Overview
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Transform your ability to monitor, diagnose, & optimize application performance with comprehensive AppDynamics training. This program addresses the critical challenge that 60% of customer-impacting incidents stem from performance issues. You'll start by learning automatic discovery, transaction analysis, & intelligent alerting for distributed applications. You'll diagnose bottlenecks using snapshot-driven troubleshooting, eliminate alert fatigue with baseline-driven health rules, & create executive dashboards that democratize observability. The program covers specialized monitoring for machine learning applications, addressing their complex data dependencies & business-critical performance requirements. Through hands-on labs simulating real production scenarios, from checkout slowdowns to database N+1 queries, you'll develop practical skills applicable to your environment. Whether you're an operations engineer implementing your first monitoring solution, a data scientist ensuring ML model reliability, or an SRE optimizing complex distributed systems, this program provides the complete AppDynamics toolkit. By completion, you'll reduce incident response times to sub-5 minutes, decrease alert noise by 50%+, & deliver monitoring solutions that protect business performance while providing actionable intelligence across your organization.
Syllabus
- Course 1: AppDynamics: From Basics to Performance Mastery
- Course 2: AppDynamics (Advanced)
- Course 3: AppDynamics Monitoring
Courses
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Mastering AppDynamics (advanced) is an intermediate-level course designed for performance engineers, site reliability engineers (SREs), and IT operations leaders who need to manage complex, large-scale applications where real-time monitoring and proactive performance management are critical. In today’s digital enterprises, reactive troubleshooting is obsolete—success depends on predictive insights, intelligent alerting, and business-aligned dashboards that drive resilience and efficiency. This course provides comprehensive coverage of AppDynamics’ advanced capabilities: end-user and business transaction monitoring for impact analysis, database and backend visibility for root cause diagnosis, custom dashboards for executive and technical reporting, and health rules and alerting frameworks for proactive system defense. Through real-world case studies from enterprises across finance, e-commerce, and cloud-native platforms, hands-on labs, and applied design challenges, you'll learn to strategically configure, optimize, and scale AppDynamics for mission-critical environments. Whether you’re optimizing hybrid cloud applications, improving SLA adherence, or enabling proactive performance strategies, this course equips you with the expertise to transform monitoring data into actionable intelligence that protects business performance and delivers measurable value.
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AppDynamics Monitoring for Machine Learning Applications is a beginner-level course designed to equip data scientists, ML engineers, and DevOps professionals with the specialized monitoring skills needed for production ML systems. Unlike traditional applications, machine learning systems have unique failure modes, complex data dependencies, and business-critical performance requirements that demand sophisticated observability approaches. This course provides hands-on experience with AppDynamics' AI-powered monitoring platform, teaching learners to implement comprehensive monitoring solutions that capture both technical performance and business outcomes. Through real-world case studies, practical exercises, and advanced troubleshooting scenarios, learners will master the art of maintaining reliable, high-performing ML applications that deliver consistent business value in production environments.
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Application performance issues cause 60% of customer-impacting incidents, making proactive monitoring critical for production systems. This course equips operations engineers to build observable distributed applications through hands-on work with AppDynamics for automatic discovery, transaction analysis, and intelligent alerting. You'll diagnose performance bottlenecks using snapshot-driven troubleshooting, eliminate alert fatigue by configuring baseline-driven health rules integrated with IT operations tools, and democratize observability through executive dashboards with automated reporting. This course eliminates the hours spent on manual log analysis across microservices. With hands-on labs, you'll simulate production scenarios including checkout slowdowns, database N+1 query patterns, and alert integration workflows. This course is designed for operations engineers, DevOps practitioners, SREs, application developers, and anyone responsible for monitoring, supporting, or optimizing production applications. If you work with distributed systems or want to strengthen your observability and incident-response skills, you’re in the right place. A basic understanding of web applications, APIs, and how backend services communicate will help you move quickly through the course. Familiarity with command-line tools and general application architecture (tiers, services, databases) is useful but not required. By course completion, you'll identify performance bottlenecks within minutes, reduce alert noise by 50%+, configure multi-channel notifications for sub-5-minute incident response, and deploy enterprise-scale monitoring with RBAC governance.
Taught by
Aseem Singhal, Hurix Digital and Starweaver