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000-400 - IBM WebSphere Operational Decision Management V8.0 Application Development - Dump Information

Vendor : IBM
Exam Code : 000-400
Exam Name : IBM WebSphere Operational Decision Management V8.0 Application Development
Questions and Answers : 51 Q & A
Updated On : February 21, 2019
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000-400 Questions and Answers

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000-400 IBM WebSphere Operational Decision Management V8.0 Application Development

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000-400 exam Dumps Source : IBM WebSphere Operational Decision Management V8.0 Application Development

Test Code : 000-400
Test Name : IBM WebSphere Operational Decision Management V8.0 Application Development
Vendor Name : IBM
Q&A : 51 Real Questions

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IBM IBM WebSphere Operational Decision

IBM to support Utilities reduce Tree Trimming Budgets and reduce Outages | killexams.com Real Questions and Pass4sure dumps

IBM unveiled new technology to cut back vigor outages by means of assisting energy organizations predict where trees and other vegetation might also threaten vigour traces. IBM labored with Oncor, the biggest utility business in Texas and the fifth largest within the u.s., to advance an answer tailor-made for the power and utility business, to aid improve operations and provide reputable electric provider for thousands and thousands of clients across the state.

The weather business Vegetation management - Predict is built on IBM PAIRS Geoscope, a know-how developed by way of IBM analysis.The gadget at once strategies massive, complex geospatial and time-based datasets accumulated with the aid of satellites, drones, aerial flights, millions of IoT sensors and climate models.

The resulting insights can assist organizations like Oncor to display screen vegetation increase throughout their whole carrier territory, permitting them to more desirable determine and predict competencies infringement with power strains. companies can more proactively and precisely plan for preventive maintenance and speedy response, focusing crews in the maximum-precedence places and validating that imperative trimming turned into achieved as anticipated.

"electrical energy is an important part of our lives, and hundreds of thousands of Texans depend on Oncor each day. Vegetation poses a major possibility to vigour lines and the surrounding areas, but monitoring it's a challenging and time-consuming manner," says Peter Stoltman, vegetation administration program supervisor, Oncor. "through working with IBM, we are capable of use analytics and AI to prioritize excessive-possibility areas. This helps us adapt protection operations to improve public defense and repair reliability."

Vegetation is a leading explanation for provider interruption for utility companies. With traditional processes, the primary perception into advantage risks includes high priced on-website inspections or realizing the last time a local become trimmed. With this new solution, hundreds of miles of transmission and distribution traces will be always monitored to give continuous insight about the state of increase and preservation. besides assisting identify and predict outage threats, geospatial-temporal insights can assist with common grid reliability and compliance, wildfire prevention, storm management and evaluation.

“Our utilities customers told us that getting detailed perception into the state of vegetation throughout their carrier territory changed into a key challenge,” says Mahesh Sudhakaran, chief digital officer of IBM energy, atmosphere and Utilities. "by using combining PAIRS with AI and industry advantage, we may give valued clientele one integrated answer, delivered through IBM Hybrid Cloud, to aid them predict and manage vegetation in a value-effective and clever means.”

“every enterprise is suffering from climate. however for power corporations and their consumers, it might imply the change between even if they could retain the lights on and heat their homes,” says Cameron Clayton, IBM’s usual manager of Watson Media and climate. “The capability to layer climate facts with satellite tv for pc and sensor records gives utility companies potent new insights to assist them enhance operations and cut impact on their purchasers.”

PAIRS Geoscope ingests greater than 10 terabytes of new records per day and has already served more than 15 million requests from greater than 4,000 researchers, information scientists and developers in 80 international locations. It removes the labor-intensive method of generating insights from geospatial-temporal information, which is universal for its sheer dimension and complexity. The lack of ability to access, query and analyze this classification of large records in a scalable manner is the motive it become long regarded unsearchable statistics. IBM scientists invented a brand new technique to run and analyze complex queries inside minutes as a substitute of weeks or months, making prior to now unimaginable insights now a fact.

PAIRS Geoscope is commonly accessible for distinctive industries and use circumstances. besides Vegetation management - Predict, PAIRS is additionally the underlying technology for Watson choice Platform for Agriculture, a collection of agribusiness tools that uses the power of AI and geospatial records to help farmers make greater suggested choices about their plants.

