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Course Outline
Advanced AIOps Architecture and Strategy for Government
- Review of AIOps platform stacks and components for government
- Designing scalable AIOps pipelines for government operations
- Service observability and telemetry strategy for enhanced governance
Data Normalization and Correlation for Government
- Ingesting logs, metrics, events, and traces from various sources for government systems
- Data cleaning, normalization, and context mapping to ensure accuracy and reliability
- Event correlation and noise reduction techniques to improve operational efficiency
Anomaly Detection and Machine Learning Extensions for Government
- Advanced anomaly detection models (statistical and ML-driven) tailored for government use cases
- Model training, validation, and continuous tuning to maintain high performance standards
- Handling unbalanced and high-dimensional datasets common in government data environments
Root Cause Analysis and Predictive Analytics for Government
- ML-based root cause workflows to enhance incident resolution for government agencies
- Predictive modeling for incident forecasting to improve proactive management
- Implementing RCA dashboards and timelines to support transparent and accountable operations
Tools and Platform Labs for Government
- Hands-on labs with tools such as Splunk ITSI, Moogsoft, Dynatrace, IBM Watson AIOps tailored for government use
- Integrations with ITSM (ServiceNow, Jira) and DevOps toolchains to streamline operations
- Playbooks and automation pipelines to enhance operational efficiency
Cloud, Multi-Cloud, and Hybrid AIOps Integration for Government
- AIOps in AWS, Azure, and GCP environments to support government cloud strategies
- Multi-cloud observability patterns to ensure seamless monitoring across platforms
- Capacity forecasting and predictive scaling to optimize resource utilization for government agencies
Automation and Self-Healing Workflows for Government
- Designing closed-loop automation to enhance operational resilience
- Runbooks, playbooks, and event triggers to support rapid response
- Self-healing and resilience patterns to ensure continuous service delivery
Real-World Use Cases and Best Practices for Government
- Case studies across industries with a focus on government applications
- Operational metrics correlation with business outcomes to drive informed decision-making
- Optimization and tuning strategies to maximize the effectiveness of AIOps for government operations
Summary and Next Steps for Government
Requirements
- Completion of the AIOps Foundation course or equivalent foundational knowledge
- Proficiency in data analytics, machine learning basics, and IT incident management processes
- Experience in IT operations, site reliability engineering (SRE), or DevOps environments
Audience
- Advanced IT operations engineers and architects for government
- AIOps tool administrators and implementers
- Site Reliability Engineers (SRE)
- DevOps platform and observability teams
21 Hours