Dynatrace
by Dynatrace • • Application Performance Monitoring (APM) Tools
Dynatrace is an observability platform for APM, infrastructure monitoring and log analytics in enterprises, with usage-based pricing and unlimited seats.
Dynatrace watches the applications, hosts, containers and logs behind a digital service and works out which component caused a slowdown or a failure. Instead of separate tools for traces, metrics and logs, it collects them on one platform and ties each signal to the service and host it came from. Behind it is Dynatrace LLC, a Boston company dating from 2005 whose whole business is this platform. OneAgent installs on each host and instruments Java, .NET, Node.js and Python services automatically, while OpenTelemetry and Prometheus data arrive beside it. Smartscape maps how services, processes and hosts depend on one another as they change. PurePath distributed tracing follows each request across services down to the code and database calls it touched. OpenPipeline parses, filters and masks logs as they are ingested, Grail keeps them in buckets with their own retention, and Logs pattern analysis groups repeated lines. Real User Monitoring, Session Replay, Synthetic Monitoring, Code Monitoring and Application Security extend the same platform to user experience, live debugging and runtime vulnerabilities. Dynatrace is built for enterprises whose systems span on-premise data centres, Kubernetes clusters and AWS, Azure or Google Cloud. Platform engineering and site reliability teams use it to find the root cause of an incident without stitching traces, logs and metrics together by hand. Application owners follow response times and failure rates per service, and security teams check the same hosts for vulnerabilities at runtime. Every capability runs on the one platform, so a team adds log analytics or synthetic checks without deploying a second tool. When a service slows after a release, anomaly detection raises it, a dashboard annotation marks the deployment, and the trace shows which database call changed. Workflows then page the on-call engineer through PagerDuty or post the alert to a chat channel. From the failing span, the engineer opens the log lines written during that request. Logs shipped by Fluent Bit or Logstash land in the same store as those OneAgent collects. On Kubernetes, each log line carries its pod metadata, so an engineer narrows a search from the whole cluster to one workload.
Pricing
View plans-
Foundation & Discovery
$7 per month
Per host per month, metered at $0.01 a host-hour and drawn from an annual platform commitment
- Usage beyond the commitment billed monthly on demand at the same rates
- Basic host health, filesystem and OS services monitoring
- Host and process topology detection
- Logs collected and correlated in context
- 15-day trial of the whole platform
- Unlimited seats with no per-seat fee
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Infrastructure Monitoring
$29 per month
Per host per month, metered at $0.04 a host-hour against the annual commitment
- Everything in Foundation & Discovery
- Process, disk, memory and network analysis
- Custom metrics for extensibility
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Full-Stack Monitoring
$58 per month
Per 8 GiB host per month, metered at $0.01 per memory-GiB-hour against the annual commitment
- Price scales with host memory in GiB
- Everything in Infrastructure Monitoring
- APM with automated root cause analysis for end-to-end transactions
- OpenTelemetry metrics and traces
- 10 days of trace retention, extendable to 10 years
- Kubernetes Platform Monitoring included at no additional charge
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Container Observability
Custom pricing
- Kubernetes Platform Monitoring $1.40 a pod per month ($0.002 a pod-hour), included on Full-Stack hosts
- Code Monitoring $3.60 a container per month ($0.005 a container-hour)
- Kubernetes metrics, events, health views and topology
- Live code debugging with non-breaking breakpoints in Visual Studio Code and JetBrains
Features
- Included: Distributed tracing across services
- Included: Code-level transaction traces
- Included: Automatic service dependency map
- Included: Database query performance breakdown
- Included: Continuous code profiling in production
- Included: Deployment markers on performance charts
- Included: Apdex and latency percentile tracking
- Included: Error rate tracking per endpoint
- Included: Alert thresholds on latency and error rate
- Included: OpenTelemetry trace ingestion
- Included: Auto-instrumentation for major languages
- Included: Kubernetes and container-aware tracing
- Included: Serverless function tracing
- Included: Trace-to-log correlation
- Included: Trace sampling controls
- Not included: Free APM tier with usage caps
Additional Features
- OneAgent automatic instrumentation for Java, .NET, Node.js and Python
- PurePath distributed traces down to code level
- Smartscape real-time topology of services and hosts
- Automated root cause analysis for end-to-end transactions
- Dynatrace Intelligence anomaly detection with static thresholds
- Continuous thread analysis for production profiling
- Database call analysis per service
- Response time percentiles and failure analysis in the Services app
Best for
- Enterprises monitoring hybrid estates across data centres and several clouds
- Platform and site reliability teams running Kubernetes in production
- Operations teams that want a root cause named, not a stream of raw alerts
- Application owners tracking response times and failure rates per service
- Organizations standardizing on OpenTelemetry instrumentation
- Security teams that need runtime vulnerability detection on monitored hosts
- Companies that want every engineer on the platform without per-seat fees
- Teams consolidating APM, infrastructure and log tools onto one platform
Use cases
- Tracing a slow request across microservices to the code behind it
- Finding the database call that slowed a service after a release
- Monitoring Kubernetes clusters, nodes and workloads
- Watching host health across on-premise and cloud servers
- Searching and filtering logs during an incident
- Masking personal data in logs before they are stored
- Turning log records into metrics and alerts
- Paging the on-call engineer through PagerDuty
- Replaying a user session to reproduce a front-end error
- Checking API availability from synthetic locations
- Detecting vulnerable libraries in running applications
- Monitoring LLM token usage and agent traces
- Debugging live code with non-breaking breakpoints
Screenshots & Videos
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