For greater suggestions, view the net website. 


international Healthcare choice assist and IBM Watson Market, 2019: analysis & Outlook via 2016-2026 - ResearchAndMarkets.com | killexams.com Real Questions and Pass4sure dumps

The "world Healthcare decision help and IBM Watson Market size, Market Share, utility evaluation, Regional Outlook, growth tendencies, Key players, competitive recommendations and Forecasts, 2018 To 2026" file has been brought to ResearchAndMarkets.com's offering.

The world healthcare resolution support and IBM Watson market are anticipated to expand at a CAGR of eleven.four% from 2018 to 2026.

IBM Watson has developed a core engine which aids the scientific community in understanding scientific literature by cross-referencing and extracting assistance related to genes, diseases, medicine and promote dissimilar access to users global.

Healthcare decision support is greatly employed by using medical professionals to support them in providing cost-based care and mediate strategic resolution touching on the treatment routine. it's positive in featuring services reminiscent of purchaser engagement and fraud detection in executive and privately held clinical facilities.

excellent points corresponding to information warehousing, streamlining administrative operations and stakeholder administration are being imparted to healthcare determination help capabilities. population trend evaluation, demographics, can charge-sharing, and recipient profiling are being developed under novel healthcare reform initiatives promoted by means of executive healthcare organizations international.

IT healthcare options are reigning the choices section for healthcare decision support market. a tremendous era of scientific statistics, pressing requirement of medical insights to help in the choice making for medicine of sick sufferers power the IT healthcare solutions market growth.

Genomic reviews are being fortified with previous scientific facts to supply valuable therapeutic options for malignant tumors and increase affected person compliance. synthetic intelligence and cognitive computing are being combined with true-time scientific facts to promote helpful medicine guidelines and sickness analysis.

North the usa is at the moment leading the regional phase for healthcare resolution help and IBM Watson market. abode of key gamers comparable to IBM Watson, Accenture, American well methods, AT&T, McKesson employer and many others. provide IT-healthcare options to the medical fraternity of North the us. The burgeoning requirement of novel drug discovery within the light of increasing mortality caused with the aid of persistent diseases drives the healthcare decision help market boom in North the us.

Strategic collaboration between pharmaceutical giants and research academia and proactive executive policies in proposing positive remedy guidelines propel the healthcare decision help market boom within the European region.

The Asia Pacific can be the quickest starting to be market all the way through the forecast length from 2018 to 2026 due to constructing IT-healthcare sector and extending mortality linked to an absence of constructive medicine bearing on continual disorder.

Key Market movements

  • The rising incidence of persistent disease and the burgeoning requirement of novel drug discovery during the globe
  • developing healthcare infrastructure and extending demand for IT-healthcare solutions within the patient medication
  • Cognitive computing and synthetic intelligence being clubbed with real scientific evidence to promote dazzling scientific effects
  • issues lined

    Chapter 1. Preface

    1.1. report Scope and description

    1.2. analysis Scope

    1.3. analysis Methodology

    1.4. Market Segmentation

    Chapter 2. govt abstract

    2.1. world Healthcare resolution aid and IBM Watson Market Portraiture

    2.2. international Healthcare determination support and IBM Watson Market, by choices, 2017 (US$ Mn)

    2.three. international Healthcare resolution support and IBM Watson Market, through Geography, 2017 (US$ Mn)

    Chapter 3. Healthcare decision support and IBM Watson Market: Dynamics and Future Outlook

    three.1. Market Overview

    3.2. Drivers

    3.three. Challenges

    3.four. alternatives

    3.5. captivating investment Proposition, by Geography, 2017

    3.6. competitive evaluation: international Healthcare decision assist and IBM Watson Market, through Key avid gamers, 2017

    Chapter four. global Healthcare decision aid and IBM Watson Market, through offerings

    four.1. Overview

    four.2. IT-Healthcare options

    four.three. medical records management

    4.4. Genomics

    four.5. Drug Discovery

    Chapter 5. international Healthcare determination help and IBM Watson Market, by way of Geography

    5.1. Overview

    5.2. North america Healthcare decision help and IBM Watson Market evaluation, 2016-2026

    5.three. Europe Healthcare decision assist and IBM Watson Market evaluation, 2016-2026

    5.four. Asia Pacific Healthcare resolution aid and IBM Watson Market evaluation, 2016-2026

    5.5. Latin america Healthcare determination aid and IBM Watson Market analysis, 2016-2026

    5.6. middle East & Africa Healthcare decision support and IBM Watson Market evaluation, 2016-2026

