Which fits a team replacing AppDynamics with Prometheus and Grafana
AppDynamics fits teams that want an integrated APM with business transactions, agent-based discovery and vendor support under one contract. Prometheus, Grafana and an OpenTelemetry trace backend fit teams that want composable, self-hosted parts they control and that have the staff to run them. The decision turns on whether you can staff the operation, because the open-source stack moves the work of integration, upkeep and upgrades onto your team. A renewal, a per-host or vCPU cost review, or a data residency rule can start the conversation, but none of them alone settles it.
Three questions decide most of the choice. First, do you need business transaction views, meaning per-transaction tracking tied to business flows such as checkout or payment, as a first-class feature? Prometheus and Grafana can show service and request metrics well, but business transaction models are not something they provide out of the box, so you would build them from traces and labels. Second, how many services and telemetry types need coverage? Metrics, traces and logs each need a backend, and the count of services sets the instrumentation and storage workload. Third, who owns the stack after go-live? Prometheus is single-node by design in its storage model, so high availability, long-term retention and alert delivery need explicit design.
Before you commit, confirm with AppDynamics which agents, business transaction features and add-ons your environment depends on, and list them against what OpenTelemetry instrumentation covers for each language in your estate. Check the OpenTelemetry status page for the maturity of the signals and languages you run. Then run a short proof of concept sending the same telemetry to both backends, and measure the staff hours it took. Those results tell you more than any general comparison about which side of the decision your team is on.
Which option fits which scenario
This table matches common reasons for leaving AppDynamics to the stack that fits each one. Read each row as a condition: if it describes your situation, the named option is the stronger starting point, and the condition explains why.
| Scenario | Better fit | Condition that drives the choice |
|---|---|---|
| Integrated APM with business transactions and agent-based discovery | AppDynamics or an integrated APM product, not the composable stack | Your teams rely on automatic code-level discovery and business transaction views out of the box. The Prometheus and Grafana stack needs OpenTelemetry instrumentation and custom work to match them. |
| Metrics-first infrastructure teams | Prometheus with Grafana | Your main need is host, container and service metrics with dashboards and alerting. Prometheus scrapes these over HTTP and PromQL covers most of the query work. |
| Traces as a primary need | Prometheus and Grafana plus an OpenTelemetry trace backend such as Jaeger | Distributed tracing is required across services. Prometheus does not store traces, so a separate trace backend is part of the design. |
| Strict data residency | Self-hosted Prometheus, Grafana and trace backend in your own environment | Telemetry must stay in named regions or on your own infrastructure. Confirm how each component handles data at rest and in transit before you commit. |
| Existing Prometheus and Grafana skills | Prometheus with Grafana | Your engineers already write PromQL, maintain exporters and build dashboards. The learning curve for these teams is lower than for a new APM model. |
| Low in-house operations capacity | Commercial SaaS or a managed service, or a fixed-scope implementation partner | Nobody on staff can run Prometheus storage, Grafana high availability and a trace backend. Self-hosting shifts that work to your team, so confirm operations capacity first. |
How the Prometheus, Grafana and trace backend stack fits together
OpenTelemetry is the instrumentation and collection layer, not a backend. In this stack, applications and the OpenTelemetry Collector generate and route telemetry, while separate tools store and show it. Prometheus stores metrics in its own local time series database, organized into two-hour blocks, with a default retention of 15 days that you can set by time or size. Local storage is not clustered or replicated, so treat the Prometheus server as a single-node database: plan disk sizing, backups of the data directory, and a restart procedure, and confirm your retention requirement before you size it. For anything longer, configure remote write to an external long-term store. Also note that Prometheus documents that it values reliability over precision, so it is not the right tool where every individual event must be counted exactly, such as per-request billing.
