 Adobe AD0-E106 : Adobe Experience Manager Dev/Ops Engineer ExamExam Dumps Organized by Michael
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Test Number : AD0-E106
Test Name : Adobe Experience Manager Dev/Ops Engineer
Vendor Name : Adobe
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AD0-E106 test Format | AD0-E106 Course Contents | AD0-E106 Course Outline | AD0-E106 test Syllabus | AD0-E106 test Objectives
Exam Information
Exam number: AD0-E106
Exam name: Adobe Experience Manager Dev/Ops Engineer Exam
Certificate level: Certified Expert
Status: Active
Available languages: English, Japanese
Number of questions: 54
Formats: Multiple choice and multiple select
Duration: 108 minutes
Delivery: Online proctored (requires camera access) or Test Center proctored
Passing mark: 64.81% or 550 using a scaled score format of 300 to 700
The Adobe Certified Expert - Adobe Experience Manager Dev/Ops Engineer test guide provides potential candidates with information they need to prepare for the certification exam.
Intended Audience
- Architects
- Cloud Engineers
- AEM Developers
- Technical Managers
- System Administrators
- Infrastructure Engineers
- System Reliability Engineers
Exam Objectives and Scope
Section 1: Install and Configure AEM (24%)
- Given a scenario, determine the appropriate method to manager the OSGi service configurations.
- Identify the steps necessary to configure agents.
- Given a scenario, determine the appropriate method to configure security.
- Identify the steps to configure authentication and authorization.
- Given a scenario, determine the appropriate method to configure environment settings.
- Given a scenario, determine the prerequisites needed for the installation of AEM instance
- Determine the appropriate method to install AEM instances
- Determine the correct method to configure segment store and data store repository.
Section 2: Troubleshoot AEM Environments (22%)
- Given a scenario, troubleshoot application level issues
- Given a scenario, troubleshoot index issues
- Given a scenario, troubleshoot OSGi issues
- Given a scenario, troubleshoot slow requests
- Given a scenario, troubleshoot JVM issues
- Given a scenario, troubleshoot caching issues
- Given a scenario, troubleshoot rights management issues
Section 3: Install and configure Dispatcher (13%)
- Determine the correct method to configure the dispatcher
- Determine the appropriate steps needed to apply the security checklist
- Identify the tasks needed to manage the dispatcher cache
Section 4: Build and Deployments (15%)
- Identify the steps to deploy AEM packages
- Determine the appropriate steps to configure a deployment pipeline with AEM packages
- Determine the correct method to manage content packages
- Identify the steps to manage a project in the code repository
- Identify the steps to set-up a build pipeline
Section 5: Maintenance and Operations (26%)
- Determine the correct method to perform a back-up and restore
- Identify the steps to perform online and offline compaction
- Identify the steps to perform AEM maintenance tasks
- Given a scenario, determine monitoring criteria and analyze reports
- Determine the correct method to remove a publish instance out of production
- Determine the correct method to clone the AEM environment
- Identify the steps to resolve the rights management issues
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Adobe Dev/Ops Practice Questions

Seth Dobrin, VP & Chief records Officer, IBM Analytics
The value of records continues to grow within the commercial enterprise. consequently, statistics experts are getting increasingly influential in and valuable to their businesses. The reality is in the numbers: records scientist salaries are anticipated to attain $163,500 this yr, up 6.4 percent from final 12 months.
For Chief information Officers (CDOs), starting an information science transformation can be daunting. Even finding out the place to beginning can feel like trying to boil the ocean. To beginning to prioritize efforts in the firm, the CDO should start via settling on key data property and organising lengthy-time period dreams for the statistics science software.
the key to a a success data observe contains: creating cost from facts and ensuring compliance with data governance. whereas the insights gleaned from facts are what truly count in the end, how a data science crew achieves these findings is equally as vital.