    Chapter 6. enterprise Profiles

    6.1. Accenture

    6.2. Aetna

    6.3. American neatly methods

    6.four. AT&T

    6.5. Cisco

    6.6. EMC fitness Care Ltd.

    6.7. IBM Watson

    6.eight. McKesson business enterprise

    6.9. Optum Inc.

    6.10. Vangent Inc.

    For more counsel about this document visit https://www.researchandmarkets.com/analysis/nlndxb/global_healthcare?w=4

    View supply edition on businesswire.com: https://www.businesswire.com/news/home/20190206005356/en/

    source: research and Markets

    ResearchAndMarkets.comLaura timber, Senior Press Managerpress@researchandmarkets.comFor E.S.T office Hours name 1-917-300-0470For U.S./CAN Toll Free name 1-800-526-8630For GMT workplace Hours name +353-1-416-8900Related topics: Healthcare services, synthetic Intelligence

    Copyright business Wire 2019


    IBM: a way to Play It post revenue Rally | killexams.com Real Questions and Pass4sure dumps

    IBM (IBM) has been a inventory to be averted in the past a number of years. however, the undeniable fact that so many of its most bullish shareholders have thrown in the towel on IBM has led to it to have mostly been forgotten.

    Admittedly, IBM has many problems, both when it comes to governance and expertise. in spite of this, I contend that ordinary, IBM nowadays is still very a lot under undervalued and below-liked.

    fresh Rally post-revenue

    Shareholders positively received IBM's this autumn 2018 results, which confirmed right-line revenue down 1% 12 months-over-12 months at regular currency to $21.8 billion, and largely flat full-12 months over 12 months.  in spite of this, in spite of feeble exact-line performance, IBM's shares rallied roughly eight% post-earnings and have remained at that level seeing that. 

    So What basically Drove This Rally?

    mighty guidance made traders flip advantageous on IBM. however IBM presents no correct line forecast, it does offer each base line non-GAAP EPS numbers and its forecast at no cost cash stream for FY 2019.

    whereas IBM's non-GAAP EPS of $13.90 for FY 2019, which exceeded analyst estimates for $13.eighty, actually looks enticing, I have little self assurance in the substance of this number. it is made from so many assumptions, which makes it a largely useless determine on which to base any type of funding determination. then again, IBM's free cash movement expectation of approximately $12 billion is each significant and reassuring.

    in spite of this, one could factor out that this volume of free money stream is flat with what IBM generated in FY 2018. To which, i might counter, that investors are unlikely to get a cheaply valued inventory when its free cash movement is growing at a robust clip.

    biggest Strategic Pivot in Years

    IBM recently acquired red Hat. on the time, back in October 2018, IBM deployed the equal of a third of its market cap into acquiring pink Hat (approximately $34 billion). This new acquisition turned into meant to be a latest-ditch effort by IBM to stay primary within the cloud wars.

    pink Hat focuses on offering a multi-cloud platform. IBM hopes that IBM's infrastructure and customer base, at the side of crimson Hat's technology, will create a strong providing in order that collectively it might be triumphant in carving out a niche alongside the likes Amazon's (AMZN) AWS, Microsoft's (MSFT) Azure and Alphabet's (GOOGL) Google Cloud.

    besides the fact that children, regardless of being several months after the announcement of this groundbreaking acquisition, IBM has remained quite tight-lipped on the tangible numbers and outcomes this acquisition would subsequently give to IBM. furthermore, CFO James Kavanaugh talked about on the call that the acquisition of crimson Hat is anticipated to close in the 2nd half on 2019, and as such, the expectations from this business have not been fully mirrored in IBM's fiscal 2019 forecast expectations.

    Capital Return: a powerful nice

    As a price investor, whereas i'm interested in a companies' dynamic developments, i'm passionate about how my agencies go about deploying their extra capital. usually, groups which have a powerful heritage of having powerful cash move era capabilities commonly become complacent with their extra capital and subsequently come to be squandering this capital. currently, notwithstanding, this has no longer been the case with IBM.

    definitely, during q4 2018, while IBM's share price became south and hit multi-year lows, IBM used the chance to aggressively repurchase its personal shares. principally, all over this fall 2018, IBM deployed $2.1 billion in opposition t share repurchases. additional, FY 2018 saw IBM set up extra capital against repurchases than all through the outdated two full fiscal years of 2017, 2016.

    Valuation - competencies Upside?

