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C5050-384 IBM Cloud Platform Application progress v2

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

Test Code : C5050-384
Test appellation : IBM Cloud Platform Application progress v2
Vendor appellation : IBM
: 56 actual Questions

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IBM IBM Cloud Platform Application

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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 exact for AI grows.

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IBM publicizes Cloud-based mostly neighborhood Platform for Cyber safety functions | killexams.com actual Questions and Pass4sure dumps

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 novel cloud-based neighborhood platform for cyber safety applications. IBM safety unite is the primary safety cloud platform developed on open federated technologies, with AI at its core, to analyze 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 unite is designed to befriend enhance effectivity and collaboration as groups gape 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 novel personalized and complete options to manipulate safety consequences, reminiscent of SOC Operations workflows or Digital trust. 

IBM safety unite will prolong the wealthy set of capabilities from IBM's protection items, by the consume 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 live 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 unite 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 befriend manipulate one of the greatest safety challenges today by means of open requirements, that could support pave the way towards collaborative innovation. as it is developed on open necessities, it may possibly support corporations construct exciting microservices, forward novel 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 besides live leveraged by means of any app or reply integrated with the platform. 

IBM security connect will turn into the domestic of IBM's current protection App trade and every bit of IBM security functions developed on a platform powered by IBM Cloud, however entirely compatible with different cloud providers.  IBM security will besides champion the creation of novel open standards in burgeoning areas such as the sharing of response playbooks and analytics patterns and should actively invest in constructing novel 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 bit of the way 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 recrudesce 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 routine of federating facts permits purchasers to depart their information where it's, as adverse to pile costly statistics lakes, that may complicate or outright evade protection statistics analysis.

IBM security connect will besides live an integral fragment 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 beneficial 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 unite will operate as an open platform with an open construction community.  As a fragment 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 absorb committed to integrating with IBM security connect so as to befriend deliver more suitable information sharing across safety companies for their joint shoppers.  many of these vendors will besides contribute to pile 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 live built into IBM security unite inside months of launch, widening the attain of the platform to support control compliance and manipulate threats.

as an instance, some of the first options being established by clients will heart 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 constituent security items will besides live 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 erudition 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 position security practitioners can collaborate and share integrations.

IBM safety connect is designed to Make 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 unite is predicted to live obtainable in 1Q 2019.

About IBM security 

IBM safety presents probably the most superior and built-in portfolios of trade 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, please determine www.ibm.com/protection, comply with IBMSecurity on Twitter or debate with the IBM security Intelligence weblog. 

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

View customary content material to down load multimedia:http://www.prnewswire.com/information-releases/ibm-proclaims-cloud-based-community-platform-for-cyber-security-purposes-300730681.html


tons of of leading world organizations set up IBM Cloud private | killexams.com actual 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 novel 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 absorb turned to the platform to assist modernize their operations. They embrace novel Zealand Police, China's Fuyao community, Japan's Aflac assurance, Turkey's credit score bureau Kredi Kayit Bürosu and Brazil's fidelity 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 effectual AI capabilities comparable to IBM Watson assistant and IBM Watson Speech-to-textual content, as well as befriend 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 live 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 manipulate crime and preserve the community protected. NZP is exploring how IBM Cloud inner most and Kubernetes containers can befriend to modernize its present techniques as well as instantly launch novel 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 consume of IBM Cloud private to assist integrate the administration of enterprise applications throughout its world manufacturing and enterprise operations, guaranteeing the free flood 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 pile of novel items and features.
  • Kredi Kayit Bürosu (KKB) provides the country wide cloud infrastructure for Turkey's finance trade. eventual 12 months KKB dependent a novel statistics core in Ankara and is now using IBM cloud inner most to befriend 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 inordinate requirements for statistics protection and privateness.
  • Brazil's fidelity national assistance capabilities (FIS), a global leader in saturate processing options for the monetary 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 keep away from fraud.
  • "The cloud has evolved in a extremely short time from being a way to Cut 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, maxim primary enhancements to the platform, ranging from AI capabilities to additional public cloud assist. beginning today, IBM Watson Speech-to-textual content is now obtainable with the brand novel IBM Cloud private edition 3.1, making it the first time the tool is obtainable in an on-premises atmosphere. With Watson Speech-to-text, users can immediately transcribe and analyze audio from seven distinctive languages.

