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C9530-519 | IBM API Connect v. 5.0.5 Solution Implementation

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C9530-519 - IBM API Connect v. 5.0.5 Solution Implementation - braindump

Vendor IBM
Exam Number C9530-519
Exam Name IBM API Connect v. 5.0.5 Solution Implementation
Questions 74 Q & A
Recent Update February 15, 2019
Free PDF Download C9530-519 Brain Dump
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C9530-519 exam Dumps Source : IBM API Connect v. 5.0.5 Solution Implementation

Test Code : C9530-519
Test Name : IBM API Connect v. 5.0.5 Solution Implementation
Vendor Name : IBM
Q&A : 74 Real Questions

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IBM IBM API Connect v.

Deploying IBM DataPower into IBM BlueMix Kubernetes carrier for API join v2018 | killexams.com Real Questions and Pass4sure dumps

this text goes in the course of the steps required to install IBM DataPower to the IBM Bluemix Kubernetes capabilities.

necessities

· Bluemix Kubernetes services Deployed

· Bluemix Container Registry Deployed in the same statistics centre because the Kubernetes provider

· Helm put in in the community

· apicup installed locally

· kubectl installed in the community

add the DataPower graphic to the Container Registry

docker pull ibmcom/datapower:newest

docker tag ibmcom/datapower:newest <bluemix server>/<namespace>/ibmcom/datapower:newest

bx cr login #log into the container registry

docker push <bluemix server>/<namespace>/ibmcom/datapower:latest

where

<namespace> is the container registry namespace configured

<bluemix server> the server the container registry is working on

Create the Configuration

set up kubectl

ibmcloud cs cluster-config <kubernetes cluster>

where

<kubernetes cluster> is the name of your cluster

Run the export command back

in case you are not running in the default namespace you should run the following command

kubectl get secret bluemix-default-secret-regional -o yaml | sed ‘s/default/<kube namespace>/g’

Run here commands

helm init

apicup init dpIBMBlueMix

cd dpIBMBlueMix

apicup subsys create gw gateway — k8s ;

apicup endpoints set gw gateway gw.enterprise.com ; #ensure here's regsitered to your dns server pointing tothe employee node

apicup endpoints set gw gateway-director gwd.enterprise.com ; #make certain here is regsitered to your dns server pointing tothe employee node

apicup subsys set gw namespace “<kube namespace>” ;

apicup subsys set gw max-cpu 2 ;

apicup subsys set gw max-reminiscence-gb four ;

apicup subsys set gw replica-count 1 ;

apicup subsys set gw picture-repository <bluemix server>/<namespace>/ibmcom/datapowerapicup subsys set gw graphic-tag “latest”

apicup subsys set gw registry-secret bluemix-<kube namespace>-secret-regional

apicup subsys set gw mode demo

apicup subsys installation gw

where

<namespace> is the container registry namespace configured

<bluemix server> the server the container registry is running on

<kube namespace> the kubernetes namespace

gw.company.com is the API Endpoint Base

gwd.company.com is the Gateway service endpoint

Configure the DNS Server

run the following command

ibmcloud cs cluster-get <kubernetes cluster> | grep Subdomain

the place

<kubernetes cluster> is the name of your cluster

within the DNS Server create an alias between both URLs in the outdated section and the outcomes of the command above.

regulate Ingress

kubectl get ing

edit the the ingress file for the entries with dynamic-gateway-carrier within the name

kubectl edit ing <unencumber>-dynamic-gateway-provider -o yaml

and

kubectl edit ing <release>-dynamic-gateway-provider-gw -o yaml

Add the following lines to the metadata.annotations

Conclusion

The datapower is now able to be registered in the Cloud supervisor of your APIC 2018 stack.


Santander strikes a $seven hundred million cope with IBM | killexams.com Real Questions and Pass4sure dumps

This story turned into brought to enterprise Insider Intelligence "Fintech Briefing" subscribers. To learn extra and subscribe, please click on right here.

Spanish multinational bank Banco Santander reached a $seven hundred million five-year international technology settlement with IBM to deepen its enterprise transformation efforts, per an announcement.

business Insider Intelligence

IBM talked about the deal will allow Santander to accelerate its movement toward an open and contemporary IT environment, whereas additionally presenting annual discounts on the financial institution's IT spend.

The settlement is gigantic for the financial institution, allowing it to deliver more desirable options in three key areas of center of attention:

  • Santander will be in a position to meet its strategic aim of constructing an superior IT architecture. IBM's solutions and information will aid Santander in its circulate towards a multicloud environment: IBM will collaborate with the financial institution's Cloud Competence middle to define approaches and methodologies that can accelerate its transformation. additional, by using applied sciences corresponding to IBM API join and IBM DevOps, Santander can take manage of its software programming interface (API) lifecycle, in addition to construct and set up new purposes with speed.
  • IBM's applied sciences will permit Santander to boost its services. by using IBM Watson, for instance, the financial institution will take expertise of AI capabilities to improve customer adventure and branch advisors abilities, as two examples.
  • The deal will aid Santander conform with excessive business protection and regulatory standards as it progresses with its transformation. through the use of IBM safety equipment in areas such as incident response and mobile purposes, the bank will be certain more desirable protection for its operations and customers.
  • Santander's agreement with IBM will assist it understand the merits of digital capabilities and expertise in its company transformation. Many ordinary banks nonetheless function legacy systems, making it painful and high priced to retain and alter their IT architecture, while the inability of up to date applied sciences to analyze client information makes it difficult to meet the altering calls for of their consumers.

    Optimizing facts evaluation is also vital for reporting purposes and guaranteeing regulatory compliance. Santander seems to be employing a holistic strategy to its transformation with a purpose to permit it to stream to a modern IT environment to make its operations extra productive and adaptable, assist its regulatory work, and assist it convey creative solutions to its purchasers.

    Get the latest IBM stock expense here.