    As proven within the above table, IBM's cash flows are being meaningfully undervalued. IBM is cheaply valued relative to itself, because it trades on 8x cash flows from operations in comparison with 8.5x for its historic valuation. youngsters, much more meaningful is that IBM at this time trades for just 10x its free money move.

    additionally, for the reason that IBM at this time supports a dividend yield of four.7%, as smartly as the incontrovertible fact that its dividend continues to grow, I argue that this, too, features to another aspect of IBM it's undervalued.

    last observe

    I believe that IBM shareholders are likely to see potent advantageous returns from the roughly $a hundred and twenty billion market cap IBM currently trades at. nonetheless, these returns aren't prone to come rapidly, but I trust that over the next one to two years, IBM's valuation will greater carefully fit its intrinsic cost.

    Amazon, Microsoft and Alphabet are holdings in Jim Cramer's motion alerts PLUS Charitable have confidence Portfolio. are looking to be alerted earlier than Cramer buys or sells AMZN, MSFT or GOOGL? learn more now.


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    IBM WebSphere Operational Decision Management V8.0 Application Development

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    IBM Adds Analytics to Business Processes | killexams.com real questions and Pass4sure dumps

    Posted October 7, 2011 By Sean Michael Kerner     Feedback

    IBM integrates analytics and business processes to create agile enterprises.

    Data is at the root of good decision making, but how do you get the right data in the right place to make those decisions?

    IBM (NYSE:IBM) is enhancing its software portfolio with new capabilities for analytics and business intelligence. The new software releases span the IBM Rational and Tivoli product groups.

    "We want to help our client infuse analytics and intelligence into their infrastructure, to support better decision making and more integrated processes," Nancy Pearson, vice president of market strategy at IBM WebSphere, told InternetNews.com. "We're doing an integrated launch that takes the capabilities from Rational and Tivoli and puts them together against some key pain points that clients have."

    Those pain points include dealing with the complexity inherent in rapid rates of change. Enabling business agility is also a key goal of the new IBM push. One of the enhanced solutions is IBM Tivoli Analytics for Service Performance. Pearson explained that Tivoli Analytics enables enterprises to make better decisions throughout the business process. Additionally, the new IBM Tivoli Business Service Manager software release provides the ability to help forecast IT service levels. Pearson said that the new applications enable enterprises to automate the way they gain insight throughout the business process.

    Randy Newell, program director at IBM Rational, noted that there are also enhancements being made in the area of application portfolio management.

    "What we're providing there is a view that can look across a combination of data, systems, networks, applications and processes to provide visibility into better decision making," Newell said.

    That visibility can help an organization understand the impact of a change initiative. Newell said the visibility can also deliver insight into which projects an organization should actually initiate.

    "Most IT budgets typically fund maintenance activities, so how do you actually fund initiatives that are about innovation?" Newell said. "It's about making hard decisions about which projects you're not going to do, as well as identifying redundancies so you can free up funds for an innovation initiative."

    The new Rational Insight 1.1 release is one of the key enhanced products that provides the application development visibility.

    "It allows you to look across the application lifecycle and bubble the information up to a dashboard to provide a view of project health," Newell said.

    Another enhanced project is the Rational Automation Framework version 3.0 release, which helps to enable collaborative integration between development and operations. Newell said the framework is an automated deployment tool that helps to provide business agility.

    "If you can't build agility into software delivery, then you haven't built an agile business yet," Newell said. "The hand-off from development to operation to speed up application to use is essentially where we reach from the world of development with Rational into the world of operations, which is the Tivoli world."

    Sean Michael Kerner is a senior editor at InternetNews.com, the news service of Internet.com, the network for technology professionals.


    IBM Completes Acquisition of ILOG, Extending IBM BPM Portfolio | killexams.com real questions and Pass4sure dumps

    Jan 13, 2009

    IBM has completed its approximately $340 million tender offer for the shares of ILOG, which offers Business Rule Management System (BRMS), Optimization, Visualization, and Supply Chain Management (SCM) portfolios. The tender offer was initially announced July of 2008. "I think it is going to be one of our strongest strategic acquisitions that we have made at IBM," Sandy Carter, IBM vice president for SOA and WebSphere Strategy, Channels and Marketing, tells 5 Minute Briefing.

    Headquartered in Paris, France, ILOG has more than 2,500 customers, 850 employees and operations in 30 countries around the world. ILOG will become part of the IBM WebSphere software portfolio.

