1. Introduction & Overview
What is Embedded Analytics?
Embedded Analytics is the integration of analytical capabilities and data visualizations directly into business applications or software workflows. Unlike traditional analytics tools that require users to switch platforms, embedded analytics brings insights natively into the user interface of operational systems.
In DevSecOps, embedded analytics enables security, development, and operations teams to monitor, analyze, and act on key metrics such as:
- Vulnerability trends
- Code quality metrics
- Compliance scores
- Real-time CI/CD pipeline security insights
History or Background
- Early 2000s: Business Intelligence (BI) tools emerged, focusing on dashboards and reporting.
- Mid-2010s: Rise of cloud-native and SaaS platforms led to embedded dashboards within apps.
- Today: Embedded analytics is a cornerstone in observability and DevSecOps, offering actionable intelligence within CI/CD pipelines, monitoring platforms, and security dashboards.
Why is it Relevant in DevSecOps?
DevSecOps emphasizes integrating security into DevOps processes. Embedded analytics:
- Surfaces real-time security insights during development and deployment
- Empowers developers to act on issues without leaving their tools
- Helps compliance teams automate auditing
- Enables stakeholders to make data-driven decisions
2. Core Concepts & Terminology
Key Terms and Definitions
| Term | Definition |
|---|---|
| Embedded Analytics | Analytics functionality embedded into an application’s user interface |
| Visualization | Graphical representation of data like charts, heatmaps, graphs |
| Observability | Capability to infer internal states of a system from metrics/logs/traces |
| KPI | Key Performance Indicator, used to assess security or operational performance |
| Telemetry | Automated data collection from tools, processes, or infrastructure |
How It Fits into the DevSecOps Lifecycle
Embedded analytics enhances multiple stages:
- Plan: Track security risk metrics during sprint planning
- Develop: Identify vulnerable dependencies from IDEs
- Build: View static analysis reports inline in CI pipelines
- Test: Analyze test coverage vs vulnerability density
- Release: Monitor compliance gates
- Operate: Use runtime metrics (e.g., from Falco or Prometheus) in embedded dashboards
- Monitor: Alert on anomalies and provide contextual drilldowns
3. Architecture & How It Works
Components
- Data Source Layer: Logs, CI/CD metadata, scan results, cloud security data
- Data Processing Layer: Aggregates, transforms, or correlates data
- Embedding Layer: SDKs/widgets added to apps or pipelines
- User Interface Layer: Visualizations within dashboards, IDEs, or UIs
Internal Workflow
[ Data Sources (e.g., SonarQube, GitHub, AWS CloudTrail) ]
↓
[ ETL or Stream Processor (e.g., Fluentd, Logstash, Kafka) ]
↓
[ Data Warehouse or Analytics Engine (e.g., ClickHouse, Redshift) ]
↓
[ Embedded UI (e.g., Grafana panel inside Jenkins/GitLab) ]
Architecture Diagram (Descriptive)
- Step 1: Data is collected from CI/CD and security scanners (e.g., Trivy, Snyk).
- Step 2: Data is sent to a backend analytics engine (e.g., ElasticSearch, Snowflake).
- Step 3: Widgets or REST APIs expose this data to front-end components.
- Step 4: Embedded widgets show real-time graphs inside Jenkins, Jira, etc.
Integration Points with CI/CD or Cloud Tools
| Tool | Integration Use |
|---|---|
| Jenkins | Embed dashboards showing static analysis trends |
| GitLab CI | Show merge request vulnerability diffs |
| Kubernetes Dashboards | Real-time container threat analytics |
| AWS/GCP/Azure | Embed cloud compliance and cost anomaly dashboards |
4. Installation & Getting Started
Basic Setup or Prerequisites
- A running CI/CD environment (Jenkins, GitLab, etc.)
- Security scanners (e.g., SonarQube, Trivy)
- Analytics engine (e.g., Grafana, Kibana, or a BI platform like Metabase)
- Dashboard embedding support (iframe/JS SDK/API access)
Hands-on: Step-by-Step Beginner-Friendly Setup Guide (Using Grafana + Jenkins)
- Install Grafana
docker run -d -p 3000:3000 grafana/grafana
- Configure Data Source (e.g., Prometheus or JSON API Plugin)
- Go to
http://localhost:3000 - Add Prometheus or use JSON API for external sources
- Create Dashboard with Security Metrics
- Visualize metrics like failed builds, critical CVEs
- Embed Grafana Panel into Jenkins
In Jenkins, install Dashboard View Plugin and embed Grafana via iframe:
<iframe src="http://localhost:3000/d/example-dashboard" width="100%" height="400"></iframe>
5. Real-World Use Cases
1. Shift-Left Security Visualization
- Display static analysis results from tools like SonarQube in GitLab merge requests.
2. CI/CD Pipeline Insights
- Embed dashboards in Jenkins showing:
- Test coverage vs code changes
- Failed security scans
3. Cloud Security Compliance
- Embed GCP/AWS security posture dashboards in internal portals for auditors.
4. Runtime Threat Monitoring
- Use Falco + Grafana to embed real-time dashboards in Kubernetes control planes.
6. Benefits & Limitations
Key Advantages
- Real-time insights where decisions are made
- Context-rich visualizations boost decision speed
- Improved collaboration between Dev, Sec, Ops
- Better compliance via embedded audit tracking
Common Challenges or Limitations
| Challenge | Detail |
|---|---|
| Performance | Can impact app speed if poorly implemented |
| Security | Embedding external analytics must follow CSP and sandboxing rules |
| Data Silos | Integration complexity increases if tools are not API-first |
| Version Drift | Embedded widgets might break on tool upgrades |
7. Best Practices & Recommendations
Security Tips
- Use OAuth or token-based auth for secure data access
- Always use HTTPS and CSP headers for embedded dashboards
- Prefer read-only data in embedded widgets
Performance & Maintenance
- Cache results for expensive queries
- Use lazy loading for analytics widgets
- Monitor for API quota limits
Compliance & Automation Ideas
- Embed audit trails inside CI tools
- Show code ownership + security risk in dashboards
- Automate alert generation on SLA breaches
8. Comparison with Alternatives
| Feature | Embedded Analytics | Traditional BI Tools | External Dashboards |
|---|---|---|---|
| Context Awareness | ✅ High | ❌ Low | ⚠️ Medium |
| Real-Time Updates | ✅ Yes | ⚠️ Delayed | ⚠️ Configurable |
| Developer Friendly | ✅ Yes | ❌ No | ⚠️ Limited |
| CI/CD Integration | ✅ Tight | ❌ Not Native | ⚠️ Possible with effort |
When to Choose Embedded Analytics
- If real-time, in-context visibility is required
- When teams need immediate actionability
- For automated compliance reporting inside pipelines
9. Conclusion
Embedded Analytics empowers DevSecOps teams by delivering data and security insights exactly where they’re needed — within the tools developers and operators already use. It facilitates faster decisions, continuous compliance, and improved security posture without switching contexts.
Future Trends
- Increased use of AI-enhanced analytics (e.g., anomaly detection)
- Native embedding of LLM-based insights into dashboards
- Self-service analytics inside DevOps tools
Next Steps
- Explore Grafana, Kibana, or Metabase for embedding
- Integrate your security tool data (e.g., Trivy, Aqua)
- Start with one dashboard — iterate continuously