Grafana is the dashboard and alerting front end. It reads from Prometheus and the trace backend, and its provisioning files in YAML or JSON let you define data sources, dashboards and alerting resources as code. Alertmanager receives alerts from Prometheus and handles grouping, inhibition and silences. Prometheus should point at every Alertmanager instance rather than a load balancer, and Alertmanager's cluster flags provide high availability. Decide early which system owns each alert, because duplicate notifications are a common result of running alerting in two places. For traces, Jaeger is Apache-2.0 licensed and built on OpenTelemetry Collector components in its v2 line. Other OpenTelemetry trace backends can fill the same role, so confirm trace storage sizing, retention and query needs with the vendor or project before you commit.
Operationally, Grafana needs MySQL or PostgreSQL for configuration in production and high availability, since its docs state SQLite does not scale for production. Its high availability model uses two or more active-active servers behind a load balancer, and the docs note that alerting needs extra configuration to avoid duplicate notifications. Check whether the SAML and SCIM features your identity team needs are in the edition you choose, because the authentication docs limit them to Grafana Enterprise and Grafana Cloud. Map each team's access to Grafana roles and folders before migration, not after.
What self-hosting changes for data location, identity and compliance
Moving from AppDynamics to a self-hosted Prometheus, Grafana and OpenTelemetry stack changes where telemetry lives, who signs in, and what evidence you must produce. Each of these areas depends on choices you make during implementation, so they belong in the plan before the first agent is replaced.
Data location in your infrastructure
Prometheus keeps its time series on the disk of the host that runs it, and Grafana keeps its configuration in a database you choose. Traces and logs from the Collector go to whatever backend you deploy. Confirm with AppDynamics, in writing, where SaaS controllers and on-premises Controllers store data for your region, and whether any support access copies it elsewhere, so you can compare the two locations directly.
Hosting models for each component
Prometheus runs as a single-node database and is not clustered or replicated, so it needs its own backup and failover design. Grafana needs MySQL or PostgreSQL for production and high availability, with two or more active-active servers behind a load balancer. The OpenTelemetry Collector can run as an agent beside services or as a gateway. Decide which components sit in which network zone before you size them.
Identity options by edition
Grafana supports LDAP, generic OAuth, Entra ID, Okta, GitHub, GitLab and Google OAuth in all editions, along with auth proxy and JWT. SAML, team sync, active sync and SCIM provisioning are available only in Grafana Enterprise and Grafana Cloud. If your policy requires SAML or automated deprovisioning, plan for the Enterprise license or an upstream identity pattern, and confirm the terms before design starts.
Security hardening settings
Grafana's hardening guidance covers secure and SameSite cookies, a Content Security Policy, Trusted Types, hiding the version from unauthenticated users, requiring authentication on the metrics endpoint, and domain verification against DNS rebinding. Apply these as explicit configuration and record the values in your baseline. Also restrict the Prometheus web interface and the Alertmanager cluster traffic to the networks that need them.
Compliance readiness and evidence
DeployOpen prepares systems, configuration baselines, access records and evidence for your compliance assessment, including the monitoring controls your auditors will ask about. Auditors and certification bodies issue any attestation or report, not DeployOpen. Ask your assessor which evidence they accept from a self-hosted monitoring stack, and how they treat the AppDynamics vendor's own attestations while both run in parallel.
How the cost structure differs from AppDynamics licensing
AppDynamics is licensed on a per host or per vCPU basis, and add-ons such as end-user monitoring, synthetic monitoring or security capabilities sit on top of that base. The exact metering unit, edition and add-on list belong to your contract, so pull them from your order form before comparing anything. The open-source side has a different shape. Prometheus is Apache-2.0 licensed and has no paid enterprise edition, and Grafana Open Source is AGPL-3.0-only with no license fee for the open edition. The license line for core metrics and dashboards therefore drops to zero, and the spending moves to the components that someone must pay for, host and operate.
