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C5050-380 exam Dumps Source : IBM Cloud Platform Solution Architect v2

Test Code : C5050-380
Test title : IBM Cloud Platform Solution Architect v2
Vendor title : IBM
: 63 real Questions
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IBM IBM Cloud Platform Solution

BMC Expands Cognitive Partnership with BMC Helix and IBM, pronounces BMC Helix on IBM Cloud | killexams.com real Questions and Pass4sure dumps

No consequence found, are attempting recent keyword!The BMC Helix acknowledge is expanding with the addition of an insight ... by using offering BMC Helix on the IBM Cloud platform, businesses can elope BMC Helix on their cloud of preference – including IBM Cloud, A...

American airlines partners with IBM to develop utilize of IBM Cloud for huge Cloud Transformation | killexams.com real Questions and Pass4sure dumps

Jun 30, 2017
Stephanie Simone
American airways will utilize IBM Cloud as the basis for a big cloud transformation designed to develop inside techniques extra efficient, quicker, less demanding and adaptable to more suitable tackle site traffic perquisite through extreme quantity periods.
building on the strategic cloud partnership signed with IBM in 2016, American airlines will migrate to the IBM Cloud a ingredient of its well-known functions, including aa.com, its client-dealing with cellular app and its world community of check-in kiosks.
additionally, other workloads and tools, such because the company’s Cargo client site, will too exist moved to the IBM Cloud.
As a participate of the solution, American and IBM will drudgery together to circulate vital applications to the IBM Cloud. In parallel, the two businesses contain teamed to rewrite these applications to the IBM Cloud Platform as a service (PaaS), and set up a cloud-native structure.
As a participate of this system, American will drudgery with IBM world functions to leverage IBM’s garage Methodology of growing imaginitive applications perquisite away via a micro-services architecture, design pondering, agile methodology, DevOps, and gaunt building.
IBM Cloud will assist permit developers to rapidly construct and change application functionalities for the airline’s clients. These customer-facing techniques will exist on the IBM Public Cloud, while American maintains backend connectivity to other on-premise legacy and third-celebration programs, for unquestionable Hybrid Cloud functionality.
For extra suggestions about this news, talk over with www.ibm.com. 

IBM Brings Watson AI To The inner most Cloud And compete Public Cloud systems | killexams.com real Questions and Pass4sure dumps

IBM enabled Watson AI to elope throughout the enterprise data centers and mainstream public cloud platforms. Branded as Watson anywhere, the flagship information and analytics platform that changed into at the birth constructed for the IBM Cloud can too exist deployed in a lot of environments including VMware, IBM Cloud deepest, AWS, Azure, and Google Cloud platforms.
Ginni Rometty, CEO, IBMSource: IBM
on the suppose 2019 conference hosted in San Francisco, Ginni Rometty, IBM’s CEO announced Watson anywhere.
IBM Watson anywhere is constructed on proper of Kubernetes, the open supply orchestration engine that can too exist deployed in different environments. on the grounds that the Watson any location platform is built as a set of microservices designed to elope on Kubernetes, it is bendy and conveyable.
IBM bets on stout on Kubernetes. As a member of the Cloud autochthonous Computing groundwork and a a must-have contributor to the open supply assignment, it presents Kubernetes as a carrier in its public cloud. IBM Cloud deepest, the hybrid cloud platform from stout Blue is completely developed on Kubernetes.
based on IBM, the microservices-based Watson anyplace offers two solutions -
Watson OpenScale: IBM's open AI platform for managing numerous instances of AI, no matter where they contain been developed – including the capability to clarify how AI selections are being made in real time, for enhanced transparency and compliance.
Watson Assistant: IBM's AI device for structure conversational interfaces into functions and instruments. greater advanced than a traditional chatbot, Watson lieutenant intelligently determines when to search for a influence, when to inquire the consumer for clarification, and when to dump the person to a human for private guidance. also, the Watson lieutenant Discovery Extension makes it workable for organizations to release hidden insights in unstructured facts and files.
IBM Cloud private for records is an extension of the hybrid cloud concentrated on records and analytics. in response to IBM, it simplifies and unifies how consumers compile, prepare and resolve statistics to accelerate the value of statistics science and AI. The multi-cloud platform promises a big range of core statistics microservices, with the option so as to add extra from a growing services catalog.
IBM Watson any location is seamlessly built-in with Cloud deepest for records. The combination allows consumers to manipulate conclusion-to-conclusion records workflows to assist develop sure that statistics is with no grief accessible for AI.
presently after the announcement from IBM on Watson any place, Pat Gelsinger, VMware’s CEO mentioned Watson’s integration with Workspace One, an endpoint management product that offers start and administration of apps across instruments. Watson any location will become purchasable within Workspace ONE ingenious Hub, a flavor of the endpoint administration platform built-in with AirWatch.
With the approaching acquisition of crimson Hat, IBM is expected to wager big on OpenShift, pink Hat’s personal commercial enterprise distribution of Kubernetes that runs very nearly in each public cloud.
IBM hopes that the multi-cloud system of Watson helps the trade compete more advantageous with its opponents.
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IBM Cloud Platform Solution Architect v2