    The acquisition will allow IBM to enter several new markets, observes Carter. One of them is a standalone rules business. "Today, we have some rules capability within our WebSphere Suite but this product is much more robust and allows us to sell rules all by itself, which is a growing marketplace," she notes. The ILOG BRMS products help businesses improve their decision making by letting them adapt and respond dynamically. 

    The acquisition also adds in other new pieces to IBM's business, including optimization. Based on applied mathematics and computer science, the ILOG optimization products allow enterprises to transform business objectives, resources and operational constraints into best possible action plans and schedules to enhance service, revenue and profits, according to IBM.  In fact, Carter says, IBM uses that optimization technology in its own supply chain.

    A third new piece ILOG adds is in the area of supply chain management solutions, which include Network Design, Inventory Optimization, Production Planning, and Scheduling. And the fourth key piece that the ILOG acquisition adds is visualization, which allows users to take information and transform it into a visual picture so action can be taken, explains Carter. Germany's national railway company uses ILOG technology to visualize the trains as they dispatch. As a result of the deployment, Carter states, the transportation company has achieved improvement in on-time performance, reductions in staff training time, and more accurate decision-making.

    According to IBM, the ILOG acquisition will strengthen IBM's business process management (BPM) and SOA position by providing customers a broad set of rule management tools for information and application lifecycle management across a comprehensive platform, including IBM's leading WebSphere application development and management platform.  Many of the ILOG products will also become part of IBM's Industry Frameworks, which are integrated solutions that support industry specific business and technology standards.

    For more information, go here. To watch a demo on YouTube showing how WebSphere Dynamic Process Edition and ILOG JRules, visualizations and optimization technology combine to offer an end-to-end business process management solution, allowing a business leader to make decisions more quickly, go here.


    IBM Cloud Automation Manager, a primer. | killexams.com real questions and Pass4sure dumps

    The development community is adopting containers at a remarkably breakneck pace. Organizations are looking to containerize their workloads for different reasons. Whether it’s the packaging advantage of containers, their smaller size (compared to VMs), or their ‘build once, run anywhere’ attribute, the main motivation that is commonly shared across individuals and organizations alike — the agility and ephemeral nature of containers.

    But with all of their benefits, enterprises consider containers to be bleeding edge, and are cautiously (and curiously) accepting the reality that the world is adopting hybrid architectures composed of containers and VMs that work side-by-side in multi-cloud platforms. This “new world order” of containers + VMs isn’t without its challenges and complexities when dealing with operations and workload management.

    To this intention, and while it is industry-wide agreed that VMs (and infrastructure in general) are here to stay for the foreseeable future, this made some very smart people think of ways to bring some qualities of the container world to VMs. Welcome to the exciting world of Infrastructure as Code (IaC).

    In this article, I introduce IBM Cloud Automation Manager, an enterprise-ready Infrastructure as Code (IaC) platform that provides a single pane of glass to provision VM-based alongside Kubernetes-based workloads by simply using templates (text files).

    IBM Cloud Automation Manager

    IBM Cloud Automation Manager (or CAM for short) was released late 2017 alongside IBM Cloud Private, IBM’s enterprise-grade Kubernetes platform. Simply put, CAM is an enterprise-ready Infrastructure as Code (IaC) manager that allows you to:

  • Automate the provisioning of workloads, whether virtual machines and/or containers and their infrastructure pre-requisites.
  • Compose and orchestrate services made out of both VMs and containers.
  • Integrate multiple Infrastructure as Code and Configuration Manager solutions.
  • Provision workloads on multiple clouds (whether public or private).
  • Integrate with DevOps toolchains.
  • Integrate with day-2 ITSM solutions.
  • As seen in the diagram above, IBM Cloud Automation Manager has 3 main user-visible components:

  • Terraform, which handles the provisioning of cloud and infrastructure resources using providers such as VMware vSphere, Microsoft Azure, IBM Cloud Platform, Amazon Web Services, Google Cloud Platform and even OpenStack.
  • Chef, which does configuration management and compliance automation. Chef normally takes over the provisioning after Terraform to start deployment and configuration of middleware and applications.
  • Service Composer, which is where administrators can author, compose and design services that are made out of not only multiple VMs, but also Kubernetes resources by invoking Helm charts.
  • Take this scenario for example: A common practice is to have front-end apps deployed on containers and databases (or legacy middleware) deployed on VMs, and to take things up a notch, containers might be living on a public cloud while databases might reside behind an enterprise firewall.

    Service Composer helps organizations create hybrid workloads of containers, public cloud resources, and on-premise VMs with the click of a button. This simplicity comes in handy at the end of the DevOps toolchain, when environments need to be deployed on demand for Dev, Test, QA and then Production.

