DEVOPS

What is Nagios?

<h3>What is Nagios?</h3> Nagios is used for Continuous monitoring of systems, applications, services, business processes, etc. in a DevOps culture. If a failure occurs, Nagios has the alerting ability to inform the technical staff about the problem, allowing them to begin remediation processes before outages affect business processes, end-users, or customers. With Nagios, you don’t have to explain why an unseen infrastructure outage affects your application’s performance in a production environment. By using Nagios you can: <ul><li>Plan for infrastructure upgrades proactively, before outdated systems cause failures.</li></ul> <ul><li>Respond to issues at the first sign of a problem.</li></ul> <ul><li>Automatically fix problems when they are detected.</li></ul> <ul><li>Coordinate technical team responses.</li></ul> <ul><li>Ensure your organization’s SLAs are being met.</li></ul> <ul><li>Monitor your entire infrastructure and business processes.</li></ul>

Learn about Nagios, an open-source IT monitoring tool. Understand how it helps in monitoring systems, networks, and infrastructure for optimal performance.

What is Nagios? IT Monitoring Tool Overview

 Ethical Considerations in Prompt Engineering
*Addressing bias and fairness in AI responses
*Best practices for ethical prompt design
*Project Work
*Group project: Developing prompts for a specific application
*Presentations of group projects and peer feedback
* Future Trends in Prompt Engineering
*Emerging technologies and trends in AI
*The evolving role of prompt engineers in AI development


*Introduction to Prompt Engineering
*Overview of Prompt Engineering
*Importance and applications in AI
*Understanding AI Models
*Types of AI models (e.g., GPT, BERT)
*How models interpret prompts
*Crafting Effective Prompts
*Key principles for prompt design
*Techniques for clarity and specificity
*Hands-on practice: Writing basic prompts

 Analyzing Prompt Responses
*Evaluating the effectiveness of prompts
*Techniques for refining prompts based on outputs
*Contextual and Conditional Prompting
*Using context to improve responses
*Conditional prompts for specific tasks
*Hands-on practice: Contextual prompt crafting
*Case Studies and Real-World Applications
*Examining successful prompt engineering examples
*Discussion of industry applications (e.g., chatbots, content generation)

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*Hands-on Lab 1: Test Generation
*Clone starter repository: repo-copilot-app
*Select API controller
*Generate unit tests via Copilot
*Execute and debug generated tests
*Refine test quality

*Hands-on Lab 2: Code Documentation
*Identify complex function
*Use Chat to explain functionality
*Generate comprehensive docstrings
*Add inline comments
*Create README sections

*Hands-on Lab 3: Endpoint Scaffolding
*Design new endpoint structure
*Use Copilot for implementation
*Scaffold test suite
*Implement basic validation

*Project Task: Metrics Endpoint with Rate Limiting
*Implement /metrics endpoint
*Add rate limiting logic
*Create comprehensive tests
*Document API specifications
*Ensure CI passes
*Create PR


*AI-Assisted Review Process:
*Leveraging Copilot for PR reviews
*Identifying code smells
*Security vulnerability detection
*Best practice recommendations

*Review Workflow Integration:
*Setting up automated checks
*Custom review checklists
*Collaborative review processes


*Metrics Collection:
*Response time measurements
*Throughput analysis
*Security scan results
*Code quality scores

*Optimization Strategies:
*Query optimization
*Caching strategies
*Connection pooling
*Asynchronous processing

DAY 2 DELIVERABLES:
*PR: pagination + caching + security fixes
*Security review checklist
*Benchmark notes and metrics
*PR review summary


*Effective Copilot Prompting:
*Comment-driven development
*Natural language specifications
*Example-based prompting
*Iterative refinement techniques

*Quality Control:
*Reviewing AI-generated code
*Testing and validation strategies
*Security considerations
*Performance implications
*
*DAY 1 DELIVERABLES:
*PR with /metrics endpoint + tests + docs
*CI green confirmation
*Prompt/response snippets collection
*Commit log
*CI badge screenshot


*Setup Implementation:
*Verify Copilot access/license
*Install GitHub Copilot extension
*Enable Copilot Chat
*Configure IDE settings
*Review organization policies

*Security and Governance:
*Data handling policies
*Secure prompting practices
*Avoiding credential exposure
*Managing sensitive information
*Content filtering options


*Hands-on Lab 2: Pagination Implementation
*Analyze listing endpoint
*Implement cursor-based pagination
*Add query parameter handling
*Create pagination tests
*Validate performance improvements

*Hands-on Lab 3: Caching Layer
*Design in-memory cache strategy
*Implement caching logic
*Add cache invalidation
*Write invalidation tests
*Benchmark performance gains

*Project Task: Security Hardening
*Review auth/validation on API routes
*Implement security enhancements
*Update security documentation
*Create security review checklist
*Create PR: pagination + caching + security


*Complete Development Lifecycle:
*Issue analysis and planning
*Solution design
*Implementation strategy
*Testing approach
*Documentation requirements
*Release preparation

*Best Practices Consolidation:
*Lessons from Days 7-8
*Prompt library organization
*Workflow optimization
*Team collaboration patterns


*Overall Program Retrospective:
*Cross-tool comparisons (Qodo vs. Windsurf vs. Copilot)
*Use case alignment
*Tool selection criteria
*Integration opportunities

*Learning Metrics:
*Productivity improvements
*Code quality enhancements
*Test coverage increases
*Time savings quantification

*Next Steps & Resources:
*Advanced learning paths
*Community resources
*GitHub Copilot updates and roadmap
*Enterprise adoption strategies
*Continuous improvement framework

*Final Q&A and Feedback:
*Open discussion
*Addressing remaining questions
*Program evaluation
*Certificate distribution