The Apache Software Foundation Announces Apache® jclouds™ v2.0 | killexams.com real questions and Pass4sure dumps

November 15, 2016 06:00 ET | Source: The Apache Software Foundation
Forest Hill, MD, Nov. 15, 2016 (GLOBE NEWSWIRE) -- The Apache Software Foundation (ASF), the all-volunteer developers, stewards, and incubators of more than 350 Open Source projects and initiatives, announced today the availability of Apache® jclouds™ v2.0, the Java multi-cloud toolkit.
Apache jclouds gives users the liberty to create applications that are portable across clouds while providing complete control to utilize cloud-specific features. As a cloud-agnostic library, jclouds enables developers to access a variety of supported cloud providers using one API.
"Apache jclouds 2.0 represents a significant milestone for the project" said Ignasi Barrera, Vice President of Apache jclouds. "We are proud to back complete major cloud providers in the marketplace with a mature, stable, codebase that is ready for production."
jclouds entered the Apache Incubator in April 2013 and graduated as a Top-Level Project (TLP) in October of the very year. The Apache jclouds 2.0 release is the 11th release as a TLP and the consolidation of the project, with more than 13K commits (1K in the final release) made by more than 250 contributors (35 recent final year).
Under The HoodApache jclouds 2.0 features include:
  • Wider compatibility with the Guava and Guice libraries.
  • Configuration of capricious hardware values in the compute abstraction.
  • Support for recent cloud providers such as Microsoft Azure Resource Manager, ProfitBricks v3, OneAndOne and Backblaze B2.
  • Better integration with OSGi and Apache Karaf.
  • Numerous bug fixes and performance improvements.
  • Apache jclouds is used by Abiquo, Adobe, CloudBees, Cloudify, Cloudsoft, Mesosphere, and RedHat, among many others. In addition, jclouds is supported by cloud companies and communities such as Amazon Web Services, Backblaze B2, Apache CloudStack, Docker, Google Cloud Platform, Microsoft Azure, OpenStack, Rackspace, and many more.
    "Abiquo, as the creator of the leading commercial cloud management platform, relies on jclouds to give their customers the agility they need," said Ian Finlay, CEO of Abiquo. "Using jclouds and their plugin architecture they contain been able to deliver back for recent cloud providers and features demanded by their customers in days or weeks rather than months. This approach ensures that their service provider and enterprise customers can bring together the cloud providers they need to deliver a mighty hybrid cloud solution to their customers."
    "Apache jclouds provides Cloudsoft AMP with a layer of abstraction across clouds allowing Cloudsoft AMP to model, deploy and manage applications in line with their customers’ requirements," said Duncan Johnston-Watt, Founder and CEO of Cloudsoft. "Many of their customers contain multi-cloud application strategies and need rapid back for target locations as these emerge. I’m pleased to remark back Microsoft Azure Resource Manager and improvements for OpenStack (Mitaka) and IBM cloud targets."
    "We are very proud of their achievement and welcome contributions that succor grow the Apache jclouds community, including joining their mailing lists and submitting feedback, utilize cases, bug reports, patches, and documentation," added Barrera.
    Availability and OversightApache jclouds software is released under the Apache License v2.0 and is overseen by a self-selected team of lively contributors to the project. A Project Management Committee (PMC) guides the Project's day-to-day operations, including community progress and product releases. For downloads, release notes, documentation, and more information on Apache jclouds, visit http://jclouds.apache.org/ and https://twitter.com/jclouds
    Get Involved!Apache jclouds welcomes contribution and community participation through mailing lists, an IRC channel, as well as attending face-to-face MeetUps, developer trainings, and user events. Those wishing to salvage involved in the project can find out more at http://jclouds.apache.org/community/
    About The Apache Software Foundation (ASF)Established in 1999, the all-volunteer Foundation oversees more than 350 leading Open Source projects, including Apache HTTP Server --the world's most celebrated Web server software. Through the ASF's meritocratic process known as "The Apache Way," more than 550 individual Members and 5,300 Committers successfully collaborate to develop freely available enterprise-grade software, benefiting millions of users worldwide: thousands of software solutions are distributed under the Apache License; and the community actively participates in ASF mailing lists, mentoring initiatives, and ApacheCon, the Foundation's official user conference, trainings, and expo. The ASF is a US 501(c)(3) charitable organization, funded by individual donations and corporate sponsors including Alibaba Cloud Computing, ARM, Bloomberg, Budget Direct, Capital One, Cerner, Cloudera, Comcast, Confluent, Facebook, Google, Hortonworks, HP, Huawei, IBM, InMotion Hosting, iSigma, LeaseWeb, Microsoft, OPDi, PhoenixNAP, Pivotal, Private Internet Access, Produban, Red Hat, Serenata Flowers, WANdisco, and Yahoo. For more information, visit http://www.apache.org/ and https://twitter.com/TheASF
    © The Apache Software Foundation. "Apache", "jclouds", "Apache jclouds", and "ApacheCon" are registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries. complete other brands and trademarks are the property of their respective owners.
    # # #
    Sally Khudairi Vice President The Apache Software Foundation +1 617 921 8656

