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govindhtech · 8 days

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Red Hat Openshift Virtualization Unlocks APEX Cloud Platform

Dell APEX Cloud Platform

With flexible storage and integrated virtualization, you may achieve operational simplicity. In the quickly changing technological world of today, efficiency is hampered by complexity. The difficult task of overseeing complex systems, a variety of workloads, and the need to innovate while maintaining flawless operations falls on IT experts. Dell Technologies and Red Hat have developed robust new capabilities for Dell APEX Cloud Platform for Red Hat Openshift Virtualization that are assisting enterprises in streamlining their IT systems.

Openshift Virtualization

Utilize Integrated Virtualization to Simplify and Optimize

Many firms are reevaluating their virtualization strategy as the use of AI and containers picks up speed, along with upheavals in the virtualization industry. Red Hat OpenShift Virtualization, which offers a contemporary platform for enterprises to operate, deploy, and manage new and current virtual machine workloads together with containers and AI/ML workloads, is now included by default in APEX Cloud Platform for Red Hat OpenShift. Operations are streamlined by having everything managed on a single platform.

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APEX Cloud Platform

Adaptable Infrastructure for All Tasks

Having the appropriate infrastructure to handle your workload needs is essential for a successful virtualization strategy. An increased selection of storage choices is now available with APEX Cloud Platform for Red Hat OpenShift to accommodate any performance demands and preferred footprint. Block storage is needed by the APEX Cloud Platform Foundation Software, which offers all of the interface with Red Hat Openshift Virtualization.

For clients that want a smaller footprint, Dell have added PowerStore and Red Hat OpenShift Data Foundation to the list of block storage choices available from PowerFlex. In order to avoid making redundant expenditures, customers may use the PowerStore and PowerFlex appliances that are already in place.

Customers may easily connect to any of Their business storage solutions for additional storage to meet their block, file, and object demands. This is particularly crucial for the increasing amount of AI workloads that need PowerScale and ObjectScale’s file and object support.

Support for a range of NVIDIA GPUs and Intel 5th Generation Xeon Processors further increases this versatility and improves performance for your most demanding applications.

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Continuity Throughout Your Red Hat OpenShift Estate

Red Hat OpenShift 4.14 and 4.16 support is now available in the APEX Cloud Platform, adding a new degree of uniformity to your Red Hat OpenShift estate along with features like CPU hot plug and the option to choose a single node for live migration to improve OpenShift Virtualization. This lessens the complexity often involved in maintaining numerous software versions, streamlining IT processes for increased productivity.

Red Hat Virtualization

Overview

Red Hat OpenShift includes Red Hat OpenShift Virtualization, an integrated platform that gives enterprises a contemporary way to run and manage their virtual machine (VM) workloads, both new and old. The system makes it simple to move and maintain conventional virtual machines to a reliable, dependable, and all-inclusive hybrid cloud application platform.

By using the speed and ease of a cloud-native application platform, OpenShift Virtualization provides a way to modernize infrastructure while maintaining the investments made in virtualization and adhering to contemporary management practices.

What advantages does Red Hat OpenShift virtualization offer?

Simple transfer: The Migration Toolkit for Virtualization that comes with Red Hat Openshift Virtualization makes it easy to move virtual machines (VMs) from different hypervisors. Even VMs can be moved to the cloud. Red Hat Services offers mentor-based advice along the route, including the Virtualization move Assessment, if you need practical assistance with your move.

Reduce the time to manufacture: Simplify application delivery and infrastructure with a platform that facilitates self-service choices and CI/CD pipeline interfaces. Developers may accelerate time to market by building, testing, and deploying workloads more quickly using Red Hat Openshift Virtualization.

Utilize a single platform to handle everything: One platform for virtual machines (VMs), containers, and serverless applications is provided by OpenShift Virtualization, simplifying operations. As a consequence, you may use a shared, uniform set of well-known corporate tools to manage all workloads and standardize the deployment of infrastructure.

A route towards modernizing infrastructure: Red Hat Openshift Virtualization allows you to operate virtual machines (VMs) that have been migrated from other platforms, allowing you to maximize your virtualization investments while using cloud-native architectures, faster operations and administration, and innovative development methodologies.

How does Red Hat OpenShift virtualization operate?

Included with every OpenShift subscription is Red Hat Openshift Virtualization. The same way they would for a containerized application, it allows infrastructure architects to design and add virtualized apps to their projects using OperatorHub.

With the help of simple, free migration tools, virtual machines already running on other platforms may be moved to the OpenShift application platform. On the same Red Hat OpenShift nodes, the resultant virtual machines will operate alongside containers.

Update your approach to virtualization

Virtualization managers need to adjust as companies adopt containerized systems and embrace digital transformation. Teams may benefit from infrastructure that enables VMs and containers to be managed by the same set of tools, on a single, unified platform, using Red Hat Openshift Virtualization.

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computingpostcom · 2 years

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In an OpenShift or OKD Kubernetes Cluster, the ClusterVersion custom resource holds important high-level information about your cluster. This information include cluster version, update channels and status of the cluster operators. In this article I’ll demonstrate how Cluster Administrator can check cluster version as well as the status of operators in OpenShift / OKD Cluster. Check Cluster Version in OpenShift / OKD You can easily retrieve the cluster version from the CLI using oc command to verify that it is running the desired version, and also to ensure that the cluster uses the right subscription channel. # Red Hat OpenShift $ oc get clusterversion NAME VERSION AVAILABLE PROGRESSING SINCE STATUS version 4.8.10 True False 10d Cluster version is 4.8.10 # OKD Cluster $ oc get clusterversion NAME VERSION AVAILABLE PROGRESSING SINCE STATUS version 4.7.0-0.okd-2021-05-22-050008 True False 66d Cluster version is 4.7.0-0.okd-2021-05-22-050008 To obtain more detailed information about the cluster status run the oc describe clusterversion command: $ oc describe clusterversion ...output omitted... Spec: Channel: fast-4.8 Cluster ID: f3dc42b3-aeec-4f4c-780f-8a04d6951595 Desired Update: Force: false Image: quay.io/openshift-release-dev/ocp-release@sha256:53576e4df71a5f00f77718f25aec6ac7946eaaab998d99d3e3f03fcb403364db Version: 4.8.10 Status: Available Updates: Channels: candidate-4.8 candidate-4.9 fast-4.8 Image: quay.io/openshift-release-dev/ocp-release@sha256:c3af995af7ee85e88c43c943e0a64c7066d90e77fafdabc7b22a095e4ea3c25a URL: https://access.redhat.com/errata/RHBA-2021:3511 Version: 4.8.12 Channels: candidate-4.8 candidate-4.9 fast-4.8 stable-4.8 Image: quay.io/openshift-release-dev/ocp-release@sha256:26f9da8c2567ddf15f917515008563db8b3c9e43120d3d22f9d00a16b0eb9b97 URL: https://access.redhat.com/errata/RHBA-2021:3429 Version: 4.8.11 ...output omitted... Where: Channel: fast-4.8 – Displays the version of the cluster the channel being used. Cluster ID: f3dc42b3-aeec-4f4c-780f-8a04d6951595 – Displays the unique identifier for the cluster Available Updates: Displays the updates available and channels Review OpenShift / OKD Cluster Operators OpenShift Container Platform / OKD cluster operators are top level operators that manage the cluster. Cluster operators are responsible for the main components, such as web console, storage, API server, SDN e.t.c. All the information relating to cluster operators is accessible through the ClusterOperator resource. It allows you to access the overview of all cluster operators, or detailed information on a given operator. To retrieve the list of all cluster operators, run the following command: $ oc get clusteroperators NAME VERSION AVAILABLE PROGRESSING DEGRADED SINCE authentication 4.8.10 True False False 2d14h baremetal 4.8.10 True False False 35d cloud-credential 4.8.10 True False False 35d cluster-autoscaler 4.8.10 True False False 35d config-operator 4.8.10 True False False 35d console 4.8.10 True False False 10d csi-snapshot-controller 4.8.10 True False False 35d dns 4.8.10 True False False 35d etcd 4.8.10 True False False 35d image-registry 4.8.10 True False False 35d