Most of the recurring cost sits in infrastructure, storage and people. Prometheus keeps its data in a local time series database that is not clustered or replicated and defaults to 15 days of retention, so longer retention or high availability means adding remote storage, which is a separate component with its own hosting and operating effort. In production, Grafana needs MySQL 8.0 or later or PostgreSQL 12 or later for its configuration database, and high availability means two or more active-active servers behind a load balancer, plus extra alerting configuration to avoid duplicate notifications. One-time costs include instrumenting services with OpenTelemetry, rebuilding health rules as alerts and dashboards, and deciding which historical views to keep. The main cost drivers are the volume of series and samples, retention, the number of services and the on-call hours your team must cover.
Grafana Cloud offers a reference point for what a hosted version of the same stack costs, though it is not a quote for your environment. Its pricing page lists a free tier, a Pro tier with a 19 US dollar monthly platform fee plus usage, and an Enterprise tier with a 25,000 US dollar per year minimum commitment. Use these figures to frame a question: what would a hosted option cost at your volumes, compared with running your own infrastructure and staff time? For your own scope, request a written quote that lists the services in scope, metric and log volumes, retention periods, high availability design, backup and upgrade work, support hours and training. Ask the provider to mark each item as one-time or recurring. DeployOpen publishes no price list, so its quote follows from the written scope.
Cost components on each side, one-time and recurring
Commercial APM bills for the product and its add-ons on a recurring basis, while a self-hosted stack moves cost into infrastructure, instrumentation and people. Comparing the two means splitting each into one-time work and recurring spend, then asking what drives each line up or down.
Licensing and subscription fees
On the AppDynamics side, the recurring fee follows the licensing model in your agreement, which is usually tied to hosts or vCPUs plus any add-ons you bought. On the open-source side, Prometheus, Grafana, OpenTelemetry and Jaeger carry no license fee, but some teams buy Grafana Enterprise or a support subscription. Ask your vendor which entitlements, metrics or capabilities drive the fee, and what changes at renewal.
Infrastructure and metrics storage
Prometheus runs on your servers or Kubernetes cluster and keeps data in a local time series database with a default retention of 15 days. Longer retention or high availability needs remote storage, which is a recurring cost for compute, disks and backups. Cost rises with active series count, scrape interval and retention, so label discipline matters more than the tool itself.
Implementation and instrumentation
Replacing AppDynamics agents with OpenTelemetry instrumentation is mostly one-time work: auditing agent coverage, adding SDKs or auto-instrumentation to each service, and deploying Collectors. Expect this to scale with the number of services and languages, and to run in parallel with the existing agents during cutover. Ask for a service inventory and a per-language plan before accepting any estimate.
Dashboard and alert rebuild
Health rules, baselines and business transaction views in AppDynamics do not map one to one to Grafana dashboards and Alertmanager rules. Rebuilding them is one-time work, but it also introduces a recurring cost of maintaining alert rules as code. The effort grows with the number of applications and alert policies, so inventory existing rules and count which ones still matter before you scope the rebuild.
Upgrades, patching and on-call staffing
On the AppDynamics side, Controller and agent upgrades are handled under the vendor's maintenance schedule, but your team still schedules and tests them. Self-hosted components need your own upgrade cadence: Prometheus minor releases ship every 6 weeks, while Grafana patch releases come at least monthly. Staffing for on-call, patching and capacity planning is the largest recurring line, and it is set by team size and how much you automate.
Support contracts and external help
Commercial support is included in the AppDynamics subscription, while open-source options rely on community channels, vendor support contracts or an implementation partner. Some teams buy a support subscription for a specific component, and others retain an implementation partner for upgrades and hardening. Ask each option for what response times, escalation paths and named responsibilities are included, and whether those terms renew annually or per incident.
What a move from AppDynamics involves at a high level
The sequence moves telemetry to OpenTelemetry first, so both backends can run side by side, and then retires AppDynamics agents only after Grafana and Prometheus cover the same questions.
Inventory agents, health rules and business transactions
List every application with an AppDynamics agent, the health rules and alerts attached to each, the dashboards people use, and the business transaction definitions that matter to the business. Assign an owner to each application and note which teams receive which alerts. The step is done when the inventory is reviewed by the application owners and every health rule has a named owner and a stated purpose.
