Serverless Deployments for Developers

Serverless computing allows developers to build and run applications without having to manage servers. Explore the evolution of cloud computing along with the features and applications of serverless architecture through this course. Over the length of the course, examine the cloud application maturity model, layers of the data center network architecture, and considerations for outsourcing IT operations. Furthermore, investigate the distinction between serverless computing and Platform as a Service (Paas), the impact of NoOps on serverless deployment, and migration of existing services and monolithic apps to a serverless architecture. Upon completion of this course, you'll have a good understanding of the benefits of serverless computing, use cases for serverless deployment, and steps involved in migrating to serverless.

Implementing serverless solutions allows developers to move away from servers and infrastructure concerns and focus on building efficient applications. This course will acquaint you with the considerations and use cases for serverless implementation and the features and architectures of common serverless computing platforms. You'll recognize attributes of serverless systems, the concept of Function as a Service (FaaS), and the role of programming models in selecting serverless architectures and runtimes. You'll also examine the features of different serverless services provided by Amazon Web Services (AWS), serverless computing and implementation costs, and use cases for multi-cloud serverless solutions. After finishing this course, you'll be able to identify the concerns, considerations, and costs related to serverless implementation and set up a development environment for building serverless applications.

Implementing a serverless mindset can help enterprises scale their business and deliver focused, accelerated, and cost-effective solutions. Use this course to examine the benefits of serverless architectures and their impact on development processes and service delivery. Familiarize yourself with the distinction between containerized and serverless implementations, uses cases for serverless compute products, and how serverless influences DevOps and CloudOps mindsets. Having completed this course, you'll be able to recognize the advantages of serverless application architectures, business impacts and benefits of the serverless solutioning mindset, and the ecosystem of technologies involved in the deployment of serverless solutions.

Cloud portability allows developers to transfer data, applications, and services from one cloud service to another with ease. Take this course to explore the features, principles, and benefits of data and application portability in the cloud. Over the length of this course, you'll delve into various elements of cloud computing portability: software development lifecycle, the role of specification in maximizing portability, application design considerations for interoperable software applications, the OpenAPI specification, containerization, and essential characteristics of Docker and Kubernetes that enable application portability. You'll also outline how to work with Application programming Interfaces (APIs) in Swagger and configure a development environment in Google Cloud Platform (GCP). After completing this course, you'll be able to identify key components of data and code portability in the cloud and how cloud portability allows re-usability and interoperability.

Application portability enables developers to move and adapt applications across multiple cloud service providers and eliminates the need for application redesign and redeployment. Use this course to discover the advantages and use cases of multi-cloud architectures. Through this course, you'll outline the use of open-source serverless frameworks in deploying serverless computing solutions, common multi-cloud portable app patterns, and Kubernetes environment configuration for multi-cloud application portability. You'll also investigate the considerations for cloud infrastructure selection for containerized applications, the use of Python in writing applications with functional programming, and how to work with CNCF-compatible buildpacks. Upon finishing this course, you'll have the skills and knowledge to identify the portability and flexibility afforded by multi-cloud and recognize the purpose of containers in a multi-cloud environment.

A fundamental aspect of cloud development is choosing the most suitable serverless computing framework provider and serverless environment development language for your serverless application project. Use this course to identify the languages used for serverless application development and the prominent serverless computing systems and their languages and runtimes. Getting hands-on, use the three most popular serverless computing services to set up local development environments. Then, deploy a reporting service using Serverless Framework Open Source CLI and serverless Azure Functions using Python and Visual Studio Code. When you're done with this course, you'll be equipped with the know-how to choose the ideal serverless computing provider and language for your deployment tasks.

There are diverse languages and environments to choose from when building serverless applications. Developers should know which one to employ for which intricate task. Use the demonstrations in this course to set up REST APIs and HTTP GET endpoints using Serverless, Express, Node.js, Java, Ruby, Python, Maven, and Gradle on AWS and GCP. Furthermore, deploy HTTP Node.js Azure Functions, publish a Java Function project to Azure Functions, deploy and test a sample Serverless app using AWS SAM, and build a Web API using Go and AWS Lambda. Upon completing this course, you'll be able to conduct various essential serverless application development activities using several prominent services, frameworks, and languages.

Final Exam: Beginning with Serverless Solutions will test your knowledge and application of the topics presented throughout the Beginning with Serverless Solutions track of the Skillsoft Aspire Serverless Deployments for Developers Journey.

Developing serverless applications for the cloud requires the knowledge of base components and essential tools. Use this course to familiarize yourself with serverless architectures and the tools of an AWS serverless deployment. This course will enable you to recognize the attributes and advantages of the AWS Serverless Application Model (SAM), the role of AWS Serverless Application Repository, and the features of Amazon SNS and SQS for implementing a fully-managed messaging service. You'll also discover prominent AWS Developer Tools services and the characteristics of AWS Cloud Development Kit (CDK), core components and benefits of AWS DynamoDB, and the creation of Rest APIs using AWS CDK. Upon completion of this course, you'll be able to understand the AWS Serverless Application Model and identify the tools and components for writing serverless applications in the AWS cloud.