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

    IBM besides announced these days that IBM Cloud inner most is now purchasable on the IBM Public Cloud, to support clients to with ease circulation their enterprise workloads from on-premises methods to the public cloud to live 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 fancy AI, Blockchain and IoT, they should live able to secure much more trade 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 absorb 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 altenative 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 trade cloud with a platform designed to meet the evolving needs of company and society. relocating past productiveness and cost advancements, the IBM Cloud is tuned for the AI and data demands that are using actual differentiation in modern commercial enterprise. IBM's inner most, public and hybrid choices deliver the international scale agencies should pilot 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 besides modernize on-premises functions in an endeavor 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 pile gadget, commercial motors, zone of expertise motors and powertrain segments, has signed a multi-year cloud settlement with IBM. through the deal it will consume IBM Cloud deepest and Watson synthetic Intelligence to seriously change its trade 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 manipulate of its personal on-premises infrastructure. The agility and flexibility of ICP has the long-term odds of producing improved efficiencies in utility construction and will permit quicker time to market for brand spanking novel innovative client capabilities.

    Klirinski Interbankarski Sistemi ad Skopje (KIBS), Macedonia Klirinski Interbankarski Sistemi advert Skopje (KIBS), a Macedonia-based payment gadget operator owned by way of 12 banks is working with IBM to seriously change payment clearing tactics and befriend quicker the mixing of Macedonia's banking paraphernalia with the european. With IBM Cloud inner most KIBS might live 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 novel digital products from one-and-a-half years to simply a brace 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 synthetic 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 erudition of and difficulty-solving. using IBM Cloud deepest, Sentient.io will befriend 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 novel 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 Cut back infrastructure expenses, cutting the full software free up time from days to minutes. here is above every bit of 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 consume of IBM Cloud deepest for a brand novel service called TK-protected which gives clients with their medical health insurance statistics by the consume 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 way of an open service platform, TK-safe clients can improvement from novel value-addedservices for his or her own health keeping and are in a position to share 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 besides live accessed remotely by way of any student. IBM Cloud private will hasten on the tuition's IBM power servers as fragment of a complete solution which besides includes QRadar, MaaS360 and Cognos utility. The solution may live 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 solid and IBM trade accomplice in South Korea turned to IBM Cloud deepest to birthright away and easily package functions as containers and re-aspect them with IBM microservices. additionally, the trade is leveraging the software to assist valued clientele modernize their legacy functions and provide a at ease platform from which to hasten enterprise crucial software across each public and private clouds, in a factual multi-cloud structure.

    Five9 Vietnam Corp., VietnamFive9 Vietnam is a fast-becoming IT and cloud provider provider that gives its shoppers with every dinky 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

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    C5050-384 IBM Cloud Platform Application progress v2

    Study pilot Prepared by Killexams.com IBM Dumps Experts


    Killexams.com C5050-384 Dumps and actual Questions

    100% actual Questions - Exam Pass Guarantee with towering Marks - Just Memorize the Answers



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

    Test Code : C5050-384
    Test appellation : IBM Cloud Platform Application progress v2
    Vendor appellation : IBM
    : 56 actual Questions

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    SoftLayer IaaS v2.1 Manager Now Available for the Ensim Automation Suite | killexams.com actual 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 full 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 full 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 springy subscription and payment plans. Single 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 bit of 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 trade objectives and enforcing policy requirements," said David Wippich, CEO, Ensim. "Ensim is disdainful to present a comprehensive platform that enables providers to offer, bundle and differentiate the SoftLayer offerings from a single 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 bit of SoftLayer Datacenter locations
  • Virtual machine management: Create, Start, Stop, Clone, Edit
  • Create and allot 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 absorb 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 single portal and provides robust end-to-end ordering, provisioning, and billing every bit of through a single 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 trade 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 sweep from Web startups to global enterprises. Products and services embrace bare metal and virtual servers, networking, turnkey stately data solutions, private cloud solutions, and more. Unique advantages embrace the industry's first Network-Within-a-Network topology for factual out-of-band access, and an easy-to-use customer portal and robust API for full remote-access of every bit of 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 actual questions and Pass4sure dumps

    How to elect a Video AI Platform and Evaluate its Results

    Meet the stately four players in the video synthetic intelligence space, then learn how they can speed up time-consuming tasks fancy generating metadata or creating transcriptions.

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

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

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

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

    The stately 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 stately disagreement 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 artic user interface you can log into and upload videos to, and start getting AI-generated metadata birthright away for free.

    This article will gape 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, keep in intelligence that it’s every bit of about the consume case. every bit of four platforms recrudesce JSON (JavaScript protest Notation) data, so there’s nothing stopping you from using every bit of 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 secure Started

    If you don’t absorb 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 win widgets and embed them into your own systems. Of the four platforms they debate in this article, Video Indexer is the most complete product you can access without having to travel through compress 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 secure 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 work with your videos.