ingress 4.8.10 True False False 35d insights 4.8.10 True False False 35d kube-apiserver 4.8.10 True False False 35d kube-controller-manager 4.8.10 True False False 35d kube-scheduler 4.8.10 True False False 35d kube-storage-version-migrator 4.8.10 True False False 10d machine-api 4.8.10 True False False 35d machine-approver 4.8.10 True False False 35d machine-config 4.8.10 True False False 35d marketplace 4.8.10 True False False 35d monitoring 4.8.10 True False False 3d5h network 4.8.10 True False False 35d node-tuning 4.8.10 True False False 10d openshift-apiserver 4.8.10 True False False 12d openshift-controller-manager 4.8.10 True False False 34d openshift-samples 4.8.10 True False False 10d operator-lifecycle-manager 4.8.10 True False False 35d operator-lifecycle-manager-catalog 4.8.10 True False False 35d operator-lifecycle-manager-packageserver 4.8.10 True False False 18d service-ca 4.8.10 True False False 35d storage 4.8.10 True False False 35d Key Columns in the ouptut: NAME – Indicates the name of the operator. AVAILABLE – Indicates operator state if successfully deployed or has issues. TRUE means the operator is deployed successfully and is available for use in the cluster. The degraded state means the current state does not match its desired state over a period of time. PROGRESSING – Indicates whether an operator is being updated to a newer version by the cluster version operator. True means update in pending completion. DEGRADED – This entry returns the health of the operator. True means the operator encounters an error that prevents it from working properly. You can limit the output to a single operator: $ oc get co authentication NAME VERSION AVAILABLE PROGRESSING DEGRADED SINCE authentication 4.8.10 True False False 2d14h To get more information about an operator use: $ oc describe clusteroperators Example: $ oc describe co authentication If you’re in a process of upgrading your OpenShift / OKD cluster from one minor version to another, we have a guide dedicated to upgrade shared in the link below: How To Upgrade OpenShift / OKD Cluster Minor Version

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thaipolar · 2 years

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Citrix xenapp 6.5 policy not applying

This document does not replace comprehensive product documentation about XenApp and XenDesktop policies. The intended audience for this document is an advanced Citrix administrator who is familiar with HDX concepts, policy templates, and previous versions of the product. We’ve also provided planning guidance to help you determine the right settings for a given use case.

This document provides design considerations when you use these templates to create policies. XenApp and XenDesktop includes HDX policy templates that simplify deployment to users.

Latency and SQL Blocking Query Improvements in XenApp and XenDesktopĮxtending the Life of Your Legacy Web Applications by Using Citrix Secure BrowserĬitrix Universal Print Server load balancing in XenApp and XenDesktop 7.9Īctive Directory OU-based Controller discovery Group Policy management template updates for XenApp and XenDesktop HDX Policy Templates for XenApp and XenDesktop 7.6 to the Current Version

Use Citrix ADM to Troubleshoot Citrix Cloud Native Networkingĭeployment Guide Citrix ADC VPX on Azure - Autoscaleĭeployment Guide Citrix ADC VPX on Azure - GSLBĭeployment Guide Citrix ADC VPX on Azure - Disaster Recoveryĭeployment Guide Citrix ADC VPX on AWS - GSLBĭeployment Guide Citrix ADC VPX on AWS - Autoscaleĭeployment Guide Citrix ADC VPX on AWS - Disaster RecoveryĬitrix ADC and OpenShift 4 Solution BriefĬreating a VPX Amazon Machine Image (AMI) in SC2SĬonnecting to Citrix Infrastructure via RDP through a Linux Bastion Host in AWSĬitrix ADC for Azure DNS Private Zone Deployment GuideĬitrix Federated Authentication Service Logon Evidence Overview VRD Use Case Using Citrix ADC Dynamic Routing with KubernetesĬitrix Cloud Native Networking for Red Hat OpenShift 3.11 Validated Reference DesignĬitrix ADC CPX, Citrix Ingress Controller, and Application Delivery Management on Google CloudĬitrix ADC Pooled Capacity Validated Reference DesignĬitrix ADC CPX in Kubernetes with Diamanti and Nirmata Validated Reference DesignĬitrix ADC SSL Profiles Validated Reference DesignĬitrix ADC and Amazon Web Services Validated Reference DesignĬitrix ADC Admin Partitions Validated Reference DesignĬitrix Gateway SaaS and O365 Cloud Validated Reference DesignĬitrix Gateway Service SSO with Access Control Validated Reference DesignĬonvert Citrix ADC Perpetual Licenses to the Pooled Capacity Model Service Migration to Citrix ADC using Routes in OpenShift Validated Reference Design

#Citrix xenapp 6.5 policy not applying

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karonbill · 2 years

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IBM C1000-143 Practice Test Questions

Now you can pass C1000-143 IBM Cloud Pak for Watson AIOps v3.2 Administrator exam with ease. PassQuestion provides you a number of C1000-143 Practice Test Questions, exactly on the pattern of the actual exam. They are not only helpful for the exam candidates to evaluate their level of preparation but also provide them the opportunity to enhance their weaknesses well in time. The C1000-143 Practice Test Questions include the latest questions and answers which help you in clearing all of your doubts of the IBM C1000-143 exam. With the help of the C1000-143 practice test questions, you will be able to feel the real exam scenario and pass your exam successfully on your first attempt.