*DAY 3 DELIVERABLES:
*Capstone PR
*Final showcase recording
*Enablement pack (complete)
*Final report draft
*Prompt library
*Complete checklist collection
*Training completion certificates


*Primary Use Cases:
*Real-time code suggestions
*Test generation
*Documentation creation
*Code explanation and learning
*Boilerplate generation
*API integration assistance

*Enterprise Capabilities:
*Organization policy controls
*IP indemnification
*Usage analytics
*Security and compliance features


*Team Presentations:
*Capstone project demos
*Technical deep-dives
*Before/after comparisons
*ROI metrics presentation

*Enablement Pack Creation:
*Prompt library compilation
*Checklist collection

*Best practices documentation
*Troubleshooting guides
*Quick reference cards


*Project Selection:
*Choose from COPILOT-issues.md backlog
*Analyze complexity and scope
*Plan end-to-end approach
*Rolling Lab: Full Cycle Execution
*Issue -> Planning -> Implementation -> Testing -> Documentation -> PR -> Merge
*Continuous Copilot integration
*Regular progress checkpoints
*Demo preparation

*Deliverable Creation:
*Capstone PR with complete documentation
*Final showcase recording
*Enablement package preparation


*Introduction to GitHub Copilot:
*Evolution and development by GitHub/Microsoft
*OpenAI Codex foundation
*Enterprise vs. Individual vs. Business plans
*Integration ecosystem

*Core Capabilities:
*Code completion engine
*Chat interface features
*Context awareness mechanisms
*Multi-language support

*Competitive Landscape:
*Comparison with Amazon CodeWhisperer
*Comparison with Tabnine
*GitHub's market position


*Hands-on Lab 1: Security-Focused Review
*Analyze vulnerable PR

*Identify security issues:
*Hardcoded secrets
*SQL injection vulnerabilities
*XSS vulnerabilities
*Authentication bypasses
*Apply Copilot-suggested fixes
*Implement security best practices
*Add validation layers

*Secure Coding Patterns:
*Input validation
*Output encoding
*Authentication and authorization
*Secrets management
*Error handling security

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*Primary Use Cases:
*Intelligent code planning and architecture
*Multi-file refactoring
*Complex feature implementation
*Debugging and troubleshooting
*Documentation generation

*Cascade AI Capabilities:
*Natural language to code
*Codebase understanding
*Task decomposition
*Dependency tracking
*Test-driven development assistance

*Hands-on Lab 3: Agent-Guided Debugging
*Identify flaky test
*Use Cascade to analyze root cause
*Implement fix with AI guidance
*Verify test stability
*Document debugging process

*Advanced Debugging Techniques:
*Breakpoint strategies
*Log analysis with AI
*Race condition detection
*Memory leak identification

*Repository Pattern Introduction:
*Benefits of repository pattern
*Separation of concerns
*Testability improvements
*Dependency injection principles

*Refactoring Strategy:
*Identifying code smells
*Planning refactoring approach
*Maintaining backward compatibility
*Incremental refactoring techniques

*Hands-on Lab 2: CLI Development with Cascade
*Task: Implement 'report:lint' command
*Use Cascade for planning
*Generate command structure
*Add auto-lint functionality
*Create test hooks
*Verify execution

*Hands-on Lab 3: Multi-File Editing
*Identify files requiring changes
*Use Cascade for coordinated edits
*Maintain consistency across files
*Run tests from IDE terminal
*Debug failures with AI assistance

*Project Task 4: Health-Check Endpoint
*Design health-check API endpoint
*Implement service layer logic
*Create comprehensive tests
*Update README documentation
*Ensure CI pipeline passes

*Setup Implementation:
*Download and install Windsurf IDE
*Authentication and account setup
*Project workspace configuration
*Terminal access verification
*Agent permissions and settings

*Hands-on Lab 1: Environment Familiarization
*Clone starter repository: repo-windsurf-refactor
*Navigate Windsurf interface
*Activate Cascade assistant
*Explore code reading features
*Run initial task breakdown exercise

*Effective Cascade Prompting:
*Structuring complex requests
*Providing context effectively
*Iterative refinement techniques
*Multi-step task management

*IDE Workflow Optimization:
*Keyboard shortcuts and efficiency
*Terminal integration best practices
*File navigation strategies
*Git workflow within Windsurf

*DAY 1 DELIVERABLES:
*PR#4 with health-check endpoint + tests
*Updated README
*Passing CI confirmation
*Cascade prompt log
*PR diff documentation
*Test run screenshots

*Project Task 5: UserService Refactor
*Complete repository pattern implementation
*Ensure all tests pass
*Improve test reliability metrics
*Create changelog entry
*Document architectural changes
*Create PR#5

*Hands-on Lab 1: Cascade Refactor Planning
*Analyze UserService module
*Identify seams and interfaces
*Design repository structure
*Plan dependency injection approach
*Create refactoring checklist

*Hands-on Lab 2: Implementation
*Create repository interfaces
*Implement concrete repositories
*Refactor UserService to use repositories
*Update dependency injection configuration
*Modify existing tests
*Add new tests for repositories


*Implementing Robust Systems:
*Structured logging patterns
*Error handling strategies
*Observability considerations
*Performance monitoring

*DAY 2 DELIVERABLES:
*PR#5 with refactor + test updates
*Changelog entry
*Refactor checklist completed
*Before/after structure diagram
*Regression safety documentation


*Feature Selection:
*Review WIN-Feature.md
*Select "Export to CSV" feature
*Analyze requirements and scope
*Rolling Lab: Full Feature Implementation
*Service layer implementation
*CLI command creation
*CSV generation logic
*Error handling and validation
*Comprehensive test suite
*Documentation updates
*Release notes drafting

