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C5050-384 exam Dumps Source : IBM Cloud Platform Application progress v2

Test Code : C5050-384
Test name : IBM Cloud Platform Application progress v2
Vendor name : IBM
: 56 true Questions

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totally obtainable later this year on IBM Cloud and IBM Cloud deepest, AI OpenScale is an open platform that enables organizations to operate and automate AI at scale, anyplace it resides -- with transparent, explainable effect.

The platform solution makes it less complicated for data scientists, software builders, IT and AI operations teams, and company manner house owners to collaborate in deploying, managing, monitoring and updating AI assets in production. This empowers corporations to confidently combine computing device researching and abysmal discovering capabilities into their functions, and scale seamlessly because the require for AI grows.

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IBM security hook up with allow Open specifications-based mostly Collaboration on AI Platform Backed by more than a Dozen groups

CAMBRIDGE, Mass., Oct. 15, 2018 /PRNewswire/ -- IBM (NYSE: IBM) these days announced a brand modern cloud-based neighborhood platform for cyber safety applications. IBM safety combine is the primary safety cloud platform developed on open federated technologies, with AI at its core, to dissect safety information across prior to now unconnected paraphernalia and environments. 

IBM organization emblem. (PRNewsFoto/IBM supplier) (PRNewsFoto/) (PRNewsfoto/IBM)

more

An IBM analysis of consumers' environments discovered that on commonplace, cybersecurity groups are the usage of over 80 diverse security items from forty diverse companies. Their analysis additionally shows below 20 p.c of the aspects in these on-premise paraphernalia are used and may no longer supply the results valued clientele are expecting due to integration and complexity challenges.  

through integrating protection information from IBM protection products with an ecosystem of security providers, customers, and enterprise partners, IBM security combine is designed to relieve enhance effectivity and collaboration as groups recognize after against cybercrime. IBM security connect will enable clients to apply laptop researching and AI, together with Watson for Cyber protection, for evaluation to aid them determine threats or hazards and enhance the efficacy and efficiency of risk detection and response. users can design and installation modern personalized and complete options to handle safety consequences, reminiscent of SOC Operations workflows or Digital trust. 

IBM safety combine will prolong the wealthy set of capabilities from IBM's protection items, by the employ of potent integration capabilities to connect records, applications and tools from an ecosystem of vendors, made viable with the aid of the cloud.   

"The boom of cybersecurity technology and information mixed with a turning out to exist competencies shortage is growing an sudden degree of complexity for protection groups," referred to Marc van Zadelhoff, widespread supervisor, IBM safety. "Leveraging the power of the cloud, they are able to now assemble equipment, facts and people with out costly customization and integration initiatives. information federation through IBM security combine helps supply security professionals multiplied protection visibility and efficiency without the bother of migrating records or overly complicated product integrations."

a new, Open strategy to Cloud protection

IBM protection connect will relieve handle one of the greatest safety challenges today by means of open requirements, that could champion pave the route towards collaborative innovation. as it is developed on open necessities, it may possibly champion corporations construct exciting microservices, further modern security functions, combine present security options, and leverage statistics from open shared functions. 

Key services encompass: Open protection information integration services for sharing and normalizing threat intelligence, federated records browsing throughout on-premise and cloud information repositories and safety solutions, and real-time sharing of security signals/hobbies and insights that will also exist leveraged by means of any app or reply integrated with the platform. 

IBM security connect will swirl into the domestic of IBM's current protection App trade and every IBM security functions developed on a platform powered by IBM Cloud, however entirely compatible with different cloud providers.  IBM security will also champion the creation of modern open standards in burgeoning areas such as the sharing of response playbooks and analytics patterns and should actively invest in constructing modern open supply tasks that align with these efforts.

Story Continues

IBM safety's commitment to openness additionally skill that many present open security and protocol specifications are leveraged every the route through the platform, akin to STIX™ (Structured possibility tips eXpression) and TAXII™ (trusted automated exchange of Indicator suggestions). The IBM security mission STIX-Shifter, which is publicly available on GitHub, incorporates an open source library which permits software to connect with items that condominium data repositories using STIX Patterning, and recur outcomes as STIX Observations.  using these open necessities for connecting to any data source mixed with IBM safety's already potent safety analytics and incident response capabilities helps consumers to profit broader visibility and become aware of threats and hazards that had been in any other case missed because of disconnected data throughout complicated hybrid environments. 

IBM protection connect's initial set of applications and capabilities will permit clients to instantly connect to dissimilar safety items or facts repositories to automatically federate facts for the purpose of prioritizing and responding to threats. This progressive manner of federating facts permits purchasers to depart their information where it's, as adverse to edifice costly statistics lakes, that may complicate or outright evade protection statistics analysis.

IBM security connect will also exist an integral Part of IBM safety capabilities offerings each as a purchaser and a contributor of recent innovation; including advancements in voice-enabled AI, computing device studying for security threat scoring, world hazard analytics, orchestration playbooks and mobile-enabled MSS purposes.  IBM security services will leverage the open vigour of IBM protection connect with boost abysmal and advantageous integrations throughout its associate ecosystem to deliver stronger cost for its international clients.

Addressing Complexity in Cybersecurity Operations

Designed to carry "neighborhood-pushed" security options, IBM protection combine will operate as an open platform with an open construction community.  As a Part of trendy announcement, a significant variety of know-how companions and world device integrators together with Cisco, Capgemini, Carbon Black, determine point, CrowdStrike, EY, ForeScout, Forcepoint, Fortinet, McAfee, Qualys, Smarttech, Symantec, Tenable, trend Micro, and VMware savor committed to integrating with IBM security connect so as to relieve deliver more suitable information sharing across safety companies for their joint shoppers.  many of these vendors will also contribute to edifice integrated purposes on IBM security connect.  IBM already has tons of of pre-built apps built through IBM and partners attainable by means of the IBM safety App exchange for integrating on the product stage. as soon as obtainable, these extra integrations might exist built into IBM security combine inside months of launch, widening the achieve of the platform to champion control compliance and handle threats.

as an instance, some of the first options being established by clients will hub of attention on possibility Operations Workflow. This solution is designed to empower security analysts to proactively establish, investigate, and respond to their most captious threats from a single, cloud-primarily based answer. probability Operations Workflow integrates seamlessly via open connectors to QRadar (each on-premise or cloud), as well as different SIEMs and endpoint solutions. by using leveraging open SDKs, different safety statistics ponds or lakes equivalent to Hadoop, and factor security items will also exist supported to supply a federated view and workflow for security analysts throughout previously unintegrated and siloed products.    

inbuilt expertise and talents

With the smartly-documented talents problem the protection industry is dealing with, IBM safety connect will additionally characteristic digitized information from IBM's four,000+ global protection practitioners to supply choicest practices and assistance on how to implement protection and possibility administration concepts. The pre-integrated apps allow users to create easy-to-use regular workflows throughout multiple applications, so teams can focal point on solving security concerns as an alternative of struggling to integrate dozens of security products. furthermore, IBM security has dedicated 50 developers towards construction of the group, the plot security practitioners can collaborate and partake integrations.

IBM safety connect is designed to gain gaining access to IBM X-drive safety features talents even simpler for consumers in any respect degrees; including choices and talents in X-force red safety testing, Managed safety services and Incident Response functions.

