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Test Number : AZ-400
Test Name : Microsoft Azure DevOps Solutions
Vendor Name : Microsoft
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AZ-400 test Format | AZ-400 Course Contents | AZ-400 Course Outline | AZ-400 test Syllabus | AZ-400 test Objectives


Design a DevOps strategy (20-25%)
Recommend a migration and consolidation strategy for DevOps tools
=> analyze existing artifact (e.g., deployment packages, NuGet, Maven, npm) and container repositories
=> analyze existing test management tools
=> analyze existing work management tools
=> recommend migration and integration strategies for artifact repositories, source control, test management, and work management
Design and implement an Agile work management approach
=> identify and recommend project metrics, KPIs, and DevOps measurements (e.g., cycle time, lead time, WIP limit)
=> implement tools and processes to support Agile work management
=> mentor team members on Agile techniques and practices
=> recommend an organization structure that supports scaling Agile practices
=> recommend in-team and cross-team collaboration mechanisms
Design a quality strategy
=> analyze existing quality environment
=> identify and recommend quality metrics
=> recommend a strategy for feature flag lifecycle
=> recommend a strategy for measuring and managing technical debt
=> recommend changes to team structure to optimize quality
=> recommend performance testing strategy
Design a secure development process
=> inspect and validate code base for compliance
=> inspect and validate infrastructure for compliance
=> recommend a secure development strategy
=> recommend tools and practices to integrate code security validation (e.g., static code analysis)
=> recommend tools and practices to integrate infrastructure security validation
Design a tool integration strategy
=> design a license management strategy (e.g., VSTS users, concurrent pipelines, test environments, open source software licensing, third-party DevOps tools and services, package management licensing)
=> design a strategy for end-to-end traceability from work items to working software
=> design a strategy for integrating monitoring and feedback to development teams
=> design an authentication and access strategy
=> design a strategy for integrating on-premises and cloud resources
Implement DevOps development processes (20-25%)
Design a version control strategy
=> recommend branching models
=> recommend version control systems
=> recommend code flow strategy
Implement and integrate source control
=> integrate external source control
=> integrate source control into third-party continuous integration and continuous deployment (CI/CD) systems
Implement and manage build infrastructure
=> implement private and hosted agents
=> integrate third party build systems
=> recommend strategy for concurrent pipelines
=> manage Azure pipeline configuration (e.g., agent queues, service endpoints, pools, webhooks)
Implement code flow
=> implement pull request strategies
=> implement branch and fork strategies
=> configure branch policies
Implement a mobile DevOps strategy
=> manage mobile target device sets and distribution groups
=> manage target UI test device sets
=> provision tester devices for deployment
=> create public and private distribution groups
Managing application configuration and secrets
=> implement a secure and compliant development process
=> implement general (non-secret) configuration data
=> manage secrets, tokens, and certificates
=> implement applications configurations (e.g., Web App, Azure Kubernetes Service, containers)
=> implement secrets management (e.g., Web App, Azure Kubernetes Service, containers, Azure Key Vault)
=> implement tools for managing security and compliance in the pipeline
Implement continuous integration (10-15%)
Manage code quality and security policies
=> monitor code quality
=> configure build to report on code coverage
=> manage automated test quality
=> manage test suites and categories
=> monitor quality of tests
=> integrate security analysis tools (e.g., SonarQube, White Source Bolt, Open Web
Application Security Project)
Implement a container build strategy
=> create deployable images (e.g., Docker, Hub, Azure Container Registry)
=> analyze and integrate Docker multi-stage builds
Implement a build strategy
=> design build triggers, tools, integrations, and workflow
=> implement a hybrid build process
=> implement multi-agent builds