    In simple terms, with IBM Cloud Automation Manager, administrators and developers alike are able to define where and how target environments should look like, author declarative code, save and then version to Git. And because environments are written as declarative templates, they can be re-produced and re-deployed over and over.

    What does it solve?

    Well, many things. First of all, administrators can automate most (if not all) of the processes that come with provisioning environments, avoiding manual processes that are tedious and error prone.

    With CAM and Terraform, administrators have to simply declare how they want the environment to look, launch the provisioning, and forget all about it. Terraform will figure out how to deploy.

    See the following image, which displays a typical deployment procedure:

    Imagine having an application made out of 10 VMs and then having to repeat these steps for each and every environment in a typical enterprise scenario: Dev, QA, UAT, Production and DR, that’s roughly a total of 50 VMs…

    CAM’s automation reduces provisioning time from weeks to hours (dare I say minutes?).

    Second, it solves the issue of configuration drifts. Gone are the days when applications don’t behave uniformly when the environments they sit on are supposedly identical. Configuration drifts happen when somebody, somewhere messed up and never reflected the config change to rest of the environments. This happens quite often in a typical Dev, QA, UAT, Production and DR deployment scenario.

    And because Terraform templates are text files that are stored in Git, it simplifies integration into existing DevOps tools (such as Jenkins) to help automate the dev-test-prod promotion alongside the application.

    Third, just like application code, infrastructure should be versioned. Infrastructure encompasses everything in a software-defined environment, so in the example of VMware we’re talking, amongst other things, Storage I/O Control, Admission Control, vSwitch config, Port Groups, HA Affinity rules, OS customizations (think sysprep), core count, and also sometimes the type of CPU the VM is emulating to enable and disable processor features.

    Infrastructure doesn’t stop there, it also includes /etc/hosts files, IP configuration, DNS entries, iptables rules, apt-get/yum repos and then, perhaps, middleware configuration might also be part of the responsibility of the infrastructure team, depending on the organization structure.

    Tracking and versioning all aspects of an environment while consolidating VM and container artifacts allow configurations to be branched, forked, rolled-back and then promoted from Dev, QA, UAT, and then Production alongside every other element in an app development delivery process.

    Fourth, Infrastructure as Code allows Ops to rebuild instead of fixing when things go wrong. It has been proven time and again that rebuilding an entire environment and then rolling back to a known working version will save time and effort helping achieving SLOs and SLAs.

    Finally, it saves on disk space. Currently, organizations rely on VM templates, VM snapshots and a spaghetti of VM clones to quickly provision environments. This is an operational nightmare and wastes disk space, which incidentally opened the doors for storage appliance companies to introduce expensive deduplication technologies.

    Infrastructure as Code allows for replacing clones of VM images with text files that store descriptive declarative statement that reflect configurations and end targets.

    IBM Cloud Automation Manager Concepts

    Before digging into CAM, there are some concepts that need to be explained.

    IBM Cloud Private: IBM Cloud Automation Manager is a Dockerized application that runs on top of IBM Cloud Private, the documentation on how to deploy it can be found here. Although available on DockerHub, CAM is tightly integrated with IBM Cloud Private as its Kubernetes platform for authorization, RBAC and others functions.

    Git: Although Git isn’t bundled as part of CAM, it is highly recommended that all the templates and content libraries that are created are stored and versioned on a Git repo. This is also a pre-requisites for air-gapped environments that can’t reach github.com where IBM stores its sample templates.

    Terraform: By default, IBM Cloud Automation Manager only manages Terraform. Terraform is the module within CAM that talks to and provisions infrastructure. CAM comes with a bunch of Terraform Providers pre-packaged such as: IBM Cloud, AWS, Azure, GCP and OpenStack and the list is growing. Bringing-Your-Own-Provider (BYOP) can be done by following this link. Terraform has dozens of providers for different types of clouds and infrastructure which can be found here.

    Chef: Chef is a configuration management tool responsible to deploy and configure simple and complex software from templates (also called cookbooks). There are cookbooks for thousands applications from major software vendors available from http://supermarket.chef.io.

    Note: Terraform and Chef overlap in some situations, IBM Cloud Automation Manager takes care of segregating responsibilities, where Terraform will mostly do infrastructure and Chef will mostly do configuration and software deployment.