IBM safety combine is predicted to exist obtainable in 1Q 2019.

About IBM security 

IBM safety presents probably the most superior and built-in portfolios of traffic protection items and capabilities. The portfolio, supported by means of world-famous IBM X-force® research, permits groups to quite simply control possibility and protect in opposition t rising threats. IBM operates probably the most world's broadest security research, progress and birth corporations, screens 60 billion security events per day in more than a hundred thirty international locations, and has been granted greater than 8,000 security patents global. For more suggestions, delight determine www.ibm.com/protection, comply with IBMSecurity on Twitter or discuss with the IBM security Intelligence weblog. 

CONTACT: Dillon Townsel dillon.townsel@ibm.com 512-571-3455

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tons of of leading world organizations set up IBM Cloud private | killexams.com true Questions and Pass4sure dumps

TMCNet: Hundreds of Leading Global Enterprises Deploy IBM Cloud Private

tons of of leading international corporations install IBM Cloud inner most

to fill transforming into demand, IBM advances on-prem private cloud with modern Watson AI capabilities

ARMONK, N.Y., Oct. 11, 2018 /CNW/ -- IBM (NYSE: IBM) has introduced that in lower than twelve months since the liberate of IBM Cloud deepest – an open source technology that brings cloud capabilities to organizations working on-premises IT systems – lots of of leading enterprises international savor turned to the platform to assist modernize their operations. They involve modern Zealand Police, China's Fuyao community, Japan's Aflac assurance, Turkey's credit score bureau Kredi Kayit Bürosu and Brazil's loyalty national suggestions features.

IBM Corporation logo. (PRNewsFoto/IBM Corporation) (PRNewsFoto/) (PRNewsfoto/IBM)

building on this momentum, IBM is asserting a slate of latest superior facets for the on-premises private cloud platform, including the mixing of efficient AI capabilities comparable to IBM Watson aide and IBM Watson Speech-to-textual content, as well as relieve for further public clouds, together with the IBM Cloud. The updates give consumers with even more alternative and adaptability for their IT journeys, and, for the first time, carry the vigour of IBM's Watson AI in the back of the company firewall.

IBM is releasing particulars of over a dozen organizations which might exist driving transformation with IBM Cloud deepest, including:

  • New Zealand Police (NZP) is the usage of the latest applied sciences to seriously change its operations and raise its capacity to handle crime and preserve the community protected. NZP is exploring how IBM Cloud inner most and Kubernetes containers can relieve to modernize its present techniques as well as instantly launch modern capabilities equivalent to a cell based mostly communications paraphernalia for its officers.
  • Fuyao group is China's biggest and most superior manufacturer of automobile glass presenting Audi, Bentley, universal Motors, Toyota and different excellent car makers. to fulfill transforming into demand, Fuyao has launched into a smart Manufacturing initiative and is the employ of IBM Cloud private to assist integrate the administration of enterprise applications throughout its world manufacturing and enterprise operations, guaranteeing the free tide of suggestions across the company.
  • Aflac coverage, Aflac insurance, a leading provider of scientific and cancer assurance providing insurance policy to 1 in 4 households in Japan, has signed an agreement with IBM to assist simplify and automate its IT infrastructure. With IBM Cloud inner most, Aflac plans to expand the efficiency of its operations and velocity up the edifice of modern items and features.
  • Kredi Kayit Bürosu (KKB) provides the country wide cloud infrastructure for Turkey's finance trade. last 12 months KKB dependent a modern statistics core in Ankara and is now using IBM cloud inner most to relieve consolidate and localize the banking programs of over a hundred and fifty members together with banks and other monetary features agencies. With IBM Cloud deepest, KKB is capable of power innovation throughout its fiscal capabilities ecosystem whereas assembly the extreme requirements for statistics protection and privateness.
  • Brazil's loyalty national assistance capabilities (FIS), a global leader in permeate processing options for the financial trade, has adopted IBM Cloud deepest to assist streamline credit card chargebacks for its Brazilian operations. IBM Cloud inner most is assisting FIS to orchestrate the a number of IT systems involved in reconciling and checking of transaction chargebacks whereas meeting the stringent regulatory requirements of the trade and helping to retain away from fraud.
  • "The cloud has evolved in a extremely short time from being a route to crop prices to a platform for enterprise transformation and innovation," spoke of Robin Hernandez, Director, IBM deepest Cloud offering management. "Our IBM Cloud private affords valued clientele a transition to cloud it's designed to allow them to maintain their on-premises programs on which they nonetheless depend for many mission-critical functions and sensitive information units."

    putting AI inner the EnterpriseToday IBM is advancing IBM Cloud inner most even further, aphorism primary enhancements to the platform, ranging from AI capabilities to additional public cloud assist. genesis today, IBM Watson Speech-to-textual content is now obtainable with the brand modern IBM Cloud private edition 3.1, making it the first time the appliance is obtainable in an on-premises atmosphere. With Watson Speech-to-text, users can immediately transcribe and dissect audio from seven distinctive languages.

    moreover, IBM Watson aide is now available on IBM Cloud deepest. The Watson aide platform helps builders and non-technical users to create conversational AI options, from fundamental chatbots to advanced traffic grade options for customer carrier and more.

    IBM also announced these days that IBM Cloud inner most is now purchasable on the IBM Public Cloud, to champion clients to with ease circulation their enterprise workloads from on-premises methods to the public cloud to exist able to create hybrid cloud environments.

    customer quote"IBM Cloud inner most is assisting us to set up an conclusion-to-end digital platform so one can underpin a smarter, extra agile, and greater bendy company operating constitution," stated Mr. Lebing Xia, vp and CIO of the Fuyao community. "And with the aid of enabling us to hook up with other cloud-based capabilities like AI, Blockchain and IoT, they should exist able to win much more traffic cost from the cloud."

    Analyst quoteAccording to IDC's international Quarterly 2Q18 Cloud IT Infrastructure Tracker, September 2018, total international spending on cloud IT infrastructure is expected to total $62.2 billion in 2018 with 12 months-over-year expand of 31.1%. while public cloud datacenters will account for the majority of this spending, on-premises deepest clouds will account for very nearly 20% of the overall cloud IT infrastructure market, transforming into at 19.3% yr over year in 2018. "firms savor more than a few enterprise and IT needs a few of which are neatly served through public cloud offerings and a few which are not," pointed out Natalya Yezhkova, research Director, IDC. "On-premises private cloud is an impressive selection for based groups that are seeking for a gradual strategy for remodeling their organization whereas protecting control of their IT infrastructure."

    About IBM CloudWith $18.5B in annual cloud profits, IBM is the world leader in traffic cloud with a platform designed to meet the evolving needs of company and society. relocating past productiveness and charge advancements, the IBM Cloud is tuned for the AI and data demands that are using true differentiation in modern commercial enterprise. IBM's inner most, public and hybrid choices deliver the international scale agencies should sheperd innovation throughout industries.

    developed on open supply frameworks Docker containers and Cloud Foundry, and managed with the Kubernetes container structure, IBM Cloud deepest makes it practicable for corporations to enhance cloud-native functions and also modernize on-premises functions in an trouble to installation them in either deepest cloud settings or the public cloud of their option.

