Introducing StackOps Dynatrace

StackOps Dynatrace is an observability platform for analysing and automating data across:

• Application observability
• Infrastructure observability
• Container observability
• Digital experience monitoring
• Metrics
• Log analytics

The StackOps offering of Dynatrace provides a unified observability framework tailored for Whole-of-Government (WOG) requirements:

• Centrally-managed infrastructure and backend services, so agencies can focus on core monitoring activities
• Easy integration with collaboration platform tools
• Consolidated onboarding experience across user management, billing, and cost estimation.
• Price discounts

Capabilities

Dynatrace offers a wide range of capabilities at individual rates. Refer to [Pricing] for more details.

Full-stack monitoring

Full-stack monitoring provides end-to-end visibility across your applications and infrastructure. It unifies tracing, profiling, and process monitoring, offering features such as:

• Distributed tracing
• Code-level visibility
• CPU profiling
• Memory profiling
• Deep process monitoring for hosts and containers

This capability accelerates root-cause analysis and reduces mean-time-to-resolution (MTTR), ensuring a seamless user experience.

Infrastructure monitoring

Infrastructure monitoring ensures the stability of foundational systems like hosts, VMs, containers, and cloud networks. It tracks vital resource metrics like CPU, memory, and disk usage to maintain reliable operations:

• Detailed process performance metrics
• Disk performance metrics
• Process-to-process network analysis
• Per-process memory analysis

Unlike full-stack monitoring, it focuses strictly on this underlying layer, stopping short of capturing application performance, distributed tracing, and user-experience insights.

Container observability

StackOps Dynatrace provides the following capabilities for Container observability:

• Kubernetes platform monitoring — Provides insights into your Kubernetes clusters.
• Code monitoring — Enables you to analyse and debug running code in production environments.

Kubernetes platform monitoring

Kubernetes platform monitoring provides visibility into the health and performance of clusters, nodes, pods, and workloads by tracking metrics, events, and resource utilisation. It helps detect issues such as pod failures or resource contention, optimise scaling and scheduling, and ensure reliable, efficient operation of containerised applications.

Code monitoring

Container (code-level) monitoring provides visibility into the performance of containerised applications by capturing code-level activity, execution traces, and resource usage within containers. It enables teams to detect performance bottlenecks, troubleshoot issues at the code level, and optimise application behaviour to ensure efficient and reliable container performance.

Digital experience monitoring

Digital experience monitoring provides complete visibility into how users experience your applications through:

• HTTP monitoring — Check the availability of websites, API endpoints, or even internal network resources.
• Synthetic monitoring — Validate business-critical workflows by simulating a user visiting your application in a modern browser.
• Real user monitoring (RUM) — Collects detailed data about each user’s interactions with your application.

HTTP monitoring

HTTP monitoring provides visibility into the performance and reliability of web requests by tracking response times, status codes, and latency across services. It helps detect slow or failed requests, troubleshoot service dependencies, and ensure consistent application availability.

Synthetic monitoring

Synthetic monitoring simulates user behaviour through scripted tests to proactively monitor application availability and performance, measuring response times, uptime, and key transaction success across locations. It helps detect issues before users are impacted, validate critical user journeys, and ensure consistent performance and reliability across environments.

Real user monitoring (RUM)

Real user monitoring (RUM) captures real-time user interactions across web and mobile applications, tracking metrics such as load times, errors, and user journeys. It enables teams to understand actual user experience, identify performance issues by location or device, and optimise for seamless digital interactions.

Telemetry metrics

Telemetery data are stored in and powered by Grail, Dynatrace’s data lakehouse. Its Ingest and Process capability provides data delivery, topology enrichment, data transformation, and retention controls for metrics, traces, and events.

Ingest and Process: Metrics

This capability covers the ingestion and pipeline processing of external, high-volume quantitative data into Dynatrace. It captures real-time numerical health data (e.g., utilisation, capacity, and performance trends) from systems outside your core host coverage, allowing you to unify your external infrastructure and third-party telemetry into a single dashboard. Examples include:

• Native cloud platform metrics directly from AWS CloudWatch or Azure Monitor.
• Performance metrics for agentless databases (such as tracking query speeds and connection pools for Oracle, MSSQL, or PostgreSQL).
• Hardware health and bandwidth data from network devices via SNMP (Simple Network Management Protocol).
• Any custom business or technical data points pushed via the Dynatrace API.

Ingest and Process: Traces

This capability tracks the exact, end-to-end journey of a digital request as it moves across cloud environments, serverless functions, and third-party systems. It acts as a digital map for your architecture, eliminating blind spots in modern, cloud-native environments where a standard host agent cannot be deployed. Examples include:

• Native cloud platform metrics directly from AWS CloudWatch or Azure Monitor.
• P*erformance metrics for agentless databases (such as tracking query speeds and connection pools for Oracle, MSSQL, or PostgreSQL).
• Hardware health and bandwidth data from network devices via SNMP.
• Any custom business or technical data points pushed via the Dynatrace API.

Ingest and Process: Events

This capability manages the collection, enrichment, and secure processing of discrete, timestamped occurrences from across your IT ecosystem. It centralises system state changes and critical hardware alerts from external sources, allowing you to instantly correlate third-party incidents with your overall infrastructure baseline health. Examples include:

• Centralising cloud infrastructure alerts (such as auto-scaling events or configuration alarms from AWS and Azure).
• Correlating real-time SNMP traps and link-down alarms from network hardware, critical cluster failovers and state changes from databases like Oracle and MSSQL, and custom high-value business milestones (e.g., “User Checkout Completed”) directly alongside your IT performance data.

Log analytics

In StackOps Dynatrace, log analytics are provided through the following dimensions:

• Ingest and Process
• Retain

Ingest and Process: Log analytics

This capability manages the data delivery and real-time processing of log data via OneAgent or the Log ingestion API, preparing raw logs for secure storage and analysis.

As data enters the platform, it is automatically enriched with data source and topology metadata. Furthermore, it safeguards your environments by masking sensitive information in real-time. To help optimise storage costs, it provides filtering controls to exclude unnecessary incoming logs based on content or metadata meaning you only consume usage for the initial ingestion and processing, avoiding downstream retention costs for unwanted data.

Retain: Log analytics

This capability governs the continuous availability and secure storage of your processed logs once they reside in Dynatrace log buckets, ensuring the historical data remains reliably accessible for DQL querying and analysis. By keeping processed log data securely preserved, it supports historical troubleshooting and helps organisations meet strict regulatory and internal auditing requirements throughout the data’s lifecycle.

Application security

This suite of capabilities includes:

• Runtime Vulnerability Analytics —

  • Provides real-time visibility into vulnerabilities in running applications by correlating them with actual execution paths, dependencies, and service context.
  • Helps prioritise truly exploitable risks, reduce false positives, and accelerate remediation based on real business impact.

• Runtime Application Protection (To be offered at a later stage)

• Security Posture Management (To be offered at a later stage)