees the self-hosted view is adequate for that service, and the list of gaps is recorded.
Run a parallel period with dual export
Configure the same OpenTelemetry pipeline to export OTLP to the Dynatrace endpoint and to the self-hosted stack at the same time. Dynatrace documents OTLP ingestion, and New Relic and Datadog document it too, which is why one instrumented codebase can feed both destinations during a migration. Compare trace coverage, metric values and alert timing between the two systems for each service in scope. The step is done when discrepancies have been explained or fixed and the on-call team has used the self-hosted view during real alerts.
Rebuild dashboards and alerts in Grafana
Recreate the dashboards and alert rules from the inventory in Grafana, using Prometheus data sources for metrics and the trace backend for traces. Remove duplicates and retire alerts that no owner can justify, because a migration is a good point to cut noise. Route alerts through the existing on-call tool and test every paging path. The output is a dashboard set and alert catalog that service owners have reviewed. The step is done when each critical alert from the register has a tested equivalent or a documented reason for removal.
Cut over and retire the Dynatrace agents
Before cutover, read the notice and termination terms in the Dynatrace agreement, including the minimum annual commitment and any notice period, and confirm them with procurement and legal. Then switch alerting and on-call to the self-hosted stack, stop OneAgent deployments, and remove the agent from hosts and images. Keep Dynatrace read-only for historical lookups until the retention you need is exported or no longer required. The step is done when OneAgent is removed from all in-scope hosts and the commercial consumption has been formally wound down under the agreement terms.
Decommission and document the platform
Once the agreement has ended or the commitment is settled, close Dynatrace tenant access, rotate any tokens that were issued for ingestion, and archive configuration exports. Document the Collector configuration, backend versions, retention policies, runbooks and ownership in the platform team's repository. Schedule upgrades for the self-hosted components, since no vendor now patches them for you. The output is a runbook set and a decommission record. The step is done when access has been revoked, tokens rotated, and the documentation has been reviewed by the on-call and security teams.

Which option fits your situation

Teams that run Dynatrace Managed because data must stay in their own environment usually want the same control with a self-hosted stack. Prometheus, Grafana and Jaeger cover metrics, dashboards, alerting and traces without sending telemetry to a third party. The trade-off is that you assemble and operate several components yourself, and the automatic discovery that OneAgent provides has to be replaced by explicit instrumentation.

Operational ownership: Your platform team runs Prometheus, Grafana and Jaeger, including upgrades, storage sizing, retention and backups.
Discovery gap: Expect to instrument services with OpenTelemetry SDKs or auto-instrumentation agents and maintain that configuration across releases.
Grafana licensing: Grafana moved to AGPL-3.0-only in Grafana 8.0. If you modify Grafana and make it available to users over a network, the AGPL source obligations apply, so have counsel review your deployment.
Mimir licensing: If you add Grafana Mimir for long-term metrics storage, it is also AGPL-3.0-only and the same review applies.
Access controls: Confirm that your audit and access requirements map to Grafana and Jaeger features in your target versions.

Confirm your licensing position and operating model with your legal and platform teams before choosing components.

How much effort and cost does moving off Dynatrace take?

How long does a migration off Dynatrace usually take?

No duration can be stated from the researched facts, so treat any timeline as something to confirm against your own estate. The main drivers are the number of services and hosts, how many languages and runtimes are instrumented, how many custom dashboards, alerts and maintenance windows must be rebuilt, and whether OneAgent-style automatic discovery is replaced service by service or all at once. A parallel run, where the same OpenTelemetry telemetry goes to Dynatrace and a self-hosted backend, adds time but lowers cutover risk. Ask any provider for a written inventory-based schedule before committing.

Can our own team migrate off Dynatrace without outside help?

A small estate with engineers who already know OpenTelemetry can often do much of the work in-house, since OTLP is documented by Dynatrace and by the self-hosted options alike. The effort rises quickly with many languages, legacy agents, custom Dynatrace extensions, and dashboards that depend on Davis-driven problem detection. The practical test is whether you have people who can instrument each runtime, run a Collector pipeline, operate Prometheus or Jaeger storage, and own alert tuning after cutover. If any of those are missing, a fixed-scope engagement covering planning, implementation and handover is one option to compare.