*Periodic Commits:
*Atomic commit strategy
*Meaningful commit messages
*Branch management


*Deliverable Creation:
*Record feature demo (5-10 minutes)
*Complete reviewer checklist
*Finalize PR#6 documentation
*Prepare CLI help output
*Generate PR review summary

*Team Showcase:
*Feature demonstrations
*Technical deep-dives
*Lessons learned sharing
*Q&A session


*Developer Experience (DX) Focus:
*Documentation quality review
*Script and automation assessment
*Onboarding considerations

*Continuous Improvement:
*Advanced Windsurf features to explore
*Integration with team workflows
*Performance optimization opportunities

*DAY 3 DELIVERABLES:
*Capstone PR#6
*Demo clip
*Reviewer checklist completed
*Release notes draft
*CLI help output
*PR review summary

*Introduction to Windsurf IDE
*Purpose-built AI-native IDE
*Cascade AI assistant capabilities
*Difference from traditional IDEs
*Integration philosophy

*Core Technology:
*Cascade AI engine architecture
*Multi-file reasoning capabilities
*Context management systems
*Terminal and tooling integration

*Comparison with Other AI IDEs:
*Cursor AI comparison
*VS Code Copilot comparison
*Unique Windsurf advantages


*End-to-End Feature Planning:
*Requirements analysis
*Component identification
*API design considerations
*Data model planning
*Test strategy definition

*Cascade Orchestration:
*Managing complex multi-file changes
*Maintaining context across sessions
*Iterative development approach
*Code review preparation

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*CI/CD Integration Deep Dive
*Automated test execution in pipelines
*Quality gates and thresholds
*Failure analysis and reporting

*Coverage Analysis:
*Interpreting coverage reports
*Identifying untested code paths
*Prioritizing test creation

*DAY 2 DELIVERABLES:
*PR#2 with feature flag + tests
*Coverage report delta
*Prompt templates (spec-first/TDD)
*Refactor checklist
*Backward compatibility notes

*Retrospective:
*What worked well
*Challenges encountered
*Improvements for ongoing use

*Next Steps:
*Continued learning resources
*Community engagement
*Advanced features to explore
*Integration with next tool (Windsurf)

*DAY 3 DELIVERABLES:
*Capstone PR#3
*Before/after metrics report
*Demo recording
*Capstone presentation deck (3 slides)
*Merged PR or sign-off documentation

*Introduction to Qodo (formerly Codium)
*Evolution from Codium to Qodo
*AI-powered code integrity platform overview
*Integration with development workflows
*Privacy and security architecture
*Core Technology Stack
*Large Language Models (LLMs) used in Qodo
*Code analysis engine
*Test generation algorithms
*Integration with Git providers (GitHub, GitLab, Bitbucket)
*Licensing and Enterprise Considerations
*Individual vs. Team vs. Enterprise plans
*Data handling and privacy policies
*On-premise vs. cloud deployment options

*Complete Development Cycle:
*Issue selection and analysis
*Planning and decomposition
*Implementation with AI assistance
*Test generation and validation
*Code review and refinement
*PR creation and merge process

*Quality Metrics Framework:
*Before/after measurements
*Quantifying improvements
*Building business cases for AI tools

*Hands-on Lab 1: Spec-First Prompting
*Write specification for service module
*Generate comprehensive test suite from spec
*Review test coverage across scenarios
*Refine and optimize tests

*Hands-on Lab 2: Cross-Module Testing
*Generate tests across two interdependent modules
*Handle dependencies and mocking
*Ensure integration test coverage
*Validate test isolation

*Primary Use Cases:
*Automated unit test generation
*AI-powered code review
*Test coverage improvement
*Bug detection and code quality enhancement
*Technical debt reduction

*ROI Metrics:
*Time savings in test writing (60-70% reduction)
*Defect detection rate improvements
*Code coverage increase benchmarks
*Developer productivity metrics

*Setup Checklist Implementation:
*IDE extension installation (VS Code, IntelliJ, etc.)
*Git provider authentication
*Repository connection and configuration
*Privacy settings and data governance
*Team workspace setup (if applicable)

*Hands-on Lab 1: Environment Setup
*Clone starter repository: repo-qodo-quality
*Install Qodo extension
*Authenticate with Git provider
*Verify connectivity and permissions
*Run baseline test suite

*Hands-on Lab 3: Review-Driven Improvements
*Apply Qodo review suggestions
*Enhance error handling patterns
*Implement defensive coding practices
*Strengthen input validation

*Concept Overview:
*Specification-driven test generation
*Test-Driven Development (TDD) with AI assistance
*Creating effective test specifications

*Advanced Prompting Techniques:
*Crafting detailed test scenarios
*Edge case identification
*Boundary condition testing
*Mock and stub generation strategies

*Hands-on Lab 2: AI Code Review Workflow
*Create sample pull request
*Trigger Qodo AI review
*Analyze suggestions and recommendations
*Apply automated fixes
*Review security and best practice alerts

*Hands-on Lab 3: Automated Test Generation
*Select existing module for test coverage
*Generate unit tests using Qodo
*Review and customize generated tests
*Execute test suite
*Analyze coverage reports

*Project Task 1: Fix Failing Tests
*Identify failing tests in baseline
*Use Qodo suggestions to diagnose issues
*Apply AI-recommended fixes
*Improve test coverage
*Create PR: Fix failing tests and improve coverage via Qodo

*Project Selection:
*Choose issue from QODO-issues.md backlog
*Analyze requirements and acceptance criteria
*Plan implementation approach
*Rolling Lab: Full Cycle Implementation
*Issue -> Design -> Code -> Test -> Review -> PR
*Continuous Qodo integration throughout
*Documentation at each stage
*Regular checkpoint reviews