To build serverless applications, developers and project managers must know how to transition to an API-driven development environment. Use this course to learn how to leverage APIs within AWS's serverless platform. Distinguish between REST and SOAP APIs. Examine the purpose of the REST architecture style and the benefits of using REST APIs. Explore AWS API Gateway and the process of designing, building, and optimizing API Gateway to create REST APIs. Create HTTP APIs and API Gateway APIs. Implement AWS Lambda using Node.js. Then create Lambda functions to consume events from Amazon DynamoDB streams. Outline how to set up authentication and authorization in AWS serverless implementations. Work with Lambda authorizers and functions. Lastly, customize content delivered by CloudFront. Upon completing this course, you'll be able to build RESTful APIs and leverage them within the AWS serverless environment.

Testing, debugging, and monitoring serverless applications are critical tasks when building and deploying serverless solutions. Developers, engineers, and project managers alike can use this course to discover the most appropriate application, cloud, and automated testing mechanisms, frameworks, and tools for use with serverless implementations. Outline the challenges of testing cloud applications, the role of mock and dummy data in testing APIs, and the prominent testing strategies for local and cloud environments. Learn how to simplify Lambda function testing. Then practice testing and debugging serverless applications using AWS SAM and SAM CLI. Recognize the prominent AWS services for monitoring AWS applications. Explore the AWS Lambda console's role in monitoring AWS Lambda functions. Practice monitoring AWS Lambda functions and applications. Then fetch, tail, filter, and highlight Lambda function errors using AWS SAM CLI commands. Upon completion, you'll be able to discern the best methods for ensuring the smooth running of your serverless applications.

Azure offers numerous solutions for building and deploying scalable serverless applications successfully. This course shows developers and project managers how to use the various tools in Azure to enhance the serverless development and deployment experience. Investigate the prominent Azure serverless solutions, application development architectures, and execution environments. Explore the key features of Azure Functions, Azure Logic Apps, and the Azure serverless monitoring solutions. Examine how to create and deploy Azure serverless services using Azure tools and Visual Studio Code and validate Azure functions. Upon completion, you'll recognize why the various Azure serverless services and app development tools help infrastructure management and how to start using them.

Azure serverless compute services remove the need for manual infrastructure management. This course, aimed at developers and project managers, offers explanations and demonstrations on using Azure compute services for serverless projects. Outline the different approaches to managing compute with Azure. Differentiate between Azure compute services and serverless architecture as well as Azure Functions and Azure WebJobs. Explore durable functions for complex stateful function implementation, security strategies for running secure function code, and Azure App Service's role in securing functions. Create back-end compute services, test Azure functions locally, orchestrate long-running workflows as a set of activities, and create, test, and deploy Azure functions with C# and Python. Upon completion of this course, you'll be able to start using Azure compute services in your serverless development and deployment projects.

Azure offers several fully managed database and storage solutions to help developers focus on building apps instead of infrastructure management. This course shows you how to avail of these services during serverless app development and deployment. Explore Azure SQL databases, the Azure services based on relational and non-relational data stores, and the different approaches to implementing non-relational databases using Azure Cosmos DB. Create different Azure storage types, serverless Azure SQL databases, and functions that get triggered based on Blob storage activity. Use Node.js to perform CRUD operations on Azure Cosmos DB resources and create, design, and connect to Azure databases using cloud-native apps. Manage Azure Cosmos DB resources and SQL API accounts using Node.js web apps and create Azure Cosmos DB accounts, databases, containers, and items. When you're done, you'll know how to select, set up, and use the best storage and database services for your serverless projects.

For developers building and deploying serverless RESTful APIs, Azure has several tools for an enhanced and successful development and deployment experience. Use this course to build your knowledge of the serverless architectures implemented using Azure, the orchestration and integration processes in Azure, and how triggers and bindings are used in Azure Functions. Learn how to build Azure API Management service instances and serverless application workflows. Practice using prominent Azure services to implement serverless workflow orchestration. Then, work with Azure SignalR, real-time chatrooms, and serverless workflows in Azure Logic Apps. Next, create serverless workflows to automate app and data integration, basic serverless workflows to consume Azure services, and conditional statements to control workflow actions in Azure Logic Apps. You'll also build Logic apps to orchestrate workflows running on defined recurring schedules. Upon completion of this course, you'll be confident in orchestrating serverless tasks using Azure.

Developers who choose Azure to aid in their serverless DevOps tasks have several tools available to them. Use this course to become familiar with and practice using some of these services. Investigate the features and capabilities of the prominent Azure DevOps services, such as Azure Pipelines and Azure Test Plans. Create Azure pipelines for building GitHub repositories. Use the Azure CLI to build, test, and deploy JavaScript and Node.js apps. As you advance, use Azure DevOps services to implement end-to-end automated testing. Then, use Azure Pipelines to implement continuous integration and continuous deployment (CI/CD) pipelines for Azure Functions and automate Azure Functions deployment. By the end of the course, you'll be able to use the suite of Azure DevOps services to complete the DevOps cycle for your serverless projects.