Instrument services with OpenTelemetry
Add OpenTelemetry instrumentation to each service, using the language SDKs and auto-instrumentation where they fit. Trace SDKs are stable in most languages, but log SDK maturity varies, so confirm the status of each language your estate uses before relying on logs from it. The output is services emitting traces and metrics in OTLP to a Collector, with the instrumentation changes recorded per service.
Run dual export through the OpenTelemetry Collector
Deploy the OpenTelemetry Collector as an agent or gateway and configure its pipelines to send the same telemetry to the new Prometheus and trace backend and, during the transition, to AppDynamics. Prometheus can receive OTLP metrics when started with the OTLP receiver flag, and Jaeger v2 is built on Collector components. The step is done when both backends show matching request volumes and error counts for the same services over a comparison period you agree with the operations team.
Rebuild dashboards and alerts in Grafana as code
Recreate the dashboards and alerts in Grafana, defining data sources, dashboards and alerting resources in provisioning files kept in version control, so each change is reviewed and reproducible. Alerts from Prometheus rules go through Alertmanager, which should be configured with every instance it runs. The step is done when each retired health rule has a matching alert, a tested notification route and a dashboard that the owning team has accepted.
Replace business transaction views with a new approach
AppDynamics business transactions have no direct one-to-one equivalent in Prometheus and Grafana. Decide with the business owners which journeys need a view, then build it from trace attributes, service-level metrics or dashboards keyed to the instrumented operations. Some business reporting may need custom work or a different tool. The output is a short list of business views with a documented method for each, and any gaps that the business accepts.
Cut over service by service
Move alerting and on-call decisions one service at a time. For each service, confirm that the open-source views and alerts answer the same questions as before, then switch its operational reliance to the new stack while keeping the AppDynamics data available for reference. Prometheus stores data locally by default and is not clustered, so plan the storage and retention for each cut-over service. The step is done when the owning team signs off that the service is no longer monitored primarily through AppDynamics.
Retire AppDynamics agents and keep an audit trail
Remove AppDynamics agents from cut-over services and then decommission the Controller or SaaS tenant once no service depends on it. Keep exported history, dashboards and alert definitions in a retained location, and confirm with your records or compliance team what must be preserved. Confirm the contractual notice and data export terms with AppDynamics before ending the subscription. The step is done when no agent remains in production and the retention requirements are documented.
Questions buyers ask before switching from AppDynamics
What drives the total effort and cost of replacing AppDynamics with Prometheus and Grafana?
The effort is driven mainly by how many services, hosts and business transactions you need to replace, and by how much of your alerting and dashboarding depends on AppDynamics-specific health rules. Prometheus and Grafana carry no license fee, so the cost is made up of infrastructure for Prometheus storage and Grafana, the labor to instrument and migrate, the people who operate the stack, and any outside help you buy. Prometheus is licensed under Apache-2.0 and has no paid enterprise edition of the project itself, so your costs come from infrastructure, storage, implementation and operations. Ask any vendor or partner for a quote built from a written scope that lists these components separately, and compare it with your current AppDynamics renewal line by line.
How long does a migration from AppDynamics take?
No duration can be stated before the scope is known, so treat any single number as unreliable. The timeline depends on the number of applications, the languages they use, how many AppDynamics health rules and business transaction views you must rebuild, and how much your teams can change in parallel. A written plan should break the work into phases such as inventory, instrumentation, parallel running, alert rebuilding and cutover, with a duration for each phase tied to the agreed scope. Ask for that plan in writing before you commit a date to your executives.
What does the internal team need to run Prometheus and Grafana?
The team needs skills in Linux operations, Kubernetes or container hosting if you use it, PromQL for querying metrics, Grafana provisioning, and OpenTelemetry Collector configuration. Prometheus stores data in a local time series database that is not clustered or replicated, so someone must own its storage sizing, retention and backups. Grafana requires MySQL 8.0 or later or PostgreSQL 12 or later for production, so a database operator is also needed. Assign named owners for each component, define an on-call rota for the alert path, and confirm these responsibilities before cutover.