*Deliverable Creation:
*Capstone PR#3 with full documentation
*Before/after metrics compilation
*Demo recording (5-10 minutes)
*Capstone presentation (3 slides)

*Understanding AI-Generated Code Quality
*How to evaluate AI suggestions
*When to accept vs. modify recommendations
*Best practices for prompt engineering with Qodo
*Integration with CI/CD pipelines
*Documentation and Knowledge Sharing
*Creating lab manual entries
*Building team quick-reference guides
*Establishing review protocols

*DAY 1 DELIVERABLES:
*PR#1 merged or reviewed
*Test run logs
*Qodo review report
*Day 1 lab manual
*Qodo quick-reference guide
*Commit history documentation

*Team Presentations:
*Individual capstone demos
*Lessons learned sharing
*Best practices documentation
*Q&A and peer feedback

*Building Organizational Assets:
*Team playbooks
*Prompt libraries
*Review checklists
*Troubleshooting guides

*Project Task 2: Feature Flag with Testing
*Create feature branch: feature/flags
*Implement 'betaMode' feature flag
*Write comprehensive unit tests
*Ensure backward compatibility
*Document migration path
*Create PR#2 with change summary

*Backward Compatibility Strategies:
*A/B testing approaches
*Gradual rollout patterns
*Rollback procedures

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*Reducing hallucination risks
*Maintaining data accuracy
*Ethical AI usage
*Validation techniques
*Balancing speed and accuracy

*Image generation for business
*No-code app development
*AI agent ecosystem
*Workflow automation strategies

*Task + Objective: Defining precise tasks and clear objectives
*Role + Context: Establishing professional context and background information
*Output Format: Specifying desired response structure and presentation requirements
*Guardrails: Setting explicit boundaries to prevent undesired outputs
*Includes practical exercises like:
*Crafting prompts for various business scenarios
*Analyzing and improving existing prompts
*Hands-on prompt engineering workshops

*Chain of Thought Prompting
*Step-Back Prompting
*Zero-Shot vs. Few-Shot Prompting
*Context Optimization
*Covers business application scenarios such as:
*Report generation
*Data analysis
*Email drafting
*Strategic planning
*Research compilation

*Practical prompt engineering test
*Case study analysis
*Individual and group exercises
*Feedback and continuous improvement strategies

*Advanced document and data management
*Comprehensive data analysis techniques
*Communication and workflow tool mastery
*In-depth research and insight generation strategies

*Basics of Large Language Models
*Differences between traditional search and AI interaction
*Potential risks like hallucination and digression
*Understanding AI's capabilities and limitations

*Document Management (PDF analysis, report summarization)
*Data Analysis (Excel insights, visual representations)
*Communication Tools (email drafting, multilingual communication)
*Research and Insight Generation (credible information sourcing)

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Artificial Intelligence (AI) Engineering is a rapidly growing field focused on developing innovative AI solutions that enhance business operations and decision-making processes. With the increasing demand for AI professionals, key skills in AI Engineering include machine learning, data science, and natural language processing (NLP). Our comprehensive, hands-on AI Engineering courses and training cover essential topics such as data preprocessing, model training, and ethical AI practices. By gaining practical experience in building and managing real-world AI applications, you'll be well-prepared for a rewarding career in this transformative industry. Explore our courses today to unlock your potential in AI Engineering!

Artificial Intelligence Engineering

WLANS
*Define a SSIDs, BSSIDs, and their functions
*Review additional WLAN configuration options
*Explain WLAN security options and how they are configured in a Juniper Mist WLAN configuration object
*Describe data rates and how they are configured in Juniper Mist
*Explain SSID strategies for multiband deployments


Juniper Mist Edge
*Define the features and benefits
*Identify popular use cases
*Categorize the product options
*Summarize the installation
*Review the Edge management
*Troubleshoot the device and connectivity

Guest Portals
*Describe the Juniper Mist guest options

Juniper Mist WxLAN Policies
*Explain WLAN policies and how they are configured


Juniper Mist Wi-Fi Security
*Describe WLAN security threats detected by the Juniper Mist WLAN system

Juniper Mist Service-Level Expectations
*List Wi-Fi Assurance SLEs and their classifiers

Juniper Mist Events and Insights
*Describe site, AP, and client events
*Explain the packet capture functionality of the Juniper Mist system
*Describe the 802.11 MAC header and list 802.11 MAC frame types

Juniper Mist Dashboard and Reports
*Explain custom dashboard and report options

Juniper Mist Artificial Intelligence and Troubleshooting Options
*Assess Juniper Mist's application of artificial intelligence
*Describe the reactive and proactive troubleshooting methodologies

Marvis Queries
*Explain the difference between Marvis natural language and Marvis query language

Wi-Fi Standards
*Describe the purpose of the 802.11 standard and its physical later amendments

Wi-Fi Radio Frequency Bands
*Describe the 2.4-GHz, 5-GHz, and 6-GHz frequency bands used for WLANs and their channels

Applying Radio Frequency Basics to Wi-Fi
*Describe the properties of an RF wave
*Convert dBm to Milliwatts using RF math
*Explain factors that contribute to RF signals and how they relate to WLANS

Modulation and Coding for Wireless Networks
*Explain RF modulation and how it relates to WLAN data rates
*Describe the relationship between SNR and MCS

Understanding Client Association and Roaming
*Describe the 802.11 state machine and steps required for an 802.11 station to connect to an access point
*Explain the protocols used in a client's connection to the network

Network Contention Factors
*Describe 802.11 contention

Wi-Fi Architectures and Life Cycle
*Differentiate WLAN architectures
*Describe the stages of the WLAN life cycle

