#OpenShift

[qcs01]

Optimizing Performance on Enterprise Linux Systems: Tips and Tricks

Introduction: In the dynamic world of enterprise computing, the performance of Linux systems plays a crucial role in ensuring efficiency, scalability, and reliability. Whether you're managing a data center, cloud infrastructure, or edge computing environment, optimizing performance is a continuous pursuit. In this article, we'll delve into various tips and tricks to enhance the performance of enterprise Linux systems, covering everything from kernel tuning to application-level optimizations.

Kernel Tuning:

Adjusting kernel parameters: Fine-tuning parameters such as TCP/IP stack settings, file system parameters, and memory management can significantly impact performance. Tools like sysctl provide a convenient interface to modify these parameters.

Utilizing kernel patches: Keeping abreast of the latest kernel patches and updates can address performance bottlenecks and security vulnerabilities. Techniques like kernel live patching ensure minimal downtime during patch application.

File System Optimization:

Choosing the right file system: Depending on the workload characteristics, selecting an appropriate file system like ext4, XFS, or Btrfs can optimize I/O performance, scalability, and data integrity.

File system tuning: Tweaking parameters such as block size, journaling options, and inode settings can improve file system performance for specific use cases.

Disk and Storage Optimization:

Utilizing solid-state drives (SSDs): SSDs offer significantly faster read/write speeds compared to traditional HDDs, making them ideal for I/O-intensive workloads.

Implementing RAID configurations: RAID arrays improve data redundancy, fault tolerance, and disk I/O performance. Choosing the right RAID level based on performance and redundancy requirements is crucial.

Leveraging storage technologies: Technologies like LVM (Logical Volume Manager) and software-defined storage solutions provide flexibility and performance optimization capabilities.

Memory Management:

Optimizing memory allocation: Adjusting parameters related to memory allocation and usage, such as swappiness and transparent huge pages, can enhance system performance and resource utilization.

Monitoring memory usage: Utilizing tools like sar, vmstat, and top to monitor memory usage trends and identify memory-related bottlenecks.

CPU Optimization:

CPU affinity and scheduling: Assigning specific CPU cores to critical processes or applications can minimize contention and improve performance. Tools like taskset and numactl facilitate CPU affinity configuration.

Utilizing CPU governor profiles: Choosing the appropriate CPU governor profile based on workload characteristics can optimize CPU frequency scaling and power consumption.

Application-Level Optimization:

Performance profiling and benchmarking: Utilizing tools like perf, strace, and sysstat for performance profiling and benchmarking can identify performance bottlenecks and optimize application code.

Compiler optimizations: Leveraging compiler optimization flags and techniques to enhance code performance and efficiency.

Conclusion: Optimizing performance on enterprise Linux systems is a multifaceted endeavor that requires a combination of kernel tuning, file system optimization, storage configuration, memory management, CPU optimization, and application-level optimizations. By implementing the tips and tricks outlined in this article, organizations can maximize the performance, scalability, and reliability of their Linux infrastructure, ultimately delivering better user experiences and driving business success.

For further details click www.qcsdclabs.com

[hawkstack]

Master Advanced OpenShift Administration with DO380

Red Hat OpenShift Administration III: Scaling Kubernetes Like a Pro

As enterprise applications scale, so do the challenges of managing containerized environments. If you've already got hands-on experience with Red Hat OpenShift and want to go deeper, DO380 - Red Hat OpenShift Administration III: Scaling Kubernetes Deployments in the Enterprise is built just for you.

Why DO380?

This course is designed for system administrators, DevOps engineers, and platform operators who want to gain advanced skills in managing large-scale OpenShift clusters. You'll learn how to automate day-to-day tasks, ensure application availability, and manage performance at scale.

In short—DO380 helps you go from OpenShift user to OpenShift power admin.

What You’ll Learn

✅ Automation with GitOps

Leverage Red Hat Advanced Cluster Management and Argo CD to manage application lifecycle across clusters using Git as a single source of truth.

✅ Cluster Scaling and Performance Tuning

Optimize OpenShift clusters by configuring autoscaling, managing cluster capacity, and tuning performance for enterprise workloads.

✅ Monitoring and Observability

Gain visibility into workloads, nodes, and infrastructure using Prometheus, Grafana, and the OpenShift Monitoring stack.

✅ Cluster Logging and Troubleshooting

Set up centralized logging and use advanced troubleshooting techniques to quickly resolve cluster issues.

✅ Disaster Recovery and High Availability

Implement strategies for disaster recovery, node replacement, and data protection in critical production environments.