    IBM is all-in on hybrid cloud | killexams.com Real Questions and Pass4sure dumps

    (photograph: Stockfresh)

    a number alterations to cloud capabilities introduced all over the suppose convention, all aimed toward assisting shoppers go truly hybrid

    Print

    PrintPrint seasoned

    read extra: cloud computing Ginni Rometty hybrid cloud IBM feel conference

    Following its $33 billion (€29.2 billion) acquisition of the open supply Linux company red Hat remaining yr, IBM has naturally set out its approach for the longer term, and it is all concerning the hybrid cloud.

    “IBM will become the realm’s number one hybrid cloud company, providing agencies the simplest open cloud solution for you to liberate the entire price of the cloud for his or her agencies,” IBM CEO Ginni Rometty noted at the time of the acquisition, making a transparent remark concerning IBM’s hybrid-led strategy. furthermore, she informed CNBC  that hybrid cloud is a “trillion dollar market and we’ll be number one”.

    all the way through the business’s flagship feel experience in San Francisco, the dealer firmed up these plans with a raft of announcements geared toward just about helping shoppers circulation to a hybrid cloud model, from a new integration platform to a military of consultants concentrated on helping valued clientele go hybrid.

    Accommodating workloads Hybrid cloud is an business IT approach that includes operating definite workloads throughout distinctive infrastructure environments, be it probably the most most important public cloud suppliers (Amazon web capabilities (AWS), Microsoft Azure or Google Cloud Platform (GCP), a non-public cloud, or on-premise, usually with a homegrown orchestration layer on suitable. Multi-cloud is a similar conception but tends to now not involve inner most cloud or on-premises infrastructure.

    This architecture permits organizations to diversify their spend and abilities, build resiliency and cherry decide upon points and capabilities counting on where they see a dealer’s strengths.

    That final half is above all mentioned within the enviornment of AI and computing device discovering, the place companies like HSBC and the Telegraph Media group have chosen GCP for its AI features alone (The Telegraph has since long past ‘all in’ on GCP).

    Santander financial institution also announced this week all through think that it could be investing $seven-hundred million (€618.8 million) over 5 years to vicinity IBM as “one among Santander neighborhood’s leading transformation partner — assisting Banco Santander to enforce their hybrid cloud method.”

    IBM is aiding the bank with its “methodologies and tactics to speed up that transformation journey. additionally, the financial institution is the use of a variety of technologies including IBM DevOps solutions and IBM API connect, aimed to increase, iterate and launch new or upgraded functions and digital functions lots greater all of a sudden,” according to a statement.

    Banking, with all of its legacy expertise, looks essentially the most naturally inclined industry to turn to hybrid cloud. Regulatory and security considerations go away them desirous to maintain key statistics and workloads on-premise, however newfound competitors from agile fintechs skill they deserve to circulate to the variety of faster deployment cycles that can best be carried out in a cloud environment. IBM boasts of BNP Paribas, Westpac, Lloyds Banking community, credit Mutuel, Krungsri, Royal bank of Canada, and Mizuho financial institution all turning to them for hybrid cloud options.

    definitely, a recent file from 451 research found that 60% of EMEA and North American economic features corporations predict to run a multi-cloud structure inside the next two years.

    assisting to go hybridThe two important bulletins by using IBM concentrated on first helping purchasers go hybrid, and secondly opening up its cognitive IBM Watson services to run throughout the important public cloud providers’ infrastructure.

    the first announcement became in fact an entire range of tools and functions “to support groups migrate, integrate and manipulate functions and workloads seamlessly and with security across any public or deepest cloud and on-premises IT atmosphere,” the supplier pointed out in a statement.

    extra in particular, this includes a brand new IBM Cloud Integration Platform to assist function cloud functions throughout cloud and on-premise environments beneath one, comfortable working mannequin and toolset. The ‘container-based’ platform guarantees handy porting of records and functions throughout infrastructure and aligns API management, routine and business messaging.

    On the features side, IBM looks to be aligning lots of its earnings and consulting teams around advising valued clientele on “how to architect the correct holistic cloud strategy from design, migration, integration, road mapping and architectural services to navigating their journey to cloud,” the vendor pointed out.

    Watson run The 2d announcement was the opening out of its AI carrier, IBM Watson, to run on rival public cloud infrastructure, namely: AWS, Azure and GCP.

    Watson, which began existence beating people at the game reveal Jeopardy!, is a set of AI equipment that enable all kinds of companies to boost AI capabilities to observe to their business problems, primarily via Watson Assistant chatbots.

    “businesses have largely been limited to experimenting with AI in siloes due to the barriers caused by cloud company lock-in of their information,” mentioned Rob Thomas, time-honored manager for IBM information and AI. “With most giant establishments storing information across hybrid cloud environments, they need the freedom and selection to apply AI to their information wherever it's kept. via breaking open that siloed infrastructure we can help organizations speed up their transformation via AI.”

    In practice this ability “Watson and Watson OpenScale can now be run in any environment – on premises, or on any private, public or hybrid-multicloud – enabling companies to apply AI to facts anyplace it's hosted,” the seller stated.

    “companies should be able to infuse AI into their apps, regardless of where they dwell. the flexibility this affords can get rid of one of the vital foremost limitations to scaling AI, on the grounds that corporations can now go away facts in comfy or favored environments and take Watson to that records.”

    under the hood this means a new set of Watson microservices which have been containerised the usage of Kubernetes so that they may also be run in IBM Cloud or another public, hybrid or multi-cloud atmosphere.

    Cloud market implications As AWS has grown its trade hegemony, a lot of its competitors are looking less to compete, and greater to enrich Amazon, whereas also taking part in on consumer’s fears of supplier lock-in.

    IBM has long been a player in the cloud vendor wars but has languished outdoor of the ‘massive three’. With this flow IBM is pretty much course correcting, environment out its stall to be the hybrid cloud provider: an unbiased intermediary to support consumers take capabilities of hybrid cloud deployments with much less of the overhead usually required. by way of being as open, and open source, as viable, IBM is displaying shoppers that it should be an unbiased player within the cloud market.

    There are of direction other alternate options for this, OpenStack for one, and tooling like Cisco CloudCenter or VMware vCloud Suite, but there are few which have the useful resource and new center of attention of IBM. The big three all have their personal hybrid solutions too, similar to Azure Stack and AWS Outposts, but these once again come with a certain diploma of dealer lock-in.