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

    All this means that with PCF, your build artifact is your autochthonous deployment artifact, while in Kubernetes your build artifact is a docker image. With Kubernetes, you need to define the template for this docker image yourself in a Dockerfile, while in PCF you salvage 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 answerable 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 answerable for pushing application code to testing or production environments. The developer is completely unaware of the underlying infrastructure that runs its PCF cluster. complete he can really remark is the quotas assigned to his organization, such as remembrance limits.
  • Kubernetes
    Kubernetes takes a different approach. You salvage one dashboard to manage everything. Here’s a typical Kubernetes dashboard:
    As you can remark from the left-hand side, there is a lot of data to process here. You contain 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 inform you this is the very 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 complete aspects of the developer interaction. Following in the footsteps of simplicity that you might contain already noticed, the understanding is to Take 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 complete you need. PCF will lookup the current working directory and find the jar executable. It will then update bits to the platform, where the java buildpack would create a container, reckon the required remembrance settings, deploy 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 dote remembrance 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 contain a lot of customizations available in PCF. You can define your own routes, set the number of instances, max remembrance and disk space, environment variables etc. complete 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 noiseless a higher learning curve from what I’ve experienced so far.
    For starters, a basic assumption is that you contain a private docker registry available and configured (unless you only map to deploy images available on public registries such as docker hub). Once you contain that registry up and running, you will need 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 example of starting up an nginx server:
    # start the pod running nginx$ kubectl elope --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 very 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 contain a solitary docker container, but you can elope more. For example, an application container might want to contain some monitoring dameon container in the very pod.
    In order to develop the container accessible to other pods in the Kubernetes cluster, you need 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 noiseless not exposed to the outside world. For that, you need to wrap your service with an ingress.
    Note: Ingress is noiseless considered a beta feature!
    I could not find a simple command to expose an ingress at this point (please amend 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 solitary 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 call 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 utilize 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 need to exist specific. Don’t expect deployments to exist implied. If I had to create a haiku for Kubernetes, it’ll exist probably something dote this:
    Here’s my code
    I’ll inform you exactly how you should elope it on the cloud for me
    And don’t you dare develop any assumptions on the delployment without my written consent!
    Zero Downtime Deployments
    Both platforms back the capacity to deploy applications with zero downtime, however this is one belt where Kubernetes wins in my opinion, since it provides a built-in mechanism for zero downtime deployments with rollback.
    2019 update: As of Pivotal Cloud Foundry 2.4, autochthonous zero-downtime deployments are available out of the box!
    Cloud Foundry
    With Pivotal Cloud Foundry, t̶h̶e̶r̶e̶’̶s̶ ̶n̶o̶ ̶b̶u̶i̶l̶t̶-̶i̶n̶ ̶m̶e̶c̶h̶a̶n̶i̶s̶m̶ ̶t̶o̶ ̶s̶u̶p̶p̶o̶r̶t̶ ̶a̶ ̶r̶o̶l̶l̶i̶n̶g̶ ̶u̶p̶d̶a̶t̶e̶, you’re basically expected to achieve some cf cli trickery to execute the update with zero downtime. The concept is called blue-green deployment. If I had to account for it in step-by-step guide, it’ll probably exist something dote this:
  • Starting point: you contain myApp in production, and you want to deploy a recent version of this app — v2.
  • Deploy v2 under a recent application name, for example — myApp-v2
  • The recent app will contain its own initial route — myApp-v2.mysite.com
  • Perform testing and verification on the recent app.
  • Map an additional route to the myApp-v2 application, using the very 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 execute A/B testing. For example — if you contain 4 instances of v1 and 1 instance of v2, 20% of your clients will exist routed to the recent 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 contain now fully migrated to the recent codebase with zero downtime, including sanity testing aspect 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 institute blue-green-deploy to exist very facile and intuitive, especially due to its back for automated smoke tests as participate of the deployment.
    Kubernetes
    kubectl has a built-in back for rolling updates. You basically pass a recent 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 execute a rolling update between complete pods of the kubernetes-bootcamp deployment from its current image to the recent 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 Take an external view of the levels of abstraction that are needed to reach your application, they can report 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 certain 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 leisure of the cluster. Eureka server maintains a heartbeat health check of complete registered clients to withhold an up-to-date list of wholesome instances.
    Registered clients can connect to Eureka and inquire 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 complete 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 dote 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 complete 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 dote a glove.
    Kubernetes
    Kubernetes uses DNS resolution to identify other services within the cluster. Inside the very namespace, you can lookup another service by its name. In another namespace, you can lookup the service’s title followed by a dot and then the other namespace.
