Final Exam: DevOps Support Practitioner
DevOps | Intermediate
- 1 video | 32s
- Includes Assessment
- Earns a Badge
Final Exam: DevOps Support Practitioner will test your knowledge and application of the topics presented throughout the DevOps Support Practitioner track of the Skillsoft Aspire Infrastructure Support Engineer to CloudOps Engineer Journey.
WHAT YOU WILL LEARN
configure a Cloud Build trigger to build code whenever there are any changes to the source repositoryuse the Cloud Build GitHub app to automatically build code whenever there are new commits being pushed to GitHubcreate GKE clusters that can be used in continuous deployment with Cloud Buildspecify the benefits of GCP DevOps pipeline when implemented using Google Cloud Computing serviceslist the Google Cloud Platform products that help build DevOps pipelines and implement CI/CDcreate repositories to host sample app source codes and set up automated triggers in Cloud Builddefine the concept of "jobs" in Azure Pipelines and classify the different types of jobs that can be configuredcreate an automated continuous integration and release management workflow using Release Manager and AWSconnect external repositories, set up repository mirroring and create lightweight projects with GitLabdemonstrate the steps involved in setting up HTTPS connections to AWS CodeCommit using git-remote-codecommitdescribe the packaging approach provided by AWS to manage application packaging and distributiondescribe the steps that release engineers need to follow as a Foundation to streamline release managementlist the prominent cloud deployment technologies that can be used to facilitate deployments using IaaS, PaaS, and SaaS and identify the prominent use cases to help DevOps Support Practitioner identify the right deployment technologyrecall the history of application server and deployment models that can be adopted to manage server-based applicationsdescribe the features of major cloud monitoring platforms along with their classification based on their taxonomycreate and configure CloudTrail to manage logs for management events, insight events, data events and KMS eventswork with Azure Monitor to monitor and collect metrics and activity logs from host VMs to gain insight for fine-tuning instance as per the architectural requirementsidentify the prominent AWS services and tools that can be used to monitor infrastructure, resources, applications while also enabling governance, compliance, operational auditing and risk auditing of AWS accountsconfigure and use the AWS Elastic Beanstalk console to upload updated source bundles and deploy them to Elastic Beanstalk environmentlist the essential components and patterns that are used to set up monitoring systems for IT applications and platformsuse the Google Cloud Deployment Manager to create virtual machine instances and set up deployment environmentslist the components of application server that helps set up run environment to manage applications and middleware componentsconfigure Azure Services to implement continuous deployment from GitHub by pulling in the latest updatesdescribe the architecture of Azure DevOps Server along with the critical considerations for a DevOps Support Practitioner to plan robust local and hosted deploymentsclassify the prominent types of a source control system along with the scenarios where can adopt the right source control systemsrecall the essential DevOps stages that needs to be configured in order to create pipelines that deploys or tests applications after they've been built and tested for every committed changesdescribe the components of application package along with the critical packaging guidelines for packaging applicationsdescribe the features of AWS CodePipeline that help model and configure different stages of the software release processdefine the concept, characteristics and benefits of software packagecompare the difference between the traditional deployment approach and DevOps powered deployment approach along with the value stream realized by DevOps in the context of deployment
recognize the key terms and processes involved in defining a series of Pipeline stages used in AWS CodePipelinelist the solutions that are provided by AWS to manage configuration and release solutionsoutline the approach to implementing continuous integration and recognize the benefits afforded by using AWS CodePipeline for continuous integrationcreate IAM users and configure IAM managed policy to assign CodePipeline permissions to the IAM usersconfigure and execute Azure Pipelines jobs based on the status of running previous jobs and set timeouts for each tasks individuallycreate pipelines to build GitHub repository using Azure Pipelines from Azure CLIlist the critical steps involved in setting up continuous deployment and delivery using AWS CodePipelinerecall the history of release management along with the key terms that are used in release managementcreate two-stage pipelines and configure CodeDeploy to deploy applications from CodeCommit repository to Amazon EC2 instancesdescribe the concept of stages in Azure Pipelines and list the major divisions of a logical release pipeline to set up right abstraction of Stages in Azure Pipelinesrecall the essential application packaging standards and participants that are involved in the package integration processconfigure and use AWS CodeStar to plan releases from development to productionrecall the history of source control systems along with the benefits that we can realize by adopting source control systems as a part of the development practicedescribe the features and benefits afforded by AWS Systems Manager Distributorrecall the concept and the role of continuous monitoring in DevOps along with the benefits afforded by adopting the right monitoring practicesdescribe the core features and capabilities of Azure Pipelines and recognize how they're used to build and test code projects automaticallylist the benefits of AWS CodeDeploy along with the various deployment types that can be used by DevOps Support Practitioner to adopt the right strategy for deploying applications on compute platformdemonstrate the use of commands to monitor CPU, memory, disk usages, network and load statistics of the servers that are installed on Linux where the applications are to be deployeddescribe the fundamental concept of version control systems along with the architecture of the prominent types of version control systems independent of clouddemonstrate the steps to clone, export, and import pipelines in the same projectrecognize the cycle of release management along with the critical challenges that release management can help addressdescribe Google's approach to implementing continuous integration using the GCP reference pipeline to automate building, testing, and delivering quality deploymentillustrate the use of version control systems as a mandatory component to implement continuous delivery with agile and DevOps practicesdescribe the features of Git and GitLab CI/CD toolchain that can be used as a complete DevOps platform to deliver DevOps solution as a single applicationrecall the key concepts and components that are used in Azure Pipelines to deliver better codes more efficiently and reliablylist the prominent compute products provided by GCP that helps enable faster computations, run large in-memory databases and build cloud‐native appscreate an application, package the application into a container image and deploy the container image to Cloud Runrecognize the use of continuous integration and pull request validation triggers based on the type of repository that was built in Azure Pipelinesset up staging environments in Azure App Service to use separate deployment slots for applicationsinstall Concurrent Versions System and demonstrate the steps of using Concurrent Versions System to manage DevOps pipelines' assets
IN THIS COURSE
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