    Commenting on the information, Nick McQuire, VP of business research at CCS insight talked about: “IBM’s AI business took centre stage at suppose 2019 and the adventure’s predominant bulletins replicate a a good deal clearer and differentiated strategy emerging from IBM at the moment.”

    He added that Watson any place is “a massive stake within the floor in the commercial enterprise AI market and a key logo of the brand new faith taking shape in IBM now concentrated on hybrid, multi-cloud features, Kubernetes containers and its pink Hat acquisition.”

    IDG information provider

    read extra: cloud computing Ginni Rometty hybrid cloud IBM consider convention

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    How to simplify enterprise-scale data management (part 4) | killexams.com real questions and Pass4sure dumps

    Welcome back to the fourth and final part of this article series about modern, enterprise-scale data management. If you should have missed the beginning of this series, here you can find part 1, part 2 and part 3.

    Big Data vs. All Data

    A couple of years ago Gartner coined the “3Vs” of Data Management as Volume, Velocity and Variety. ‘Volume’ describes the amounts of data that is now being stored and processed on a daily basis. And this volume is indeed humongous: 90% of today’s data has been created in the past 2 years, and volumes are growing nearly 60% year on year. Data volume is also what most people think of first when hearing “Big Data”.

    ‘Velocity’ describes the frequency and speed at which data and information are being created and exchanged, as well as the need to process it. While previously it might have been sufficient to just run batch processes at the end of the day/week/month/quarter, information now needs to be available in real-time to facilitate instant analytics and support meaningful insight generation.

    While Volume and Velocity are indeed critical, the most important “V” stands for Variety. If you look at Enterprise Data today, according to IBM 80% is unstructured and it grows at 2x the rate of structured data. IDC and EMC expect global data volumes to grow to ~40 zettabytes by 2020 (that is 21 Zeros!), a 50x growth from 2010. The variety of unstructured data is being described by industry experts like Forrester as by far the biggest challenge for Information Management today.

    Is your relational database solution really capable of efficiently storing and managing the hundreds of data feeds arriving at your doorstep today, i.e. product catalogue information, images, videos, sensor data streams, metadata, social media feeds, market and financial data, orders, supply chain information, customer sentiment analysis, predictive analytics, etc. So, I believe the problem focus needs to be shifted towards “All Data”, which describes the current problem much more accurately than “Big Data”.

    Operationalising “All Data”

    Enterprises today are at different levels of maturity on their “All Data” journey. As mentioned before, many have already taken a leap of faith and invested heavily in Hadoop deployments in hope of getting a quick return on their investment. Without taking additional steps though, most of these programmes will fail.

    By adding an operational data layer to augment an existing Hadoop deployment, it is possible to leverage MongoDB as real-time access point for pre-processed data from Hadoop batch processes, e.g. long-running Map-Reduce jobs. This pattern can also provide the foundation to build out a two-speed Lambda architecture. The combination of Hadoop + MongoDB enables an easy way to ingest data into a “data lake”, but also provides a real-time access layer, making it simpler for applications and services to use the available information and insight. If you’d like to learn more about how we can help you derive value from your Hadoop deployments, have a look at this whitepaper on operationalising Hadoop data lakes using MongoDB.

    Of course, fixing a potentially failing Hadoop programme is not my preferred way of providing value to my customers. I’d much rather work on a more appropriate, scalable, and efficient solution right from the start. Non-Relational databases like MongoDB have proven time and time again that they are the right solution for today’s requirements to develop and run mission-critical, enterprise-scale applications and solutions.

    At MongoDB, we are working closely with big names from every industry to develop the right information management strategy for them. By building a Minimum Viable Platform (MVP) using MongoDB to run a handful of initial projects, we quickly show the value and ROI opportunities. With an agile deployment model, MongoDB enables companies to deliver incremental value early and frequently, rather than forcing business teams to wait for a long-stretched Hadoop implementation that might struggle to actually deliver on its promises in the end. For example, KPMG France has realised this early on and built their required data lake solely on MongoDB.

    Designed as highly-available, scalable information management solution, MongoDB offers you seamless scaling capabilities for global, always-on, mission-critical deployments. The flexible data model lets you ingest any type of data easily while at the same time providing ultimate flexibility in using the data through the rich and intuitive query language. You can either connect individual applications directly or by leverage a micro services architecture through an API layer, effectively establishing a Data-as-a-Service model.

    You can find more information about how to leverage MongoDB for modern microservice architecture in this 2-part series (part 1, part 2), or on our recent success story about Swisscom building an entire PaaS platform with MongoDB. Other modern design patterns like event sourcing (for example in combination with Apache Kafka) or CQRS (Command Query Responsibility Segregation) are equally well enabled by a MongoDB data platform.

    If you would like to hear more about how MongoDB has helped dozens of successful digital initiatives and how we can help you and your team achieve your goals faster and be more successful, please get in touch with me via LinkedIn or Email and I can arrange a workshop with key business and technology stakeholders in your organization. You can also find the latest customer success stories from our MongoDB World 2017 and MongoDB Europe 2017 conferences on our website, together with a comprehensive list of additional whitepapers and webinars.

    (UPDATE: Direct links to part 1, part 2, part 3)


    Relation of Middleware to Microservices, Docker, and Cloud-Native Architectures | killexams.com real questions and Pass4sure dumps

    The IT world is moving forward fast. I wrote about Microservices and whether that spells the death of the Enterprise Service Bus and other middleware a year ago. This article is a “follow-up” and update to discuss how relevant microservices, containers, and a cloud-native architecture is for middleware. It is unbelievable how fast enterprises of all sizes are moving forward with these topics!

    Today, in June 2016, many enterprises have already adopted containers and cloud-native architectures or are adopting them. This topic is also getting more and more relevant for middleware vendors. Therefore, let’s do an update about the status quo of microservices, containers, and cloud-native architectures in the middleware world.