Course Format

Classroom & Virtual Training Available

Duration: 4 Days

Exam (Optional): EX380 – Red Hat Certified Specialist in OpenShift Automation and Integration

This course prepares you not only for real-world production use but also for the Red Hat certification that proves it.

Who Should Take This Course?

OpenShift Administrators managing production clusters

Kubernetes practitioners looking to scale deployments

DevOps professionals automating OpenShift environments

RHCEs aiming to level up with OpenShift certifications

If you’ve completed DO180 and DO280, this is your natural next step.

Get Started with DO380 at HawkStack

At HawkStack Technologies, we offer expert-led training tailored for enterprise teams and individual learners. Our Red Hat Certified Instructors bring real-world experience into every session, ensuring you walk away ready to manage OpenShift like a pro.

🚀 Enroll now and take your OpenShift skills to the enterprise level.

🔗 Register Here www.hawkstack.com

Want help choosing the right OpenShift learning path?

📩 Reach out to our experts at training@hawkstack.com

[hawskstack]

Backup, Restore, and Migration of Applications with OADP (OpenShift APIs for Data Protection)

In the world of cloud-native applications, ensuring that your data is safe and recoverable is more important than ever. Whether it's an accidental deletion, a system failure, or a need to move applications across environments — having a backup and restore strategy is essential.

OpenShift APIs for Data Protection (OADP) is a built-in solution for OpenShift users that provides backup, restore, and migration capabilities. It's powered by Velero, a trusted open-source tool, and integrates seamlessly into the OpenShift environment.

🌟 Why OADP Matters

With OADP, you can:

Back up applications and data running in your OpenShift clusters.

Restore applications in case of failure, data loss, or human error.

Migrate workloads between clusters or across environments (for example, from on-premises to cloud).

It simplifies the process by providing a Kubernetes-native interface and automating the heavy lifting behind the scenes.

🔧 Key Features of OADP

Application-Aware Backup It captures not just your application’s files and data, but also its configurations, secrets, and service definitions — ensuring a complete backup.

Storage Integration OADP supports major object storage services like AWS S3, Google Cloud Storage, Azure Blob, and even on-prem solutions. This allows flexibility in choosing where your backups are stored.

Volume Snapshots It can also take snapshots of your persistent storage, making recovery faster and more consistent.

Scheduling Backups can be automated on a regular schedule (daily, weekly, etc.) — so you never have to remember to do it manually.

Selective Restore You can restore entire namespaces or select individual components, depending on your need.

🛠️ How It Works (Without Getting Too Technical)

Step 1: Setup An admin installs the OADP Operator in OpenShift and connects it to a storage location (like S3).

Step 2: Backup You choose what you want to back up — specific applications, entire projects, or even the whole cluster. OADP securely saves your data and settings.

Step 3: Restore If needed, you can restore applications from any previous backup. This is helpful for disaster recovery or testing changes.

Step 4: Migration Planning a move to a new cluster? Back up your workloads from the old cluster and restore them to the new one with just a few clicks.

🛡️ Real-World Use Cases

Disaster Recovery: Quickly restore services after unexpected outages.

Testing: Restore production data into a staging environment for testing purposes.

Migration: Seamlessly move applications between OpenShift clusters, even across clouds.

Compliance: Maintain regular backups for audit and compliance requirements.

✅ Best Practices

Automate Backups: Set up regular backup schedules.

Store Offsite: Use remote storage locations to protect against local failures.

Test Restores: Periodically test your backups to ensure they work when needed.

Secure Your Backups: Ensure data in backups is encrypted and access is restricted.

🧭 Conclusion

OADP takes the complexity out of managing application backups and restores in OpenShift. Whether you’re protecting against disasters, migrating apps, or meeting compliance standards — it empowers you with the confidence that your data is safe, recoverable, and portable.

By using OpenShift APIs for Data Protection, you’re not just backing up data — you're investing in resilience, reliability, and peace of mind.

For more info, Kindly follow: Hawkstack Technologies

[simple-logic]

🌐Openshift Middleware Services Transform Your IT with Openshift Middleware

☁️Hybrid Cloud Flexibility Easily manage hybrid cloud environments with Openshift solutions

📦Containerized Deployment Streamline app deployment with container based architecture

⚙️Scalability & Automation Automatically scale applications based on real time demand

🔐Enterprise-Grade Security Benefit from robust security features and compliance support

🚀Empower Your Cloud Journey with Openshift 📧 Email: marketing@simplelogic.in 📞 Phone: +91 86556 16540

To know more about Openshift Middleware Services click here 👉 https://simplelogic-it.com/openshift-middleware-services/

Visit our website 👉 https://simplelogic-it.com/

💻 Explore insights on the latest in #technology on our Blog Page 👉 https://simplelogic-it.com/blogs/

🚀 Ready for your next career move? Check out our #careers page for exciting opportunities 👉 https://simplelogic-it.com/careers/

[cubensquare-blogs]

From Zero to Production: Real-World OpenShift Internship for DevOps and Cloud Engineers

In today's fast-paced IT world, mastering container orchestration platforms like Red Hat OpenShift isn’t just an advantage — it’s a necessity. Whether you're an aspiring DevOps engineer, a cloud administrator, or an IT professional aiming to stay ahead, OpenShift offers the power, flexibility, and security needed to deploy modern applications at scale.

