Mastering GCP Architecture

Inquire now

Duration: 5 days – 35 hrs

 

Overview

The Mastering GCP Architecture Training Course is an advanced program designed for experienced IT professionals and cloud practitioners aiming to deepen their expertise in designing, implementing, and managing complex, scalable, and secure solutions on Google Cloud Platform (GCP). This course covers advanced architectural patterns, GCP services, and best practices for building resilient and optimized cloud architectures. Through in-depth lectures, hands-on labs, and real-world scenarios, participants will gain the skills needed to tackle sophisticated cloud challenges and achieve excellence in GCP architecture.

 

Objectives

• Advanced Architectural Patterns: Master advanced design patterns and best practices for building complex solutions on GCP.
• Scalable and Resilient Architectures: Learn how to design highly available, fault-tolerant, and scalable architectures using advanced GCP services.
• Advanced Security Practices: Deep dive into advanced security features and strategies to protect GCP environments.
• Cost Optimization Techniques: Explore advanced techniques for managing and optimizing costs while maintaining performance and reliability.
• Performance Tuning and Monitoring: Gain expertise in optimizing and monitoring GCP services for peak performance.
• Hybrid and Multi-Cloud Architectures: Understand how to design and implement hybrid and multi-cloud architectures using GCP and other cloud platforms.

 

Audience

• Experienced GCP Solutions Architects: Professionals with foundational knowledge and experience in designing and implementing solutions on Google Cloud Platform (GCP).
• Senior IT Professionals: IT leaders and engineers with significant experience in cloud computing and infrastructure design.
• DevOps Engineers: Individuals responsible for managing and optimizing complex GCP environments and implementing advanced DevOps practices.
• System Architects: Architects designing large-scale, resilient, and highly available systems on GCP.
• Cloud Engineers: Engineers focused on advanced cloud infrastructure who need to master GCP services and architecture.
• Security Engineers: Security experts looking to enhance their understanding of advanced security features and best practices on GCP.
• Network Architects: Professionals specializing in network design and management within GCP and hybrid/multi-cloud environments.
• Technical Leads and Managers: Leaders overseeing cloud projects who need to understand and implement advanced architectural principles and practices.
• IT Consultants: Consultants advising clients on cloud adoption and architecture who need in-depth knowledge of GCP.
• Candidates for GCP Certification: Individuals preparing for the Google Cloud Professional Cloud Architect certification and seeking advanced skills in GCP architecture.

 

Prerequisites

• Prior GCP Experience: Significant hands-on experience with Google Cloud Platform (GCP) services and solutions.
• Knowledge of Core GCP Services: Strong understanding of key GCP services, including Compute Engine, Cloud Storage, Networking, and BigQuery.
• GCP Professional Cloud Architect Certification: Recommended but not required.
• Experience in Designing and Implementing GCP Solutions: Practical experience in creating scalable, secure, and resilient architectures on GCP.

 

Course Content

Section 1: Designing and Planning Cloud Solution Architecture

• Advanced Design Scenarios: Addressing complex business and technical requirements.
• Cost Optimization Techniques: Detailed strategies for minimizing costs while maximizing efficiency.
• Integration with External Systems: Designing hybrid and multicloud architectures.
• Data Movement Strategies: Advanced techniques for efficient data transfer and processing.
• Migration and Future Planning: Creating detailed migration plans and preparing for future improvements.

 

Section 2: Managing and Provisioning Solution Infrastructure

• Advanced Network Configurations: Hybrid connectivity, optimizing network topologies.
• Complex Storage Systems: Data lifecycle management, advanced data storage strategies.
• Sophisticated Compute Provisioning: Handling volatile compute needs, using preemptible VMs, and custom machine types.

 

Section 3: Designing for Security and Compliance

• In-depth Security Architectures: Detailed IAM configurations, and advanced data security (encryption, key management).
• Compliance Deep Dive: Navigating complex compliance requirements, and designing for industry-specific legislation.

 

Section 4: Analyzing and Optimizing Technical and Business Processes

• Technical Process Optimization: Implementing SDLC, CI/CD, and testing/validation best practices.
• Business Process Management: Change management, stakeholder management, and decision-making processes.
• Ensuring Reliability: Developing procedures like chaos engineering and penetration testing.

 

Section 5: Managing Implementation

• Deployment Strategies: Advanced deployment techniques, using Google Cloud SDK and Cloud Emulators.
• Programmatic Interactions: Scripting and automating tasks with gcloud, gsutil, and bq.

 

Section 6: Ensuring Solution and Operations Reliability

• Comprehensive Monitoring and Logging: Setting up sophisticated monitoring and logging for high availability.
• Release and Deployment Management: Best practices for smooth rollouts and updates.
• Support and Quality Control: Evaluating and improving the quality of deployed solutions.

