StackOps Elastic vs Dynatrace

This guide compares StackOps Elastic and StackOps Dynatrace to help teams choose the right platform based on their operating model, data strategy, and desired outcomes.

StackOps Elastic offers a highly customisable, open-source-based observability solution with excellent log aggregation capabilities for teams that prioritise control, extensibility, and in-depth analytics. It is data-agnostic and supports ingesting logs, metrics, traces, and other data (e.g., business and security events) into a unified platform for search, correlation, and investigation. It also supports AI-assisted troubleshooting through its AI Assistant capabilities. The trade-off is more platform engineering effort for configuration and lifecycle management.

Choose StackOps Elastic if:

You have strong in-house DevOps or SRE expertise to tune and operate your data and observability stack, and want complete control for customisation and flexibility.
You need to ingest and analyze a wide variety of data types beyond your application logs and metrics for observability purposes. For example, business data for insights, or security events for proactive incident detection.
You want to minimise vendor lock-in so that your data can be exported or migrated to other platforms, or want to leverage the open-source community for support.
You need a multi-tenant yet centralised setup, where product teams want autonomy but central teams need oversight.

StackOps Elastic is best for teams that want deep customisation, data flexibility, and strong control over architecture and long-term extensibility.

StackOps Dynatrace

StackOps Dynatrace offers an AI-driven observability solution for teams that prioritise rapid onboarding and operational simplicity. It is especially suited for Application Performance Monitoring, User Experience Monitoring, and in-depth problem analysis. With its OneAgent, it automatically discovers workloads, applications, and infrastructure, to provide dependencies and service mappings across services and components. The trade-off is a more opinionated operating model with less low-level control.

Choose StackOps Dynatrace if:

You want a solution with minimal configuration using agents or polling.
Your primary focus is on Application Performance Monitoring (APM) with in-depth correlation to infrastructure metrics.
You need a simple setup, where metrics are ingested through a GovTech-managed platform, so that maintenance is transparent to tenants (similar to government-managed data centre services).

StackOps Dynatrace is best for teams that want fast time-to-value and automatic discovery with minimal setup effort.

Detailed comparison

Platform model and operations

Area	StackOps Elastic	StackOps Dynatrace
Service model	SaaS subscription. Each subscription provides access to one or more deployments. Each deployment provides a dedicated, segregated Elastic Cloud Hosted cluster. Each deployment natively supports multi-tenancy patterns such as spaces and index isolation, with data sharing across subscriptions or deployments through Cross-Cluster Search and Cross-Cluster Replication.	SaaS subscription. Each subscription generally provides a data-segregated space within a multi-tenanted account. More plug-and-play, with no tenant-managed infrastructure to operate.
Setup and maintenance	More manual setup for agent configuration, component upgrades, performance tuning, index lifecycle policies, and capacity planning. Can be automated using StackOps CLI tool, StackOps Resiliency Accelerator (SORA).	Faster setup with OneAgent auto-discovery and instrumentation, and with more out-of-the-box extensions/workflows.
Control and transparency	High control over architecture and data, including parsing, indexing, pipelines, and ML job configuration.	Limited control over internal baseline and sampling behaviour.
Data residency	AWS, Azure, and Google Cloud in Singapore.	AWS and Azure in Singapore.
Cost model	Based on deployment sizes (compute, storage, nodes) and usage consumption (data transfer, monitoring, LLM tokens). Costs may vary month to month. Enables flexible architecture that optimises for both cost and performance needs.	Based on usage consumption of capabilities in use (e.g., AI, monitoring, topology mapping). More predictable costs, but may vary month to month depending on the usage.

Data, instrumentation, and ecosystem

Area	StackOps Elastic	StackOps Dynatrace
Supported data type	Data-agnostic platform for any data: Logs, metrics, APM traces, infrastructure events - Security (including SIEM events, endpoint security, and network telemetry) - Business data	Data-agnostic platform, primarily focused on observability: - Logs, metrics, APM traces, metadata, user behaviour, events
Ingestion model	Modular, multi-tool ecosystem with extensibility for open-source tools, offering maximum control over pipeline, transformation, and collection layers.	Unified, single-agent core focused on automated discovery, zero-code instrumentation, and low setup friction.
Primary native agent	Elastic Agent: handles data collection via configurable integrations and policy definitions.	OneAgent: single binary that automatically injects into runtimes, discovers application topologies, and traces calls without any code change required.
Open standards and extensibility	Strong open-source and custom integration posture; good fit for bespoke pipelines and heterogeneous sources.	Strong extension ecosystem with out-of-the-box integrations and curated platform patterns, including support for standards and tools such as Micrometer, StatsD, Fluentd, Fluent Bit, and Logstash.
OpenTelemetry strategy	EDOT (Elastic Distribution for OTel): Native OTel language SDKs and Collector distributions tailored for Elastic storage.	OTel Ingestion Endpoint: Accepts standard OpenTelemetry traces/metrics alongside native telemetry.
Cloud resources monitoring (AWS, Azure, Google)	Out-of-the-box integration available: - AWS - Azure - Google Cloud	Out-of-the-box integration available - AWS - Azure - Google Cloud
On-premise workload	Supported: Ingests OS, application, and database logs and metrics via Elastic Agent integration modules. Requires configuration: Telemetry from network appliances (firewalls, routers, switches) requires SNMP or Syslog receiver setup via Elastic Agent or Logstash.	Supported: Ingests OS, application, and database logs and metrics via Dynatrace OneAgent auto-discovery. Requires configuration: Telemetry from network appliances (firewalls, routers, switches) requires SNMP extension setup or Syslog endpoint configuration via Dynatrace ActiveGate.
Automated discovery and dependency mapping	Cloud resource discovery (AWS, Azure) can be automated with StackOps Resiliency Accelerator (SORA). Distributed tracing service maps are automated via Elastic APM or OpenTelemetry OpenTelemetry Universal Profiling provides granular performance visibility and cost mapping without code instrumentation.	Dynatrace automatically discovers all services, processes, hosts, and containers Dynatrace maps complete application and infrastructure topology with dependencies out of the box.

Features

Area	StackOps Elastic	StackOps Dynatrace
APM and tracing	Code-level tracing and performance monitoring via Elastic APM agents or OpenTelemetry. APM agents often require manual instrumentation, enabling flexible deployment for security and compliance control. Supports synthetic monitoring and real user monitoring	Highly automated code-level distributed tracing with deep service context and dependency mapping. Supports synthetic monitoring and real user monitoring
Log analytics	Excellent for high-volume, exploratory, unstructured, ad-hoc log forensics and broader use cases (including security/compliance).	Optimised for correlated AI-driven log analysis and operational RCA workflows.
AI and automation	Machine Learning capabilities for intelligent alerting and forecasting. Conversational AI Assistant capabilities for context-aware insights, with support for third-party LLMs and knowledge-base grounding to meet strict data sovereignty requirements.	Davis AI continuously baselines performance, detects anomalies, and suggests remediation. Automated topology mapping and dependency analysis without manual intervention.
Root-cause analysis	AI-assisted correlation across logs, metrics, and traces via Anomaly Explorer.	AI-driven root cause with strong topology/context automation via Davis AI.
Workflow integration	Broad integration ecosystem for ticketing, automation, and enterprise data sources, including connectors that can enrich AI-assisted workflows.	Built-in workflow and action framework with connectors for automation and operational actions.
Other capabilities	Strong search use cases and an adjacent security ecosystem, including SIEM-oriented workflows.	Additional platform capabilities such as application security, workflow automation, and AppEngine-based extensibility.

⋙ Dynatrace

StackOps Resiliency Accelerator (SORA)