=> recommend build tools and configuration (e.g. Azure Pipelines, Jenkins)
=> set up an automated build workflow
Implement continuous delivery (10-15%)
Design a release strategy
=> recommend release tools
=> identify and recommend release approvals and gates
=> recommend strategy for measuring quality of release and release process
=> recommend strategy for release notes and documentation
=> select appropriate deployment pattern
Set up a release management workflow
=> automate inspection of health signals for release approvals by using release gates
=> configure automated integration and functional test execution
=> create a release pipeline (e.g., Azure Kubernetes Service, Service Fabric, WebApp)
=> create multi-phase release pipelines
=> integrate secrets with release pipeline
=> provision and configure environments
=> manage and modularize tasks and templates (e.g., task and variable groups)
Implement an appropriate deployment pattern
=> implement blue-green deployments
=> implement canary deployments
=> implement progressive exposure deployments
=> scale a release pipeline to deploy to multiple endpoints (e.g., deployment groups, Azure Kubernetes Service, Service Fabric)
Implement dependency management (5-10%)
Design a dependency management strategy
=> recommend artifact management tools and practices (Azure Artifacts, npm, Maven, Nuget)
=> abstract common packages to enable sharing and reuse
=> inspect codebase to identify code dependencies that can be converted to packages
=> identify and recommend standardized package types and versions across the solution
=> refactor existing build pipelines to implement version strategy that publishes packages
Manage security and compliance
=> inspect open source software packages for security and license compliance to align with corporate standards (e.g., GPLv3)
=> configure build pipeline to access package security and license rating (e.g., Black Duck, White Source)
=> configure secure access to package feeds
Implement application infrastructure (15-20%)
Design an infrastructure and configuration management strategy
=> analyze existing and future hosting infrastructure
=> analyze existing Infrastructure as Code (IaC) technologies
=> design a strategy for managing technical debt on templates
=> design a strategy for using transient infrastructure for parts of a delivery lifecycle
=> design a strategy to mitigate infrastructure state drift
Implement Infrastructure as Code (IaC)
=> create nested resource templates
=> manage secrets in resource templates
=> provision Azure resources
=> recommend an Infrastructure as Code (IaC) strategy
=> recommend appropriate technologies for configuration management (e.g., ARM
Templates, Terraform, Chef, Puppet, Ansible)
Manage Azure Kubernetes Service infrastructure
=> provision Azure Kubernetes Service (e.g., using ARM templates, CLI)
=> create deployment file for publishing to Azure Kubernetes Service (e.g., kubectl, Helm)
=> develop a scaling plan
Implement infrastructure compliance and security
=> implement compliance and security scanning
=> prevent drift by using configuration management tools
=> automate configuration management by using PowerShell Desired State Configuration (DSC)
=> automate configuration management by using a VM Agent with custom script extensions
=> set up an automated pipeline to inspect security and compliance
Implement continuous feedback (10-15%)
Recommend and design system feedback mechanisms
=> design practices to measure end-user satisfaction (e.g., Send a Smile, app analytics)
=> design processes to capture and analyze user feedback from external sources (e.g., Twitter, Reddit, Help Desk)
=> design routing for client application crash report data
=> recommend monitoring tools and technologies
=> recommend system and feature usage tracking tools
Implement process for routing system feedback to development teams
=> configure crash report integration for client applications
=> develop monitoring and status dashboards
=> implement routing for client application crash report data
=> implement tools to track system usage, feature usage, and flow
=> integrate and configure ticketing systems with development team's work management
system (e.g., IT Service Management connector, ServiceNow Cloud Management, App Insights work items)
Optimize feedback mechanisms
=> analyze alerts to establish a baseline
=> analyze telemetry to establish a baseline
=> perform live site reviews and capture feedback for system outages
=> perform ongoing tuning to reduce meaningless or non-actionable alerts