That’s why CubenSquare is launching an industry-ready, hands-on internship: From Zero to Production with OpenShift – Mastering Installation to CI/CD Deployment — a comprehensive, project-based learning experience for IT professionals. https://www.linkedin.com/pulse/from-zero-production-real-world-openshift-internship-devops-y8ufc/

[preeyash]

Want to Advance Your IT Career? Check Out Red Hat Certification Courses!

Hey fellow tech enthusiasts! 👋

If you're looking to boost your Linux, cloud computing, or DevOps skills, I recently came across COSS India, an authorized Red Hat training partner, offering some fantastic certification courses. Thought I’d share in case anyone is considering upskilling!

Register Now: https://forms.gle/gdEXuyxsRMFUgjQF9

Why Consider Red Hat Certifications?

✅ Industry Recognition – Red Hat certifications are globally recognized in IT. ✅ Career Growth – Opens doors to high-paying jobs in system administration, cloud computing, and automation. ✅ Hands-on Training – Real-world applications, not just theory. ✅ Expert Trainers – Learn from professionals with years of experience. ✅ 100% Placement Assistance – They help you land jobs in top IT firms.

Popular Courses Offered by COSS India

📌 Red Hat Certified System Administrator (RHCSA) – Master Linux basics & system administration. 📌 Red Hat Certified Engineer (RHCE) – Advance in automation & DevOps. 📌 Red Hat OpenShift Administration – Cloud-native skills for Kubernetes & containers. 📌 Red Hat Ansible Automation – Simplify IT with automation tools. 📌 Red Hat OpenStack – Build scalable enterprise cloud solutions.

Whether you're an aspiring Linux admin, DevOps engineer, or cloud architect, these certifications can give your career a serious boost! 🚀

Has anyone here completed a Red Hat certification? How was your experience? Would love to hear your thoughts!

🔗 Check out the courses here!

[virtualizationhowto]

OpenShift Local on Windows 11 and Troubleshooting Errors

OpenShift Local on Windows 11 and Troubleshooting Errors #openshift #container #kubernetes #openshiftlocal #openshiftcluster #openshiftvms #openshiftsetup #openshiftwindows #containerapps #docker #kubevip #openshiftdevelopment

With all the tumult across the virtualization space this year, many have been looking at alternative solutions to running virtualized environments, containers, VMs, etc. There are many great solutions out there. One that I haven’t personally tried before putting the effort getting into my lab is Red Hat OpenShift. In case you didn’t know, there is a variant of OpenShift called OpenShift Local…

[shris890]

🚀 Exciting News, Tumblr Fam! Dive into the tech wonders with Linux Rabbit's Blog & News! 🐇✨

🌐 Explore OpenShift, containers, and cloud marvels with us!

1️⃣ Navigating the Tech Wonderland: Simplifying complexities for everyone.

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👉 Join Linux Rabbit for the tech adventure! 🚀✨

[amritatechnologieshyd]

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[qcs01]

The Future of Container Platforms: Where is OpenShift Heading?

Introduction

The container landscape has evolved significantly over the past few years, and Red Hat OpenShift has been at the forefront of this transformation. As organizations increasingly adopt containerization to enhance their DevOps practices and streamline application deployment, it's crucial to stay informed about where platforms like OpenShift are heading. In this post, we'll explore the future developments and trends in OpenShift, providing insights into how it's shaping the future of container platforms.

The Evolution of OpenShift

Red Hat OpenShift has grown from a simple Platform-as-a-Service (PaaS) solution to a comprehensive Kubernetes-based container platform. Its robust features, such as integrated CI/CD pipelines, enhanced security, and scalability, have made it a preferred choice for enterprises. But what does the future hold for OpenShift?

Trends Shaping the Future of OpenShift

Serverless Architectures

OpenShift is poised to embrace serverless computing more deeply. With the rise of Function-as-a-Service (FaaS) models, OpenShift will likely integrate serverless capabilities, allowing developers to run code without managing underlying infrastructure.

