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Rahul Patel

This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate the knowledge for managing Platform as a Service (PaaS) in the Cloud. Students will learn to deploy, operate, and maintain cloud platforms for storing, processing, and transferring information with architecture design principles and a structured approach. Students will also learn the shared responsibility model and cloud security best practices to secure PaaS platforms for the application-hosting environments.

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What's inside

Syllabus

Module 1: Introduction to Platform as a Service (PaaS)
Welcome to Introduction to Platform as a Service (PaaS)! In Module 1, we will define the PaaS and differentiate it from all other cloud services. We will also define scope and boundaries of platform as a service which will guide us for topics covered in rest of the modules of the course. The benefits of using PaaS and recognize the limitations are discussed in this module. Students will also compare, contrast, and understand the best fit for PaaS to help make informed decisions for selecting appropriate cloud implementation strategy. Students will explore various PaaS offerings from various vendors for making the best choice decisions for solving business problems. Finally, students will explore several ways to manage PaaS offering.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Introduces learners to fundamental concepts in PaaS, including its definition, scope, and how it differs from other cloud services
Explores various PaaS offerings from different vendors to aid in selecting the best solution for specific business needs
Provides insights into modern application design principles and structured approaches for storing, processing, and transferring information in cloud platforms
Focuses on the shared responsibility model and cloud security best practices for securing PaaS platforms
Covers key concepts related to containerization, including benefits, limitations, and best practices for managing containerized applications
Provides guidance on designing, implementing, and operating cloud platforms for high reliability, scalability, and performance

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Reviews summary

Foundational paas expertise for cloud careers

According to students, this course provides a comprehensive and practical foundation in Platform as a Service, equipping learners with essential skills for cloud careers. Students particularly commend its well-structured curriculum covering crucial aspects like containerization, serverless computing, and cloud security best practices. The course offers valuable hands-on experience with real-world examples, helping to solidify theoretical knowledge. While generally well-received, some learners suggest a prior understanding of cloud basics can enhance the learning experience, indicating it may be challenging for complete beginners due to its depth and pace.
Requires continuous learning beyond the course due to rapid changes.
"Given how fast cloud technology changes, I hope the course receives regular updates to stay current."
"The core principles are solid, but specific tools and platforms mentioned might evolve quickly."
"This course provides a great foundation, but I know I need to keep learning outside of it."
Directly applicable to professional cloud and DevOps roles.
"This course is highly relevant for anyone pursuing a career in cloud architecture or DevOps."
"I can immediately apply the concepts learned to my work in cloud operations."
"It filled crucial knowledge gaps for my professional development in PaaS management."
Integrates hands-on exercises and real-world application.
"The practical examples using Docker on AWS were incredibly helpful for understanding deployments."
"Creating a serverless function on AWS Lambda solidified my understanding of serverless platforms."
"I appreciated the focus on real-world development and deployment strategies."
Offers a wide-ranging exploration of core PaaS concepts.
"I found the course to be very comprehensive, touching upon containers, serverless, and even ML platforms."
"The syllabus provided a solid overview of key PaaS services and how they fit together."
"It really broadened my understanding of the PaaS ecosystem from security to operational maturity."
Assumes some prior technical knowledge, challenging for novices.
"While providing a strong foundation, I'd recommend some prior cloud exposure to fully benefit."
"The pace was quite fast, especially for someone new to many of these advanced concepts, requiring extra study."
"I needed to do additional research on certain topics to keep up, but the effort was rewarding."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Cloud: Platform as a Service - Bachelor's with these activities:
Review containerization concepts
Refresh your understanding of containerization to enhance your grasp of PaaS platforms.
Browse courses on Containerization
Show steps
  • Review key containerization concepts
  • Practice using containerization tools
Participate in peer discussion forums
Engage with fellow learners to share insights, ask questions, and consolidate your understanding.
Show steps
  • Identify relevant discussion forums
  • Pose thoughtful questions
  • Engage in discussions
  • Summarize key takeaways
Practice managing PaaS platforms
Reinforce your understanding of PaaS platform management by completing practice drills and exercises.
Show steps
  • Review PaaS management concepts
  • Configure and manage PaaS platforms
  • Monitor and troubleshoot PaaS platforms
Show all three activities