    Key takeaways of this article:

  • A cloud-native architecture enables flexible and agile development, deployment, and operations of all kinds of software
  • Modern middleware leverages containers, microservices, and a cloud-native architecture
  • Packaging and isolation in containers is not enough, there are many more concepts to understand and leverage
  • The Momentum of Microservices and Docker

    The main goal of microservices and containers is a shorter time to results and increased flexibility for development, deployment, and operations of software. Why has it received so much momentum in the last few months? Because almost any enterprise beyond tech giants such as Amazon, Google, Facebook, or Netflix struggles here significantly.

    Microservices is like a Service-oriented Architecture (SOA): It is an architectural concept and vendor respectively technology independent. Therefore, no clear standard definition or specification is available. You always need to define what you mean with the term microservices before you discuss it with others. Everybody has a different definition. For this article microservices are services that are developed, deployed, and scaled independently. They are not specific to any technology and can offer business or integration logic. Several vendors offer specific support for building microservices (as we will see later in the article) but basically it is not related to any technology.

    While the discussion about microservices architectures started with a famous article by Martin Fowler back in 2014 the actual widespread implementation was intially started by Netflix which open-sourced plenty of frameworks for implementing microservices. We will come back to many of these later, and a lot of the content in the article is inspired by Netflix’ awesome and detailed tech blog posts.

    A Container is dependent on the operating system it runs on. Containers use the resource isolation features of the Linux kernel such as kernel namespaces (isolates an application’s view of the operating environment including process trees, network, user IDs and mounted file systems) and cgroups (provides resource limiting, including the CPU, memory, block I/O and network), and a union-capable file system such as aufs and others. This allows independent containers to run within a single Linux instance, avoiding the overhead of starting and maintaining virtual machines.

    Key differentiators of containers compared to VMs are packaging, portability, created as fit for purpose and therefore lower footprint and startup times, repeatability, better resource utilization of servers, and better integration into the whole development ecosystem (such as Continuous Integration/Delivery lifecycle). Containers with your applications can be built, ship, and run anywhere: on your laptop, on test systems, in pre-production, and in production systems. This is all without changes to any content of the container and the application inside.

    In contrary to microservices, there are several specific implementations of container software. Most of the momentum these days is behind Docker. Its ecosystem is growing daily. This will definitely consolidate again in the coming years, but it will also become much more mature than it is today. Other examples for container technologies are CoreOS’ rkt (Rocket) or Cloud Foundry’s Garden / Warden. Notice that all these container concepts are nothing new, but leveraged in UNIX systems for years, for example, take a look at Solaris Zones.

    Other commercial examples are VMware Photon Platform / vSphere Integrated Containers or Microsoft’s Windows Server containers / Hyper-V containers or VMware Thinapp.

    A great introduction to Docker—and containers in general—can be found here: Docker, the Future of DevOps. "The Open Container Initiative (OCI)"—an Open Standard for Containers—was created in mid-2015 to establish a global, vendor-agnostic standard. Many software vendors are part of the committee, including Amazon, Intel, Docker, Facebook, IBM, Microsoft, Oracle, Pivotal, and VMware, to name a few of the many official supporters.

    A Cloud-Native Architecture

    Microservices and containers with their independent services and flexible deployment are just the foundation. The following sections discuss additional requirements for a cloud-native architecture. Please be aware that a lot of examples for available frameworks are listed in every section but they are not intended to be complete lists.

    A cloud-native architecture enables:

  • Scalable services
  • Resiliency
  • High uptime
  • Automatic load balancing and failover
  • DevOps
  • Usage of public cloud platforms but also private or hybrid
  • Vendor-agnostic deployment
  • Faster upgrades
  • Higher utilization and lower infrastructure cost
  • Shorter time to results and increased flexibility
  • With all this you can focus on innovation and solving your business problems instead of spending your time with plenty of technical issues in ”static and inflexible legacy architectures”. Be aware that cloud-native does not mean that you can deploy software just in the public cloud. Private or hybrid cloud deployments are also contained in the definition of cloud-native!

    Continuous Integration and Continuous Delivery

    Continuous Integration (CI) and Continuous Delivery (CD) require a lot of different things to automatically build, deploy and run microservices. This includes scripting for automatic test and deployment, internal and external service discovery and distributed configuration of microservices and containers.

    Scripting / Automatic Test and Deployment

    This is what CI / CD began with several years ago. You build, test and deploy services automatically. This improved productivity, efficiency, and product quality. The following frameworks and tools are used to create scripts for enabling CI / CD:

    Service Discovery

    We have to work with plenty of different independent services and a huge number of distributed instances of each service. An internal service discovery framework is used to locate services for the purpose of load balancing and failover. Therefore, a service provider registers to the registry when it is available. Consumers discover the service from the registry to be able to connect and consume it.

    A lot of options are available for using a service registry, such as Netflix’ Eureka, Apache Zookeeper, Consul, Etcd. Many of the later discussed frameworks also include a service registry implicitly. It is not always easy to classify each of the frameworks in this article for just one component. Often the features are overlapping.

    In addition to an internal service discovery, an external service discovery framework is used to expose internal microservices to the outside world (which can be the public internet, just partners or other internal departments). This is often called an “Open API initiative” or “API Management” and offers features such as a portal for easy packaging and self-provisioning of APIs (i.e. microservices in this case), monetization and a gateway for security enforcement (e.g. authentication, authorization, throttling). Some relevant options for API Management are:

  • JBoss apiman: Open source, low-level coding framework, can leverage other Red Hat JBoss projects
  • Apigee: Pure player in the API Management market
  • Akana (former SOA Software): Pure player in the API Management market
  • CA’s Layer7: Strong security gateway, can leverage other CA products
  • TIBCO’s Mashery: Strong portal and community, can leverage other TIBCO products, including TIBCO API Exchange Gateway for advanced security and routing requirements
  • See the following article for more details about use cases and product categorization for “Open API”: API Management as a Game Changer for Cloud, Big Data, and IoT.