AI and Machine Learning Integration

As AI and ML continue to dominate the tech landscape, OpenShift is expected to offer enhanced support for these workloads. This includes better integration with data science tools and frameworks, facilitating smoother deployment and scaling of AI/ML models.

Multi-Cloud and Hybrid Cloud Deployments

OpenShift's flexibility in supporting multi-cloud and hybrid cloud environments will become even more critical. Expect improvements in interoperability and management across different cloud providers, enabling seamless application deployment and management.

Enhanced Security Features

With increasing cyber threats, security remains a top priority. OpenShift will continue to strengthen its security features, including advanced monitoring, threat detection, and automated compliance checks, ensuring robust protection for containerized applications.

Edge Computing

The growth of IoT and edge computing will drive OpenShift towards better support for edge deployments. This includes lightweight versions of OpenShift that can run efficiently on edge devices, bringing computing power closer to data sources.

Key Developments to Watch

OpenShift Virtualization

Combining containers and virtual machines, OpenShift Virtualization allows organizations to modernize legacy applications while leveraging container benefits. This hybrid approach will gain traction, providing more flexibility in managing workloads.

Operator Framework Enhancements

Operators have simplified application management on Kubernetes. Future enhancements to the Operator Framework will make it even easier to deploy, manage, and scale applications on OpenShift.

Developer Experience Improvements

OpenShift aims to enhance the developer experience by integrating more tools and features that simplify the development process. This includes better IDE support, streamlined workflows, and improved debugging tools.

Latest Updates and Features in OpenShift [Version]

Introduction

Staying updated with the latest features in OpenShift is crucial for leveraging its full potential. In this section, we'll provide an overview of the new features introduced in the latest OpenShift release, highlighting how they can benefit your organization.

Key Features of OpenShift [Version]

Enhanced Developer Tools

The latest release introduces new and improved developer tools, including better support for popular IDEs, enhanced CI/CD pipelines, and integrated debugging capabilities. These tools streamline the development process, making it easier for developers to build, test, and deploy applications.

Advanced Security Features

Security enhancements in this release include improved vulnerability scanning, automated compliance checks, and enhanced encryption for data in transit and at rest. These features ensure that your containerized applications remain secure and compliant with industry standards.

Improved Performance and Scalability

The new release brings performance optimizations that reduce resource consumption and improve application response times. Additionally, scalability improvements make it easier to manage large-scale deployments, ensuring your applications can handle increased workloads.

Expanded Ecosystem Integration

OpenShift [Version] offers better integration with a wider range of third-party tools and services. This includes enhanced support for monitoring and logging tools, as well as improved interoperability with other cloud platforms, making it easier to build and manage multi-cloud environments.

User Experience Enhancements

The latest version focuses on improving the user experience with a more intuitive interface, streamlined workflows, and better documentation. These enhancements make it easier for both new and experienced users to navigate and utilize OpenShift effectively.

Conclusion

The future of Red Hat OpenShift is bright, with exciting developments and trends on the horizon. By staying informed about these trends and leveraging the new features in the latest OpenShift release, your organization can stay ahead in the rapidly evolving container landscape. Embrace these innovations to optimize your containerized workloads and drive your digital transformation efforts.

For more details click www.hawkstack.com 

[hawkstack]

Master Enterprise Kubernetes Storage with Red Hat OpenShift Data Foundation (DO370)

As Kubernetes adoption grows across enterprises, storage becomes a critical component of a scalable, secure, and reliable platform. That’s where Red Hat OpenShift Data Foundation (ODF) comes in — and the DO370 course helps you master it.

At HawkStack Technologies, we’re offering hands-on training in DO370 — designed to equip IT professionals with the skills to manage, scale, and secure storage in Red Hat OpenShift environments.

Why DO370? The DO370 course is focused on giving you a deep dive into how Kubernetes handles storage and how OpenShift integrates with ODF to solve real-world enterprise challenges.

Key Skills You'll Learn: ✅ Understanding software-defined storage in a containerized environment ✅ Deploying and managing OpenShift Data Foundation ✅ Creating and managing persistent volumes for pods ✅ Implementing dynamic provisioning ✅ Monitoring and troubleshooting storage performance

This is not just theory — the course includes lab-heavy sessions where you’ll deploy ODF, manage storage classes, and configure data resiliency and performance.

Who Should Take This Course? OpenShift Administrators

Storage Engineers

Cloud Platform Engineers

Anyone preparing for Red Hat Certified Specialist in OpenShift Data Foundation exam

Why Learn from HawkStack? 🔸 Certified Trainers with deep industry experience 🔸 Real-time lab environments to simulate production use cases 🔸 Personalized doubt-clearing sessions 🔸 Access to post-training support and guidance

We're committed to helping you not just pass the exam, but implement ODF confidently in real-world scenarios.