IBM Cloud Pak for Watson AIOps v3.2 Administrator

An IBM Certified Administrator on IBM Cloud Pak for Watson AIOps v3.2 is a system administrator who has extensive knowledge and experience on IBM Cloud Pak for Watson AIOps v3.2 including AI Manager, Event Manager and Metric Manager. This administrator can perform the intermediate tasks related to planning, sizing, installation, daily management and operation, security, performance, configuration of enhancements (including fix packs and patches), customization and/or problem determination.

Exam Information

Exam Code: C1000-143 Exam Name: IBM Cloud Pak for Watson AIOps v3.2 Administrator Number of questions: 65 Number of questions to pass: 46 Time allowed: 90 minutes Languages: English Price: $200 USD Certification: IBM Certified Administrator - Cloud Pak for Watson AIOps v3.2

Exam Sections

Section 1: IBM Cloud Pak for Watson AIOps Overview 11% Section 2: Install the IBM Cloud Pak for Watson AIOps 17% Section 3: Configuration 30% Section 4: Operate the Platform 22% Section 5: Manage User Access Control 8% Section 6: Troubleshoot 12%

View Online IBM Cloud Pak for Watson AIOps v3.2 Administrator C1000-143 Free Questions

Which collection of key features describes Al Manager? A.Al data tools and connections and Metric Manager B.Al data tools and connections and infrastructure automation C.Al models and Chat Ops D.Network management and service and topology management Answer: C

In Event Manager, which event groupings usually occur within a short time of each other? A.Scope-based B.Seasonal C.Temporal D.Topology Answer: C

When a user logs on to any of the components on a Cloud Pak for Watson AlOps deployed cluster and it is too slow or times out, what can be done to resolve the issue? A.Update the Idap-proxy-config ConfigMap and set the LDAP_RECURSIVE_SEARCH to "false". B.Update the platform-auth-idp ConfigMap and set the LDAP_TIMEOUT to a higher value. C.Update the Idap-proxy-config ConfigMap and set the LDAP_TiMEOUT to a higher value. D.Update the platform-auth-idp ConfigMap and set the LDAP_RECURSIVE_SEARCH to "false" Answer: A

When installing Al manager or Event Manager in an air-gapped environment, which registry must the OpenShift cluster be connected to in order to pull images? A.Docker V2 compatible registry running behind B.quay.io C.Red Hat OpenShift internal registry D.docker.io Answer: C

For Al Manager, which type of ChatOps channel surfaces stories? A.Reactive B.Proactive C.Public D.Private Answer: A

What are two valid Runbook types in Event Manager? A.Partial B.Semi-automated C.Initial D.Fully-automated E.Locked-partial Answer: C, D

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codecraftshop · 2 years

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Introduction to Openshift - Introduction to Openshift online cluster

Introduction to Openshift – Introduction to Openshift online cluster OpenShift is a platform-as-a-service (PaaS) offering from Red Hat. It provides a cloud-like environment for deploying, managing, and scaling applications in a secure and efficient manner. OpenShift uses containers to package and deploy applications, and it provides built-in tools for continuous integration, continuous delivery,…

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govindhtech · 10 months

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IBM Cloud Mastery: Banking App Deployment Insights

Hybrid cloud banking application deployment best practices for IBM Cloud and Satellite security and compliance

Financial services clients want to update their apps. Modernizing code development and maintenance (helping with scarce skills and allowing innovation and new technologies required by end users) and improving deployment and operations with agile and DevSecOps are examples.

Clients want flexibility to choose the best “fit for purpose” deployment location for their applications during modernization. This can happen in any Hybrid Cloud environment (on premises, private cloud, public cloud, or edge). IBM Cloud Satellite meets this need by letting modern, cloud-native applications run anywhere the client wants while maintaining a consistent control plane for hybrid cloud application administration.

In addition, many financial services applications support regulated workloads that require strict security and compliance, including Zero Trust protection. IBM Cloud for Financial Services meets that need by providing an end-to-end security and compliance framework for hybrid cloud application implementation and modernization.

This paper shows how to deploy a banking application on IBM Cloud for Financial Services and Satellite using automated CI/CD/CC pipelines consistently. This requires strict security and compliance throughout build and deployment.

Introduction to ideas and products

Financial services companies use IBM Cloud for Financial Services for security and compliance. It uses industry standards like NIST 800-53 and the expertise of over 100 Financial Services Cloud Council clients. It provides a control framework that can be easily implemented using Reference Architectures, Validated Cloud Services, ISVs, and the highest encryption and CC across the hybrid cloud.

True hybrid cloud experience with IBM Cloud Satellite. Satellite lets workloads run anywhere securely. One pane of glass lets you see all resources on one dashboard. They have developed robust DevSecOps toolchains to build applications, deploy them to satellite locations securely and consistently, and monitor the environment using best practices.

This project used a Kubernetes– and microservices-modernized loan origination application. The bank application uses a BIAN-based ecosystem of partner applications to provide this service.

Application overview

The BIAN Coreless 2.0 loan origination application was used in this project. A customer gets a personalized loan through a secure bank online channel. A BIAN-based ecosystem of partner applications runs on IBM Cloud for Financial Services.

BIAN Coreless Initiative lets financial institutions choose the best partners to quickly launch new services using BIAN architectures. Each BIAN Service Domain component is a microservice deployed on an IBM Cloud OCP cluster.

BIAN Service Domain-based App Components

Product Directory: Complete list of bank products and services.

Consumer Loan: Fulfills consumer loans. This includes loan facility setup and scheduled and ad-hoc product processing.

Customer Offer Process/API: Manages new and existing customer product offers.

Party Routing Profile: This small profile of key indicators is used during customer interactions to help route, service, and fulfill products/services.

Process overview of deployment

An agile DevSecOps workflow completed hybrid cloud deployments. DevSecOps workflows emphasize frequent, reliable software delivery. DevOps teams can write code, integrate it, run tests, deliver releases, and deploy changes collaboratively and in real time while maintaining security and compliance using the iterative methodology.

A secure landing zone cluster deployed IBM Cloud for Financial Services, and policy as code automates infrastructure deployment. Applications have many parts. On a RedHat OpenShift Cluster, each component had its own CI, CD, and CC pipeline. Satellite deployment required reusing CI/CC pipelines and creating a CD pipeline.