    Media contacts:Jonathan BattyIBM Media family members (Europe)jjbatty@ibm.com

    Michael ZimmermanIBM Media members of the family (US)mrzimmerman@us.ibm.com

    Notes for journalists and editorsExamples of different main international organisations reworking with IBM Cloud deepest:

    CNH Industrial, ItalyCNH Industrial, a frontrunner within the capital items sector operating in the agricultural and edifice gadget, commercial motors, region of expertise motors and powertrain segments, has signed a multi-year cloud settlement with IBM. through the deal it will employ IBM Cloud deepest and Watson synthetic Intelligence to seriously change its traffic approaches - from manufacturing to give chain, earnings & marketing and economic services. IBM Cloud deepest will aid CNH Industrial to optimize its management of commercial enterprise purposes whereas still benefitting from the safety of handle of its personal on-premises infrastructure. The agility and flexibility of ICP has the long-term advantage of producing improved efficiencies in utility construction and will permit quicker time to market for brand spanking modern innovative client capabilities.

    Klirinski Interbankarski Sistemi ad Skopje (KIBS), Macedonia Klirinski Interbankarski Sistemi advert Skopje (KIBS), a Macedonia-based payment gadget operator owned by route of 12 banks is working with IBM to seriously change payment clearing tactics and relieve quicker the mixing of Macedonia's banking paraphernalia with the european. With IBM Cloud inner most KIBS might exist capable of consolidate and seriously change their existing substances into a "digital manufacturing unit" in a position to creating and operating up to date cloud-native applications on the fly. it is hoped that this transformation will reduce time to market for brand spanking modern digital products from one-and-a-half years to simply a pair of months, while optimising working prices and helping KIBS' compliance activities concerning stringent banking laws.

    Sentient.io, SingaporeSentient.io, considered one of Singapore's leading artificial Intelligence businesses, is working with IBM to deliver on its mission to enhance well-known lifestyles with the aid of making human and desktop interactions more herbal and pervasive.Sentient.io has chosen the IBM Cloud deepest as a platform to host Singapore's first AI-as-a-provider (AaaS) platform to allow its customers to seriously change and automate their organizations with AI capabilities reminiscent of notion, understanding, self-gaining information of and difficulty-solving. using IBM Cloud deepest, Sentient.io will relieve executive and enterprise purchasers to fill strict records protection and privateness requirements, modernize current applications by using relocating them to the cloud, and comfortably manipulate the lifecycle of their digital assets.

    Ilmarinen, FinlandIlmarinen, the greatest private insurer in Finland chargeable for the pensions of over 1.1 million finish residents and more than EUR forty five billion in investment assets, has shifted functions to IBM Cloud private to enable it to strengthen modern digital capabilities whereas maximizing its existing IT infrastructure. by inserting its software construction pipeline onto IBM Cloud deepest, Ilmarinen is capable of enormously velocity up construction cycles and crop back infrastructure expenses, cutting the complete software free up time from days to minutes. here is above every essential with increased drive on the world's pension systems because of an aging population.

    Techniker Krankenkasse (TK), GermanyGermany's largest statutory health insurance fund Techniker Krankenkasse (TK) is the employ of IBM Cloud deepest for a brand modern service called TK-protected which gives clients with their medical health insurance statistics by the employ of their smartphone - in spite of time and placement. IBM is already providing information as-a-provider to TK-secure's relaxed facts vault which contains the encrypted health records of TK's insurees across Germany. by route of an open service platform, TK-safe clients can improvement from modern value-addedservices for his or her own health keeping and are in a position to partake suggestions with their physicians, hospitals and service suppliers.

    Mangalore institution, IndiaMangalore university, considered one of India's proper public training associations, will give new-age courses in rising technologies through its affiliated faculties and is leveraging the energy of IBM Cloud private to deliver a common platform that can also exist accessed remotely by route of any student. IBM Cloud private will accelerate on the tuition's IBM power servers as Part of a complete solution which also includes QRadar, MaaS360 and Cognos utility. The solution may exist integrated with the aid of Nihon conversation solutions, an education birth companion of IBM, which is accountable for the start of advanced lessons on cybersecurity and massive information Analytics and provides high-efficiency systems for network and safety purposes.

    SK Holdings C&C, Ltd., South KoreaSK Holdings C&C, a leading IT features firm and IBM traffic accomplice in South Korea turned to IBM Cloud deepest to right away and easily package functions as containers and re-aspect them with IBM microservices. additionally, the traffic is leveraging the software to assist valued clientele modernize their legacy functions and provide a at ease platform from which to accelerate enterprise crucial software across each public and private clouds, in a accurate multi-cloud structure.

    Five9 Vietnam Corp., VietnamFive9 Vietnam is a fast-becoming IT and cloud provider provider that gives its shoppers with every minute thing from cellular and analytics application construction, to deepest and public cloud capabilities. The company has been using IBM Cloud private on account that April to design, strengthen, and paraphernalia functions as containers for handy deployment on the universal public cloud. From there, their clients can tap into IBM microservices, similar to analytics, AI and blockchain, to extend their performance even additional.

    Cision View long-established content to down load multimedia:http://www.prnewswire.com/news-releases/tons of-of-leading-international-corporations-deploy-ibm-cloud-inner most-300729130.html

    supply IBM

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    C5050-384 exam Dumps Source : IBM Cloud Platform Application progress v2

    Test Code : C5050-384
    Test name : IBM Cloud Platform Application progress v2
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    SoftLayer IaaS v2.1 Manager Now Available for the Ensim Automation Suite | killexams.com true questions and Pass4sure dumps

    Enables Service Providers to Expand Their IaaS Offering Portfolio With a Complete Quote to Cash Process

    SAN JOSE, CA--(Marketwired - Mar 15, 2016) - Ensim Corporation, a leading provider of an end-to-end platform for monetizing any offering with marketplace, subscription management, service catalog, provisioning, usage collection, and billing for service providers, MSPs, and enterprises, today announced the availability of a major update to their integrated solution with IBM Cloud / SoftLayer. The integration with the Ensim Automation Suite enables complete customer life-cycle management with complete usage collection, rating, payment, and billing.

    The Ensim Automation Suite enables the complete quote to cash process, from the initial order configuration, quote, approval process, notifications, deployment, and usage tracking, to billing and payment for the complete array of SoftLayer offerings. Providers can bundle with 100s of other XaaS applications that are pre-integrated with the Ensim Automation Suite for monthly, yearly, or supple subscription and payment plans. separate sign-on directly via the Ensim portal to the SoftLayer administrative console ensures ease of management, while automated usage collection ensures accounts are always in sync and accurate. Delegated administration portals enable simplified and automated user and administrator self-service at every levels (customer, agent, reseller, service provider).

    "The progress of Ensim Service Manager for IBM Cloud / SoftLayer enables providers to expand their IaaS offering portfolio and bundling a variety of add-on services, while effectively maintaining traffic objectives and enforcing policy requirements," said David Wippich, CEO, Ensim. "Ensim is supercilious to present a comprehensive platform that enables providers to offer, bundle and differentiate the SoftLayer offerings from a separate portal."