    IBM sells a brace of Watson products, such as Video Enrichment (top birthright 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 stately consume cases for AI. Let’s pronounce you’ve archived multiple seasons of a TV show, and you absorb a media asset manager (MAM) that houses every bit of this metadata about every bit of of those stored assets. Wouldn’t it live noteworthy to absorb the computer generate some of that metadata for you, so that in addition to the title, season, and episode name, you’d absorb things fancy “car crash,” “leopard,” and “little baby girl” (or whatever terms apply to your content) that you can actually consume to search and ascertain 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 absorb to write every bit of 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 absorb establish 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 live more productive if they don’t absorb to spend as much time trying to grok how to work 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 secure 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 ship a video up to the Google service, rather than seeing the signature of the payload that you want to upload, you absorb to wade through three or four paragraphs on every single data point within that signature.

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

    Azure has client SDKs, but to interact with the Video Indexer you will just consume its API without an SDK. If you exigency the extra hoist that an SDK can provide, then Video Indexer might not live the birthright solution for you. Amazon and Google absorb things fancy Java, Android, iOS, Ruby, and so on, as you can notice in pattern 2. Your developers might live 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 absorb an lively 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 consume cases. When it comes to translation and transcription, video surveillance, or metadata and objects, which platforms work best in those cases?

    One thing to keep in intelligence 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 gape 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 absorb more accurate results for you when it comes to protest detection or seeing when a ball is being hit across the court. On the other hand, if you accomplish news footage, Google might serve you better, because users live stream their news over YouTube.

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

    That’s a way to deem about AI: You’re going to live 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 Make it more accurate in one way or another.

    Interpreting the Data

    Figure 3 shows an case of the benign of data you secure back with these systems. Generally, AI solutions work fancy this: They absorb an API that allows your developers to hit an stay 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 stay point fancy google.com. It might live something fancy “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 fancy when you travel to Google and type in a search string and then hit Enter. A developer will ship up a payload that says, “My video is here. please process it.” Then you wait for the processing to happen, because it’s not instantaneous. Once the processing is done, you’ll absorb data that you can tow down, comparable to search results in Google.

    All of these services consume JSON, the data exchange format shown in pattern 3. This is great, because it enables you to secure 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 secure back.

    In the case 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 establish a person at timestamp 18196 milliseconds, and I’m 97.8222 percent sure.” That’s the data you secure back with protest detection in AWS.

    With Azure Video Indexer (second column from left), it says, “I establish a person in the time sweep 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 intelligence that the computer doesn’t actually “see” a person; it’s learning from every bit of 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 live 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 synthetic intelligence and machine learning to help content delivery, video compression, and viewer personalization, strengthening the entire workflow.


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

    All this means that with PCF, your build artifact is your indigenous 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 secure this template automatically from a buildpack.

    Management Console Cloud Foundry

    PCF separates the web dashboard to two separate target audiences.

  • Ops Manager is targeted at the IT professional that is responsible for setting up the virtual machines or hardware that will live 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 bit of he can really notice is the quotas assigned to his organization, such as reminiscence limits.
  • Kubernetes

    Kubernetes takes a different approach. You secure 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 absorb access to persistent volumes, daemons, definition of roles, replication controllers etc. It’s hard to focus on what are the developer’s needs and what are the IT needs. Some might bid 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 bit of aspects of the developer interaction. Following in the footsteps of simplicity that you might absorb already noticed, the notion is to win 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 push myapp -p myapp.jar

    That’s it! That’s every bit of you need. PCF will lookup the current working directory and find the jar executable. It will then download the java buildpack, create a container, reckon 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 push 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 fancy 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 express you give up any control. You absorb 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 bit of of this can live done in the cf cli or by having a manifest.yml file available as a parameter to the cf push command. A typical manifest.yml file can live 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 absorb a private docker registry available and configured (unless you only way to deploy images available on public registries such as docker hub). Once you absorb that registry up and running, you will exigency to push 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 case of starting up an nginx server:

    # start the pod running nginx$ kubectl hasten --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 single docker container, but you can hasten more. For example, an application container might want to absorb some monitoring dameon container in the selfsame pod.

    In order to Make 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 redress 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 single 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 muster 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 consume 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 live specific. Don’t await deployments to live implied. If I had to create a haiku for Kubernetes, it’ll live probably something fancy this:

    Here’s my code

    I’ll bid you exactly how you should hasten it on the cloud for me

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

    Zero Downtime Deployments

    Both platforms support the faculty to deploy applications with zero downtime, however this is one zone 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 support a rolling update, you’re basically expected to accomplish some cf cli trickery to fulfill the update with zero downtime. The concept is called blue-green deployment. If I had to define it in step-by-step guide, it’ll probably live something fancy this:

  • Starting point: you absorb myApp in production, and you want to deploy a novel version of this app — v2.
  • Deploy v2 under a novel application name, for example — myApp-v2
  • The novel app will absorb its own initial route — myApp-v2.mysite.com
  • Perform testing and verification on the novel 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 fulfill A/B testing. For example — if you absorb 4 instances of v1 and 1 instance of v2, 20% of your clients will live routed to the novel 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 absorb now fully migrated to the novel codebase with zero downtime, including sanity testing phase 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 establish blue-green-deploy to live very simple and intuitive, especially due to its support for automated smoke tests as fragment of the deployment.

