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NEW QUESTION: 1
A. Option A
B. Option B
C. Option D
D. Option C
Answer: B
Explanation:
EMC Atmos
EMC Atmos supports object-based storage for unstructured data, such as pictures and videos.
Atmos combines massive scalability with specialized intelligence to address the cost, distribution,
and management challenges associated with vast amounts of unstructured data.
Atmos can be deployed in two ways: as a purpose-built hardware appliance or as software in
VMware environments, where Atmos VE can leverage the existing servers and storage. The
hardware appliance is comprised of servers (nodes) connected to standard disk enclosures.
The rack includes a 24-port Gigabit Ethernet switch to provide internode communication.
The Atmos software is installed on each node.
Atmos VE enables users to exploit the power of Atmos in a virtualized environment. It can be
deployed on a virtual machine in VMware ESXi hosts and configured with the VMware certified
back-end storage.
Following are the key features offered by EMC Atmos:
Policy-based management: EMC Atmos improves operational efficiency by automatically
distributing content based on business policy. The administrator-defined policies dictate how, when, and where the information resides.
Protection: Atmos offers two options to protect the objects, replication and Geo Parity: Replication ensures that the content is available and accessible by creating redundant copies of an object at multiple designated locations.
Geo Parity ensures that the content is available and accessible by dividing objects into multiple segments plus parity segments and distributing them to one or more designated locations.
Data services: EMC Atmos includes the data services, such as, compression, and deduplication. These features are native to Atmos and can be managed and accessed via a policy.
Web services and legacy protocols: EMC Atmos provides flexible web services access (REST/SOAP) for web-scale applications and file access (CIFS/NFS/Installable File System/Centera API) for traditional applications.
Automated system management: EMC Atmos provides auto-configuring, auto-managing, and auto-healing capabilities to reduce administration and downtime.
Multitenancy: EMC Atmos enables multiple applications to be served from the same infrastructure. Each application is securely partitioned and cannot access the other application's data. Multitenancy is ideal for service providers or large enterprises that want to provide cloud computing services to multiple customers or departments allowing logical and secure separation within a single infrastructure.
Flexible administration: EMC Atmos can be managed via a graphical user interface (GUI) or command line interface (CLI). EMC E10-001 Student Resource Guide. Module 8: Object-based and Unified Storage
NEW QUESTION: 2
An external penetration tester compromised one of the client organization's authentication servers and retrieved the password database. Which of the following methods allows the penetration tester to MOST efficiently use any obtained administrative credentials on the client organization's other systems, without impacting the integrity of any of the systems?
A. Use the pass the hash technique
B. Use the existing access to change the password
C. Use social engineering to obtain the actual password
D. Use rainbow tables to crack the passwords
Answer: A
Explanation:
With passing the hash you can grab NTLM credentials and you can manipulate the Windows logon sessions maintained by the LSA component. This will allow you to operate as an administrative user and not impact the integrity of any of the systems when running your tests.
NEW QUESTION: 3
Case Study: 2 - MJTelco
Company Overview
MJTelco is a startup that plans to build networks in rapidly growing, underserved markets around the world. The company has patents for innovative optical communications hardware. Based on these patents, they can create many reliable, high-speed backbone links with inexpensive hardware.
Company Background
Founded by experienced telecom executives, MJTelco uses technologies originally developed to overcome communications challenges in space. Fundamental to their operation, they need to create a distributed data infrastructure that drives real-time analysis and incorporates machine learning to continuously optimize their topologies. Because their hardware is inexpensive, they plan to overdeploy the network allowing them to account for the impact of dynamic regional politics on location availability and cost. Their management and operations teams are situated all around the globe creating many-to- many relationship between data consumers and provides in their system. After careful consideration, they decided public cloud is the perfect environment to support their needs.
Solution Concept
MJTelco is running a successful proof-of-concept (PoC) project in its labs. They have two primary needs:
Scale and harden their PoC to support significantly more data flows generated when they ramp to more than 50,000 installations.
Refine their machine-learning cycles to verify and improve the dynamic models they use to control topology definition.
MJTelco will also use three separate operating environments ?development/test, staging, and production ?
to meet the needs of running experiments, deploying new features, and serving production customers.
Business Requirements
Scale up their production environment with minimal cost, instantiating resources when and where needed in an unpredictable, distributed telecom user community. Ensure security of their proprietary data to protect their leading-edge machine learning and analysis.
Provide reliable and timely access to data for analysis from distributed research workers Maintain isolated environments that support rapid iteration of their machine-learning models without affecting their customers.
Technical Requirements
Ensure secure and efficient transport and storage of telemetry data Rapidly scale instances to support between 10,000 and 100,000 data providers with multiple flows each.
Allow analysis and presentation against data tables tracking up to 2 years of data storing approximately
100m records/day
Support rapid iteration of monitoring infrastructure focused on awareness of data pipeline problems both in telemetry flows and in production learning cycles.
CEO Statement
Our business model relies on our patents, analytics and dynamic machine learning. Our inexpensive hardware is organized to be highly reliable, which gives us cost advantages. We need to quickly stabilize our large distributed data pipelines to meet our reliability and capacity commitments.
CTO Statement
Our public cloud services must operate as advertised. We need resources that scale and keep our data secure. We also need environments in which our data scientists can carefully study and quickly adapt our models. Because we rely on automation to process our data, we also need our development and test environments to work as we iterate.
CFO Statement
The project is too large for us to maintain the hardware and software required for the data and analysis.
Also, we cannot afford to staff an operations team to monitor so many data feeds, so we will rely on automation and infrastructure. Google Cloud's machine learning will allow our quantitative researchers to work on our high-value problems instead of problems with our data pipelines.
MJTelco's Google Cloud Dataflow pipeline is now ready to start receiving data from the 50,000 installations. You want to allow Cloud Dataflow to scale its compute power up as required. Which Cloud Dataflow pipeline configuration setting should you update?
A. The number of workers
B. The disk size per worker
C. The zone
D. The maximum number of workers
Answer: C
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