    The major benefit 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 such as Steeltoe for .NET). With Kubernetes, you can develop 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 title is simply the title of the service that exposes the pods. For example:
  • You contain an application called my-app in namespace zone1
  • It exposes a salvage /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.
    2018 update: Pivotal Cloud Foundry now supports polyglot, platform-managed service discovery similar to Kubernetes, using Envoy proxy, apps.internal domain and BOSH DNS.
    Marketplace
    PCF offers a services marketplace. It provides a ridiculously simple course to bind your application to a service. The term service in PCF is not the very as a service in kubernetes. A PCF service binds your application to things dote a database, a monitoring tool, a message broker etc. Some example services 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 comprehend MongoDB Enterprise 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 little database for progress or a highly-available database for a production environment.
    Last but not least, you contain 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 offer a marketplace out of the box. There is a service catalog extension that allows for a similar service catalog, however it is noiseless in beta.
    Note that since it can elope any docker container — Dockerhub can exist considered as a kubernetes marketplace in a way. You can basically elope anything that can elope in a container.
    Kubernetes does contain 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 call 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 mighty solution, but again assumes that your applications are based on the Spring Cloud (or .NET Steeltoe) stack. If you’re already using spring boot with a config server today — PCF fits dote a glove.
    In Kubernetes, you can noiseless elope a config server as a container, but that would probably become an unneeded operational overhead since you already contain built-in back for ConfigMaps. utilize the autochthonous solution for the platform you evaporate with.
    Storage Volumes
    A stout 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 salvage a dependable storage solution, which lets you elope storage-based containers dote 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 Take the very application that runs today in your on-prem data center, run 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 handicap or a drawback depending on your application and architecture. For stateless application runtimes such as web servers, it is always a estimable understanding 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 need to know and too many assumptions about what you already contain (docker registry and a git repository are often taken for granted).
    Just taking a inspect at the excellent Kubernetes Basics interactive tutorial shows the smooth 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 need to understand. Trying to follow 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 contain some jenkins pipeline in place. They just want to elope the very thing in a cloud environment.
    If we’ll Take a inspect at PCF’s “Getting Started with Pivotal Cloud Foundry”, it’s almost comical how minute is required to salvage something up and running. When you need more complex interaction, it’s complete available for you, either in the cf cli, as participate 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 mighty open source platform. Kudos to Google for giving up control and letting the community achieve its thing. That’s probably the number one judgement why Kubernetes has taken off so quickly while other solutions dote Docker swarm are falling behind. Other vendors too offer solutions that offer 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 exist one of many different directions. It really does feel dote 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 Kill it and run to the next stout thing (Does anyone remember Google Buzz, Google Wave or Google Reader?). Any AngularJS developer who’s trying to run to Angular 5 can inform you that backwards compatibility is not a top priority.
    Cloud Foundry
    Cloud Foundry is too 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 dote 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 acknowledge 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 mighty product. I feel dote the platform is more focused, and focus is captious in my line of work.
    PKS
    The real astound of the recently announced PCF 2.0 was that complete I’ve been talking about throughout this article is now just one participate of a larger offering. The application runtime (everything that is referred to as PCF in this article) is now called Pivotal Application Service (PAS). There is too a recent serverless solution called Pivotal role Service (PFS), and lastly — a recent Kubernetes runtime called Pivotal Container Service (PKS). This means that Pivotal Cloud Foundry now gives you the best of both worlds: A mighty application runtime for quickly onboarding of cloud-native applications, as well as a mighty container runtime when you need to develop generic low-level containers.
    Conclusion
    In this article I tried to participate my personal experiences of working with both platforms. Although I am a bit biased towards PCF, it is for a estimable reason — it has served me well. I approached Kubernetes with an open mind, and institute it to exist a very versatile platform, but too one that requires a steeper learning curve. Maybe I got spoiled by alive in the Spring eco-system for too long :). With the latest announcement of PKS, it appears that Pivotal Cloud Foundry is set to offer the best integrated PaaS — one that lets you elope cloud autochthonous applications as quickly and simply as possible, while too exposing the best generic container runtime when that is needed. I can remark this becoming very useful in many scenarios. For example, Apache Kafka is one of the best message brokers available today, but this message broker noiseless doesn’t contain a PCF service available, so it has to elope externally on virtual machines. Now with PCF 2.0, I can elope Apache Kafka in docker containers inside PCF itself.
    The main conclusion is that this is definitely not a this or that discussion. Since both the application runtime and the container runtime now live side by side in the very product, the future seems promising for both.
    Thank you for reading, and gay 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