Career center

Learners who complete Cloud: Platform as a Service - Bachelor's will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Cloud: Platform as a Service - Bachelor's.
The premier applied machine learning masterwork, taking practitioners through intuitive concept breakdowns, production-grade Scikit-Learn workflows, and deep neural architecture implementations.
A timeless mathematical masterpiece that provides an uncompromising Bayesian and probabilistic foundation for linear classifiers, graphical models, kernel methods, and sampling algorithms.
Is highly relevant for understanding contemporary database topics, particularly in the context of distributed systems, scalability, and various data storage technologies like NoSQL. It is excellent for professionals and advanced students looking to deepen their understanding of modern data systems and their trade-offs.
The definitive mathematical and theoretical canon of statistical learning, establishing the rigorous analytical foundations of regularized regression, tree ensembles, and high-dimensional inference.
Provides a comprehensive overview of building serverless applications specifically on the AWS platform. It covers key AWS services like Lambda, API Gateway, and Kinesis, offering practical insights and real-world use cases. It's valuable for understanding the practical application of serverless principles within a major cloud ecosystem and is suitable for those looking to implement serverless solutions on AWS.
Presents the results of a four-year study of high-performing technology organizations. It identifies the key factors that drive success, and it provides a roadmap for organizations that want to improve their performance.
La edición en español de este reconocido libro de texto ofrece una introducción completa a los conceptos fundamentales de los sistemas de bases de datos, cubriendo teoría y práctica. Es un recurso excelente para estudiantes de habla hispana que buscan una comprensión amplia y a menudo se utiliza como libro de texto principal en instituciones académicas.
A distilled practitioner field guide outlining best practices for the entire machine learning lifecycle, from problem formulation and feature engineering to model deployment and monitoring.
A recent publication focusing on leveraging AWS Lambda for building scalable and cost-effective serverless solutions. It covers basics to advanced deployment, including event-driven design, hyper-scaling, and operational techniques. is highly relevant for those specifically focused on AWS Lambda and seeking to deepen their expertise.
Delivers an end-to-end systems architecture guide for building reliable production ML systems, addressing data engineering trade-offs, real-time feature computation, and model drift mitigation.
Bridges linear algebra, multivariable calculus, vector geometry, and probability directly to fundamental machine learning algorithms like PCA, Gaussian mixture models, and support vector machines.
Provides the monumental mathematical foundation of modern neural networks, connecting deep representation learning, backpropagation dynamics, and sequence modeling to empirical machine learning.
Provides a comprehensive overview of scalability, covering the principles, patterns, and practices for designing and building systems that can handle increasing demands. It is an excellent resource for software engineers and architects who need to understand how to design and build scalable systems.
For those looking to deepen their understanding of how database systems function internally, this book provides a detailed exploration of topics like storage engines, indexing, and transaction processing in distributed systems. It is suitable for advanced students and professionals.
This handbook provides a step-by-step guide to implementing DevOps in your organization. It covers all aspects of DevOps, from planning to implementation to measurement, and it valuable resource for anyone looking to get started with DevOps.
This practical guide focuses on the implementation and management of Kubernetes, the leading container orchestration platform. It offers hands-on guidance on configuring, deploying, and scaling containerized applications with Kubernetes.
Offers a vendor-agnostic view of serverless computing, covering AWS, Azure, GCP, Kubernetes, and open-source options. It provides a broad understanding of the serverless landscape and helps in selecting appropriate technologies. It's a good resource for gaining a wider perspective beyond a single cloud provider.
Provides a deep dive into the technical aspects of cloud security. It covers topics such as cloud security architectures, security controls, and threat detection and response.
Instructs data scientists on applied model evaluation, cross-validation, hyperparameter tuning, and pipeline construction through Scikit-Learn maintainers Andreas Müller and Sarah Guido.
Provides a comprehensive overview of cloud security, covering everything from basic concepts to advanced topics such as threat detection and incident response. It is an excellent resource for anyone who wants to learn more about cloud security.
This handbook focuses on best practices and real-world applications of serverless architecture, particularly using the AWS Well-Architected Framework's Serverless Lens. It's designed for technology leaders and architects, offering insights into operational excellence, security, reliability, performance, cost optimization, and sustainability in a serverless context.
Investigates the engineering realities of running automated ML pipelines in production, addressing data drift detection, automated retraining loops, telemetry infrastructure, and continuous validation.