    Dynamic Distributed Configuration Management

    Numerous agile and dynamic changes in a cloud-native architecture demand that you cannot manage configuration manually anymore when adopting distributed microservices and containers. Services are designed to fail, respawn and get updated frequently. Therefore, you need automated configuration to setup new containers on distributed nodes quickly and automatically. Some required features:

  • Make changes dynamically at runtime (e.g. change service behavior, database connection or log level of a specific instance)
  • Change multi-dimensional properties based on a complex request or deployment context
  • Enable / disable features based on the request context (e.g. display of a specific user interface for a specific region or device)
  • Change behavior of cloud design patterns (see the later section “Resiliency Design Patterns”)
  • Two relevant frameworks for dynamic distributed configuration management are Netflix’ Archaius and Spring Cloud Config. These frameworks use polling and callback mechanisms for dynamic configuration as the traditional push concept (to specific IP addresses and hosts) does not work in elastic and ever changing cloud-native environments.

    Scalability and Failover

    A key feature of a cloud-native architecture is the ability of elastic scaling depending on load and SLAs. This requires advanced cluster management, server-side and client-side load balancing, and resilient design patterns.

    Cluster Management (Scheduling and Orchestration)

    Flexible development and deployment is a key advantage of microservices and containers. New features are added and old ones pruned. Zero-downtime and failover are required but you also need efficient usage of your resources.

    A cluster manager is designed for failover and high scalability. It is used to automatically orchestrate container scheduling and managing hosts including the application of rules and constraints to each host.

    Various cluster management frameworks are already available especially for Docker. The following examples are some of the most relevant (and discussed in more detail here):

  • Docker Swarm: A Docker-native framework, uses the Docker API, can easily leverage other Docker frameworks such as Docker Compose, it has to be combined with other frameworks such as etcd, Consul or ZooKeeper
  • CoreOS Fleet: Low-level framework built directly on systemd, often used as “foundation layer” for higher-level solutions
  • Kubernetes: Open sourced by Google and adopted by many other companies including IBM, Red Hat and Microsoft. Kubernetes is a great mix of sophisticated features and relatively simple installation / configuration. In contrast to some other sophisticated cluster managers you can even set it up on your local machine for development with just a single “Docker run” command. If you install it on a cloud platform it leverages the platforms specific features, for example on AWS it uses Amazons ELB while it leverages Googles LB on Google Cloud Platform.
  • Mesos’ Marathon: An orchestration framework on top of the powerful (but complex) Apache Mesos, a “distributed systems kernel.” Mesos is intended for large scale and multi-use of different frameworks on top of it (e.g. Apache Hadoop, containers via Marathon, batch processing via Chronos).
  • Load Balancing (Server-side and Client-side)

    Servers come and go in a cloud-native architecture. Load balancing needs to become much more sophisticated (and therefore complex) with microservices and containers. Just distributing load based on well-known IP addresses and hosts is not sufficient anymore. Concepts such as weighted load balancing based on several factors like traffic, resource usage or error conditions provide superior resiliency.

    Traditional server-side load balancing is used for years to distribute network or application traffic across a number of servers and to increase capacity and reliability of applications. Well-known examples are F5’s Big-IP products or Amazon AWS Elastic Load Balancing (ELB) service. They are used for so-called edge services i.e. external service consumers respectively end-user web traffic.

    In addition, many microservices architectures include client-side load balancing to avoid unnecessary inter-service communication. Therefore frameworks such as Netflix Ribbon “embed” the client-side LB into each microservice. This reduces the communication to one hop instead of two hops for service communication between internal microservices, so-called mid-tier or core services.

    Resilience Design Patterns

    All the new concepts for a cloud-native architecture require new design patterns to offer a general repeatable solution to commonly occurring problems. Resilience design patterns prevent cascading failures, allow failing fast and recover rapidly by implementing logic for latency tolerance, fault tolerance, and failback logic.

    One of the most well-known patterns is the Circuit Breaker which is used to detect failures and encapsulate logic for preventing a failure to reoccur constantly (during maintenance, temporary external system failure or unexpected system difficulties). The Akka framework has a nice explanation and implementation of this pattern. Netflix Hystrix also offers sophisticated implementations to enable latency and fault tolerance in distributed systems. “Application Resiliency Using Netflix Hystrix” is a great post by the Ebay Tech Blog explaining how they leveraged it to realize cloud patterns.

    There are plenty of cloud patterns emerging (and more will come in the future). For example, the Kubernetes Tech Blog explains “Patterns for Composite Containers” such as “Sidecar Containers,” “Ambassador Containers,” or “Adapter Containers”.

    Container Solution Stacks

    As you have seen in the above sections, there are plenty of frameworks and tool chains available. The number is growing every month. This might remind many readers of Apache Hadoop and its unbelievably growing ecosystem with mature and less mature frameworks. The same is true for containers today. Therefore some “solution stacks” are emerging to help getting started and managing all the different challenges with one single (and commercially supported) container stack—well known as “distribution” in the Hadoop environment. Examples for container solution stacks are Tectonic (a Kubernetes + CoreOS Platform), Docker Datacenter, Mantl or HashiCorp’s Nomad. More will probably arise in the next months.

    We have now discussed several concepts, frameworks, and patterns to realize a cloud-native architecture leveraging containers and microservices. However, you also need some kind of cloud platform where you deploy and run all this on.

    Private, Public, or Hybrid Cloud-Native Platform

    A cloud-native platform is a private, public or hybrid cloud which offers a self-service and agile cloud infrastructure (Infrastructure-as-a-Service, IaaS). On top of a cloud infrastructure, you need a platform (Platform-as-a-Service, PaaS) where you can deploy and run your containers. The following picture shows the key characteristics of both:

    image

     

    Most enterprises select available mature offerings such as Amazon Web Services, Microsoft Azure or open source OpenStack for IaaS and PaaS platforms such as Red Hat’s OpenShift (which is based on Docker and Kubernetes) or Cloud Foundry (offered open source and enhanced by several vendors such as IBM with Bluemix or Pivotal).

    The key advantage of using an existing PaaS platform is the out-of-the-box support for most requirements of a cloud-native architecture such as elastic scalability, container orchestration, dynamic service discovery, load balancing, or dynamic distributed configuration management. Thus, you should evaluate different PaaS platforms before deciding to build your own one based on all the different frameworks discussed above. Most platforms leverage one or the other of these frameworks implicitly.

    After discussing all the requirements and available frameworks for a cloud-native architecture in much detail let’s now take a look at how all this is related to middleware.