To achieve this, each CDO needs to address five key questions for their business:
What are their Core statistics property?
each organization has a collection of property which have information linked to them and have big value in and of themselves. Conducting a thorough audit of all statistics property is the most efficient location to begin because it helps to identify an business’s statistics probability.
the important thing to a a hit information apply comprises: developing value from data and ensuring compliance with information governance 
there's a finite variety of ways information will also be prepared inside a company, and it continually boils all the way down to three to 5 key property. essentially the most ordinary groupings of data are customer, Product and business. The consumer asset is all about having a quantitative realizing of your customer. The Product asset ranges from lifecycle administration to deliver chain stock to earnings data. whereas the business asset is a seize-curious about information that doesn't healthy into a specific bucket, the two most vital components of the company asset are talent and finance. without finance information, the Product asset can be incomplete as a result of fiscal performance of any given product is essential in deriving value from that asset, driving the success of any corporation. as soon as the belongings had been described conceptually, logical representations of the statistics with the intention to make up these assets need to be built.
How will they unify their approach to Governance?
historically, information governance has been considered as an obstacle, however it can basically be an impactful enabler. in spite of everything, which you can’t democratize data unless you gain handle over it. Having a unified strategy to governance (throughout deepest and public clouds) is the important thing. And ideally, governance will be managed from a single area, though this is a challenge for these days’s complex corporations. the important thing to governance is that it’s greater than just a policy. Governance requires a cultural shift that starts with the query—who should have entry to statistics within your company?
How can they construct Deployable statistics Science assets?
the key to cognitive enterprise is inserting information to work. In layman’s phrases, this means that the intrinsic cost of records isn’t in the statistics itself, but within the utility of statistics to company selections. Making bound your facts assets are organized to be deployed is key to extracting advantageous insights.
constructing deployable facts science belongings potential a number of things. First, businesses should still build analytics fashions like they construct application. statistics scientists are usual for their creativity and potential to apply scientific rigor to solve enterprise issues and utilize equipment equivalent to code repositories to share and edit code.
second, how models are built-in into applications or workflows is a vital consideration. The models deserve to be deployed in real utility and delivered by means of an software or as a part of a workflow to supply the next choicest action in a process.
Third, and perhaps the most challenging aspect of deploying facts science property, is that protection is often an afterthought for most companies. when you construct, teach and deploy a mannequin there continues to be lots work required, including making bound the model remains performing and retraining on new records at described increments in accordance with either time or performance.
what's their integrated Cloud approach?
The thought that an commercial enterprise will “pause” all through a knowledge science transformation is misguided, which is why planning an integrated cloud method is crucial. Many enterprises feel the need to choose from public and personal cloud alternatives, but hybrid cloud is in reality essentially the most cohesive answer.
there's lots of pressure within the business to stream to the cloud, but in reality, most businesses don't seem to be able or able to stream every little thing to the cloud. This creates a predicament for information science method as a lot of effort has long gone into building the general public cloud and there are many tools for extracting records and delivery it to those public environments. Hybrid cloud is the most effective solution that supports this and is in fact the holy grail for organisations to flow to the cloud.
CDOs, CIOs and CISOs frequently cite records protection as a intent to delay transition to the cloud. besides the fact that children, relocating to the cloud can current an opportunity for firms to re-architect protection from the ground up and put into effect new, greater useful security practices and technologies.
How do they construct a Sustainable ability Pipeline?
A seamless statistics science transformation isn’t viable with out the correct group. looking beyond the information assets and technological equipment, what are the human supplies your facts science program has to be successful? the important thing members of any records science crew (the facts scientist, the facts engineer, the developer and the enterprise analyst) must excel at their individual constituents of the facts procedure, but should additionally work collectively as a team. knowing every position on the team and how they all collaborate is the key to discovering the appropriate americans to build out your crew.
someplace in your organization, there is a group of facts gurus which are excited and inclined to take dangers. they are likely speaking about Agile, DevOps, microservices, APIs and cloud, but have got some hesitation to enforcing these applied sciences with legacy models.
It’s essential to word that a data science transformation isn’t quite simply a technological shift, it’s a cultural one. personnel at every level should agree with every point of the business as a supply for statistics, and its CDOs as the drivers who put into effect this approach. Investing in data helps company decisions be extra recommended, consistent and impactful. When statistics permeates a business, true exchange may also be made.