    CAM Content Provider (or CAMC Provider): After Terraform completes the provisioning of the VM and if a Chef template is chosen as part of the deployment, CAM engage the CAMC Provider. The CAMC Provider is nothing more than an gateway to a Chef server that takes care of configuration management, middleware and application deployment.

    There are few things to note here:

  • The CAMC Provider isn’t installed as part of the CAM installation by default, it’s an optional step that should be executed within CAM. This basically installs a Chef Server on a separate VM.
  • The standard Chef that comes with CAMC is pre-populated with some Chef cookbooks also referred to as ‘Pre-Built Content’ covering mostly IBM Oracle and LAMP cookbooks. It is however, the responsibility of administrators to populate other cookbooks from the thousands of cookbooks available on Chef Supermarket onto the Chef server and this can be done with Chef’s client: knife. Follow this link to understand how to properly manage Chef.
  • Although CAM will deploy Chef by default, organizations can choose another configuration manager such as Ansible, Puppet or even their own existing Chef servers. What’s powerful here is that within CAM, organizations can deploy multiple CAMC Providers and multiple configuration managers. For a tutorial on deploying Ansible instead of or alongside Chef, follow this link.
  • Helm: Helm charts are to Kubernetes what Terraform templates are to VMs. They also are a type of Infrastructure as Code that allow authoring of Kubernetes resources such as deployments, services, replica sets, stateful sets, volumes, ingress rules etc… With Helm charts, developers can package container information and Kubernetes resources as templates, version them and deploy them on-demand, while avoiding the tedious tasks of managing the Kubernetes aspect of things.

    Software Repository: This is where software binaries will be residing. Normally this should be an NFS share that has ample capacity to store large binaries such as IBM WebSphere, Oracle, Apache, MySQL and other software. This is important for packages that are not publicly accessible, not available on a public repo such as via apt-get/yum or if CAM is residing in an air-gapped environment (with no internet connectivity).

    Administrators should populate the Software Repository with binaries based on a directory structure, to do that, follow the link here. For IBM specific software, I highly recommend using PUCL to prepare the software repo, follow this link.

    Following is a diagram that describes how CAM, Terraform and Chef come together.

    Templates Library: A template is nothing more than a Terraform template that declares a VM (or other cloud resources) based on some specifications. All information about the VM such as CPU, disk size, cloud provider is defined there. The Template Library lists all the available templates that are available for provisioning. This is where administrators will spend time creating, authoring and editing Terraform templates.

    Service Library: A service is a collection of templates executed as one process. IBM Cloud Automation Manager can chain the provisioning and creation of CAM Templates and ICP Helm charts while providing the possibility to pre-set variables and composable execution plans. At the time of writing (CAM 2.1.0.3), provisioning of templates within a service is sequential, however optional parallelism is on the roadmap. What’s more is that within the Service Library, the output parameters from one template can be used as an input to another.

    Service Library is where administrators will spend time creating, authoring, editing and then publishing CAM services to the Service Library.

    Service Composer: Within the Service Library resides the Service Composer. This is CAM’s management console that allows authoring of CAM Services. After the creation of CAM templates (Terraform), administrators can head to the Service Composition section of the Service Library to drag and drop the created CAM templates and/or Kubernetes Helm charts (from IBM Cloud Private) based on a decided sequence and/or decision. Service Composition can also call REST APIs for third party integration and send emails.

    Decision: A Decision is simply a prompt that a CAM user will face during the provisioning of a service. For example, the service could prompt the user for the size of the VM or whether the workload should be deployed on a Dev or Production environment. During the creation of the service, administrators can choose different CAM templates for each environment. Alternatively, administrators could potentially use Docker versions of certain software for Dev and Test, but then deploy VM based versions for Production.

    A REST hook is a powerful tool that allows CAM to tell something to do something. For example, using REST hooks, CAM can plug-in onto an IPAM to request and fetch IP addresses that can be used as parameters (more on that later). REST hooks could also register the newly created service or template to a Change Management Database (CMDB).

    Parameters and Shared Parameters: One of the powerful features of CAM are Parameters and Shared Parameters.

    Parameters are data that can be fed onto CAM templates. Things like CPU cores, RAM size, OS could be parameterized and not hard coded within the CAM templates. This is important as it brings modularity and flexibility. CAM templates authors could also choose to prompt users for these parameters or pre-set them during the creation of the templates. One good example of parameters are OS passwords and private ssh keys, no one wants to see those hard coded in templates.

    The image above depicts how Terraform consumes parameters so they are not hard coded onto the CAM templates.