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Microsoft Azure learn

evaluate: Microsoft Azure AI and desktop discovering goals for the enterprise | AZ-400 Free PDF and test Cram

Microsoft has a presence in most business construction and IT retail outlets, so it’s not a shock that the Azure AI and desktop learning platform has a presence in most business development, statistics evaluation, and data science shops. enterprise AI often has worrying necessities, and the Azure choices do their most beneficial to satisfy them.

Azure AI and machine gaining knowledge of includes 17 cognitive features, a laptop studying platform pitched at three distinct ability degrees, cognitive search, bot services, and Azure Databricks, an Apache Spark product optimized for the Azure platform and integrated with different Azure services.

in preference to drive businesses to run all Azure features on the Azure platform, Microsoft additionally presents a few Docker containers that permit organizations to use AI on premises. These guide a subset of Azure Cognitive services, and enable corporations to run the cognitive capabilities inside their firewall and near on-prem facts, which is a sine qua non for agencies with tight statistics security policies and groups area to restrictive facts privateness regulations.

liable AI was in the information recently, youngsters no longer in a great way, when Google fired Timnit Gebru. earlier in 2020, the accountable AI information became extra high quality, as numerous organizations introduced tools to promote more in charge laptop studying. Microsoft, for example, delivered interpretability points to its Azure machine discovering product, and additionally released three in charge AI initiatives as open source: FairLearn, InterpretML, and SmartNoise.

Fairlearn incorporates mitigation algorithms in addition to a Jupyter widget for model evaluation, and has been integrated right into a equity panel in Azure computing device researching. InterpretML helps you bear in mind your mannequin’s international behavior, or bear in mind the explanations in the back of particular person predictions, and has been integrated into an explanation dashboard in Azure computer researching. The SmartNoise task, in collaboration with OpenDP, goals to make differential privateness commonly accessible to future deployments by means of offering a couple of basic constructing blocks that can be used by means of individuals concerned with delicate facts. which you could carry SmartNoise into a Python notebook through setting up and importing the project, and including just a few calls to fuzz your delicate records.

there's a plethora of frameworks and equipment in use within the machine researching, deep gaining knowledge of, and AI world. whereas Azure AI supports dozens of those directly, there are hundreds more, which Azure handles by using proposing or enabling integration. Some, corresponding to MLflow, integrate as Python packages; others, corresponding to Pachyderm, integrate as containers, frequently on Kubernetes (AKS).

microsoft azure ai 01 IDG

As proven in this Azure reveal shot, the Azure AI and computing device studying product includes cognitive services, computer gaining knowledge of, cognitive search, bot carrier, and Databricks.

Microsoft describes Azure Cognitive functions as “a comprehensive family unit of AI features and cognitive APIs to help you construct intelligent apps,” and claims to have the “most finished portfolio of domain-selected AI capabilities available on the market,” despite the fact its competitors might disagree with that assessment. Azure Cognitive capabilities are aimed at developers who wish to incorporate machine learning into their applications.

The services cover 4 areas: determination guide, language, speech, and vision. web search was once blanketed below Cognitive capabilities, however has moved to another enviornment, and that i received’t cover it.

In accepted, Azure Cognitive functions don’t deserve to be trained, at the least on the stage you’d expect from Azure laptop getting to know. Some Azure Cognitive capabilities do allow customization, but you don’t need to remember laptop gaining knowledge of in an effort to accomplish that. just about all Azure Cognitive capabilities have a free trial tier.

choice help

The resolution support enviornment of Azure Cognitive functions includes an anomaly detector provider, a content moderator, a metrics consultant, and a personalizer.

Anomaly Detector

With the ambiguity Detector service, that you could embed anomaly detection capabilities into your apps so that clients can at once identify issues as quickly as they take place. No experience with computer getting to know is required. through an API, Anomaly Detector ingests time series information of every kind and selects the most useful-becoming anomaly detection mannequin to your information to make sure high accuracy. that you can customize the service to your business’s chance profile via adjusting one parameter. that you would be able to run Anomaly Detector anywhere from the cloud to the clever edge.

There are three endpoints to an Anomaly Detector service: discover the anomaly repute of the latest factor in the time sequence; locate anomalies for the whole series in batch; and find vogue alternate points for the whole collection in batch. below the covers, there are six algorithms for anomaly detection, used in three ensembles reckoning on the granularity and seasonality of the statistics; the service performs the preference immediately. The handiest parameter a consumer must alter is the sensitivity.

I validated all three endpoints within the Azure console using trial facts in opposition t a free Anomaly Detector carrier that I created. For each and every look at various I had to fill in the carrier identify (iw-anomaly) and subscription key. the most interesting of the three changed into the style change points, shown under. The third screenshot under indicates a considerable number of sorts of anomalies that the service can discover.

in addition to console-based service checking out, Azure components code samples the use of curl, C#, Java, JavaScript, goal-C, personal home page, Python, and Ruby. There are also brief starts in C#, Python, and Node.js.

microsoft azure ai 02 IDG

An anomaly detection request in the Azure console to find trend change features. here's a look at various dataset to be submitted to my free service instance.

microsoft azure ai 03IDG

An anomaly detection carrier response to the outdated request. I count three exchange features detected.

microsoft azure ai 04IDG

Six examples of anomalies that can be detected with the aid of the Azure Anomaly Detector service.

content Moderator

The content Moderator provider, designed to help administrate social media, product assessment sites, and video games with person-generated content material, performs image moderation, text moderation, video moderation, and optional human evaluate for predictions with low self assurance or mitigating context.