    Ensim Automation Suite and Ensim SoftLayer IaaS Manager v2.1 Key Features:

  • Cloud Marketplace with Catalog, Quoting, Ordering
  • Channel enablement for Resellers and Agents
  • Integration to every SoftLayer Datacenter locations
  • Virtual machine management: Create, Start, Stop, Clone, Edit
  • Create and assign Administrators
  • Bi-directional sync of User accounts
  • Detailed usage collection and reports with parameter details
  • Accurate Invoicing and Cost of Goods reconciliation
  • "Service Providers looking to present IaaS now savor the option of deploying an on-premise virtual machine management platform (Microsoft, VMware or OpenStack) or can leverage SoftLayer's cloud based IaaS platform to meet the demands of their customers," said William Fellows, Research Vice President of 451 Research. "The Ensim Automation Suite offers Private, Public and Hybrid IaaS management from a separate portal and provides robust end-to-end ordering, provisioning, and billing every through a separate pane of glass."

    About Ensim Ensim provides an end-to-end platform for marketplace, storefront, subscription management, service catalog, ticketing, provisioning, usage collection, and billing management with self-service portals for users, organizations, and channels. Monetize and manage any offering such as traffic applications, infrastructure, cloud brokerage, as well as SaaS, IaaS and ITaaS. The Ensim Automation Suite is ready-to-launch as an on-premise or cloud based solution; can integrate with any existing back office environment; and is available in both multi-tenant and dedicated versions to meet service provider and enterprise requirements. For additional information, visit http://www.ensim.com

    About SoftLayer SoftLayer, an IBM Company, provides cloud infrastructure as a service from a growing number of data centers and network points of presence around the world. Customers compass from Web startups to global enterprises. Products and services involve bare metal and virtual servers, networking, turnkey titanic data solutions, private cloud solutions, and more. Unique advantages involve the industry's first Network-Within-a-Network topology for accurate out-of-band access, and an easy-to-use customer portal and robust API for complete remote-access of every product and service management options. SoftLayer was founded in 2005 and is headquartered in Dallas, Texas. SoftLayer was acquired by IBM in July, 2013. For additional information, visit http://www.softlayer.com


    How to elect a Video AI Platform and Evaluate its Results | killexams.com true questions and Pass4sure dumps

    How to elect a Video AI Platform and Evaluate its Results

    Meet the titanic four players in the video artificial intelligence space, then learn how they can accelerate up time-consuming tasks like generating metadata or creating transcriptions.

    Learn more about the companies mentioned in this article in the Sourcebook:

    Why is artificial intelligence (AI) a buzzword right now? The more video content they create, the larger their media libraries get. They only savor a limited amount of humans on their staff to ingest that media, process it, and add metadata tags to it.

    Our organizations exigency relieve making this content more searchable so they can win some more ROI on their content. Let’s inform you toil for a surveillance firm, and you savor 24/7 feeds running on 10 cameras or 100 cameras. You may not exist able to win enough human relieve to search that media, but you could win AI help.

    On the audio side, there’s powerful require for transcription, and there are closed-caption mandates and translation needs as well. They don’t every savor translators on staff, but if they savor AI translation in their system, even an imperfect translation will relieve a lot.

    The titanic Four

    There are four key players in video AI: Amazon Web Services (AWS), Google Cloud, IBM Watson Media, and Microsoft Azure’s Video Indexer. Each has numerous services.

    The four core services that AWS has for AI are Rekognition, for computer vision and adding abysmal learning-based visual search and image classification; Comprehend, which tries to understand sentiment and what’s going on within the language; Transcribe, which converts audio to text files; and Translate.

    The Google Cloud platform features Video Intelligence, Natural Language API, Speech-to-Text, and the Translation API.

    IBM Watson Media is AI for media workflow and video processing, but the titanic dissimilarity between IBM’s platform and the others is that it requires breaking the video into individual segments. The three products created under the banner of Watson Media are Video Recommendations, Captioning (speech-to-text), and Video Enrichment (computer vision).

    The fourth is Microsoft Azure, aka Video Indexer. To access Microsoft’s cognitive and indexing features, travel to videoindexer.ai, where there’s a icy user interface you can log into and upload videos to, and start getting AI-generated metadata right away for free.

    This article will recognize at these platforms and services in terms of four main features: face/object/scene recognition, sentiment analysis, surveillance, and transcription/translation. When choosing a platform, retain in intellect that it’s every about the employ case. every four platforms recur JSON (JavaScript object Notation) data, so there’s nothing stopping you from using every of them if you want to. You can notice a demo of a custom app that my company, RealEyes Media, built on top of AWS and Google Cloud, in a clip from a presentation I did at Streaming Media East 2018.

    How to win Started

    If you don’t savor developers in-house at your organization, a lot of these vendors present demo versions of their platforms that you can play around with (Figure 1). The free version of Microsoft Azure Video Indexer, for example, is quite robust. You can actually retract widgets and embed them into your own systems. Of the four platforms they discuss in this article, Video Indexer is the most complete product you can access without having to travel through condense negotiations.

    Demo versions of leading video AI platforms, clockwise from left: Google Cloud, IBM Watson Media, Microsoft Azure Video Indexer, AWS

    Google Cloud and AWS present demos on their pages, but they don’t really expose the services to the degree that you can embed them into your own system. In this context, “embed” essentially means writing some code to win an iFrame to load on a page inside of your site. The online demo versions of Google Cloud and AWS aren’t really conducive to that, but you can upload your own videos, wait for the apps to process them, and notice how well the service will toil with your videos.

    IBM sells a pair of Watson products, such as Video Enrichment (top right in pattern 1). They are API-first. Theoretically, you can buy this paid product and communicate between your system and IBM’s to tow metadata into your system.

    Generating metadata is one of the titanic employ cases for AI. Let’s inform you’ve archived multiple seasons of a TV show, and you savor a media asset manager (MAM) that houses every this metadata about every of those stored assets. Wouldn’t it exist powerful to savor the computer generate some of that metadata for you, so that in addition to the title, season, and episode name, you’d savor things like “car crash,” “leopard,” and “little baby girl” (or whatever terms apply to your content) that you can actually employ to search and determine your content much more easily? The first thing your developers are going to want to know about is, “What’s the learning curve? What software progress kit (SDK) is available for each of these platforms?”

    AWS has a client SDK, which basically acts as an accelerator so your developers don’t savor to write every of the code from scratch. They can build their code on top of the boilerplate AWS provides, with SDKs for Android, iOS, Java, .NET, etc. My team of developers has played around with this SDK, and they savor found it comprehensive.

    One necessary step in choosing a video AI platform is to let your developers test whatever demo version is available. And listen to their feedback, because your team members are going to exist more productive if they don’t savor to expend as much time trying to grok how to toil with the software.

    Like AWS, the Google Cloud platform has a trustworthy number of client SDKs: .NET, Node.js, Go, Java, etc. But from my developers’ perspectives, Google’s API documentation is quite verbose, and it takes a lot of clicks to win to what you need—much more so than the AWS developer documentation, in their opinion. For instance, if you just want to know how to dispatch a video up to the Google service, rather than seeing the signature of the payload that you want to upload, you savor to wade through three or four paragraphs on every separate data point within that signature.

    IBM Watson Media's API reference lives behind a paywall. When you want to employ it, you counsel the IBM Watson Media people, “This is my employ case. I want to play around with your system, because I assume I’m going to buy it.” Then you badge some contracts. In my case, as an IBM partner, they were benevolent enough to partake the API documentation with me. It looked pretty straightforward.