Getting Started with Juniper Mist
*Examine the Juniper Mist architecture
*Create a Juniper Mist account
*Summarize Juniper Mist subscriptions
*Summarize the MSP dashboard

Juniper Mist Configuration Objects
*Explain the difference between organization-level and site-level configuration objects
*Define Juniper Mist configuration objects and their uses

Juniper Access Points
*Summarize access points and connectivity
*Describe the boot procedure for a Juniper Access Point, its requirements, and the process of adding a Juniper Access Point to the Juniper Mist cloud
*Describe common AP configuration settings
*Use the Juniper Access Points dashboard to get information about an Access Point

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Instructor-led Practical Oriented Training

*Validating Job Definitions
*Promoting Jobs to Production Environment
*Scheduling Approvals and Audit Trails
*Assessment: Scenario-Based Exercises + Practical Evaluation

*Control-M Job Lifecycle
*Creating and Editing Job Definitions
*Understanding Calendars, Tables, and Folders
*Setting up Dependencies and Conditions

*Viewing and Filtering Active Jobs
*Monitoring Job Status, Dependencies, and Conditions
*Handling Job Failures and Reruns
*Managing Job Outputs and Logs
*Working with Alerts

*Detailed Overview of Control-M/Enterprise Manager
*Control-M/Server and Control-M/Agent Architecture
*Communication and Configuration

*Installing and Configuring Control-M Components
*User & Security Management
*Defining Data Centers and Nodes

*Batch Flow Design Best Practices
*Utilizing Control-M Workload Policy
*Analyzing Workload Impact

*Viewing Logs and Alerts
*Generating Basic Reports
*Basic Troubleshooting Techniques
*Assessment: Hands-on Lab + Quiz

*Performing Manual Job Actions (Hold, Rerun, Force, Delete, etc.)
*Using the Monitoring Domain effectively
*Understanding Job Flow Visualization
*Incident Handling Best Practices

*Overview of Workload Automation
*Control-M Architecture and Components
*Understanding the Control-M GUI and Interfaces
*Role of an Operator

*Control-M Logs and Diagnostic Tools
*Handling Performance and Resource Issues
*Backup and Recovery Procedures
*Version Management and Upgrades

*Integrating Control-M with Other Tools (e.g., ServiceNow, SAP, AWS)
*Control-M Automation API Overview
*Using Control-M Self Service Portal

*Managing High Availability and Failover
*Configuring Alerts and Notifications
*Security and Audit Controls
*Assessment: Hands-On Lab + Final Evaluation

*Scheduling by Time, Event, or Dependency
*Managing Smart Tables and Groups
*Creating Cyclic and Repetitive Jobs
*Working with Variables and Parameters

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BMC Control-M Certification Training | Workload Automation

*Models: Understanding the difference between LLMs and ChatModels and how to integrate various providers (e.g., OpenAI, Anthropic, open-source models via Ollama).
*Prompts: Mastering PromptTemplates for creating reusable, secure, and effective prompts.
*Output Parsers: A critical component for architects. Learn how to enforce schemas and structure LLM responses into reliable data formats (like JSON or Pydantic models) to ensure clean data contracts within a larger system.
*LCEL (LangChain Expression Language): A deep dive into the | (pipe) syntax for building declarative, streamable, and batch-able data flows.
*Hands-on Lab 1: Building a Production-Ready RAG Pipeline

*The ReAct Framework: Deconstruct the core Reason-Act loop that gives an agent its autonomy.
*Tools: Define an agent's capabilities. We will cover how to create custom tools and, most importantly, how to write effective tool descriptions so the LLM can reason about their use.
*Agent Executor: Understand the runtime that orchestrates the agent's interaction with its tools.
*Observability with LangSmith: Introduce LangSmith as an essential tool for debugging and tracing an agent's "thought process." Discuss why this is non-negotiable for production systems.
*Hands-on Lab 2: Building a Research Assistant Agent

*State: The central, persistent memory of the graph. We will explore different ways to model state.
*Nodes: The functions or actions that manipulate the state.
*Edges: The directed connections between nodes, with a focus on Conditional Edges, which enable routing, loops, and complex logic.
*Hands-on Lab 3: Refactoring an Agent into a LangGraph

*Problem Statement: Discuss the architectural limitations of a basic AgentExecutor. When do you need loops, conditional branching, human-in- the-loop validation, or multi-agent collaboration?
*Conceptual Introduction to LangGraph: Position LangGraph as a library for building robust agentic state machines. It provides the control and flexibility needed for enterprise-grade workflows.

*The Architect's Choice: A detailed discussion on when to use which framework.
*CrewAI: Ideal for rapid prototyping and use cases that fit a collaborative, role-playing model.
*LangGraph: The choice for ultimate control, complex custom state, fine-grained logic, and integrating human-in-the-loop workflows.
*Hands-on Lab 5: Building a Research Team with CrewAI

*Concept: Moving beyond single-shot LLM calls to Agentic AI—systems that can perceive, reason, plan, and act to achieve a goal.
*Architectural Discussion: Contrasting traditional software architectures with agentic architectures. We will cover key challenges such as non-
determinism, state management, security, and observability.
*Introduction to LangChain: Positioning LangChain as a foundational framework for composing LLM applications.