    Cheapest enterprise cloud storage providers not always best | killexams.com real questions and Pass4sure dumps

    LAS VEGAS -- Don't choose the least expensive of the enterprise cloud storage providers, even if the vendor happens...
    to exist a stout name.
    That was the advice from Raj Bala, a Gartner research director focusing on cloud infrastructure, at the Gartner IT Infrastructure, Operations Management & Data center Conference. Bala cautioned attendees about "horror stories" he has heard from customers that made the cheapest choice, even from "big brand names."
    During a post-presentation interview, Bala declined to title any of the enterprise cloud storage providers answerable for the client anecdotes that would "make the hair on your neck stand up." But he cited an example of a customer that used an inexpensive brand-name vendor only to contain data unavailable "for days on end."
    "And the pricing changed. It went from some really inexpensive expense to a much higher price," Bala said. In contrast, he said there is "no course in the world" Amazon Web Services (AWS) would expand prices for its Simple Storage Service (S3). "There would contain to exist a catastrophic supply chain issue for disk drives -- not even SSDs -- for AWS to contain a expense increase."
    Bala's public recommendation to conference attendees was the following: "Think about the number of years that a vendor has been in this market and their commitment to the market. The final thing you want to achieve is evaporate with a vendor who says, 'Well, the v1 version of their service didn't work, and we're going to scrap it, and we're going to restart over again.' There are a lot of customers in that boat."
    Although Bala's cautionary advice did not note specific enterprise cloud storage providers that abandoned the original versions of their cloud storage services, he did offer outspoken assessments of each of the major challengers to paramount player AWS.
    IBM, Oracle rebuild public cloud storage
    Bala told attendees that Oracle and IBM are industrious rebuilding their public cloud storage. He said Oracle scrapped its open source OpenStack-based platform, because "that just did not work" and "did not salvage much traction," so the company decided to start over again.
    "Oracle did something very smart. They opened a big office in Seattle, and they've hired a bunch of AWS engineers. So, they've got several hundred AWS engineers that are structure v2 of Oracle service," Bala said. "After having failed the first time, they're doing some really solicitous things the second time."
    Bala said IBM's public cloud storage, too based on OpenStack, "didn't really evaporate anywhere" and "had lots of problems," leaving the company "trying to rebuild it." He said IBM spent lots of money trying to buy companies, as well as trying to rebuild in-house.
    "But IBM's service is a bit of mess," Bala said. "First, they called it SoftLayer. Then, they called it Bluemix. And now, it's called IBM Cloud. And that's complete happened in the span of about 2.5 years. I judge IBM Cloud is probably what they're going to withhold it at. That seems to develop the most sense to me. But they could change it next year, as well. Let's see," Bala said.
    Top-ranked enterprise cloud storage providers