    Azure has client SDKs, but to interact with the Video Indexer you will just employ its API without an SDK. If you exigency the extra hoist that an SDK can provide, then Video Indexer might not exist the right solution for you. Amazon and Google savor things like Java, Android, iOS, Ruby, and so on, as you can notice in pattern 2. Your developers might exist able to build something faster on those platforms. The Video Indexer documentation is outstanding. It’s well-laid-out, and you can inline-test it as long as you savor an energetic account.

    API Learning Curve/SDK rundown for AWS, Google Cloud, IBM Cloud/Watson Media, and Microsoft Azure Video Indexer

    Testing the Platforms

    I’ve tested lots of different kinds of footage, but because so much data comes back, I’ve narrowed the focus in my testing to emphasize specific employ cases. When it comes to translation and transcription, video surveillance, or metadata and objects, which platforms toil best in those cases?

    One thing to retain in intellect with AI is that AI is only as smart as the data you’ve trained it with. In the case of IBM Watson, if you travel to the website and recognize at some of the case studies, you’ll notice that the company did a project for the US Open tennis tournament which was instrumental in training its AI. If you’re in the sports industry, IBM Watson might savor more accurate results for you when it comes to object detection or seeing when a ball is being hit across the court. On the other hand, if you finish word footage, Google might serve you better, because users live stream their word over YouTube.

    It’s necessary to reckon these different kinds of employ cases when assessing how well a particular platform will toil for you, because ultimately, the data that’s being processed by every these machine-learning solutions is what’s training the AI to exist smarter. It’s similar to any process of accumulating knowledge. I Come from a developer background, but I’m in the streaming media industry. If you put a question to me about which camera is the best camera, I won’t savor a trustworthy answer, because I don’t savor that data in my background.

    That’s a route to assume about AI: You’re going to exist sending it specific data, and it’s going to learn off that data. The type of data that it learns off of is going to gain it more accurate in one route or another.

    Interpreting the Data

    Figure 3 shows an instance of the benevolent of data you win back with these systems. Generally, AI solutions toil like this: They savor an API that allows your developers to hit an cessation point and pass some data in. It’s similar to you going into a browser, typing “google.com,” searching for “ducks,” and hitting Enter. A developer uses an API to programmatically hit an cessation point like google.com. It might exist something like “myaiservice.com/v2/api/visionservices/detectObjects” and you would pass it a data payload that the API expects.

    Sample data from a processed video payload on an AI platform. Note that, since this screenshot was taken in May 2018, Microsoft Azure Video Indexer has started providing aplomb values in its response JSON (click to enlarge).

    Again, it’s like when you travel to Google and type in a search string and then hit Enter. A developer will dispatch up a payload that says, “My video is here. delight process it.” Then you wait for the processing to happen, because it’s not instantaneous. Once the processing is done, you’ll savor data that you can tow down, comparable to search results in Google.

    All of these services employ JSON, the data exchange format shown in pattern 3. This is great, because it enables you to win data from multiple services normalized and used in a custom application. When you’re working with one format, it makes it a lot easier to parse through the immense amount of data you win back.

    In the instance shown in pattern 3, I sent up a trailer of American Psycho. You can notice the data it returned in AWS on the far left. It says, “I found a person at timestamp 18196 milliseconds, and I’m 97.8222 percent sure.” That’s the data you win back with object detection in AWS.

    With Azure Video Indexer (second column from left), it says, “I found a person in the time compass 00:00:21.438 to 00:00:22.14.” In the Google column (third from left), you can notice that it identified a “human” “entity” in multiple instances, with time signatures in seconds and nanos, and aplomb values in the 85 percent–96 percent range.

    Keep in intellect that the computer doesn’t actually “see” a person; it’s learning from every of the data that it’s processed historically and making its best judgment based on that, so knowing the aplomb value is extremely important. If your primary interest is identifying objects and you want it to exist accurate, you should definitely pay attention to the aplomb values being reported.

    Related Articles

    Streaming Media's Tim Siglin interviews RealEyes Media Chief of Technology Jun Heider at Streaming Media East 2018.

    Publishers can set the module to notify outside partners of QoE problems, automating a process now done by technicians and engineers.

    Look for artificial intelligence and machine learning to better content delivery, video compression, and viewer personalization, strengthening the entire workflow.


    Comparing Kubernetes to Pivotal Cloud Foundry — A Developer’s Perspective | killexams.com true questions and Pass4sure dumps

    All this means that with PCF, your build artifact is your aboriginal deployment artifact, while in Kubernetes your build artifact is a docker image. With Kubernetes, you exigency to define the template for this docker image yourself in a Dockerfile, while in PCF you win this template automatically from a buildpack.

    Management Console Cloud Foundry

    PCF separates the web dashboard to two sever target audiences.

  • Ops Manager is targeted at the IT professional that is responsible for setting up the virtual machines or hardware that will exist used to create the PCF cluster.
  • Apps Manager is targeted at the developer that is responsible for pushing application code to testing or production environments. The developer is completely unaware of the underlying infrastructure that runs its PCF cluster. every he can really notice is the quotas assigned to his organization, such as reminiscence limits.
  • Kubernetes

    Kubernetes takes a different approach. You win one dashboard to manage everything. Here’s a typical Kubernetes dashboard:

    As you can notice from the left-hand side, there is a lot of data to process here. You savor access to persistent volumes, daemons, definition of roles, replication controllers etc. It’s arduous to focus on what are the developer’s needs and what are the IT needs. Some might counsel you this is the selfsame person in a Devops culture, and that’s a honest point. Still, in reality-it is a more confusing paradigm compared to a simple application manager.

    Command Line Interface Cloud Foundry

    Cloud foundry uses a command line interface called cf. It is a cli that lets you control every aspects of the developer interaction. Following in the footsteps of simplicity that you might savor already noticed, the concept is to retract an opinionated view to practically everything.

    For example, if you are in a folder that contains a spring boot jar file called myapp.jar, you can deploy this application to PCF with the following command:

    cf thrust myapp -p myapp.jar

    That’s it! That’s every you need. PCF will lookup the current working directory and find the jar executable. It will then download the java buildpack, create a container, compute the required reminiscence settings, delpoy it to the currently logged-in org and space in PCF, and set a route based on the application name:

    wabelhlp0655019:test odedia$ cf thrust myapp -p myapp.jar Updating app myapp in org OdedShopen / space production as user… OK Uploading myapp… Uploading app files from: /var/folders/_9/wrmt9t3915lczl7rf5spppl597l2l9/T/unzipped-app271943002 Uploading 977.4K, 148 files Done uploading OK Starting app myapp in org OdedShopen / space production as user…Downloading pcc_php_buildpack…Downloading binary_buildpack…Downloading python_buildpack…Downloading staticfile_buildpack…Downloading java_buildpack…Downloaded binary_buildpack (61.6K)Downloading ruby_buildpack…Downloaded ruby_buildpackDownloading nodejs_buildpack…Downloaded pcc_php_buildpack (951.7K)Downloading go_buildpack…Downloaded staticfile_buildpack (7.7M)Downloading ibm-websphere-liberty-buildpack…Downloaded nodejs_buildpack (111.6M)Downloaded ibm-websphere-liberty-buildpack (178.4M)Downloaded java_buildpack (224.8M)Downloading php_buildpack…Downloading dotnet_core_buildpack…Downloaded python_buildpack (341.6M)Downloaded go_buildpack (415.1M)Downloaded php_buildpack (341.7M)Downloaded dotnet_core_buildpack (919.8M)Creating containerSuccessfully created containerDownloading app package…Downloaded app package (40.7M)Staging…— — -> Java Buildpack Version: v3.18 |https://github.com/cloudfoundry/java-buildpack.git#841ecb2— — -> Downloading Open Jdk JRE 1.8.0_131 from https://java-buildpack.cloudfoundry.org/openjdk/trusty/x86_64/openjdk-1.8.0_131.tar.gz (found in cache)Expanding Open Jdk JRE to .java-buildpack/open_jdk_jre (1.1s)— — -> Downloading Open JDK like reminiscence Calculator 2.0.2_RELEASE from https://java-buildpack.cloudfoundry.org/memory-calculator/trusty/x86_64/memory-calculator-2.0.2_RELEASE.tar.gz (found in cache)Memory Settings: -Xmx681574K -XX:MaxMetaspaceSize=104857K -Xss349K -Xms681574K -XX:MetaspaceSize=104857K — — -> Downloading Container Security Provider 1.5.0_RELEASE from https://java-buildpack.cloudfoundry.org/container-security-provider/container-security-provider-1.5.0_RELEASE.jar (found in cache) — — -> Downloading Spring Auto Reconfiguration 1.11.0_RELEASE from https://java-buildpack.cloudfoundry.org/auto-reconfiguration/auto-reconfiguration-1.11.0_RELEASE.jar (found in cache) Exit status 0Uploading droplet, build artifacts cache…Uploading build artifacts cache…Uploading droplet…Staging completeUploaded build artifacts cache (109B)Uploaded droplet (86.2M)Uploading completeDestroying containerSuccessfully destroyed container0 of 1 instances running, 1 starting0 of 1 instances running, 1 starting0 of 1 instances running, 1 starting0 of 1 instances running, 1 starting1 of 1 instances running

    Although you can start with barely any intervention, this doesn’t spell you give up any control. You savor a lot of customizations available in PCF. You can define your own routes, set the number of instances, max reminiscence and disk space, environment variables etc. every of this can exist done in the cf cli or by having a manifest.yml file available as a parameter to the cf thrust command. A typical manifest.yml file can exist as simple as the following:

    applications:- name: my-appmemory: 512Minstances: 2env:PARAM1: PARAM1VALUEPARAM2: PARAM2VALUE

    The main takeaway is this: with PCF, provide the information you know, and the platform will imply the rest. Cloud Foundry’s haiku is:

    Here’s my code

    Run it on the cloud for me.

    I don’t keeping how.

    Kubernetes

    In kubernetes, you interact with the kubectl cli. The commands are not complicated at all, but there is still a higher learning curve from what I’ve experienced so far.

    For starters, a basic assumption is that you savor a private docker registry available and configured (unless you only draw to deploy images available on public registries such as docker hub). Once you savor that registry up and running, you will exigency to thrust your Docker image to that registry.

    Now that the registry contains your image, you can initiate commands to kubectl to deploy the image. Kubernetes documentaiotn gives the instance of starting up an nginx server:

    # start the pod running nginx$ kubectl accelerate --image=nginx nginx-app --port=80 --env="DOMAIN=cluster"deployment "nginx-app" created

    The above command only spins up a kubernetes pod and runs the container.

    A pod is an abstraction that groups one or more containers to the selfsame network ip and storage. It’s actually the smallest deployable unit available in Kubernetes. You can’t access a docker container directly, you only access its pod. Usually, a pod would accommodate a separate docker container, but you can accelerate more. For example, an application container might want to savor some monitoring dameon container in the selfsame pod.

    In order to gain the container accessible to other pods in the Kubernetes cluster, you exigency to wrap the pod with a service:

    # expose a port through with a service$ kubectl expose deployment nginx-app --port=80 --name=nginx-httpservice "nginx-http" exposed

    Your container is now accessible inside the kubernetes cluster, but it is still not exposed to the outside world. For that, you exigency to wrap your service with an ingress.

    Note: Ingress is still considered a beta feature!

    I could not find a simple command to expose an ingress at this point (please reform me if I’m wrong!). It appears that you must create an ingress descriptor file first, for example:

    apiVersion: extensions/v1beta1kind: Ingressmetadata:name: test-ingressannotations:ingress.kubernetes.io/rewrite-target: /spec:rules:- http:paths:- path: /testpathbackend:serviceName: testservicePort: 80

    Once that file is available, you can create the ingress by issuing a command

    kubectl create -f my-ingress.yaml

    Note that unlike the separate manifest.yml in PCF, the deployment yml files in Kubernetes are separated — there is one for pod creation, one for service creation and as you saw above — one for ingress creation. A typical descriptor file is not entirely overwhelming but I wouldn’t convene it the most user friendly either. For example, here’s a descriptor file for nginx deployment:

    apiVersion: apps/v1 # for versions before 1.9.0 employ apps/v1beta2kind: Deploymentmetadata:name: nginx-deploymentlabels:app: nginxspec:replicas: 3selector:matchLabels:app: nginxtemplate:metadata:labels:app: nginxspec:containers:- name: nginximage: nginx:1.7.9ports:- containerPort: 80

    All this to say — with kubernetes, you exigency to exist specific. Don’t expect deployments to exist implied. If I had to create a haiku for Kubernetes, it’ll exist probably something like this:

    Here’s my code

    I’ll counsel you exactly how you should accelerate it on the cloud for me

    And don’t you dare gain any assumptions on the delployment without my written consent!

    Zero Downtime Deployments

    Both platforms champion the capacity to deploy applications with zero downtime, however this is one region where Kubernetes wins in my opinion, since it provides a built-in mechanism for zero downtime deployments with rollback.

    Cloud Foundry

    With Pivotal Cloud Foundry, there’s no built-in mechanism to champion a rolling update, you’re basically expected to finish some cf cli trickery to achieve the update with zero downtime. The concept is called blue-green deployment. If I had to clarify it in step-by-step guide, it’ll probably exist something like this:

  • Starting point: you savor myApp in production, and you want to deploy a modern version of this app — v2.
  • Deploy v2 under a modern application name, for example — myApp-v2
  • The modern app will savor its own initial route — myApp-v2.mysite.com
  • Perform testing and verification on the modern app.
  • Map an additional route to the myApp-v2 application, using the selfsame route as the original application. For example:
  • cf map-route myApp-v2 mysite.com —hostname myApp
  • Now requests to your application are load balanced between v1 and v2. Based of the number of instances available to each version, you can achieve A/B testing. For example — if you savor 4 instances of v1 and 1 instance of v2, 20% of your clients will exist routed to the modern codebase.
  • If you identify issues at any point — simply remove v2. No harm done.
  • Once you are satisfied, scale the number of available instances of v2, and reduce or completely delete the instances of v1.
  • Remove the myApp-v2.mysite.com route from v2 of your application. You savor now fully migrated to the modern codebase with zero downtime, including sanity testing facet and potentially A/B testing phase.
  • Note: The cf cli supports plugin extensions. Some of them provide automated blue-green deployments, such as blue-green-deploy, autopilot and zdd. I personally found blue-green-deploy to exist very facile and intuitive, especially due to its champion for automated smoke tests as Part of the deployment.