*Whiteboarding Session: Design a holistic, production-grade architecture for an agentic application.
*Key Components & Concerns:
*API Layer & Task Ingestion: How users interact with the system (e.g., FastAPI, message queues like RabbitMQ or Kafka for async jobs). 
*Orchestration Service: The containerized LangGraph/CrewAI runtime. Discuss scaling strategies.
*State Management: The critical choice between in-memory, Redis, or a relational database for managing graph state, especially for long- running agents.
*Secure Tool Execution: A deep dive into security. Discuss sandboxing tool execution using Docker, WebAssembly (WASM), or serverless functions to mitigate risks.
*Evaluation & Monitoring: How do you test and monitor a non-deterministic system? Introduce evaluation frameworks (e.g., RAGAs) and the concept of a "golden dataset" for regression testing.
*Capstone Project: Design & Build
*Final Wrap-up, Future Trends & Q&A

*Introduction: Position CrewAI as an opinionated, higher-level framework for orchestrating role-playing autonomous agents.
*Core Abstractions: 
*Agents: Defined by role, goal, backstory, and tools.
*Tasks: The specific, descriptive assignments for each agent.
*Crews & Processes: How agents collaborate, focusing on Sequential and Hierarchical processes.

*Multi-Agent Collaboration: Design systems using the Agent Supervisor pattern, where one node acts as a manager that delegates tasks to specialized worker agents (other nodes or sub-graphs).
*Human-in-the-Loop: A critical pattern for safety and validation. Learn how to implement checkpoints in a graph where execution pauses and awaits human input or approval.
*Self-Correction Loops: Build graphs where one agent node critiques or reflects on the output of another, forcing a revision cycle until a quality threshold is met.
*Hands-on Lab 4: Building a Multi-Agent "Plan and Execute" Graph

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*RESTful APIs and JSON
*Authentication and authorization
*Caching and performance optimization
*Testing and debugging

*Basic syntax and data types
*Control structures and loops
*Classes, objects, and modules
*Error handling and exceptions

*MVC architecture
*Routing and controllers
*Models and database interaction
*Views and templates

*Build a complete web application using Rails

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*Setting Up Rational Rhapsody 
*Step-by-step guidance on installation and configuration.

*UML Basics
*Use Case (UC) Diagram
*Activity Diagram
*Class Diagram
*Sequence Diagram
*State Chart Diagram

*Hands-On Exercises
*Exercise 1: Hello World – Build a simple model to understand core concepts.
*Exercise 2: Count Down – Implement a countdown system to explore functionality.

*Understanding Properties 
*Learn how to configure and utilize properties in Rhapsody.

*Practical Applications
*Exercise 3: Dishwasher – Model a basic dishwasher system.
*Exercise 4: Dishwasher System – Expand the model to include system-level interactions.

*Essential Prerequisites 
*Overview of required knowledge and tools for the course.

*Course Agenda 
*Detailed breakdown of the training schedule and objectives.




*Requirements Analysis and Traceability 
*Techniques to capture and trace system requirements.

*Defining Functional Flow 
*Use activity diagrams to map system processes.

*Use Case Scenarios 
*Develop scenarios to define system interactions.

*System Modeling
*Modeling ports and interfaces.
*Modeling system behavior using state machines.

*Model Animation and Validation
*State-Chart animation.
*Animated Sequence and State Chart execution.


*Verification and validation through model execution.

*Architectural Integration
*Merging functional models into an architectural framework.
*Allocating functions to structural components.
*Hand-off of a subsystem to another team or process.

*Reverse Engineering 
*Techniques to reconstruct models from existing code.

*Rational Rhapsody Framework Overview 
*Understand the underlying framework and its applications.

*Generating Reports 
*Create detailed reports for documentation and analysis.

*Testing with Rational Rhapsody TestConductor
*Introduction to TestConductor for automated testing.
*Practical testing workflows.

*Triggered Operations 
*Explore advanced operations triggered by system events.

*Configuration Management Basics 
*Introduction to version control and model management.

*Advanced Exercises
*Stopwatch Exercise – Build and test a stopwatch model.
*Speed Camera Exercise – Model and simulate a speed camera system.

*Best Practices
*Useful tips for efficient modeling.
*Avoiding common mistakes in Rational Rhapsody.

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*Scaffolding
*The Meadowlark Travel Website
*Initial Steps
*Views and Layouts
*Static Files and Views
*Dynamic Content in Views
*Getting Organized
*File and Directory Structure
*Best Practices Version Control npm Packages
*Project Metadata
*Node Modules

*Sending Client Data to the Server
*HTML Forms
*Encoding
*Different Approaches to Form Handling
*Form Handling with Express
*Using Fetch to Send Form Data
*File Uploads
*File Uploads with Fetch
*Improving File Upload UI

*Filesystem Persistence
*Cloud Persistence
*Database Persistence
*A Note on Performance
*Abstracting the Database Layer
*Setting Up MongoDB
*Mongoose
*Database Connections with Mongoose
*Creating Schemas and Models
*Seeding Initial Data
*Retrieving Data
*Adding Data
*PostgreSQL
*Adding Data
*Using a Database for Session Storage

*Performance Considerations
*Content Delivery Networks
*Designing for CDNs
*Server-Rendered Website
*Single-Page Applications
*Caching Static Assets
*Changing Your Static Content

*Execution Environments
*Environment-Specific Configuration
*Running Your Node Process
*Scaling Your Website
*Scaling Out with App Clusters
*Handling Uncaught Exceptions
*Scaling Out with Multiple Servers
*Monitoring Your Website
*Third-Party Uptime Monitors
*Stress Testing

*Choosing a Template Engine
*Pug: A Different Approach
*Handlebars Basics
*Comments
*Blocks
*Server-Side Templates
*Views and Layouts
*Using Layouts (or Not) in Express
*Sections
*Partials
*Perfecting Your Templates

*Social Media
*Social Media Plugins and Site Performance
*Searching for Tweets
*Rendering Tweets
*Geocoding
*Geocoding with Google
*Geocoding Your Data
*Displaying a Map
*Weather Data