Continuous integration

IBM Cloud components had separate CI pipelines. CI toolchains recommend procedures and approaches. A static code scanner checks the application repository for secrets in the source code and vulnerable packages used as dependencies. For each Git commit, a container image is created and tagged with the build number, timestamp, and commit ID. This system tags images for traceability. Before creating the image, Dockerfile is tested. A private image registry stores the created image.

The target cluster deployment’s access privileges are automatically configured using revokeable API tokens. The container image is scanned for vulnerabilities. A Docker signature is applied after completion. Adding an image tag updates the deployment record immediately. A cluster’s explicit namespace isolates deployments. Any code merged into the specified Git branch for Kubernetes deployment is automatically constructed, verified, and implemented.

An inventory repository stores docker image details, as explained in this blog’s Continuous Deployment section. Even during pipeline runs, evidence is collected. This evidence shows toolchain tasks like vulnerability scans and unit tests. This evidence is stored in a git repository and a cloud object storage bucket for auditing.

They reused the IBM Cloud CI toolchains for the Satellite deployment. Rebuilding CI pipelines for the new deployment was unnecessary because the application remained unchanged.

Continuous deployment

The inventory is the source of truth for what artifacts are deployed in what environment/region. Git branches represent environments, and a GitOps-based promotion pipeline updates environments. The inventory previously hosted deployment files, which are YAML Kubernetes resource files that describe each component. These deployment files would contain the correct namespace descriptors and the latest Docker image for each component.

This method was difficult for several reasons. For applications, changing so many image tag values and namespaces with YAML replacement tools like YQ was crude and complicated. Satellite uses direct upload, with each YAML file counted as a “version”. A version for the entire application, not just one component or microservice, is preferred.

Thet switched to a Helm chart deployment process because they wanted a change. Namespaces and image tags could be parametrized and injected at deployment time. Using these variables simplifies YAML file parsing for a given value. Helm charts were created separately and stored in the same container registry as BIAN images. They are creating a CI pipeline to lint, package, sign, and store helm charts for verification at deployment time. To create the chart, these steps are done manually.

Helm charts work best with a direct connection to a Kubernetes or OpenShift cluster, which Satellite cannot provide. To fix this, That use the “helm template” to format the chart and pass the YAML file to the Satellite upload function. This function creates an application YAML configuration version using the IBM Cloud Satellite CLI. They can’t use Helm’s helpful features like rolling back chart versions or testing the application’s functionality.

Constant Compliance

The CC pipeline helps scan deployed artifacts and repositories continuously. This is useful for finding newly reported vulnerabilities discovered after application deployment. Snyk and the CVE Program track new vulnerabilities using their latest definitions. To find secrets in application source code and vulnerabilities in application dependencies, the CC toolchain runs a static code scanner on application repositories at user-defined intervals.

The pipeline checks container images for vulnerabilities. Due dates are assigned to incident issues found during scans or updates. At the end of each run, IBM Cloud Object Storage stores scan summary evidence.

DevOps Insights helps track issues and application security. This tool includes metrics from previous toolchain runs for continuous integration, deployment, and compliance. Any scan or test result is uploaded to that system, so you can track your security progression.

For highly regulated industries like financial services that want to protect customer and application data, cloud CC is crucial. This process used to be difficult and manual, putting organizations at risk. However, IBM Cloud Security and Compliance Center can add daily, automatic compliance checks to your development lifecycle to reduce this risk. These checks include DevSecOps toolchain security and compliance assessments.

IBM developed best practices to help teams implement hybrid cloud solutions for IBM Cloud for Financial Services and IBM Cloud Satellite based on this project and others:

Continuous Integration

Share scripts for similar applications in different toolchains. These instructions determine your CI toolchain’s behavior. NodeJS applications have a similar build process, so keeping a scripting library in a separate repository that toolchains can use makes sense. This ensures CI consistency, reuse, and maintainability.

Using triggers, CI toolchains can be reused for similar applications by specifying the application to be built, where the code is, and other customizations.

Continuous deployment

Multi-component applications should use a single inventory and deployment toolchain to deploy all components. This reduces repetition. Kubernetes YAML deployment files use the same deployment mechanism, so it’s more logical to iterate over each rather than maintain multiple CD toolchains that do the same thing. Maintainability has improved, and application deployment is easier. You can still deploy microservices using triggers.

Use Helm charts for complex multi-component applications. The BIAN project used Helm to simplify deployment. Kubernetes files are written in YAML, making bash-based text parsers difficult if multiple values need to be customized at deployment. Helm simplifies this with variables, which improve value substitution. Helm also offers whole-application versioning, chart versioning, registry storage of deployment configuration, and failure rollback. Satellite configuration versioning handles rollback issues on Satellite-specific deployments.

Constant Compliance

IBM strongly recommend installing CC toolchains in your infrastructure to scan code and artifacts for newly exposed vulnerabilities. Nightly scans or other schedules depending on your application and security needs are typical. Use DevOps Insights to track issues and application security.

They also recommend automating security with the Security and Compliance Center (SCC). The pipelines’ evidence summary can be uploaded to the SCC, where each entry is treated as a “fact” about a toolchain task like a vulnerability scan, unit test, or others. To ensure toolchain best practices are followed, the SCC will validate the evidence.

Inventory

With continuous deployment, it’s best to store microservice details and Kubernetes deployment files in a single application inventory. This creates a single source of truth for deployment status; maintaining environments across multiple inventory repositories can quickly become cumbersome.

Evidence

Evidence repositories should be treated differently than inventories. One evidence repository per component is best because combining them can make managing the evidence overwhelming. Finding specific evidence in a component-specific repository is much easier. A single deployment toolchain-sourced evidence locker is acceptable for deployment.

Cloud object storage buckets and the default git repository are recommended for evidence storage. Because COS buckets can be configured to be immutable, They can securely store evidence without tampering, which is crucial for audit trails.

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qcs01 · 3 months

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Getting Started with OpenShift: Environment Setup

OpenShift is a powerful Kubernetes-based platform that allows you to develop, deploy, and manage containerized applications. This guide will walk you through setting up an OpenShift environment on different platforms, including your local machine and various cloud services.