    Kubernetes

    kubectl has a built-in champion for rolling updates. You basically pass a modern docker image for a given deployment, for example:

    kubectl set image deployments/kubernetes-bootcamp kubernetes-bootcamp=jon/kubernetes-bootcamp:v2

    The command above tells kubernetes to achieve a rolling update between every pods of the kubernetes-bootcamp deployment from its current image to the modern v2 image. During this rollout, your application remains available.

    Even more impressive — you can always revert back to the previous version by issuing the undo command:

    kubectl rollout undo deployments/kubernetes-bootcamp External Load Balancing

    As they saw previously, both PCF and Kubernetes provide load balancing for your application instances/pods. Once a route or an ingress is added, your application is exposed to the outside world.

    If we’ll retract an external view of the levels of abstraction that are needed to achieve your application, they can record them as follows:

    Kubernetes ingress → service → pod → container Cloud Foundry route → container Internal Load Balancing (Service Discovery) Cloud Foundry

    PCF supports two methods of load balancing inside the cluster:

  • Route-based load balancing, in the traditional server-side configuration. This is similar to external load balancing mentioned above, however you can specify inevitable domains to only exist accessible from within PCF, thereby making them internal.
  • Client side load balancing by using Spring Cloud Services. This set of services offers features from the Spring Cloud frameworks that are based on Netflix OSS. For service discovery, Spring Cloud Services uses Netflix Eureka.
  • Eureka runs as its own service in the PCF environment. Other applications register themselves with Eureka, thereby publishing themselves to the comfort of the cluster. Eureka server maintains a heartbeat health check of every registered clients to retain an up-to-date list of sound instances.

    Registered clients can connect to Eureka and put a question to for available endpoints based on a service id (the value of spring.application.name in case of Spring Boot applications). Eureka would recur a list of every available endpoints, and that’s it. It is up to the client to actually access one of these endpoints. That is usually done using frameworks like Ribbon or Feign for client-side load balancing, but that is an implementation detail of the application, and not related to PCF itself.

    Client-side load balancing can theoretically scale better since each client keeps a cache of every available endpoints, and can continue working even if Eureka is temporarily down.

    If your application already uses Spring Cloud and the Netflix OSS stack, PCF fits your needs like a glove.

    Kubernetes

    Kubernetes uses DNS resolution to identify other services within the cluster. Inside the selfsame namespace, you can lookup another service by its name. In another namespace, you can lookup the service’s name followed by a dot and then the other namespace.

    The major profit that Kubernetes’ load balancing offers is not requiring any special client libraries. Eureka is mostly targeted at java-based applications (although solutions exist for other languages). With Kubernetes, you can gain load-balanced http calls to any Kubernetes service that exposes pods, regardless of the implementation of the client or the server. The load-balancing domain name is simply the name of the service that exposes the pods. For example:

  • You savor an application called my-app in namespace zone1
  • It exposes a win /myApi comfort endpoint
  • There are 10 pods of this container in the cluster
  • You created a service called my-service that exposes this application to the cluster
  • From any other pod inside the namespace, you can call:
  • GET https://my-service/myApi
  • From any other pod in any other namespace in the cluster, you can call:
  • GET https://my-service.zone1/myApi

    And the API would load-balance over the available instances. It doesn’t matter if your client is written in Java, PHP, Ruby, .NET or any other technology.

    Marketplace

    PCF offers a services marketplace. It provides a ridiculously simple route to bind your application to a service. The term service in PCF is not the selfsame as a service in kubernetes. A PCF service binds your application to things like a database, a monitoring tool, a message broker etc. Some services that are available out of the box are:

  • Spring Cloud Services, which provides access to Eureka, a Config Server and a Hystrix Dashboard.
  • RabbitMQ message broker.
  • MySQL.
  • Third party vendors can implement their own services as well. Some of the vendor offerings involve Datastax for Cassandra and Redislabs for Redis in-memory database. Here’s a screenshot of available services on Pivotal Web Services:

    IBM Bluemix is another Cloud Foundry provider that offers its own services such as IBM Watson for AI and machine learning applications.

    Every service has different plans available based on your SLA needs, such as a tiny database for progress or a highly-available database for a production environment.

    Last but not least, you savor the option to define user-provided services. These allow you to bind your application to an existing service that you already have, such as an Oracle database or an Apache Kafka message broker. A user provided service is simply a group of key-value pairs that you can then inject into your application as environment variables. This offloads any specific configuration such as URLs, usernames or passwords to the environment itself — services are bound to a given PCF space.

    Kubernetes

    Kubernetes does not present a marketplace out of the box. There is a service catalog extension that allows for a similar service catalog, however it is still in beta.

    Note that since it can accelerate any docker container — Dockerhub can exist considered as a kubernetes marketplace in a way. You can basically accelerate anything that can accelerate in a container.

    Kubernetes does savor a concept similar to user-provided services. Any configuration or environment variables can exist in ConfigMaps, which allow you to externalise configuration artifacts away your container, thus making it more portable.

    Configuration

    Speaking of configuration — One of the features of the Spring Cloud Services service is Spring Cloud Config. It is another service that is targeted specifically for Spring Boot applications. The config service serves configuration artifacts from a git repository of your choosing, and allows for zero-downtime configuration changes. If your Spring beans are annotated with @RefreshScope, they can exist reloaded with updated configuration by issuing a POST /refresh API convene to your application. The property files that are available as configuration sources are loaded based on a pre-defined loading order, which provides some sort of an inheritance-based mechanism to how the configuration is loaded. It’s a powerful solution, but again assumes that your applications are based on the Spring Boot stack. If you’re already using spring boot with a config server today — PCF fits like a glove.

    In Kubernetes, you can still accelerate a config server as a container, but that would probably become an unneeded operational overhead since you already savor built-in champion for ConfigMaps. employ the aboriginal solution for the platform you travel with.

    Storage Volumes

    A titanic differentiator of Kubernetes is the capacity to attach a storage volume to your container. Kubernetes uses etcd as a means to manage storage volumes, and you can attach such a volume to any of your containers. This means you win a dependable storage solution, which lets you accelerate storage-based containers like a database or a file server.

    In PCF, your application is fully stateless. PCF follows the 12-factor apps model and one of these models assumes that your application has no state. You should theoretically retract the selfsame application that runs today in your on-prem data center, amble it to AWS, and provided there is adequate connectivity, it should just work. Any storage-based solution should exist offloaded to either a PCF service, or to a storage solution outside the PCF cluster itself. This may exist regarded as an advantage or a handicap depending on your application and architecture. For stateless application runtimes such as web servers, it is always a trustworthy concept to decouple it from any internal storage facility.

    Onboarding Kubernetes

    Getting started with Kubernetes was not easy. As mentioned above, you can’t just start with a 5-minutes quick start guide, there are just too many things you exigency to know and too many assumptions about what you already savor (docker registry and a git repository are often taken for granted).

    Just taking a recognize at the excellent Kubernetes Basics interactive tutorial shows the flush of information required on the platform. For a basic on-boarding, there are 6 steps, each one of them containing quite a few commands and terminologies you exigency to understand. Trying to ensue the tutorial on a local minikube vm instead of the pre-configured online cluster is quite difficult.