*The QA Plan
*Is It Worth It?
*Logic Versus Presentation
*The Types of Tests
*Overview of QA Techniques
*Installing and Configuring Jest
*Unit Testing
*Mocking
*Refactoring the Application for Testability
*Writing Our First Test
*Test Maintenance
*Code Coverage
*Integration Testing
*Linting
*Continuous Integration

*The Principles of Maintenance
*Have a Longevity Plan
*Use Source Control
*Use an Issue Tracker
*Exercise Good Hygiene
*Don’t Procrastinate
*Do Routine QA Checks
*Monitor Analytics
*Optimize Performance
*Prioritize Lead Tracking
*Prevent “Invisible” Failures
*Code Reuse and Refactoring
*Private npm Registry
*Middleware

*HTTPS
*Generating Your Own Certificate
*Using a Free Certificate Authority
*Purchasing a Certificate
*Enabling HTTPS for Your Express App
*A Note on Ports
*HTTPS and Proxies
*Cross-Site Request Forgery
*Authentication
*Authentication Versus Authorization
*The Problem with Passwords
*Third-Party Authentication
*Storing Users in Your Database
*Authentication Versus Registration and the User Experience
*Passport
*Role-Based Authorization
*Adding Authentication Providers

*Externalizing Credentials
*Cookies in Express
*Examining Cookies
*Sessions
*Memory Stores
*Using Sessions
*Using Sessions to Implement Flash Messages
*What to Use Sessions For

*Routes and SEO
*Subdomains
*Route Handlers Are Middleware
*Route Paths and Regular Expressions
*Route Parameters
*Organizing Routes
*Declaring Routes in a Module
*Grouping Handlers Logically
*Automatically Rendering Views

*The Parts of a URL
*HTTP Request Methods
*Request Headers
*Response Headers
*Internet Media Types
*Request Body
*The Request Object
*The Response Object
*Getting More Information
*Boiling It Down
*Rendering Content
*Processing Forms
*Providing an API

*The JavaScript Revolution
*Introducing Express
*Server-Side and Client-Side Applications
*A Brief History of Express
*Node: A New Kind of Web Server
*The Node Ecosystem

*Middleware Principles
*Middleware Examples
*Common Middleware
*Third-Party Middleware

*A Short History of Web Application Development
*SPA Technologies
*Creating a React App
*React Basics
*The Home Page
*Routing
*Vacations Page—Visual Design
*Vacations Page—Server Integration Sending Information to the Server State Management
*Deployment Options

*The First Principle of Debugging
*Take Advantage of REPL and the Console
*Using Node’s Built-in Debugger
*Node Inspector Clients
*Debugging Asynchronous Functions
*Debugging Express

*JSON and XML
*Our API
*API Error Reporting
*Cross-Origin Resource Sharing
*Our Tests
*Using Express to Provide an API

*SMTP, MSAs, and MTAs
*Receiving Email
*Email Headers
*Email Formats
*HTML Email
*Nodemailer
*Sending Mail
*Sending Mail to Multiple Recipients
*Better Options for Bulk Email
*Sending HTML Email
*Images in HTML Email
*Using Views to Send HTML Email
*Encapsulating Email Functionality

*Domain Registration and Hosting
*Domain Name System
*Security
*Top-Level Domains
*Subdomains
*Nameservers
*Hosting
*Deployment

*Using the Terminal Editors npm
*Simple Web Server with Node
*Hello World
*Event-Driven Programming
*Async data
*Routing
*Serving Static Resources
*Onward to Express

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*Review & Q&A (1 hour): Clarifying content from Week 1.
*Implementation Challenges of MBSE (2 hours): Real-world challenges, Boeing case study.

*Modeling Behavior with SysML (1.5 hours): Activity, Sequence, and State Machine Diagrams for Smart Home Security System.
*Project Work Session 1 - Part A (1.5 hours): Initial hands-on modeling using open-source or conceptual tools.

*Project Session 2B: Final Feedback
*Action Plan Creation

*Integrating MBSE into System Lifecycle
*Agile + MBSE, MBSE Tooling Ecosystem
*Project Session 2A: Critique Application

*Project Work Session 1 - Part B (2 hours): Refining behavioral models with instructor guidance.
*Graded Activity / Self-Assessment (1 hour): Quiz or exercise for concept reinforcement.

*Continued Traceability (1 hour): Automated linking between requirements, activities, and test cases.
*Introduction to SysML (1 hour): Use Case, Block Definition, Activity, and other diagrams; ATM example.
*Modeling Structure with SysML (1.5 hours): BDD and IBD using a Smart Home Security System example.

*Welcome & Course Kick-off (30 min): Course navigation, collaboration tools, learning objectives, and setting expectations.
*MBSE: Beyond Documents (1 hour): Key concepts, SE vs. MBSE, MBSE benefits and use cases.
*Qualities of Excellent Models & Scoping (1 hour): Attributes like accuracy, clarity, completeness; example of drone system.
*Models as Data Repositories & Traceability (1 hour): Models as queryable data sources; safety-critical function traceability example.

*Key Takeaways
*Post-Assessment & Survey
*Flexible Deep Dive or 1:1 Consultations

*Ask the Professor
*Model Management Plans & Defined Roles
*MBSE Design Patterns

*Performing an MBSE Critique (2 hours): Critique frameworks and walkthroughs.
*Current Debates & Future Trends (1 hour): Digital Twins, AI/ML in MBSE, interoperability.

Master Model-Based Systems Engineering (MBSE) with DevLabs Alliance. Learn SysML modeling, system design, simulation, and requirements management with hands-on training and certification.