    Kubernetes

    kubectl has a built-in support for rolling updates. You basically pass a novel 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 fulfill a rolling update between every bit of pods of the kubernetes-bootcamp deployment from its current image to the novel 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 win an external view of the levels of abstraction that are needed to attain your application, they can recite 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 inescapable domains to only live 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 leisure of the cluster. Eureka server maintains a heartbeat health check of every bit of registered clients to keep an up-to-date list of wholesome instances.

    Registered clients can connect to Eureka and examine for available endpoints based on a service id (the value of spring.application.name in case of Spring Boot applications). Eureka would recrudesce a list of every bit of 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 fancy 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 bit of 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 fancy 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 appellation 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 Make 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 appellation is simply the appellation of the service that exposes the pods. For example:

  • You absorb an application called my-app in namespace zone1
  • It exposes a secure /myApi leisure 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 way 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 fancy 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 embrace 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 small database for progress or a highly-available database for a production environment.

    Last but not least, you absorb 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 hasten any docker container — Dockerhub can live considered as a kubernetes marketplace in a way. You can basically hasten anything that can hasten in a container.

    Kubernetes does absorb 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 live reloaded with updated configuration by issuing a POST /refresh API muster 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 noteworthy 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 fancy a glove.

    In Kubernetes, you can still hasten a config server as a container, but that would probably become an unneeded operational overhead since you already absorb built-in support for ConfigMaps. consume the indigenous solution for the platform you travel with.

    Storage Volumes

    A stately differentiator of Kubernetes is the faculty 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 secure a trustworthy storage solution, which lets you hasten storage-based containers fancy 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 win the selfsame application that runs today in your on-prem data center, whisk it to AWS, and provided there is adequate connectivity, it should just work. Any storage-based solution should live offloaded to either a PCF service, or to a storage solution outside the PCF cluster itself. This may live regarded as an odds or a handicap depending on your application and architecture. For stateless application runtimes such as web servers, it is always a trustworthy notion 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 absorb (docker registry and a git repository are often taken for granted).

    Just taking a gape at the excellent Kubernetes Basics interactive tutorial shows the even of erudition 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 result 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 absorb some jenkins pipeline in place. They just want to hasten the selfsame thing in a cloud environment.

    If we’ll win a gape at PCF’s “Getting Started with Pivotal Cloud Foundry”, it’s almost comical how dinky is required to secure something up and running. When you exigency more tangled interaction, it’s every bit of available for you, either in the cf cli, as fragment of a manifest.yml, or in the web console, but this doesn’t prevent 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 noteworthy open source platform. Kudos to Google for giving up control and letting the community accomplish its thing. That’s probably the number one reason why Kubernetes has taken off so quickly while other solutions fancy Docker swarm are falling behind. Other vendors besides present solutions that present a more PaaS-like sustain on top of Kubernetes, such as RedHat OpenShift.

    But with such a diverse and thriving eco-system, the path forward can live one of many different directions. It really does feel fancy 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 execute it and whisk to the next stately thing (Does anyone recollect Google Buzz, Google Wave or Google Reader?). Any AngularJS developer who’s trying to whisk to Angular 5 can bid you that backwards compatiblity is not a top priority.

    Cloud Foundry

    Cloud Foundry is besides a thriving open source platform, but it is pretty lucid 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 fancy 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 dinky more of a walled garden, more controlled, better design/experience layer, and a commitment for delivering a noteworthy product. I feel fancy the platform is more focused, and focus is captious in my line of work.

    PKS

    The actual surprise of the recently announced PCF 2.0 was that every bit of I’ve been talking about throughout this article is now just one fragment 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 besides a novel serverless solution called Pivotal office Service (PFS), and lastly — a novel Kubernetes runtime called Pivotal Container Service (PKS). This means that Pivotal Cloud Foundry now gives you the best of both worlds: A noteworthy application runtime for rapid onboarding of cloud-native applications, as well as a noteworthy container runtime when you exigency to develop generic low-level containers.

    Conclusion

    In this article I tried to share 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 establish it to live a very versatile platform, but besides one that requires a steeper learning curve. Maybe I got spoiled by live 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 hasten cloud indigenous applications as quickly and simply as possible, while besides 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 absorb a PCF service available, so it has to hasten externally on virtual machines. Now with PCF 2.0, I can hasten 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 contented 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/

    Follow me on 500px: https://500px.com/odedia



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