What inventory and ownership do we need before starting?

Before any instrumentation work, build a list of every monitored host, process group, service, database and synthetic check, and record which Dynatrace features each one uses. Assign an owner for each instrumentation change, usually the team that deploys the service, and name one owner for the shared Collector and storage platform. Alerting ownership matters most: decide who is paged, which thresholds move from Dynatrace problems to Prometheus rules, and who signs off before Dynatrace alerts are disabled. Without these owners, dual-running tends to stall.

What drives the cost of moving off Dynatrace up or down?

Cost has two sides: what you stop paying Dynatrace and what you pay to run the replacement. Dynatrace Platform Subscription is consumption-based, with an agreement typically of 1 to 3 years and a minimum annual commitment, so the remaining term and unused commitment shape the savings timing. On the replacement side, the costs are engineering time for instrumentation and dashboards, compute and storage for Prometheus, Jaeger or SigNoz, backup, upgrades, and on-call effort. Storage retention and cardinality are the biggest levers on the self-hosted side. Ask any quote to separate one-time migration work from recurring operations and support.

Does a commitment term in DPS affect when we can exit?

Yes. Dynatrace documents Dynatrace Platform Subscription as an agreement of typically 1 to 3 years with a minimum annual commitment, and usage accrues against it on a per-capability rate card. Check your contract for the exact term, the notice period, whether unused commitment carries over, and whether SaaS and Managed deployments share the same subscription. Plan the cutover so the replacement is proven before the commitment ends, and confirm these terms with Dynatrace or your procurement team rather than relying on general descriptions.

Will we lose Dynatrace's AI root-cause analysis?

Most self-hosted stacks do not offer an equivalent of Dynatrace's built-in AI root-cause analysis out of the box, so this is a genuine gap to plan for. Prometheus, Grafana and Jaeger give you the raw signals, traces and alert rules, but correlating them into a probable cause is largely manual or depends on custom queries and runbooks. Some teams add anomaly detection or AI tooling on top, which is a separate project with its own cost and validation. Confirm with each vendor what its platform offers, and test the replacement against your last several real incidents before you rely on it.

What should a migration plan include to reduce risk?

A sound plan includes an inventory, a pilot on a small set of services, OpenTelemetry instrumentation with a Collector that exports to both Dynatrace and the self-hosted backend, side-by-side dashboards and alerts, and a documented rollback path. Hardening the self-hosted stack, including access control, backup and retention, should be part of the same plan. Cut over one service group at a time, and retire Dynatrace alerts only after on-call has validated the new ones. DeployOpen plans, implements, hardens, backs up and documents self-hosted platforms in your own infrastructure under a written scope.

How DeployOpen scopes, migrates and supports the replacement

DeployOpen plans, implements, integrates, hardens, documents and supports self-hosted open-source platforms inside your own infrastructure, including the Dynatrace replacement stack. Engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work starts.

How we scope

Inventory which Dynatrace capabilities your teams actually use, such as OneAgent discovery, service flow, logs and Davis-based alerting.
Map each capability to a named open-source component and record the gaps, including AI root-cause analysis.
Agree a written scope covering deliverables, environments, cutover dates and what stays out of scope.

How we build

Deploy OpenTelemetry Collector pipelines that send the same OTLP telemetry to Dynatrace and the self-hosted backend in parallel.
Stand up Prometheus, Grafana, Jaeger or SigNoz in your cloud account, data center or air-gapped network, with access controls and backups.
Rebuild dashboards, alert rules and service ownership, then test alert routing and data retention against your requirements.

How we hand over

Provide architecture diagrams, configuration repositories, runbooks and an instrumentation guide for each application team.
Run knowledge transfer sessions so your engineers can operate, tune and extend the platform after cutover.
Document the evidence your compliance team needs for change control, retention and access reviews, without issuing audit opinions.

How we support

Offer ongoing support, upgrades and continuous security testing as a retainer after handover.
Plan version upgrades of the collector, storage and dashboard components on a schedule agreed with your team.
Confirm with us during scoping which support hours, escalation paths and response commitments apply to your retainer.