Upcoming Batch Alert 🚨 🗓 Starts: 19th July 2025 🎓 Flat 50% Discount for early enrollments!

Take the next step in your OpenShift journey. Let HawkStack train you on managing storage like a pro with DO370.

For more details www.hawkstack.com

[hawskstack]

Architecture Overview and Deployment of OpenShift Data Foundation Using Internal Mode

As businesses increasingly move their applications to containers and hybrid cloud platforms, the need for reliable, scalable, and integrated storage becomes more critical than ever. Red Hat OpenShift Data Foundation (ODF) is designed to meet this need by delivering enterprise-grade storage for workloads running in the OpenShift Container Platform.

In this article, we’ll explore the architecture of ODF and how it can be deployed using Internal Mode, the most self-sufficient and easy-to-manage deployment option.

🌐 What Is OpenShift Data Foundation?

OpenShift Data Foundation is a software-defined storage solution that is fully integrated into OpenShift. It allows you to provide storage services for containers running on your cluster — including block storage (like virtual hard drives), file storage (like shared folders), and object storage (like cloud-based buckets used for backups, media, and large datasets).

ODF ensures your applications have persistent and reliable access to data even if they restart or move between nodes.

Understanding the Architecture (Internal Mode)

There are multiple ways to deploy ODF, but Internal Mode is one of the most straightforward and popular for small to medium-sized environments.

Here’s what Internal Mode looks like at a high level:

Self-contained: Everything runs within the OpenShift cluster, with no need for an external storage system.

Uses local disks: It uses spare or dedicated disks already attached to the nodes in your cluster.

Automated management: The system automatically handles setup, storage distribution, replication, and health monitoring.

Key Components:

Storage Cluster: The core of the system that manages how data is stored and accessed.

Ceph Storage Engine: A reliable and scalable open-source storage backend used by ODF.

Object Gateway: Provides cloud-like storage for applications needing S3-compatible services.

Monitoring Tools: Dashboards and health checks help administrators manage storage effortlessly.

🚀 Deploying OpenShift Data Foundation (No Commands Needed!)

Deployment is mostly handled through the OpenShift Web Console with a guided setup wizard. Here’s a simplified view of the steps:

Install the ODF Operator

Go to the OperatorHub within OpenShift and search for OpenShift Data Foundation.

Click Install and choose your settings.

Choose Internal Mode

When prompted, select "Internal" to use disks inside the cluster.

The platform will detect available storage and walk you through setup.

Assign Nodes for Storage

Pick which OpenShift nodes will handle the storage.

The system will ensure data is distributed and protected across them.

Verify Health and Usage

After installation, built-in dashboards let you check storage health, usage, and performance at any time.

Once deployed, OpenShift will automatically use this storage for your stateful applications, databases, and other services that need persistent data.

🎯 Why Choose Internal Mode?

Quick setup: Minimal external requirements — perfect for edge or on-prem deployments.

Cost-effective: Uses existing hardware, reducing the need for third-party storage.

Tightly integrated: Built to work seamlessly with OpenShift, including security, access, and automation.

Scalable: Can grow with your needs, adding more storage or transitioning to hybrid options later.

📌 Common Use Cases

Databases and stateful applications in OpenShift

Development and test environments

AI/ML workloads needing fast local storage

Backup and disaster recovery targets

Final Thoughts

OpenShift Data Foundation in Internal Mode gives teams a simple, powerful way to deliver production-grade storage without relying on external systems. Its seamless integration with OpenShift, combined with intelligent automation and a user-friendly interface, makes it ideal for modern DevOps and platform teams.

Whether you’re running applications on-premises, in a private cloud, or at the edge — Internal Mode offers a reliable and efficient storage foundation to support your workloads.

Want to learn more about managing storage in OpenShift? Stay tuned for our next article on scaling and monitoring your ODF cluster!

For more info, Kindly follow: Hawkstack Technologies

[simple-logic]

#QuizTime Which middleware platform is best for enterprise scalability?

A) WebLogic 🧩 B) WebSphere 🌐 C) JBoss ⚙️ D) OpenShift 🚢

Comments your answer below👇

💻 Explore insights on the latest in #technology on our Blog Page 👉 https://simplelogic-it.com/blogs/

🚀 Ready for your next career move? Check out our #careers page for exciting opportunities 👉 https://simplelogic-it.com/careers/

[remitiras]

I was bored at work so I made a custom logo for our openshift test cluster.

(I drew it in ms paint and then deleted the background and added a border in Photoshop)

[govindhtech]

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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