    Cloud Foundry

    Getting started with PCF is easy. Your developers already know how to develop their spring boot / nodejs / php / ruby / .NET application. They already know what its artifacts are. They probably already savor some jenkins pipeline in place. They just want to accelerate the selfsame thing in a cloud environment.

    If we’ll retract a recognize at PCF’s “Getting Started with Pivotal Cloud Foundry”, it’s almost comical how minute is required to win something up and running. When you exigency more knotty interaction, it’s every available for you, either in the cf cli, as Part of a manifest.yml, or in the web console, but this doesn’t avert you from getting started quickly.

    If you mainly develop server-based applications in java or nodejs, PCF gets you to the cloud simply, quickly and more elegantly.

    Vision Kubernetes

    Kubernetes is truly a powerful open source platform. Kudos to Google for giving up control and letting the community finish its thing. That’s probably the number one intuition why Kubernetes has taken off so quickly while other solutions like Docker swarm are falling behind. Other vendors also present solutions that present a more PaaS-like undergo on top of Kubernetes, such as RedHat OpenShift.

    But with such a diverse and thriving eco-system, the path forward can exist one of many different directions. It really does feel like a Google product in a way — maybe it will remain supported by Google for years, maybe it will change with barely any backwards compatibility, or maybe they’ll cancel it and amble to the next titanic thing (Does anyone recollect Google Buzz, Google Wave or Google Reader?). Any AngularJS developer who’s trying to amble to Angular 5 can counsel you that backwards compatiblity is not a top priority.

    Cloud Foundry

    Cloud Foundry is also a thriving open source platform, but it is pretty limpid who sets the tone here. It is Pivotal, with additional contributions from IBM. Yes, it’s open source, but the enterprise play here is Pivotal Cloud Foundry, which provides added value like the services marketplace, Ops Manager etc. And on that side, it’s a limited democracy. This is a product that is meant to serve enterprise customers, and the feature set would first and foremost reply those needs.

    If Kubernetes is Google, then PCF is Apple.

    A minute more of a walled garden, more controlled, better design/experience layer, and a commitment for delivering a powerful product. I feel like the platform is more focused, and focus is captious in my line of work.

    PKS

    The true flabbergast of the recently announced PCF 2.0 was that every I’ve been talking about throughout this article is now just one Part of a larger offering. The aplication runtime (everything that is referred to as PCF in this article) is now called Pivotal Application Service (PAS). There is also a modern serverless solution called Pivotal office Service (PFS), and lastly — a modern Kubernetes runtime called Pivotal Container Service (PKS). This means that Pivotal Cloud Foundry now gives you the best of both worlds: A powerful application runtime for speedy onboarding of cloud-native applications, as well as a powerful container runtime when you exigency to develop generic low-level containers.

    Conclusion

    In this article I tried to partake my personal experiences of working with both platforms. Although I am a bit biased towards PCF, it is for a trustworthy reason — it has served me well. I approached Kubernetes with an open mind, and found it to exist a very many-sided platform, but also one that requires a steeper learning curve. Maybe I got spoiled by animate in the Spring eco-system for too long :). With the latest announcement of PKS, it appears that Pivotal Cloud Foundry is set to present the best integrated PaaS — one that lets you accelerate cloud aboriginal applications as quickly and simply as possible, while also exposing the best generic container runtime when that is needed. I can notice this becoming very useful in many scenarios. For example, Apache Kafka is one of the best message brokers available today, but this message broker still doesn’t savor a PCF service available, so it has to accelerate externally on virtual machines. Now with PCF 2.0, I can accelerate Apache Kafka in docker containers inside PCF itself.

    The main conclusion is that this is definetly not a this or that discussion. Since both the application runtime and the container runtime now live side by side in the selfsame product, the future seems promising for both.

    Thank you for reading, and cheerful coding!

    Oded Shopen

    Visit my homepage: http://odedia.org

    Follow me on twitter: https://twitter.com/odedia

    Follow me on LinkedIn: https://www.linkedin.com/in/odedia/

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    Computer Security: Principles and PracticeComputer Security: Principles and Practice
    By William Stallings, Lawrie Brown
    Publisher : Pearson (Aug 2017)
    ISBN10 : 0134794109
    ISBN13 : 9780134794105
    Our ISBN10 : 1292220619
    Our ISBN13 : 9781292220611
    Subject : Computer Science & Technology
    Price : $65.00
    Urban EconomicsUrban Economics
    By Arthur O’Sullivan
    Publisher : McGraw-Hill (Jan 2018)
    ISBN10 : 126046542X
    ISBN13 : 9781260465426
    Our ISBN10 : 1260084493
    Our ISBN13 : 9781260084498
    Subject : Business & Economics
    Price : $39.00
    Urban EconomicsUrban Economics
    By Arthur O’Sullivan
    Publisher : McGraw-Hill (Jan 2018)
    ISBN10 : 0078021782
    ISBN13 : 9780078021787
    Our ISBN10 : 1260084493
    Our ISBN13 : 9781260084498
    Subject : Business & Economics
    Price : $65.00
    Understanding BusinessUnderstanding Business
    By William G Nickels, James McHugh, Susan McHugh
    Publisher : McGraw-Hill (Feb 2018)
    ISBN10 : 126021110X
    ISBN13 : 9781260211108
    Our ISBN10 : 126009233X
    Our ISBN13 : 9781260092332
    Subject : Business & Economics
    Price : $75.00
    Understanding BusinessUnderstanding Business
    By William Nickels, James McHugh, Susan McHugh
    Publisher : McGraw-Hill (May 2018)
    ISBN10 : 1260682137
    ISBN13 : 9781260682137
    Our ISBN10 : 126009233X
    Our ISBN13 : 9781260092332
    Subject : Business & Economics
    Price : $80.00
    Understanding BusinessUnderstanding Business
    By William Nickels, James McHugh, Susan McHugh
    Publisher : McGraw-Hill (Jan 2018)
    ISBN10 : 1260277143
    ISBN13 : 9781260277142
    Our ISBN10 : 126009233X
    Our ISBN13 : 9781260092332
    Subject : Business & Economics
    Price : $77.00
    Understanding BusinessUnderstanding Business
    By William Nickels, James McHugh, Susan McHugh
    Publisher : McGraw-Hill (Jan 2018)
    ISBN10 : 1259929434
    ISBN13 : 9781259929434
    Our ISBN10 : 126009233X
    Our ISBN13 : 9781260092332
    Subject : Business & Economics
    Price : $76.00
    C5050-384C5050-384
    By Peter W. Cardon
    Publisher : McGraw-Hill (Jan 2017)
    ISBN10 : 1260128474
    ISBN13 : 9781260128475
    Our ISBN10 : 1259921883
    Our ISBN13 : 9781259921889
    Subject : Business & Economics, Communication & Media
    Price : $39.00
    C5050-384C5050-384
    By Peter Cardon
    Publisher : McGraw-Hill (Feb 2017)
    ISBN10 : 1260147150
    ISBN13 : 9781260147155
    Our ISBN10 : 1259921883
    Our ISBN13 : 9781259921889
    Subject : Business & Economics, Communication & Media
    Price : $64.00
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