Model-Based Systems Engineering (MBSE) Training

*What are Abstract Classes?
*What are Interfaces?
*Difference between an Abstract Class and Interface

*What are Enums?
*Operators in Java
*Modifiers-File Level, Access level and Non-access level
*Data Types, Variables, Literals, Type Conversion, Casting
*Control Statements in Java
*Method and Types of methods
*Variables and Types of Variables
*Constructors and Types of Constructors

*Introduction to Thread
*How to create and start a Thread
*Sleep Thread
*Synchronization in Threads

*Arrays
*Multi-Dimensional Arrays
*Sorting and Searching Arrays
*For-Each

*What is Generic List
*What is Generic Map in Java
*Generic Classes & Methods in Java
*For loop Generic
*Generic Wild Card

*What are Collections?
*List
*Set
*Queue
*Priority Queue
*Maps
*Hashmap

*What are Annotations?
*Why annotations are used
*Built-in Java Annotations
*Custom Annotations
*Placements in Annotations

*String Operations and Operators
*String Objects
*Passing by Value
*Immutable Strings

*What is Java?
*Editions and Versions of Java
*Java History
*Installing Java, JDK and JVM
*IDE-Eclipse
*Writing your first java program

*What is Exception?
*Types of Exception
*Throw, Throws and Throwable
*Creating Exception
*try-catch block
*Finally block

*Encapsulations
*Access Modifiers
*What is Inheritance?
*Method Overloading
*Method Overriding
*Difference between Method Overloading and Method Overriding
*What is Polymorphism?
*Benefits of Polymorphism
*Run-time and Compile-time Polymorphism

*What is Object-Oriented Programming?
*Instantiating Objects
*Using Objects
*Creating Object Types
*Default Constructors
*Building Constructors
*What is Class?
*What is Object?
*Class vs Object
*Static Variables
* Static Method
*“this” keyword
*Garbage Collection
*Java Memory Leaks
*Java Packages
*Java Classpath

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Oracle Certified Associate, Java SE 8 Program

*Lists, tuples, dictionaries, and sets
*Indexing, slicing, and built-in methods

*Defining and calling functions
*Function arguments and return values
*Creating and importing modules

*Conditional statements (if, elif, else)
*Loops (for, while)
*Loop control (break, continue, pass)

*Types of errors
*Try, except blocks
*Raising and handling exceptions

*Debugging techniques
*Writing simple test cases

*Reading from and writing to files
*Working with different file formats

*Mini projects to apply concepts
*Practice tests for certification readiness

*History and features
*Setting up the environment
*Writing your first Python program

*Numbers, strings, lists, tuples, sets, dictionaries
*Type conversion and input/output

*math, datetime, random, etc.
*Working with external libraries (intro)

*Classes and objects
*Attributes and methods
*Inheritance and encapsulation

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*Networking
*OSI Layers
*Various Protocols of Networking in Linux
*Linux Firewall

*Kernel Configuration
*Boot Management
*Grub Bootloader configurations
*Red Hat Package Manager
*Libraries

*Linux Installations
*Packages
*Architecture
*File System
*User Management
*Scripting Data

*Linux Security Administration
*Shell Scripting
*Securing Shell
*Hands on

*Process Management
*System Calls
*Bash Operations
*Expect Script
*Python Scripting

*Users in Linux
*User Configuration
*Group Administration
*Sudo
*Default File Permissions
*Access control Lists (ACLs)
*Hands on

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Software development is a multifaceted journey that demands meticulous planning, creative design, expert coding, rigorous testing, and ongoing maintenance. It's a dynamic process that aims to deliver websites that not only meet but exceed user expectations, making it an indispensable component of today's digital landscape.

Software Development

*Understanding the company’s guiding principles
*Key components of the Code of Conduct
*Demonstrating integrity, fairness, and respect in day-to-day roles

*Meaning and significance of ethical behavior
*How ethics influences organizational culture and credibility
*Simple examples of right and wrong choices at work

*Ethical behavior in communication, teamwork, and operations
*Respectful workplace conduct and data handling
*Building good habits that promote ethical culture

*Essentials of global ethical frameworks
*Responsible business guidelines followed worldwide
*Overview of recognized standards related to governance and anti-corruption

*Summary of key learnings
*Open interaction and clarification round
*Employee affirmation: Ethical Responsibility Pledge

*Major Indian laws relevant to ethical behavior at the workplace
*Responsibilities of employees under corporate and labor regulations
*Importance of legal compliance for white-collar and blue-collar roles

*Identifying ethically confusing situations
*Group activities: scenario-based discussions
*Decision-making tools to choose the right course of action

*How employees can report unethical practices
*Confidentiality, protection, and non-retaliation guidelines
*Why timely reporting strengthens the organization

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*About Excel
*Explore the User Interface
*Work with the Ribbon
*Work with Contextual Tabs
*Paste Special Preview
*Excel Options
*Auto fill
*Customize the Excel Interface

*Benefits And Purpose
*Every day Functions Conditional Function (SUM, MAX, COUNTA, COUNTIF, SUMIF...)
*Writing conditional expressions (using IF)
*Using logical functions (AND, OR, NOT)
*Work with Array Function
*Work with Rank function

*Setting up rules for conditional formats
*Clearing the conditional formats
*Writing formulas in conditional formatting
*Manage Rules

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In today’s competitive workplace, technical expertise alone is not enough. Organizations seek professionals who can lead, collaborate, and communicate effectively. DevLabs Alliance’s Soft Skills Training Programs are designed to help you master critical interpersonal and professional skills that boost career growth and organizational success.

What is Nagios?

What is Nagios?

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“ The hands-on projects helped our team put theory into practice. Thanks to this training, we've achieved seamless collaboration, faster releases, and a more resilient infrastructure. ”