Can our own engineers complete the migration without outside help?
Many teams can, provided they have engineers with the skills listed above and enough time to take on the work alongside their normal duties. Outside help is most useful for the parts that are unfamiliar, such as designing the Collector pipeline, rebuilding business transaction views, hardening Grafana and running a parallel period. Whether you need a partner depends on your team's capacity and experience, which you should assess honestly. DeployOpen plans, implements, customizes, hardens, documents and supports self-hosted open-source platforms inside your own infrastructure, typically under a fixed scope agreed in writing before work starts, and ongoing support is available as a retainer.
How do AppDynamics business transactions map to Prometheus and Grafana?
They do not map one to one. AppDynamics discovers business transactions automatically from its agents, while Prometheus and Grafana work from the metrics, traces and labels that you define. Your team must decide which request paths represent a business transaction, then emit consistent span attributes or metric labels for them with OpenTelemetry. Grafana dashboards and alert rules can then show the same business views, but they need to be built and reviewed. Keep label cardinality under control, because Prometheus reliability and query performance suffer from unbounded label values. Map each AppDynamics business transaction to a named owner and an acceptance check before cutover.
How do we make Grafana and Prometheus highly available?
Grafana supports high availability with two or more active-active servers behind a load balancer, all sharing a MySQL or PostgreSQL database, and database-backed auth tokens let users reach any node. The Grafana documentation notes that alerting needs extra configuration to avoid duplicate notifications and that Grafana Live has limitations in high availability. Prometheus is different: the storage docs say local storage is not clustered or replicated, so high availability for metrics usually means running redundant Prometheus instances, or adding remote write to external long-term storage, and pointing Alertmanager at every instance. Confirm the exact design, failover behavior and recovery steps with your engineers before go-live.
How do we keep AppDynamics running during a parallel export?
Keep the AppDynamics agents in place and add OpenTelemetry instrumentation or a Collector that sends the same telemetry to the new backend. Because AppDynamics and the OpenTelemetry backend are separate systems, the existing agents continue to report while you validate the new dashboards and alerts. Route alerts from one system at a time to avoid duplicate paging, and define which system is authoritative for each service before you switch. Each commercial vendor documents OTLP ingestion, which makes this pattern practical, but confirm the AppDynamics licensing and agent overhead during the overlap with your account team. Use the Collector authenticator extensions to secure the export path, and document the cutover criteria for each service.
How DeployOpen works on this
DeployOpen plans, implements and hands over self-hosted open-source monitoring inside your own infrastructure, including Prometheus, Grafana and an OpenTelemetry trace backend. We start from your AppDynamics coverage, not from a generic stack, so the written scope states which health rules, dashboards and transaction views map across and which need new design.
How we scope
- Inventory AppDynamics applications, tiers, health rules, dashboards and alerting that must keep working after cutover.
- Agree which business transaction views need a new approach, and which are retired, before any build work starts.
- Engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work begins.
How we build
- Instrument services with OpenTelemetry and route telemetry through the Collector to Prometheus, Grafana and a trace backend in parallel.
- Deploy Grafana on MySQL or PostgreSQL with high availability, configure authentication and provision data sources and dashboards as code.
- Test alert routing through Alertmanager and harden Grafana and Collector configuration against the vendor security guidance.
How we hand over
- Document the architecture, retention settings, storage sizing assumptions and the operating runbook for your own team.
- Deliver the provisioning files, Collector configuration and alert rules in your repositories, so changes are reviewed like code.
- Run a handover session that walks your operators through upgrades, backups and the parallel-run exit checklist.
How we support
- Ongoing support, upgrades and continuous testing are available as retainers after the initial handover is complete.
- Track Prometheus, Grafana and Collector release cycles so patch and minor upgrades are planned against published support windows.
- Confirm with your team which costs and staffing your organization will carry, and agree those responsibilities in writing.