Table of Contents

1. [Prerequisites]

2. [Setting Up OpenShift on a Local Machine](#setting-up-openshift-on-a-local-machine)

- [Minishift]

- [CodeReady Containers]

3. [Setting Up OpenShift on the Cloud]

- [Red Hat OpenShift on AWS]

- [Red Hat OpenShift on Azure]

- [Red Hat OpenShift on Google Cloud Platform]

4. [Common Troubleshooting Tips]

5. [Conclusion]

Prerequisites

Before you begin, ensure you have the following prerequisites in place:

- A computer with a modern operating system (Windows, macOS, or Linux).

- Sufficient memory and CPU resources (at least 8GB RAM and 4 CPUs recommended).

- Admin/root access to your machine.

- Basic understanding of containerization and Kubernetes concepts.

Setting Up OpenShift on a Local Machine

Minishift

Minishift is a tool that helps you run OpenShift locally by launching a single-node OpenShift cluster inside a virtual machine.

Step-by-Step Guide

1. Install Dependencies

- VirtualBox: Download and install VirtualBox from [here](https://www.virtualbox.org/).

- Minishift: Download Minishift from the [official release page](https://github.com/minishift/minishift/releases) and add it to your PATH.

2. Start Minishift

Open a terminal and start Minishift:

```sh

minishift start

```

3. Access OpenShift Console

Once Minishift is running, you can access the OpenShift console at `https://192.168.99.100:8443/console` (the IP might vary, check your terminal output for the exact address).

![Minishift Console](https://example.com/minishift-console.png)

CodeReady Containers

CodeReady Containers (CRC) provides a minimal, preconfigured OpenShift cluster on your local machine, optimized for testing and development.

Step-by-Step Guide

1. Install CRC

- Download CRC from the [Red Hat Developers website](https://developers.redhat.com/products/codeready-containers/overview).

- Install CRC and add it to your PATH.

2. Set Up CRC

- Run the setup command:

```sh

crc setup

```

3. Start CRC

- Start the CRC instance:

```sh

crc start

```

4. Access OpenShift Console

Access the OpenShift web console at the URL provided in the terminal output.

![CRC Console](https://example.com/crc-console.png)

Setting Up OpenShift on the Cloud

Red Hat OpenShift on AWS

Red Hat OpenShift on AWS (ROSA) provides a fully-managed OpenShift service.

Step-by-Step Guide

1. Sign Up for ROSA

- Create a Red Hat account and AWS account if you don't have them.

- Log in to the [Red Hat OpenShift Console](https://cloud.redhat.com/openshift) and navigate to the AWS section.

2. Create a Cluster

- Follow the on-screen instructions to create a new OpenShift cluster on AWS.

3. Access the Cluster

- Once the cluster is up and running, access the OpenShift web console via the provided URL.

![ROSA Console](https://example.com/rosa-console.png)

Red Hat OpenShift on Azure

Red Hat OpenShift on Azure (ARO) offers a managed OpenShift service integrated with Azure.

Step-by-Step Guide

1. Sign Up for ARO

- Ensure you have a Red Hat and Azure account.

- Navigate to the Azure portal and search for Red Hat OpenShift.

2. Create a Cluster

- Follow the wizard to set up a new OpenShift cluster.

3. Access the Cluster

- Use the URL provided to access the OpenShift web console.

![ARO Console](https://example.com/aro-console.png)

Red Hat OpenShift on Google Cloud Platform

OpenShift on Google Cloud Platform (GCP) allows you to deploy OpenShift clusters managed by Red Hat on GCP infrastructure.

Step-by-Step Guide

1. Sign Up for OpenShift on GCP

- Set up a Red Hat and Google Cloud account.

- Go to the OpenShift on GCP section on the Red Hat OpenShift Console.

2. Create a Cluster

- Follow the instructions to deploy a new cluster on GCP.

3. Access the Cluster

- Access the OpenShift web console using the provided URL.

![GCP Console](https://example.com/gcp-console.png)

Common Troubleshooting Tips

- Networking Issues: Ensure that your firewall allows traffic on necessary ports (e.g., 8443 for the web console).

- Resource Limits: Check that your local machine or cloud instance has sufficient resources.

- Logs and Diagnostics: Use `oc logs` and `oc adm diagnostics` commands to troubleshoot issues.

Conclusion

Setting up an OpenShift environment can vary depending on your platform, but with the steps provided above, you should be able to get up and running smoothly. Whether you choose to run OpenShift locally or on the cloud, the flexibility and power of OpenShift will enhance your containerized application development and deployment process.

[OpenShift](https://example.com/openshift.png)

For further reading and more detailed instructions, refer to the www.qcsdclabs.com

#redhatcourses #information technology #linux #container #docker #kubernetes #containerorchestration #containersecurity #dockerswarm #aws

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opsmxspinnaker · 4 years

Link

Spinnaker is a Continuous Delivery (CD) platform that was developed at Netflix where they used it to perform a high number of deployments ( 8000+/day). Later they made it available as an open-source tool. Previously enterprise release cycles used to be stretched for 7/8 months. But with the availability of the Spinnaker CD tool, enterprises have been able to shorten the release cycles from months to weeks to days (even multiple releases a day).

There are several other CD tools available in the market but what made Spinnaker so special?

Spinnaker Features:

Multicloud Deployments

It includes support of deployment to multiple cloud environments like Kubernetes (K8s), OpenShift, AWS, Azure, GCP, and so on. It abstracts the cloud environment to be worked on and managed easily.

Automated releases

Spinnaker allows you to create and configure CD pipelines that can be triggered manually or by some events. Thus the entire release process is automated end-to-end,

Safe Deployments

With a high number of release deployments, it is hard to know if some unwanted or bad release has been deployed into production which otherwise should have been failed. The built-in rollback mechanisms with Spinnaker allow you to test and quickly rollback a deployment and lets the application go back to its earlier state.

Maintain Visibility & Control

This feature in Spinnaker allows you to monitor your application across different cloud providers without needing you to log in to multiple accounts.

So Spinnaker is a foundational platform for Continuous Delivery (CD) that can be quite easily extended to match your deployment requirements.

Overview of Spinnaker’s Application Management & Deployment Pipelines Functionality

Spinnaker supports application management. In the Spinnaker UI, an application is represented as an inventory of all the infrastructure resources – clusters/server-groups, load balancers, firewalls, functions (even serverless functions) that are part of your application.

You can manage the same application deployed to different environments like AWS, GCP, Kubernetes, and so on from the Spinnaker UI itself. Spinnaker supports access control for multiple accounts. For e.g. users like dev or testers with permission can deploy to Dev or Stage environments, where as only the Ops people get to deploy the application into production. You can view and manage the different aspects of the application – like scaling the application, view health of different Kubernetes pods that are running, and see the performance and output of those pods.