    Relation to Middleware (Integration, API Management, Event Processing)

    Before going on, I have to clarify: Microservices, containers, and cloud-native architectures are not suitable for all scenarios. Remember: These introduce a lot of new concepts and complexity. “Microservices are not a free lunch”!

    I will focus especially on integration platforms in the following paragraphs because integration is key for success in most middleware projects. Due to trends such as cloud, mobile, big data and Internet of Things you cannot survive without good integration in IT architectures.

    An Enterprise Service Bus (ESB) is used in many enterprises as a strategic integration platform between custom applications, commercial-off-the-shelf software, legacy applications, databases, and cloud services. However not every ESB deployment needs to be cloud-native. In mission-critical deployments at banks, retailers, airlines, telcos, and others a central ESB with high performance, high availability, and fault-tolerance might still be the best choice for the next few decades.

    On the other hand, an ESB is not the complex, central and heavyweight beast you might think of. This might have been true 5 to 10 years ago (and one of the reasons several SOA projects failed that time) and it might still be true for some vendors today. But in general (and valid for many vendors) an Enterprise Service Bus in 2016 is a mature, stable and easy to use component, which should offer:

  • Integration
  • Orchestration and Choreography
  • APIs and Business Services
  • Messaging
  • Independent Deployments
  • Scalable and Lightweight Platform
  • Automation
  • Based on your requirements you should be able to decide how cloud-native you need to be and if you should leverage microservices and containers (and all their pros and cons) or not. Select only the concepts, tools and features you really need.

    Middleware Examples

    Having said that let’s take a look at a few different middleware examples and how you might leverage microservices, containers and a cloud-native architecture for them:

  • Integration: Build (micro)services and APIs using the integration capabilities of the ESB; integrate and orchestrate different (micro)services (build composite services)
  • API Management: Expose, publish and monetize microservices internal or to partners and the public world via APIs.
  • Event Processing: Correlate distributed microservice events in real time to add business value (e.g. fraud detection, cross-selling or predictive maintenance)
  • All the above middleware components

  • Require agility and flexibility
  • Control and leverage other microservices
  • Have to support microservice characteristics itself (containers, CI / CD, elastic scalability, etc.) to fit into a cloud-native architecture and to allow quick changes
  • Let’s come back to the example of integration platforms and the ESB. If you need a more flexible, cloud-native integration solution instead of a classical, more central ESB deployment then you have three options (but do not care about the branding or shortcut of the product name):

    Integration Middleware on Top of a PaaS

    This is very similar to an on-premise ESB and used for implementing “core services” i.e. central, often complex and mission-critical services. Development is done in the traditional IDE. However, the key difference is that the solution is cloud-native i.e. it supports containers and microservices. You use this kind of integration middleware to develop integration applications that are deployed natively onto a PaaS platform such as Cloud Foundry or OpenShift. Some vendors offer a vendor-agnostic solution where you can deploy your integration applications anywhere without relying on a specific cloud platform or vendor.

    You can develop different “cloud-native services” to be more agile, change quicker, and provide web scale:

  • Integration Apps and Services: Build consumable Web APIs out of backend web services like ERP, CRM, order management using enterprise technologies like SOAP, SAP, Oracle, IBM MQ, etc.
  • Functional Microservices: Build apps focusing on business functionality without getting into code complexity
  • API Choreography Services: Visually choreograph APIs leveraging the PaaS integration tooling (e.g. process orchestration, data mapper or connectors)
  • There are not many alternatives available on the market for building integration applications that are deployed natively onto a PaaS platform. TIBCO BusinessWorks Container Edition is a vendor-agnostic example supporting CloudFoundry, Docker, Kubernetes, AWS ECS, etc. JBoss Middleware Services allows the deployment of its middleware applications (including JBoss Fuse and A-MQ) onto OpenShift.

    Cloud Integration Middleware (iPaaS)

    An iPaaS Cloud Integration middleware is cloud-based, uses a web browser instead of a desktop IDE and supports the execution of integration flows, the development and life cycle management of integrations, the management and monitoring of application flows, governance and essential cloud features such as multi-tenancy, elasticity, and self-provisioning. iPaaS can work closely together with an on-premise ESB or integration middleware on top of a PaaS platform.

    iPaaS tooling offers intuitive web-based integration and is intended for people with some technical understanding e.g. how to create and deploy REST services or to configure connections and policies of Open APIs. It is usually used to build “edge services”, sometimes also called “microflows” which might change more frequently and which are often not that mission-critical.

    Some examples for iPaaS solutions are Dell Boomi, Informatica Cloud, MuleSoft Anypoint Platform, SnapLogic, Jitterbit, or TIBCO Cloud Integration.

    A more detailed overview including the pros and cons of iPaaS can be found here: “iPaaS: What this cloud technology is and why it’s important”.

    SaaS Cloud Integration Middleware (iSaaS)

    This kind of SaaS solution offers an intuitive web-based user interface for the business user i.e. the “Citizen Integrator” to realize personal integration without technical knowledge according to the do-it-yourself (DIY) principle. Citizen Integrators build new integration flows by configuring them rather than developing and building them from scratch. For instance, a business user creates an automatic flow to synchronize his data via self-service from SaaS offerings such as Salesforce or Marketo and his Microsoft Excel sheets.

    iSaaS integrations are clearly complementary to on-premise, PaaS and iPaaS integrations. They should also be viewed as “edge services” which are not strategic and mission-critical for the enterprise–but very relevant for the specific business user. Examples for iSaaS solutions are SnapLogic, TIBCO Simplr, or IFTTT.

    Hybrid Integration Platform (HIP)

    A key for success is that you can transfer content across different platforms. Gartner calls this a Hybrid Integration Platform (HIP). Different components share metadata, one single IDE, and consolidated operations management. Out-of-the-box integration capabilities with API Management components (API gateway and portal) are also very important for agile development, deployment, and operations.

    For example, you might want to develop an orchestration service with a PaaS-based integration solution and want to port that to an on-premise integration platform later. Or you might want to define a REST service (via “contract first principle”) with an iPaaS middleware with a mock for early testing and later implement it on an on-premise ESB. The same service also needs to be exposed via an API to partner or for public access.