    The primary challenger to AWS, No. 2 Microsoft, dipped as a visionary in Gartner's 2017 Magic Quadrant for public cloud storage, because "we're seeing very minute in terms of recent innovation," Bala said. According to Bala, Microsoft has essentially been "following the AWS roadmap" during the past year.
    Bala said Google is putting money into its public cloud storage service, but it's not having success with mainstream enterprise because it lacks a sales compel "big enough to evaporate knock on doors." He said Gartner clients inquire about Google only 3% of the time, based on his review of the entire set of inquiries on infrastructure as a service. Google's cloud storage customer foundation tends to comprehend sophisticated enterprises, such as hedge funds, Wall Street banks, and biotechnology and pharmaceutical companies, according to Bala.
    "Google is an appealing company. Google can attach satellites into space. They can build self-driving cars, but structure an enterprise strategy is apparently too much for Google," Bala said.
    Alibaba dominates the cloud trade in China, but has achieved minute success with the data centers it has opened in other locations, according to Bala. He said Alibaba essentially replicates AWS offerings, even to the point of identical names for products.
    Bala said Dell EMC's Virtustream cloud storage service, based on EMC hardware, lags in Gartner's innovation ratings, because it relies on software that "hasn't been touched in a estimable three or four years." Rackspace, once the No. 2 enterprise cloud storage provider, faded due to its inability to withhold pace with AWS. Rackspace has pivoted to start focusing on services for AWS, Bala said.
    Spotty S3 API support
    Bala warned conference attendees that compatibility varies greatly among vendors that implement Amazon's S3 API. He said his personal testing showed that some implement the S3 API "dutifully," while other vendors implement only about 40% of the API.
    Another belt of skepticism for Bala is the increasing number of vendor pitches on multi-cloud strategies. He said the vendors promoting multi-cloud are not the leaders.
    "The notion of using multiple clouds is not new, and a multi-cloud architecture is usually problematic. If a customer told me they were doing that, I would throw up stout red-flag warnings and say, 'Do not achieve this unless you absolutely know what you're getting into,'" Bala said.
    He said the complexity of an application increases tenfold by spreading it across multiple cloud providers with only marginal benefit. "It doesn't develop sense," he said.
    Cloud storage expense negotiating is another topic on which Bala cautioned clients. He said, because the expense of cloud storage falls consistently, it's a mistake to negotiate anything other than a percentage discount. He said some big customers of stout providers negotiated a per-gigabyte expense only to later find that the market expense was less than what they had negotiated.
    "If you utilize a percentage discount, then you're going to salvage the best price," Bala said. "And most of the vendors -- AWS, for instance -- will start negotiating with you on expense if you've got 2 PB of data or more. Microsoft will evaporate a total lot less. Google will evaporate even further than that."

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