The photograph moderation service scans pictures for grownup or racy content, detects text in images the usage of optical character cognizance (OCR), and detects faces.

There are two text moderation APIs, one normal and one for personalization. The commonplace API returns tips about:

  • Profanity: time period-based matching with developed-in list of profane terms in numerous languages.
  • Classification: computing device-assisted classification into three classes, ranging from sexually specific to doubtlessly offensive in some circumstances. This carrier can also recommend when human review may still be performed.
  • very own facts: e mail address, SSN, IP tackle, mobile, and mailing tackle.
  • Auto-corrected text: Correction of common typos.
  • customary text: Uncorrected text with typos.
  • Language: An not obligatory parameter that defaults to English.
  • The custom time period list management API allows you to create and manage up to 5 lists of up to 10K terms each to increase the typical terms lists used via the content moderator text API.

    The video moderation service scans movies for adult or racy content material and returns time markers for referred to content. It additionally returns a flag announcing whether it recommends a human evaluate at every detected experience.

    Microsoft recommends the content Moderator assessment tool web page for working with the content Moderator provider, to supply a single interface for image, text, and video moderation stories.

    Metrics consultant

    The Metrics guide service builds on the paradox Detector service to monitor your corporation’s growth engines, from income revenue to manufacturing operations, in near-true time. It also adapts models to your situation, presents granular evaluation with diagnostics, and signals you to anomalous activities.

    Personalizer

    Personalizer is an AI carrier that grants a personalized, imperative adventure for every person. It uses reinforcement studying to optimize its mannequin to your dreams, and has an “apprentice” mode that best lets Personalizer engage with clients after the service reaches a precise degree of self belief in matching the performance of your latest answer.

    Personalization can be an moral minefield. Microsoft has guidelines for using Personalizer ethically, which cowl the alternative of use circumstances, building reward services, and choosing points for personalization. so far as i will be able to tell, neither Microsoft nor anyone else basically enforces these instructions, although there are laws about privateness (amongst different areas) that you just might effortlessly violate in case you chose to disregard the guidelines and put into effect eventualities that might trigger the person hurt, comparable to personalizing presents on personal loan, fiscal, and coverage products, the place risk factors are in keeping with records the individuals don’t find out about, can’t reap, or can’t dispute.

    The quickest approach to remember the Personalizer service is likely to run the interactive Personalizer demo website, shown below.

    microsoft azure ai 05IDG

    during this interactive Personalizer demo, the person can set a number of parameters and scroll through the article offered to generate a ranking for that article. Personalizer makes use of a reinforcement researching (RL) model to generate rankings, and it could replace the mannequin always.

    Language

    The language enviornment of Azure Cognitive features includes an immersive reader, a language realizing carrier, a conversational question and reply layer to your records, textual content analytics, and a language translator.

    Immersive Reader

    One outcome of the 2020 pandemic has been the need to attend school remotely, which doesn’t work smartly for all students. Immersive Reader allows you to embed text analyzing and comprehension aids—i.e., audio and visible cues—into applications and web sites with one line of code. you can help clients of any age and analyzing capability with features like analyzing aloud, translating languages, and focusing consideration via highlighting and different design facets.

    Azure is the only primary cloud issuer providing this category of analyzing expertise. Immersive Reader supports users with varying advantage and adjustments—including dyslexia, ADHD, autism, and cerebral palsy—in addition to emerging readers and non-native audio system.

    microsoft azure ai 06 IDG

    Immersive Reader helps readers at all ranges study and comprehend text. here we've chosen the word “cognitive” to listen to it pronounced. The “play” icon at the backside of the monitor speaks the total text.


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