Developers need to be aware of Azure messaging and monitoring services to enhance the Serverless deployment experience that saves time and lowers overhead cost. Use this course to investigate Azure messaging and notification essentials to manage events in Serverless applications and Azure monitoring services to control the environments with simplified configurations in the Azure cloud platform. Explore the capabilities of Azure Event Grid, differences between messages and events, and prominent messaging services provided by Azure. This course will also help you examine the advantages offered by Azure Notification Hubs and how they differ from Amazon SNS, the characteristics of Azure Monitor, and how to work with Application Insights and Log Analytics. After finishing this course, you'll have the knowledge to manage serverless applications with Azure messaging and monitoring services.

Google Cloud Platform (GCP) offers several tools for serverless application development and deployment. Use this course to learn how to take advantage of GCP serverless compute, storage, and app services. Investigate the GCP tools for hosting applications and examine how Google Cloud Functions and App Engine work. Explore the pros and cons of Firebase, the benefits of using Cloud Run, the use cases of Cloud Datastore, and the GCP serverless products for building apps for analytics. Moving along, explore GCP serverless microservices and how serverless deployments can improve DevOps productivity. Finally, learn how to deploy Node.js Cloud Functions, applications to App Engine, and containers from a Container Registry repository to Cloud Run. Store and query data in Firestore in Datastore mode and create streaming pipelines. When you're done, you'll be able to use GCP tools to develop scalable serverless applications efficiently and successfully.

With the serverless execution environment Google Cloud Functions, application code executes in a fully managed environment, removing the need to provision infrastructure or manage servers. Using this course, explore the use of Google Cloud Functions, the runtimes it supports, and its frameworks. Examine the features of Cloud Firestore and Firebase Realtime Database along with some common Cloud Functions tests. Create HTTP functions using Node.js, Python, Java, and Go and deploy Cloud Functions from your local machine, source repository, and GCP console. Moving along, write background Cloud functions using Cloud Pub/Sub and Cloud Storage triggers and unit tests for the HTTP-triggered and event-driven functions. Use Log Explorer for a variety of tasks and integrate Cloud functions with ReactJS-based applications. When you're done, you'll be able to use Google Cloud Functions to write simple, single-purpose functions attached to events emitted from cloud infrastructure and services.

App Engine is a fully managed serverless platform that provides a managed environment and custom runtimes to build highly scalable applications in Node.js, Java, Ruby, C#, Go, Python, and PHP without any infrastructure concerns. Use this course to become familiar with using Google App Engine. Learn how to deploy multiple API versions to the same App Engine version and structure the services and related resources of applications for App Engine. Explore the different methods for splitting traffic in App Engine, the various mechanisms for securing web applications on App Engine, and the key features of Google Cloud's operations suite. Finally, work with web apps, data, and testing in App Engine and configure monitoring and logging for Google Serverless applications. When you're done with this course, you'll know when and how to use App Engine during serverless implementation.

Because open-source platforms provide access to IT innovations, many developers utilize them. There are several open-source projects for working with the Serverless Framework (Apache OpenWhisk, Fn from Oracle, Kubeless, Knative, Project Riff, etc.). This course helps developers and project managers choose from and work with these different open-source frameworks. Start by exploring the core features of prominent open-source serverless frameworks. Then, compare open-source and cloud-based serverless frameworks before learning how to create and invoke actions and develop Functions as a Service using Apache OpenWhisk. Moving along, set up Fn Project to create, deploy, and invoke functions. Install and configure Fission on Kubernetes clusters. Write short-lived functions in Node.js, map them to HTTP requests, and deploy them on Fission. And use Kubeless for several essential tasks. When you're done, you'll be able to choose and use the best open-source serverless framework platform for your projects.

Developers and project managers who work on serverless application projects can utilize various open-source serverless frameworks to optimize development and deployment tasks. Use this course to recognize frameworks for serverless app development and deployment as well as monitoring, troubleshooting, and fine-tuning application performance. Investigate the prominent tools that help improve development workflows and monitor and debug serverless applications. Explore the critical metrics to identify serverless application performance and the recommended serverless performance and optimization strategies. Then, learn how to configure Sentry to monitor serverless applications. Upon completion of this course, you'll be able to use several tools, including AWS Chalice, Claudia.js, OpenFaaS, and OpenLambda, to improve the development, deployment, performance, monitoring, and debugging of serverless applications.

Final Exam: Developing Serverless Applications in the Cloud will test your knowledge and application of the topics presented throughout the Developing Serverless Applications in the Cloud track of the Skillsoft Aspire Serverless Deployments for Developers Journey.