Spinnaker pipelines let you have all your application’s infrastructure up and running. You can define your deployment workflow and configure your pipeline-as-a-code (JSON). It enables github-style operations.

Spinnaker pipelines allow you to configure:

Execution options– flexibility to run fully automatically or have manual interventions

Automated triggers– the capability to trigger your workflows through Jenkins jobs, webhooks, etc

Parameters– ability to define parameter which can be also accessed dynamically during pipeline execution

Notifications– to notify stakeholders about the status of pipeline execution

As part of the pipeline, you can configure and create automated triggers. These triggers can be fired based on events like a code check-in to the github repository or a new image being published to a Docker repository. You can have them scheduled to run at frequent intervals. You can pass different parameters to your pipeline so that you can use the same pipeline to deploy to different stages just by varying the parameters. You can set up notifications for integrations with different channels like slack or email.

After configuring the setup you can add different stages each of which is responsible for doing a different set of actions like calling a Jenkins job, deploying to Kubernetes, and so on. All these stages are first-class objects or actions that are built-in and that allows you to build a pretty complex pipeline. Spinnaker allows you to extend these pipelines easily and also do release management.

Once you run the Spinnaker pipeline you can monitor the deployment progress. You can view and troubleshoot if somethings go wrong such as Jenkins build failure. After a successful build, the build number is passed and tagged to the build image which is then used in subsequent stages to deploy that image.

You can see the results of deployment like what yaml got deployed. Spinnaker adds a lot of extra annotations to the yaml code so that it can manage the resources. As mentioned earlier, you can check all aspects (status of the deployment, the health of infrastructure, traffic, etc) of the associated application resources from the UI.

So we can summarize that Spinnaker displays the inventory of your application i.e. it shows all the infrastructure behind that application and it has pipelines for you to deploy that application in a continuous fashion.

Problems with other CD tools

Each organization is at a different maturity level for their release cycles. Today’s fast-paced business environment may mandate some of them to push code checked-in by developers to be deployed to production in a matter of hours if not minutes. So the questions that developers or DevOps managers ask themselves are:

What if I want to choose what features to promote to the next stage?

What if I want to plan and schedule a release?

What if I want different stakeholders (product managers/QA leads) to sign off (approve) before I promote?

For all the above use cases, Spinnaker is an ideal CD tool of choice as it does not require lots of custom scripting to orchestrate all these tasks. Although, there are many solutions in the marketplace that can orchestrate the business processes associated with the software delivery they lack interoperability- the ability to integrate with existing tools in the ecosystem.

Can I include the steps to deploy the software also in the same tool?

Can the same tool be used by the developers, release managers, operations teams to promote the release?

The cost of delivery is pretty high when you have broken releases. Without end-to-end integration of delivery stages, the deployment process often results in broken releases. For e.g. raising a Jira ticket for one stage, letting custom scripting be done for that stage, and passing on to the next stage in a similar fashion.

Use BOM (bill-of-materials) to define what gets released

Integrate with your existing approval process in the delivery pipeline

Do the actual task of delivering the software

Say, your release manager decides that from ten releases, release A and B (i.e. components of software) will be released. Then it needs all the approvals ( from testers/DevOps/Project managers/release manager) to be integrated into the deployment process of these releases. And, all this can be achieved using a Spinnaker pipeline.

Example of a Spinnaker pipeline

The BOM application configuration ( example below) is managed in some source control repository. Once you make any change and commit, it triggers the pipeline that would deploy the version of the services. Under the hood, Spinnaker would read the file from a repository, and inject it into the pipeline, deploy the different versions of the services, validate the deployment and promote it to the next stage.

Example of a BOM

A BOM can have a list of services that have been installed. You may not install all services in the release or promote all the services. So you will declare if the service is being released or not, and the version of the release or image that is going to be published. Here in this example, we are doing it with a Kubernetes application. You can also input different parameters that are going to be part of the release e.g. release it in the US region only.

So the key features of this release process are:

Source Controlled

Versioned (Know what got released and when?)

Approved (Being gated makes the release items become the source of truth. Once it is merged with the main branch it’s ready to get deployed)

Auditable ( Being source-controlled, it will definitely have the audit history about who made the change, and what changes were made)

Some interesting ways to enforce approvals

Integrations with Jira, ServiceNow

Policy checks for release conformance

Manual Judgment

Approvals would include integrations with Jira, ServiceNow, policy checks for release conformance e.g. before you release any release items you need to have their SonarQube coverage for static analysis of code quality and security vulnerabilities at 80%. Finally, if you are not ready to automatically promoting the release to production you can make a manual judgment and promote the same

Spinnaker supports managing releases giving you control over what version of different services would get deployed and released. So all the versions need not have continuous delivery but planned release. It lets you plan releases, determine what releases would get promoted, and promote them through the whole process in an automated manner.

OpsMx is a leading provider of Continuous Delivery solutions that help enterprises safely deliver software at scale and without any human intervention. We help engineering teams take the risk and manual effort out of releasing innovations at the speed of modern business.

#Automated Pipelines #CD pipeline #CD pipelines #Continuous Delivery #Continuous Deployment #DevOps #Kubernetes #multicloud deployment #product release #release management

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karonbill · 3 years

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IBM S1000-002 Practice Test Questions

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Exam Details

Exam Code: S1000-002 Exam Name: IBM Cloud Pak for Data Systems V1.x Administrator Specialty Number of questions: 40 Number of questions to pass: 28 Time allowed: 75 minutes Languages: English Price: $100 USD

Exam Sections

Section 1: Cloud Pak for Data System Overview 15% Section 2: Cloud Pak for Data System Configuration 20% Section 3: Cloud Pak for Data System Administration 22% Section 4: Cloud Pak for Data System Operations 18% Section 5: Cloud Pak for Data System Security & Compliance 10% Section 6: Cloud Pak for Data System Problem Determination 15%

View Online IBM Cloud Pak for Data Systems V1.x Administrator Specialty S1000-002 Free Questions

Which command displays the MTM and serial number from Cloud Pak for Data System? A.ap get B.ap info C.ap list D.ap version Answer: B

In the System_Name.yml file, which node specific item must be set in each node stanza? A.IP address B.subnet mask C.gateway D.Vlan Answer: AC

Which command can be used to change the apadmin password in Cloud Pak for Data System? A.apusermgmt modify-user apadmin -p password B.ap config -u apadmin -p password C.docker setpass apadmin D.ap config modify-user apadmin -p password Answer: A

Which three components are available to monitor from the Software overview tile on the Cloud Pak for Data System web console home page? (Choose three.) A.Red Hat OpenShift B.System C.Operating system D.Docker E.Virtual machines F.Application Answer: DEF

Which two methods are used by IBM Cloud Pak for Data System to deliver alerts? (Choose two.) A.Send Email B.JSON notifications C.SNMP traps D.HTTPS protocol E.push notifications Answer: AC

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datamattsson · 5 years

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Kubernetes 1.16 released

Finally it’s the weekend. Peace and quiet to indulge yourself in a new Kubernetes release! Many others have beat me to it, great overviews are available from various sources.