La edición en español de 'Database Design for Mere Mortals' ofrece una guía práctica y accesible para el diseño de bases de datos relacionales. Es ideal para principiantes y aquellos sin experiencia técnica previa, enfocándose en principios de diseño fundamentales con explicaciones claras y sin jerga.
Offers a practical and approachable guide to relational database design, suitable for beginners and those without a strong technical background. It focuses on fundamental design principles and provides clear, jargon-free explanations. It's a good starting point for understanding how to structure data effectively.
Details cloud-native DevOps architectures for orchestrating automated machine learning lifecycles, integrating CI/CD triggers, model registry synchronization, and automated hyperparameter sweep workers.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern models.
Focused on practical SQL usage and common mistakes, this book is valuable for anyone working with relational databases. It helps solidify understanding of effective database programming and design principles by highlighting what *not* to do. It's a great supplementary read for those learning or using SQL regularly.
Written by a leading expert in cloud-native technologies, this book explores design patterns for building resilient and scalable container-based systems. Its insights into distributed systems make it valuable for understanding the challenges and best practices of containerization.
Provides a comprehensive overview of cloud computing concepts, technologies, and architecture, including discussions on cloud deployment models, service models, and cloud security.
Microservices are a popular approach to building scalable systems, and this book provides a practical guide to designing and implementing microservices-based systems. It covers topics such as service discovery, load balancing, and fault tolerance.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, showing how to fine-tune, optimize, and deploy attention architectures across diverse machine learning tasks.
Provides a comprehensive guide to deployment automation, a key part of the DevOps process. It covers the tools, techniques, and best practices for automating deployments, and it valuable resource for anyone looking to improve their deployment process.
Provides a collection of case studies from organizations that have successfully implemented DevOps. It covers a wide range of industries and organizational sizes, and it provides valuable insights into the challenges and rewards of DevOps.
While not solely focused on serverless, this book foundational text for understanding microservices architecture, which is highly relevant to serverless computing. It covers design, testing, deployment, and operational concerns of microservices. It is essential background reading for anyone designing complex serverless systems and is widely regarded as a key resource in the field.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment.
Provides a clear explanation of relational database design principles and their implementation. It is suitable for students and professionals who need to understand how to design and manage relational databases effectively, covering both theory and practical aspects.
A practical guide for MySQL users looking to optimize performance and manage their databases effectively. dives into advanced topics specific to MySQL, making it valuable for professionals working with this popular relational database system.
A comprehensive guide to MongoDB, a popular NoSQL document database. is valuable for understanding the concepts and practical applications of MongoDB, suitable for developers and database administrators working with NoSQL.
Combines interactive Jupyter notebooks with rigorous mathematical explanations to teach machine learning practitioners how modern neural architectures are designed, implemented, and trained.
Offers a practical introduction to a variety of modern databases, including both SQL and NoSQL systems. It provides a hands-on approach to understanding different database models and their strengths and weaknesses, valuable for gaining a broad perspective on the database landscape.
Provides a guide to site reliability engineering (SRE), a set of practices that helps organizations build and operate reliable systems. SRE key part of DevOps, and this book provides a valuable introduction to the field.
Provides a collection of patterns for building large-scale distributed systems in the cloud. It covers topics such as scalability, fault tolerance, and data management.
Provides a comprehensive overview of cloud computing for both beginners and experienced professionals. It covers topics such as cloud architecture, cloud services, and cloud security.
Provides a comprehensive overview of PaaS for both beginners and experienced professionals. It covers topics such as the different types of PaaS offerings, the benefits and challenges of using PaaS, and the future of PaaS.
Provides a comprehensive overview of PaaS for cloud computing. It covers topics such as the different types of PaaS offerings, the benefits and challenges of using PaaS, and the future of PaaS.
Provides a comprehensive overview of PaaS for both beginners and experienced professionals. It covers topics such as the different types of PaaS offerings, the benefits and challenges of using PaaS, and the future of PaaS.
Provides a comprehensive guide to cloud security, covering topics such as cloud security risks, security controls, and security best practices.

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