 

Capstone Projects and Case Studies

• Complex Application Deployment: Designing and deploying a scalable and secure multi-tier web application using GCP services.
• Hybrid and Multicloud Integration: Setting up a hybrid cloud environment that integrates seamlessly with on-premises infrastructure.
• Data Intensive Application Design: Building and deploying a data-heavy application leveraging BigQuery, Dataflow, and AI Platform.

 

Inquire now

Best selling courses

The Data Analytics with DAX, Python, SQL, and Business Intelligence Tools Training Course provides participants with practical knowledge and skills for collecting, preparing, analyzing, modeling, and visualizing data to support informed business decision-making. The course combines key data analytics technologies and techniques, including Python, SQL, DAX (Data Analysis Expressions), Power BI, data modeling, data transformation,...

The Project Management – SDLC (Software Project Management: The Complete Course) Training Course is a comprehensive program designed to equip project managers, software development leaders, business analysts, product owners, and IT professionals with the knowledge and practical skills required to successfully manage software development projects throughout the entire Software Development Life Cycle (SDLC). This course...

Warehouse Operations and Inventory Management Training Course     Duration 2 Days – 14 hrs.   Overview   This course provides a practical understanding of warehouse operations and inventory management for personnel who supervise, review, or audit warehouse processes. It covers the movement of goods from receiving through dispatch, with emphasis on warehouse layout, storage systems, picking strategies, stock rotation, inventory accuracy, and operational controls.   Participants will learn to identify process weaknesses, investigate stock discrepancies, reduce shrinkage, and interpret warehouse productivity indicators. The course connects day-to-day warehouse activities with the records, controls, and performance measures needed for effective supervision and auditing.   Objectives  

  • Explain warehouse processes and their impact on inventory accuracy and service performance.
  • Evaluate warehouse layouts, storage systems, and product locations.
  • Identify appropriate controls for receiving, put-away, storage, picking, and dispatch.
  • Apply First-In, First-Out (FIFO) and First-Expired, First-Out (FEFO) principles.
  • Compare picking strategies based on order characteristics and operational requirements.
  • Identify causes of inventory discrepancies and recommend corrective actions.
  • Develop a cycle counting approach based on inventory value, movement, and risk.
  • Recognize sources of shrinkage and recommend preventive and detective controls.
  • Interpret warehouse productivity and inventory performance KPIs.
  • Review warehouse processes using supporting records, observations, and control evidence.
        Target Audience  
  • Warehouse supervisors, team leaders, and managers.
  • Inventory controllers and stock control personnel.
  • Logistics and distribution supervisors.
  • Internal auditors and operational compliance personnel.
  • Supply chain and operations professionals.
  • Personnel responsible for reviewing warehouse controls and performance.
  Prerequisites  
  • Basic familiarity with warehouse, logistics, or inventory activities.
  • General understanding of business processes and operational documentation.
  • Basic numerical skills, including percentages and simple calculations.
  • Basic spreadsheet skills are helpful.
  • No prior experience with a specific Warehouse Management System (WMS) is required.
   