The most exciting thing for me in Kubernetes 1.16 is the graduation of many alpha CSI features to beta. This is removes the friction of tinkering with the feature gates on either the kubelet or API server which is pet peeve of mine and makes me moan out loud when I found out something doesn't work because of it.

TL;DR

All these features have already been demonstrated with the HPE CSI Driver for Kubernetes, it starts about 7 minutes in, I’ve fast forwarded it for you.

At the Helm

Let’s showcase these graduated features with the newly released HPE CSI Driver for Kubernetes. Be warned, issues ahead. Helm is not quite there yet on Kubernetes 1.16, a fix to deploy Tiller on your cluster is available here. Next issue up is that the HPE CSI Driver Helm chart is not yet compatible with Kubernetes 1.16. I’m graciously and temporarily hosting a copy on my GitHub account.

Create a values.yaml file:

backend: 192.168.1.10 # This is your Nimble array username: admin password: admin servicePort: "8080" serviceName: nimble-csp-svc fsType: xfs accessProtocol: "iscsi" storageClass: create: false

Helm your way on your Kubernetes 1.16 cluster:

helm repo add hpe https://drajen.github.io/co-deployments-116 helm install --name hpe-csi hpe/hpe-csi-driver --namespace kube-system -f values.yaml

In my examples repo I’ve dumped a few declarations that I used to walk through these features. When I'm referencing a YAML file name, this is where to find it.

VolumePVCDataSource

This is a very useful capability when you’re interested in creating a clone of an existing PVC in the current state. I’m surprised to see this feature mature to beta before VolumeSnapshotDataSource which has been around for much longer.

Assuming you have an existing PVC named “my-pvc”:

apiVersion: v1 kind: PersistentVolumeClaim metadata: name: my-pvc-clone spec: accessModes: - ReadWriteOnce resources: requests: storage: 32Gi dataSource: kind: PersistentVolumeClaim name: my-pvc storageClassName: my-storageclass

Let’s cuddle:

$ kubectl create -f pvc.yaml persistentvolumeclaim/my-pvc created $ kubectl create -f pvc-clone.yaml persistentvolumeclaim/my-pvc-clone created $ kubectl get pvc NAME STATUS VOLUME CAPACITY STORAGECLASS AGE my-pvc Bound pvc-ae0075... 10Gi my-storageclass 34s my-pvc-clone Bound pvc-d5eb6f... 10Gi my-storageclass 14s

On the Nimble array, we can indeed observe we have a clone of the dataSource.

ExpandCSIVolumes and ExpandInUsePersistentVolumes

This is indeed a very welcome addition to be promoted. Among the top complaints from users. This is stupid easy to use. Simply edit or patch your existing PVC to expand your PV.

$ kubectl patch pvc/my-pvc-clone -p '{"spec": {"resources": {"requests": {"storage": "32Gi"}}}}' persistentvolumeclaim/my-pvc-clone patched $ kubectl get pv NAME CAPACITY CLAIM STORAGECLASS AGE pvc-d5eb6... 32Gi default/my-pvc-clone my-storageclass 9m25s

Yes, you can expand clones, no problem.

CSIInlineVolume

On of my favorite features of our legacy FlexVolume is the ability to create Inline Ephemeral Clones for CI/CD pipelines. Creating a point in time copy of a volume, do some work and/or tests on it and dispose of it. Leave no trace behind.

If this is something you’d like to walk through, there’s a few prerequisite steps here. The Helm chart does not create the CSIDriver custom resource definition (CRD). It need to be applied first:

apiVersion: storage.k8s.io/v1beta1 kind: CSIDriver metadata: name: csi.hpe.com spec: podInfoOnMount: true volumeLifecycleModes: - Persistent - Ephemeral

Next, the current behavior (subject to change) is that you need a secret for the CSI driver in the namespace you’re deploying to. This is a oneliner to copy from “kube-system” to your current namespace.

$ kubectl get -nkube-system secret/nimble-secret -o yaml | \ sed -e 's/namespace: kube-system//' | \ kubectl create -f-

Now, assuming we have deployed a MariaDB and have that running elsewhere. This example clones the actual Nimble volume. In essence, the volume may reside on a different Kubernetes cluster or hosted on a bare-metal server or virtual machine.

For clarity, the Deployment I’m cloning this volume from is using a secret, I’m using that same secret hosted in dep.yaml.

apiVersion: v1 kind: Pod metadata: name: mariadb-ephemeral spec: spec: containers: - image: mariadb:latest name: mariadb env: - name: MYSQL_ROOT_PASSWORD valueFrom: secretKeyRef: name: mariadb key: password ports: - containerPort: 3306 name: mariadb volumeMounts: - name: mariadb-persistent-storage mountPath: /var/lib/mysql volumes: - name: mariadb-persistent-storage csi: driver: csi.hpe.com nodePublishSecretRef: name: nimble-secret volumeAttributes: cloneOf: pvc-ae007531-e315-4b81-b708-99778fa1ba87

The magic sauce here is of course the .volumes.csi stanza where you specify the driver and your volumeAttributes. Any Nimble StorageClass parameter is supported in volumeAttributes.

Once, cuddled, you can observe the volume on the Nimble array.

CSIBlockVolume

I’ve visited this feature before in my Frankenstein post where I cobbled together a corosync and pacemaker cluster running as a workload on Kubernetes backed by a ReadWriteMany block device.

A tad bit more mellow example is the same example we used for the OpenShift demos in the CSI driver beta video (fast forwarded).

Creating a block volume is very simple (if the driver supports it). By default volumes are created with the attribue volumeMode: Filesystem. Simply switch this to Block:

apiVersion: v1 kind: PersistentVolumeClaim metadata: name: my-pvc-block spec: accessModes: - ReadWriteOnce resources: requests: storage: 32Gi volumeMode: Block storageClassName: my-storageclass

Once cuddled, you may reference the PVC as any other PVC, but pay attention to the .spec.containers stanza:

apiVersion: v1 kind: Pod metadata: name: my-pod spec: containers: - name: ioping image: hpestorage/ioping command: [ "ioping" ] args: [ "/dev/xvda" ] volumeDevices: - name: data devicePath: /dev/xvda volumes: - name: data persistentVolumeClaim: claimName: my-pvc-block

Normally you would specify volumeMounts and mountPath for a PVC created with volumeMode: Filesystem.