    For example, $(var.folder), $(var.name), $(var.cpu), and $(var.ipv4_prefix_length) are parameters that can be prompted and populated during VM creation or centrally stored within CAM for modularity and do-it-once purposes.

    Parameters are bound to single templates. So what happens when CAM templates need to share certain parameters? Enter Shared Parameters. Shared Parameters allow administrators to parameterize certain data that repeat amongst CAM templates. For example, in an Azure, IBM Cloud or AWS scenario, CAM templates might require the name/ID of the cloud region, which normally don’t change often. Cloud regions such as: us-east-1, eu-central-1, eu-west-1 could be shared parameters and used across multiple templates.

    Another example of Shared Parameters usage in VMware Clusters: Imagine having multiple VMware Clusters within an organization and each clusters have different preset settings such as port groups, datastores, or IP gateways. Shared parameters bring sanity and organization to deployments.

    Parameters and Shared Parameters are even more powerful when combined with Decisions as each decision could point to different parameters and shared parameters.

    The concept of Shared Parameters promotes role separation, a cloud admin can be in charge of managing these and choose what parameters should be preset and which can be fiddled or selected by the cloud user/consumer.

    Spend some time watching this video titled, IBM Cloud Private to deploy IBM Cloud Kubernetes Service Clusters, which shows how almost all the features I covered in this article come together.

    A day in the life

    We’ve covered the basics of IBM Cloud Automation Manager and explained the different moving parts that make up CAM. Below is a brief description of what CAM administrators will face day in day out managing CAM.

    A day in the life of a CAM Administrator

    Normally, CAM administrators need to worry about the following:

  • IBM Cloud Private and IBM Cloud Automation Manager alignment (namespaces, persistent volumes, node selectors, NFS shares, LDAP and RBAC etc..).
  • Cloud providers, whether these are VMware vSphere clusters, OpenStack environments or public clouds such as AWS, Azure, GCP, IBM Cloud or even Bring-Your-Own-Provider.
  • Centralized repository on Git to store, manage, fork and version Terraform and Chef templates.
  • Content publishing, which involves managing, building and then publishing CAM content. CAM content are simply CAM templates (Terraform or Terraform+Chef).
  • Service publishing of CAM templates or CAM templates+IBM Cloud Private Helm charts by composing services that consume parameters, request decisions, prompt users for information and integrate with 3rd party tools and platform using REST hooks.
  • In the case of private clouds (VMware and OpenStack) Preparation of OS templates. CAM administrators should be responsible for building and maintaining OS templates that will be used during provisioning of workloads. For example, in the case of Linux, configuration of cloud-init, Logical Volume Manager, apt-get/yum repos etc.. for Windows, things like sysprep, Windows Updates, Windows Features and Active Directory should be accommodated for and thought through.
  • In the case of private clouds (VMware and OpenStack) Preparation of Networking and IP subnets. CAM administrators should have worked out a list of valid IP subnets, vSwitches, port groups, floating IPs, DNS and gateways that can be used in CAM.
  • In the case of private clouds (VMware and OpenStack) Preparation of Storage. CAM administrators should know about storage tiers and datastores available for VMs.
  • A day in the life of a CAM User/Consumer

    CAM users will eventually consume the templates and services built by CAM Administrators, this means:

  • CAM users will be greeted with a template library and a service library where they can browse versions of templates and services already provisioned for them by the CAM administrators.
  • Template libraries are where users will execute distinct provisioning.
  • Service libraries are where users will execute services made out of multiple templates.
  • CAM users will also be able to manage the workloads that they have provisioned. Examples of such actions are (Start, Stop, Pause, Destroy, Delete resources).
  • If the CAM user is a developer or part of the DevOps team, then such executions of templates and services can be easily integrated to their DevOps tool chain. By using the CAM API, developers can call the provisioning of templates and services from within Jenkins or any other deployment tool.
  • Conclusion

    Of course, there are far more features that I haven’t covered such as the ability to integrate CAM workloads with IBM Cloud Private’s ELK, as seen here, how to use CAM’s template designer to author Terraform templates without learning Terraform syntax as seen here or even how to use CAM’s API to call the service composer from a third party orchestration tool as seen here.

    In conclusion, IBM Cloud Automation Manager is meant for infrastructure departments who crave the agility and speed experienced when using Docker and Kubernetes (such as with IBM Cloud Private) and want to bring these capabilities to infrastructure and VMs.

    For more information please consult the following links:



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