The Catalyst 4000 with Supervisor Engine I chassis serial number on the Catalyst 4003, 2948G, and 2980G is not readable through a CLI command. The serial number that appears in the show version command output in the example in this section is the serial number of the Supervisor Engine. The actual serial number appears on a sticker on the outside of the chassis.
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On the Catalyst 4500/4000 Supervisor 2, the chassis serial number is available via CLI in versions 5.5(10), 6.3(2), and later versions. In earlier versions, theshow versioncommand shows the Supervisor Engine serial number in the place of the chassis serial number. To obtain the serial number of the chassis in these earlier versions, check the external sticker on the chassis.
Use theshow versioncommand to determine the chassis serial number and switch model type, as the example here shows. You find all switch stack members, chassis, and serial number information in the output:
IS (Inter-IC Sound, pronounced "eye-squared-ess"), is an electrical serial bus interface standard used for connecting digital audio devices together. It is used to communicate PCM audio data between integrated circuits in an electronic device. The IS bus separates clock and serial data signals, resulting in simpler receivers than those required for asynchronous communications systems that need to recover the clock from the data stream. Alternatively IS is spelled I2S (pronounced eye-two-ess) or IIS (pronounced eye-eye-ess). Despite the similar name, IS is unrelated to the bidirectional IC (IIC) bus.
The word select clock lets the device know whether channel 0 or channel 1 is currently being sent, because IS allows two channels to be sent on the same data line. It is a 50% duty-cycle signal that has the same frequency as the sample frequency. For stereo material, the IS specification states that left audio is transmitted on the low cycle of the word select clock and the right channel is transmitted on the high cycle. It is typically synchronized to the falling edge of the serial clock, as the data is latched on the rising edge.[1] The word select clock changes one bit clock period before the MSB is transmitted. This enables, for example, the receiver to store the previous word and clear the input for the next.[1]
P3 instances are the next-generation of EC2 general-purpose GPU computing instances, powered by up to 8 of the latest-generation NVIDIA Tesla V100 GPUs. These new instances significantly improve performance and scalability, and add many new features, including new Streaming Multiprocessor (SM) architecture for machine learning (ML)/deep learning (DL) performance optimization, second-generation NVIDIA NVLink high-speed GPU interconnect, and highly tuned HBM2 memory for higher-efficiency.
P3 instances with their high computational performance will benefit users in artificial intelligence (AI), machine learning (ML), deep learning (DL) and high performance computing (HPC) applications. Users include data scientists, data architects, data analysts, scientific researchers, ML engineers, IT managers and software developers. Key industries include transportation, energy/oil & gas, financial services (banking, insurance), healthcare, pharmaceutical, sciences, IT, retail, manufacturing, high-tech, transportation, government, and academia, among many others.
P3 Instances are the next-generation of EC2 general-purpose GPU computing instances, powered by up to 8 of the latest-generation NVIDIA Volta GV100 GPUs. These new instances significantly improve performance and scalability and add many new features, including new Streaming Multiprocessor (SM) architecture, optimized for machine learning (ML)/deep learning (DL) performance, second-generation NVIDIA NVLink high-speed GPU interconnect, and highly tuned HBM2 memory for higher-efficiency.
High I/O instances are ideal for applications that require access to millions of low latency IOPS, and can leverage data stores and architectures that manage data redundancy and availability. Example applications are:
Q: What monitoring tools are available to track this? ENA Express offers EthTool counters to track packets that are eligible for SRD transmission in addition to those actually sent and received with SRD. Additionally, EthTool will support an SRD resource utilization metric on a percent basis, providing insight into when you should consider scaling out your architecture. Finally, a Boolean will provide on and off status for ENA Express and the UDP protocol.
The Classic Load Balancer is ideal for simple load balancing of traffic across multiple EC2 instances, while the Application Load Balancer is ideal for applications needing advanced routing capabilities, microservices, and container-based architectures. Please visit Elastic Load Balancing for more information.