Course Outline

  Day 1: Warehouse Processes, Layout, and Storage Controls Module 1: Warehouse Operations and Process Controls  
  • Warehouse roles within the supply chain.
  • End-to-end flow: receiving, put-away, storage, replenishment, picking, packing, and dispatch.
  • Physical stock movement and corresponding system transactions.
  • Responsibilities, authorization, and segregation of duties.
  • Common operational weaknesses and audit evidence.
  Module 2: Warehouse Layout and Storage Systems  
  • Functional zones, movement paths, and space utilization.
  • Receiving, storage, picking, staging, and dispatch areas.
  • Storage options: floor stacking, shelving, pallet racking, and bin storage.
  • Fixed and dynamic location systems.
  • Product slotting based on movement, size, handling needs, and compatibility.
  • Layout bottlenecks and their effects on productivity and inventory control.
  Module 3: Receiving and Put-Away  
  • Purchase orders, delivery documents, and expected receipts.
  • Quantity, condition, and item identification checks.
  • Recording shortages, overages, damage, and discrepancies.
  • Controls for acceptance, quarantine, and release.
  • Put-away rules and location confirmation.
  • Traceability through labels, barcodes, lot numbers, and serial numbers.
  • Timely recording of receipts and stock movements.
  Module 4: Storage, Stock Rotation, and Replenishment  
  • Storage discipline and location integrity.
  • FIFO and FEFO principles, applications, and limitations.
  • Batch, lot, and expiry-date management.
  • Controls for slow-moving, obsolete, damaged, and expired stock.
  • Replenishment of picking locations.
  • Supervision and review of stock rotation compliance.
    Day 2: Order Fulfillment and Inventory Accuracy Module 5: Picking Strategies and Order Fulfillment  
  • Discrete, batch, zone, and wave picking.
  • Selecting picking strategies for different order profiles.
  • Pick paths, location sequencing, and travel reduction.
  • Replenishment coordination and stock availability.
  • Picking verification and error prevention.
  • Packing, staging, and dispatch confirmation.
  • Handling short picks, substitutions, cancellations, and returns.
  Module 6: Inventory Records and Accuracy Controls  
  • Item master data, units of measure, and location records.
  • On-hand, available, allocated, and quarantined stock.
  • Transaction controls for receipts, transfers, issues, returns, and adjustments.
  • Common causes of physical and system stock mismatches.
  • Barcode scanning and WMS control points.
  • Inventory reconciliation and supporting documentation.
  • Measuring inventory accuracy and interpreting discrepancies.
  Module 7: Cycle Counting and Physical Inventory  
  • Cycle counting versus full physical inventory.
  • ABC classification and risk-based count priorities.
  • Count frequency based on value, movement, and discrepancy history.
  • Count preparation, blind counting, and movement controls.
  • Recounts, variance investigation, and adjustment approval.
  • Root cause analysis and corrective action follow-up.
  • Reviewing the effectiveness of the counting program.
  Module 8: Shrinkage Reduction and Inventory Protection  
  • Sources of shrinkage: loss, damage, theft, misplacement, and recording errors.
  • Access controls and accountability for stock movements.
  • Controls for high-value and sensitive inventory.
  • Returns, write-offs, scrap, and disposal controls.
  • Exception reporting and unusual transaction patterns.
  • Investigating recurring losses and unexplained adjustments.
  • Preventive and detective controls for shrinkage reduction.
    Day 3: Performance Management, Process Review, and Improvement Module 9: Warehouse Productivity and Inventory KPIs  
  • Receiving productivity and dock-to-stock time.
  • Put-away productivity and replenishment performance.
  • Picking productivity and order accuracy.
  • Inventory accuracy and cycle count variance.
  • Space utilization and storage capacity.
  • Shrinkage, damage, and expiry indicators.
  • Defining KPI formulas, data sources, and reporting boundaries.
  • Interpreting trends while balancing speed, accuracy, and service.
      Module 10: Supervising and Auditing Warehouse Processes  
  • Process mapping and identification of critical control points.
  • Reviewing procedures against actual warehouse practices.
  • Tracing transactions from documents to systems and physical stock.
  • Reviewing approvals, access rights, and segregation of duties.
  • Identifying control gaps and recurring process exceptions.
  • Documenting findings with clear supporting evidence.
  • Prioritizing corrective actions and tracking closure.
  Module 11: Warehouse Improvement Planning  
  • Identifying bottlenecks, unnecessary movement, and rework.
  • Improving layout, slotting, and picking arrangements.
  • Addressing inventory discrepancy root causes.
  • Standardizing transaction recording and exception handling.
  • Assigning improvement owners and measurable targets.
  • Monitoring results and sustaining operational improvements.
  Module 12: Capstone — Warehouse Operations and Inventory Improvement Plan  
  • Review a warehouse scenario containing layout, transaction, inventory, and performance information.
  • Identify weaknesses across receiving, put-away, storage, picking, and dispatch.
  • Recommend appropriate FIFO or FEFO controls.
  • Develop a cycle counting and inventory reconciliation plan.
  • Propose controls to reduce shrinkage and improve traceability.
  • Select relevant KPIs and define their calculation and reporting requirements.
  • Produce a prioritized improvement plan with responsibilities and expected outcomes.
 

This course develops the foundational knowledge and practical skills needed to configure, administer, and maintain the ServiceNow platform. Participants explore platform navigation, instance configuration, application collaboration, self-service, automation, database management, security, and configuration migration. The proposed five-day duration accommodates foundational learning, configuration activities, and an integrated capstone. Duration 5 Days – 35 hrs.   Objectives...

Duration: 5 days – 35 hrs   Overview The “SOC Network and Threat Detection and Analysis” training course is designed to equip Security Operations Center (SOC) analysts and IT security professionals with the skills and knowledge required to detect, analyze, and respond to network threats effectively. This comprehensive course covers essential topics such as threat...

Duration 1 day – 7 hrs   Overview   This 1-day training builds upon basic warehouse operations knowledge and introduces key logistics concepts involved in the movement and coordination of goods—especially wet and dry food items—within and outside the warehouse. Participants will explore transport logistics, inbound and outbound coordination, documentation practices, and cold chain considerations,...

Duration 2 days – 14 hrs   Overview   This hands-on course provides an introduction to Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data. The training focuses on how developers and QA professionals can leverage Splunk to gain insights from logs and metrics, improve application observability, detect anomalies, and support test validation....

Duration 3 days – 21 hrs   Overview.   This course is designed for fresh graduates aspiring to build a career in Data Science. It introduces the fundamentals of data science, focusing on data analysis, visualization, and basic machine learning concepts using Python. The course provides hands-on practice with real-world datasets, equipping participants with the...

// BG EARTH WHEN NOT PLAYING

We use cookies on our website to personalize your experience by storing your preferences and recognizing repeat visits. By clicking “Accept”, you agree to the use of all cookies. You can also select “Cookie Settings” to adjust your preferences and provide more specific consent. Cookie Policy