    Some more Middleware Frameworks and Vendors

    Finally, I want to highlight some other frameworks and vendors, which might be relevant for realizing your cloud-native microservices but were not mentioned in the article yet:

  • WSO2 Microservices Framework for Java is a good example for a low-level coding framework based on top of the vendors open source middleware.
  • Amazon EC2 Container Service (ECS) and Google Container Engine are two examples of “Containers as a service (CaaS)” offerings which allow self-service usage of containers as SaaS solution
  • Cloud vendors such as Amazon, Microsoft, or Google are also middleware vendors in the meantime. For example, Amazon AWS offers services for cloud messaging (SQS and others), streaming and analytics (Kinesis), containers (ECS), microservices (Lambda) and more.
  • Plenty of other middleware vendors also work on cloud-native offerings. For more details see e.g. Software AG Cloud, Talend Integration Cloud, or Oracle Cloud Platform.
  • Middleware for the Internet of Things (IoT) is another sector which grows significantly these days. For example, take a look at open source integration solutions such as Node-RED (based on js, open sourced by IBM) or Flogo (based on Google’s Go Programming Language, to be released and open sourced by TIBCO very soon). Both offer a zero-code environment with web IDE for building and deploying integration and data processing directly onto connected devices using IoT standards such as MQTT, WebSockets, or CoaP.
  • Finally, I would like to mention The Cloud Native Computing Foundation (CNCF) which might become much more relevant in the future for plenty of frameworks discussed in this article. The CNCF was founded to help facilitate collaboration among developers and operators on common technologies for deploying cloud-native applications and services built on containers. Founding members included Google, Cisco, IBM, Docker, and VMware. The first two projects hosted by CNCF are Kubernetes and Prometheus.

    Microservices, Containers, and Cloud-Native Architectures Do NOT Fit into Every Project…

    … but they have a huge influence on our thinking about IT architectures. In many new projects, these concepts absolutely make sense and create a lot of benefits such as flexible development, deployment, and operations. Think about the trade-offs and leverage the parts of a cloud-native architecture which make sense for your project. Modern middleware will leverage microservices, containers, and cloud-native architectures! No matter if you take a look at Integration, API Management, Event Processing, Streaming Analytics, Business Process Management, or any other kind of on-premise or cloud middleware.

    Thanks for reading this extensive article. I think it is very relevant for all of us, no matter if you implement custom applications or leverage middleware in your projects. As always, I appreciate any feedback and discussions via Comment, Email, Twitter, or LinkedIn.

    By the way: The content of this article is also discussed in a slide deck which I first presented in April 2016 at JPoint in Moscow, Russia:

    Microservices, Containers, Docker and a Cloud-Native Architecture in the Middleware World from Kai Wähner


    Microsoft's Hybrid Cloud Strategy | killexams.com real questions and Pass4sure dumps

    In-Depth

    Microsoft's Hybrid Cloud Strategy

    Microsoft is building a stronger bridge between Windows Server and Microsoft Azure, but it'll also manage AWS, VMware and OpenStack infrastructure and services.

    Early visions of cloud computing saw a day when enter­prises could deploy applications and business services without the need for any datacenter compute, storage and application infrastructure. Back in 2006, Sun Microsystems Inc. introduced the Sun Cloud Compute Utility, comprised of computing for $1 per CPU hour. Obviously, the Sun offering never gained traction, but it arrived around the same time Amazon.com Inc. launched its Amazon Web Services Inc. (AWS) cloud business, which of course upended the traditional datacenter business and created the beginning of today's public cloud services market.

    It's perhaps no coincidence Amazon.com never had a software or hardware business to protect. Along with its stomach for razor-thin margins, the company delivered the first sustainable utility compute and storage services. While removing the datacenter is still a pipedream for most established enterprises (many would argue it would be a nightmare), cloud computing has very much taken root in varying forms and scope.

    Now cloud technology is undergoing another significant shift in its evolution and Amazon.com's key competitors are hoping what was once an AWS strength -- no legacy business to protect -- will become a weakness, or at the very least help level the playing field. Key infrastructure and application platform providers are developing new software-defined, hybrid cloud infrastructure and services aimed at functioning as the control plane of the datacenter. Among them, Microsoft, VMware Inc., and Citrix Systems Inc. are readying hybrid cloud platforms that enable the use of public and private clouds to build, manage, and provision IT services and deliver applications as a service, even as companies stick to keeping core components -- notably data -- on-premises.

    The cloud control planes are the latest effort to bridge the on-premises datacenter with public infrastructure and platform services. It appears they're built with the realization no organization is going to use solely one public cloud to procure infrastructure and applications. The growing shift to Software as a Service (SaaS) and modern apps designed for traditional and mobile device types is expected to compel many organizations to use multiple cloud providers to deliver, secure and manage user access to system resources apps and data. The emerging cloud control planes will let IT do so whether employees are using traditional computers, remote desktops, virtual applications or by accessing modern apps from any device.

    Certainly Citrix, Microsoft and VMware aren't the only ones building these new bridges from software-defined datacenters to next-generation public clouds. But when it comes to managing Windows client and datacenter infrastructure, all three will offer major new capabilities to consider.

    Revamping the Microsoft Cloud OSFor its part, Microsoft three years ago tried to provide a more consistent platform between Windows Server and Azure with its Cloud OS consisting of Windows Server 2012, System Center 2012 and the Windows Azure Pack. The latter was designed to put an Azure-like veneer on Windows Server. Though a major step forward, the Azure cloud and Windows Server 20012 (and the R2 release), aren't one and the same. Furthermore, Azure and other public clouds have evolved substantially in three years. Consider back in 2012 the Microsoft cloud service was still called Windows Azure -- now it's Microsoft Azure. While the move sounded superficial when Microsoft first announced the change, it has become clearly apparent why Microsoft renamed the service. Azure is not just a Windows-based cloud service.