VM Import/Export currently supports Windows and Linux VMs, including Windows Server 2003, Windows Server 2003 R2, Windows Server 2008, Windows Server 2012 R1, Red Hat Enterprise Linux (RHEL) 5.1-6.5 (using Cloud Access), Centos 5.1-6.5, Ubuntu 12.04, 12.10, 13.04, 13.10, and Debian 6.0.0-6.0.8, 7.0.0-7.2.0. For more details on VM Import, including supported file formats, architectures, and operating system configurations, please see the VM Import/Export section of the Amazon EC2 User Guide.
First, the NVMe device names used by Linux based operating systems will be different than the parameters for EBS volume attachment requests and block device mapping entries such as /dev/xvda and /dev/xvdf. NVMe devices are enumerated by the operating system as /dev/nvme0n1, /dev/nvme1n1, and so on. The NVMe device names are not persistent mappings to volumes, therefore other methods like file system UUIDs or labels should be used when configuring the automatic mounting of file systems or other startup activities. When EBS volumes are accessed via the NVMe interface, the EBS volume ID is available via the controller serial number and the device name specified in EC2 API requests is provided by an NVMe vendor extension to the Identify Controller command. This enables backward compatible symbolic links to be created by a utility script. For more information see the EC2 documentation on device naming and NVMe based EBS volumes.
A semantic data model is a conceptual model that describes the meaning of the data elements it contains. Organizations often have their own terms for things, sometimes with synonyms, or even different meanings for the same term. For example, an inventory database might track a piece of equipment with an asset ID and a serial number, but a sales database might refer to the serial number as the asset ID. There is no simple way to relate these values without a model that describes the relationship.
If you work in IT or the cloud computing field, you're probably well aware of the service-oriented architecture (SOA) vs. microservices debate. After all, everyone is talking about microservices and agile applications these days.
At first glance, the two approaches sound very similar, and in some ways, they are. Both involve cloud or hybrid cloud environments for agile application development and deployment, and both can scale to meet the speed and operational demands of big data. Both break large, complex applications into small, flexible components that are easier to work with. And both differ from a traditional, monolithic architecture in that every service has its own responsibility.
Like SOA, microservices architectures are made up of loosely coupled, reusable, and specialized components that often work independently of one another. Microservices also use a high degree of cohesion, otherwise known as bounded context. Bounded context refers to the relationship between a component and its data as a standalone entity or unit with very few dependencies. Rather than being adopted enterprise-wide, microservices typically communicate via application programming interfaces (APIs) to build individual applications that perform a specific business functionality (or functionality for specific areas of the business) in a way that makes them more agile, scalable and resilient. Typically, Java is the programming language of choice to develop Microservices. Other programming languages may also be used, such as Golang and Python.
Microservices are a true cloud-native architectural approach, often operating in containers, which make them more scalable and portable for the creation of independent services. Teams can use microservices to update code more easily, use different stacks for different components and scale the components independently of one another, reducing the waste and cost associated with having to scale entire applications because a single feature might be facing too much load. Because of their independence, microservices produce services that are more fault-tolerant than the alternatives.
The main distinction between the two approaches comes down to scope. To put it simply, service-oriented architecture (SOA) has an enterprise scope, while the microservices architecture has an application scope.
In SOA, reusability of integrations is the primary goal, and at an enterprise level, striving for some level of reuse is essential. Reusability and component sharing in an SOA architecture increases scalability and efficiency.
In microservices architecture, creating a microservices component that is reused at runtime throughout an application results in dependencies that reduce agility and resilience. Microservices components generally prefer to reuse code by copying and accepting data duplication to help improve decoupling.
For some organizations, SOA architecture is a steppingstone to replace the monolith, providing a more flexible and agile environment. SOA services can be developed and utilized in a large environment, but they do not address specific needs of individual businesses that wish to address business processes within their purview. DevOps can be used to help an organization transition from SOA architecture to microservices to address specific needs. 2ff7e9595c
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