Running this particular Pod using ioping would indeed indicate that we connected a block device:

kubectl logs my-pod -f 4 KiB <<< /dev/xvda (block device 32 GiB): request=1 time=3.71 ms (warmup) 4 KiB <<< /dev/xvda (block device 32 GiB): request=2 time=1.73 ms 4 KiB <<< /dev/xvda (block device 32 GiB): request=3 time=1.32 ms 4 KiB <<< /dev/xvda (block device 32 GiB): request=4 time=1.06 ms ^C

For competitors who landed on this blog in awe looking for Nimble weaknesses, the response time you see above is a Nimble Virtual Array running on my five year old laptop.

So, that was “it” for our graduated storage features! I'm looking forward to Kubernetes 1.17 already.

Release mascot!

I’m a sucker for logos and mascots. Congrats to the Kubernetes 1.16 release team.

#Kubernetes #HPENimbleStorage

0 notes

govindhtech · 10 months

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Mastering Wazi: Your Guide to Successful Adoption

An overview of the services offered by Wazi

Staying ahead of the curve in today’s fiercely competitive digital market requires the quick development of innovative digital services. But when it comes to fusing contemporary technology with their core systems including Mainframe applications many firms encounter formidable obstacles. Modernizing core enterprise apps on hybrid cloud platforms requires this integration. Remarkably, 33% of developers do not have the required resources or expertise, which makes it difficult for them to produce high-quality goods and services.

Additionally, 36% of developers find it difficult to collaborate with IT Operations, which causes inefficiencies in the development pipeline. To make matters worse, polls indicate time and time again that “testing” is the main reason project timeframes are delayed. To meet these issues and spur business process change, companies such as State Farm and BNP Paribas are standardizing development tools and methodologies across their platforms.

In what ways does Wazi as Service promote modernity?

Among the solutions that are gaining traction in this environment is “Wazi as a Service.” By supporting safe DevSecOps methods, this cloud-native development and testing environment for z/OS apps is transforming the modernization process. It offers on-demand access to z/OS systems with flexible consumption-based pricing. By speeding up release cycles in safe, regulated hybrid cloud environments like IBM Cloud Framework for Financial Services (FS Cloud), it significantly increases developer productivity.

Software quality is improved by shift-left coding techniques, which enable testing to start as early as the code-writing phase. By utilizing the IBM Cloud Security and Compliance Center service, the platform may be automated using a standardized architecture that has been validated for Financial Services (SCC). IBM Z modernization tools include CI/CD pipelines, Wazi Image Builder, Wazi Dev Spaces on OpenShift, z/OS Connect for APIs, zDIH for data integrations, and IBM Watson for generative AI enable innovation at scale.

What are the advantages of using IBM Cloud’s Wazi service?

Wazi as a Service offers a significant speed advantage over emulated x86 machine environments because it runs on IBM LinuxONE, an enterprise-grade Linux server. It is 15 times faster thanks to this special feature, which guarantees quick and effective application development. Wazi also fills in the gaps in the developer experiences on mainframe and distributed systems, making it easier to create hybrid applications with z/OS components.

Through the integration of secure DevOps principles with the strength of the z-Mod stack, a smooth and effective development process is produced. The service may be safely installed on IBM FS Cloud, which has integrated security and compliance capabilities, and enables easy scalability through automation, lowering support and maintenance cost. As a result, data security and regulatory compliance may be guaranteed by developers who design and implement their environments and code with industry-grade requirements in mind.

Furthermore, Wazi VSI on VPC architecture within IBM FS Cloud creates a segregated network to strengthen the perimeter of the cloud infrastructure against security breaches. Secure integration of on-premises core Mainframe applications with cloud services like API Connect, Event Streams, Code Engine, and HPCS encryptions is also made possible by the strong security and compliance controls offered by IBM Cloud services and ISVs verified for financial services.

This shift makes it possible for outdated, dispersed solutions to replace centralized core systems, enabling organizations to remain competitive and adaptable in the current digital environment. All things considered, Wazi as a Service is revolutionary in that it speeds up digital transformation while guaranteeing security, compliance, and a smooth transition between old and new technology.

How does the IBM Cloud Financial Service Framework support solutions for the industry?

The Financial Services IBM Cloud Framework, often known as The sturdy IBM FS Cloud solution was created especially to meet the special requirements of financial institutions. It guarantees regulatory compliance, excellent security, and resilience throughout both the initial deployment phase and continuous operations. By defining a set of standards that all parties must adhere to, this framework streamlines communications between financial institutions and ecosystem partners that offer software or SaaS products.

The main elements of this framework are cloud best practices and an extensive set of control requirements that cover security and regulatory compliance needs. By implementing a shared responsibility model that covers financial institutions, application suppliers, and IBM Cloud, these best practices make sure that everyone contributes to keeping an environment that is safe and compliant.

The IBM Cloud Framework for Financial Services also helps financial organizations comply with the strict security and regulatory standards of the financial sector by offering comprehensive control-by-control implementation assistance and supporting data. Reference architectures are offered to help with the implementation of control needs in order to further improve compliance. The deployment and configuration process can be streamlined by using these architectures as infrastructure as code.

In order to enable stakeholders to effectively monitor compliance, handle problems, and produce proof of compliance, IBM also provides a variety of tools and services, such as the IBM Cloud Security and Compliance Center. In addition, the framework is subject to continuous governance, which guarantees that it stays current and in line with new and developing rules as well as the shifting requirements of public cloud environments and banks. The IBM Cloud Framework for Financial Services is essentially a comprehensive solution that streamlines financial institutions’ relationships with ecosystem partners and enables them to operate securely and in accordance with industry norms.

Discover Wazi as a Service

Wazi as a Service, which operates on the reliable IBM LinuxONE infrastructure, allows for the easy development of hybrid applications by bridging the gap between distributed and mainframe platforms. Businesses can flourish in the digital age thanks to the platform’s scalability, automation, and compliance features, which enable developers to manage the complex web of security and laws.

Businesses may advance into the future of modern, distributed solutions by securely integrating cutting-edge cloud services with their on-premises core systems using Wazi. In conclusion, Wazi as a Service emphasizes the significance of technology in attaining security, compliance, and the peaceful coexistence of historical and contemporary technologies, and serves as an excellent example of how technology may accelerate digital transformation.