    At its recent Build and Ignite conferences, and the months leading up to those events, Microsoft has outlined planned upgrades to the Azure cloud, which include the Azure Service Fabric. "Service Fabric is a high-control, distributed computing framework," said Scott Guthrie, Microsoft's executive vice president for Cloud and Enterprise, speaking during the Build keynote. "We created it to power our own high-scale cloud services, and we've battle-hardened it over the last several years under extreme loads and super-demanding requirements. It supports the ability to create cloud services composed of both stateless and stateful micro-services. And it has support for hyper scale-out deployments, self-healing and core management, as well as the orchestration of code updates."

    Along with that announcement, Microsoft made available the Service Fabric SDK for both Windows and Linux systems. "In addition to supporting Azure, you'll also be able to use it to build great solutions that run in a multi-cloud environment," Guthrie said. Microsoft released Azure Service Fabric on the heels of the release of the Azure App Services, which consist of Web, mobile, BizTalk connectivity and APIs that Microsoft claims easily integrate with SaaS and on-premises systems.

    "API Apps allow you to take any existing API, whether it's an API in the cloud or an API on-premises, and project that into App Service adding some simple metadata," explains Omar Khan, Microsoft's director of Azure Engineering. The BizTalk connectors provide the links between on-premises and SaaS apps, he adds. "We have virtual networking in Azure that allows you to connect on-premises resources to the cloud. They also support hybrid connections which is a BizTalk capability that allows you to do app-to-app connection across firewalls. So these API Apps and the Oracle connector or the SAP connector, among others, utilize those connectivity options in Azure to connect to the on-premises resources and then there's a connector piece that you can run on-premises that connects to that API App."

    "Service Fabric is a high-control, distributed computing framework. We created it to power our own high-scale cloud services, and we've battle-hardened it over the last several years under extreme loads and super-demanding requirements."

    Scott Guthrie, Executive Vice President, Microsoft Cloud and Enterprise Group

    Operations Management SuiteMeanwhile, Windows Server 2016 promises to be more Azure-like than its predecessors.

    Interestingly, Microsoft hasn't, at least yet, talked up the notion of migration from AWS, VMware and others, but rather has come up with a model that embraces coexistence. Microsoft plans to do this with several new offerings that'll start to appear later this year, such as the new Operations Management Suite (OMS), a new offering intended to provide hybrid cloud management -- and not just for managing Azure. The Web-based console provides deployment, management and integration of public cloud and datacenter services running in AWS, Linux, VMware and OpenStack. OMS integrates with Microsoft System Center, but doesn't require it.

    "It gives you that any cloud, any OS, any application and you get orchestration," said corporate VP Brad Anderson, in the keynote presentation at the company's Ignite conference back in May, where he announced OMS. "You get application availability. You get disaster recovery and backup. And you get all of that capability -- again, virtual, physical, public cloud, private cloud, VMware, Hyper-V -- all in one pane of glass."

    OMS will consist of various "solution packs" such as malware assessment, system update, change tracking and run book automation, among others, and will use analytics to gather log files and correlate them. These solution packs have "ready-made intelligence" that Microsoft has built that utilizes knowledge from all the log files and analytics data Microsoft has collected, explained Jeremy Winter, Microsoft's principal group manager for System Center and Services, who discussed OMS during an Ignite press briefing.

    "Whether it's running on-premises, or sitting in another cloud infrastructure like Amazon or Azure, this is really where we're taking management and making sure that you have that hybrid view in there," Winter said. "It's not something separate, as a separate thing, we think management needs to be brought back together and hybrid should just be part of your overall management." To extend the ability to monitor infrastructure enabling visibility at the transaction level, Microsoft last month acquired BlueStripe Software, an application performance management software provider. Microsoft said it would "discontinue selling the solution in the near term" and work on integrating the BlueStripe technology into OMS and its new Azure Stack.

    Microsoft conducted telephone interviews with 600 customers and the surveys concluded that 60 percent said they were ready to start using a cloud-based management-as-a-service offering like OMS, according to Winter. "That was a big jump from where we were thinking," he admitted.

    Windows Azure Pack Grows into a StackAs noted, the Windows Azure Pack when launched three years ago was aimed at giving Windows Server 2012 the ability to look like the Azure cloud. The Microsoft Azure Stack is a much more ambitious effort, company officials explained at Ignite in that it builds on the new Azure Service Fabric and the forthcoming Windows Server 2016, which the company says will provide more seamless connectivity to the public cloud service.

    Enabling the improved portability is the fact that Windows Server 2016 will support Docker Inc. containers, its own Windows container environment and a corresponding micro-­services architecture. "We think about Azure Stack as the delivery of the Azure innovation, deployable and manageable on-premises," said Ryan O'Hara, Microsoft's director of program management for private cloud solutions. The notion of Azure Stack, which is slated to appear in the next Windows Server 2016 Technical Preview, is that it will provide consistent Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS) services on-premises, he added.

    O'Hara emphasized that Azure Stack won't just be an incremental upgrade to the Windows Azure Pack. "Windows Azure Pack is not the full stack implementation of the Azure innovations," he said. "It is a deep effort to replicate a cloud experience, but as you move over to Azure Stack you have a reimplementation of not only the experience, but the underlying services, the management model, as well as the datacenter infrastructure. It really is a rounding out and a completion of what we're learning in Azure in the customer datacenter. From a tenant experience, with Azure Stack, you'll see this based on the new Azure Portal, both GUI experience [and] programmatic experience, allowing you to bring your PowerShell, but also your development tools and developer processes. So you can expect Visual Studio and TFS [Team Foundation Server] to operate seamlessly against Azure Stack as it does against Azure, really just creating a parallel endpoint to deploy your applications."

    While Cloud OS and the Windows Azure Pack had too many holes for the liking of third-party cloud services providers, O'Hara is optimistic the new Azure Stack will appeal to them. "It's a very consistent set of experiences, it allows the single Azure ecosystem to be developed to thrive both in the public cloud [and] in the private cloud landscape. Actually, it's a critical value to the ecosystem, and with one Azure ecosystem, it's something that will yield consumption across many, many clouds."

    Of course, that remains to be seen when Azure Stack appears in the next Windows Server 2016 Technical Preview. But if it works as Microsoft envisions, it could change the way many IT pros and developers look at cloud computing.



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