Enterprise Observability Reference Architecture

A unified approach across on-premise and cloud platforms with AI-powered insights

data center servers cloud infrastructure

Highlights

Unified Monitoring: Seamlessly integrates Dynatrace monitoring with BMC Helix ITSM for both on-premise and cloud environments.
Cost-Efficiency: Leverages open-source tools and best practices to reduce costs while maintaining robust observability.
AIOps & CI/CD Visibility: Incorporates AI-driven operations and continuous delivery observability to support agile development workflows.

Overview

This reference architecture designs an enterprise observability solution that accommodates traditional on-premise systems—including mainframe and midrange servers—as well as modern cloud hyperscaler deployments. By employing Dynatrace as the primary observability tooling and BMC Helix as the go-to ITSM system, the design ensures real-time monitoring, incident management, root cause analysis, and operational automation. Open-source components are incorporated where viable to minimize costs, and AIOps capabilities are embedded to provide predictive analytics, anomaly detection, and automated remediation. Additionally, CI/CD pipeline observability is integrated to support agile solution developments, ensuring that each code commit, build, and deployment is thoroughly monitored and assessed.

Architecture Components

The solution is divided into several layers and components, which together form a cohesive and scalable observability ecosystem:

1. Infrastructure Layer

On-Premise Systems

Traditional on-premise systems, including mainframe and midrange servers (e.g., IBM zSeries, IBM iSeries, Unix-based systems), are equipped with Dynatrace OneAgent. The OneAgent automatically collects performance metrics, availability data, and system health signals. Integration with BMC Helix Discovery helps in comprehensively mapping these legacy systems.

Cloud Hyperscaler Solutions

Cloud-native applications are deployed on popular platforms such as AWS, Azure, or Google Cloud Platform. Here, Dynatrace OneAgent or Cloud Agents provide visibility into cloud workloads, microservices, and containerized environments, ensuring monitoring consistency across both on-premise and cloud infrastructures.

2. Data Collection and Integration Layer

Data collection is crucial for achieving a unified observability platform. At this layer, multiple tools contribute:

Dynatrace for Real-time Monitoring

Dynatrace is responsible for capturing telemetry data from all deployed systems. It gathers metrics, logs, events, and user experience data, centralizing this information for further analysis.

BMC Helix Intelligent Integrations

BMC Helix’s capability to integrate diverse data sources ensures that metrics from Dynatrace and additional systems (including third-party and open-source tools) are consolidated for effective ITSM. This data exchange occurs via API integrations and middleware solutions.

Open-Source Tools

To minimize cost while augmenting the observability solution, open-source technologies are incorporated:

Prometheus: Used for time-series data collection from microservices and cloud-native applications.
Grafana: Provides rich visualizations and dashboarding capabilities to complement the Dynatrace dashboards.
ELK Stack (Elasticsearch, Logstash, Kibana): Collects, processes, and visualizes log data across the enterprise platform.
Kafka: Acts as an event streaming platform to synchronize data flows between Dynatrace, BMC Helix, and other tools.

AIOps and AI-Driven Automation

AIOps, powered by artificial intelligence and machine learning, enhances the observability solution by automating incident detection, event correlation, and predictive analytics. The integrated AIOps platform leverages the consolidated data from Dynatrace and BMC Helix to:

Anomaly Detection

Continually analyze performance and operational data to identify anomalies before they result in significant outages.

Predictive Analytics & Root Cause Analysis

Use historical data trends to predict potential issues and perform automated root cause analyses that expedite troubleshooting efforts.

Automated Incident Management

Automatically prioritize incidents and trigger remediation workflows within BMC Helix, improving incident response times and reducing human error.

CI/CD Observability and Agile Developments

Modern development practices require continuous monitoring of CI/CD pipelines to ensure that application deployments meet quality and performance standards. This architecture integrates observability tools with agile development processes to monitor the complete software delivery lifecycle:

CI/CD Pipeline Integration

CI/CD tools like Jenkins, GitLab, or similar platforms are integrated with Dynatrace to provide real-time insights into build performance, deployment metrics, and application health. Each commit, build, or release is evaluated against service level indicators (SLOs) to maintain quality and compliance.

OpenTelemetry for Agile Observability

Incorporating OpenTelemetry offers a vendor-neutral framework to collect and export telemetry data from CI/CD pipelines. This enables seamless integration of performance metrics and trace data into Dynatrace, ensuring continuous visibility into agile development cycles.

Quality Gates and Feedback Loops

Automated quality gates are established, ensuring that only code meeting predefined performance benchmarks continues through the pipeline. Rapid feedback loops help developers remediate issues early, reducing downtime and deployment delays.

Detailed Component Overview

The table below summarizes the key components and their roles in the overall architecture:

Component	Functionality	Deployment Scope
Dynatrace OneAgent/Cloud Agent	Real-time collection of performance metrics, logs, and user experience data.	On-Premise and Cloud
BMC Helix ITSM	Incident, problem, and change management integrated with monitoring data.	Enterprise-wide ITSM
BMC Helix Intelligent Integrations	APIs to integrate monitoring data between Dynatrace and ITSM platforms.	Hybrid environments
Prometheus & Grafana	Open-source time-series data collection and visualization.	Cloud-native and microservices
ELK Stack	Log collection, parsing, and advanced dashboarding.	Enterprise-wide log analysis
Kafka	Real-time data and event streaming for integration.	Middleware integration
AIOps Platform	Automated anomaly detection, predictive analytics, and incident remediation.	Across all data sources
CI/CD Tools & OpenTelemetry	Observability and quality monitoring in continuous delivery pipelines.	Development and Operations

Deployment Strategy and Best Practices

Phased Rollout

Begin by deploying a pilot program within a small segment of the IT environment. Gradually expand the observability solution to cover all critical systems and applications, ensuring thorough testing and iterative enhancements.

Cloud-First Approach

Prioritize the deployment of cloud platforms first, taking advantage of their scalability and flexibility. Subsequently, extend the coverage to on-premise systems, integrating legacy technologies into the unified observability framework.

Security and Compliance

Ensure that all data collection and storage comply with industry regulations and organizational policies. Implement robust security measures, including encrypted communication channels and strict access controls, to protect sensitive observability data.

Leveraging Open-Source Tools

Emphasize the adoption of open-source frameworks wherever feasible to reduce licensing costs and foster community-driven innovation. Open-source solutions often provide extensible architectures that can be tailored to specific organizational requirements.