vSphere & Intel CPU Vulnerabilities: CacheOut & Vector Register Sampling

Server Virtualization

Article | May 17, 2023

Contents 1. Introduction 2. Software Development and Secure Testing 3. Using VMs in Software Development and Secure Testing 4. Conclusion 1. Introduction “Testing is an infinite process of comparing the invisible to the ambiguous in order to avoid the unthinkable happening to the anonymous.” —James Bach. Testing software is crucial for identifying and fixing security vulnerabilities. However, meeting quality standards for functionality and performance does not guarantee security. Thus, software testing nowadays is a must to identify and address application security vulnerabilities to maintain the following: Security of data history, databases, information, and servers Customers’ integrity and trust Web application protection from future attacks VMs provide a flexible and isolated environment for software development and security testing. They offer easy replication of complex configurations and testing scenarios, allowing efficient issue resolution. VMs also provide secure testing by isolating applications from the host system and enabling a reset to a previous state. In addition, they facilitate DevOps practices and streamline the development workflow. 2. Software Development and Secure Testing Software Secure Testing: The Approach The following approaches must be considered while preparing and planning for security tests: Architecture Study and Analysis: Understand whether the software meets the necessary requirements. Threat Classification: List all potential threats and risk factors that must be tested. Test Planning: Run the tests based on the identified threats, vulnerabilities, and security risks. Testing Tool Identification: For software security testing tools for web applications, the developer must identify the relevant security tools to test the software for specific use cases. Test-Case Execution: After performing a security test, the developer should fix it using any suitable open-source code or manually. Reports: Prepare a detailed test report of the security tests performed, containing a list of the vulnerabilities, threats, and issues resolved and the ones that are still pending. Ensuring the security of an application that handles essential functions is paramount. This may involve safeguarding databases against malicious attacks or implementing fraud detection mechanisms for incoming leads before integrating them into the platform. Maintaining security is crucial throughout the software development life cycle (SDLC) and must be at the forefront of developers' minds while executing the software's requirements. With consistent effort, the SDLC pipeline addresses security issues before deployment, reducing the risk of discovering application vulnerabilities while minimizing the damage they could cause. A secure SDLC makes developers responsible for critical security. Developers need to be aware of potential security concerns at each step of the process. This requires integrating security into the SDLC in ways that were not needed before. As anyone can potentially access source code, coding with potential vulnerabilities in mind is essential. As such, having a robust and secure SDLC process is critical to ensuring applications are not subject to attacks by hackers. 3. Using VMs in Software Development and Secure Testing: Snapshotting: Snapshotting allows developers to capture a VM's state at a specific point in time and restore it later. This feature is helpful for debugging and enables developers to roll back to a previous state when an error occurs. A virtual machine provides several operations for creating and managing snapshots and snapshot chains. These operations let users create snapshots, revert to any snapshots in the chain, and remove snapshots. In addition, extensive snapshot trees can be created to streamline the flow. Virtual Networking: It allows virtual machines to be connected to virtual networks that simulate complex network topologies, allowing developers to test their applications in different network environments. This allows expanding data centers to cover multiple physical locations, gaining access to a plethora of more efficient options. This empowers them to effortlessly modify the network as per changing requirements without any additional hardware. Moreover, providing the network for specific applications and needs offers greater flexibility. Additionally, it enables workloads to be moved seamlessly across the network infrastructure without compromising on service, security, or availability. Resource Allocation: VMs can be configured with specific resource allocations such as CPU, RAM, and storage, allowing developers to test their applications under different resource constraints. Maintaining a 1:1 ratio between the virtual machine processor and its host or core is highly recommended. It's crucial to refrain from over-subscribing virtual machine processors to a single core, as this could lead to stalled or delayed events, causing significant frustration and dissatisfaction among users. However, it is essential to acknowledge that IT administrators sometimes overallocate virtual machine processors. In such cases, a practical approach is to start with a 2:1 ratio and gradually move towards 4:1, 8:1, 12:1, and so on while bringing virtual allocation into IT infrastructure. This approach ensures a safe and seamless transition towards optimized virtual resource allocation. Containerization within VMs: Containerization within VMs provides an additional layer of isolation and security for applications. Enterprises are finding new use cases for VMs to utilize their in-house and cloud infrastructure to support heavy-duty application and networking workloads. This will also have a positive impact on the environment. DevOps teams use containerization with virtualization to improve software development flexibility. Containers allow multiple apps to run in one container with the necessary components, such as code, system tools, and libraries. For complex applications, both virtual machines and containers are used together. However, while containers are used for the front-end and middleware, VMs are used for the back-end. VM Templates: VM templates are pre-configured virtual machines that can be used as a base for creating new virtual machines, making it easier to set up development and testing environments. A VM template is an image of a virtual machine that serves as a master copy. It includes VM disks, virtual devices, and settings. By using a VM template, cloning a virtual machine multiple times can be achieved. When you clone a VM from a template, the clones are independent and not linked to the template. VM templates are handy when a large number of similar VMs need to be deployed. They preserve VM consistency. To edit a template, convert it to a VM, make the necessary changes, and then convert the edited VM back into a new template. Remote Access: VMs can be accessed remotely, allowing developers and testers to collaborate more effectively from anywhere worldwide. To manage a virtual machine, follow these steps: enable remote access, connect to the virtual machine, and then access the VNC or serial console. Once connected, full permission to manage the virtual machine is granted with the user's approval. Remote access provides a secure way to access VMs, as connections can be encrypted and authenticated to prevent unauthorized access. Additionally, remote access allows for easier management of VMs, as administrators can monitor and control virtual machines from a central location. DevOps Integration: DevOps is a collection of practices, principles, and tools that allow a team to release software quickly and efficiently. Virtualization is vital in DevOps when developing intricate cloud, API, and SOA systems. Virtual machines enable teams to simulate environments for creating, testing, and launching code, ultimately preserving computing resources. While commencing a bug search at the API layer, teams find that virtual machines are suitable for test-driven development (TDD). Virtualization providers handle updates, freeing up DevOps teams, to focus on other areas and increasing productivity by 50 –60%. In addition, VMs allow for simultaneous testing of multiple release and patch levels, improving product compatibility and interoperability. 4. Conclusion The outlook for virtual machine applications is highly promising in the development and testing fields. With the increasing complexity of development and testing processes, VMs can significantly simplify and streamline these operations. In the future, VMs are expected to become even more versatile and potent, providing developers and testers with a broader range of tools and capabilities to facilitate the development process. One potential future development is integrating machine learning and artificial intelligence into VMs. This would enable VMs to automate various tasks, optimize the allocation of resources, and generate recommendations based on performance data. Moreover, VMs may become more agile and lightweight, allowing developers and testers to spin up and spin down instances with greater efficiency. The future of VM applications for software development and security testing looks bright, with continued innovation and development expected to provide developers and testers with even more powerful and flexible tools to improve the software development process.

Virtual Desktop Tools, Virtual Desktop Strategies

Article | June 8, 2023

Introduction The early 2000s were milestone moments for the cloud. Amazon Web Services (AWS) entered the market in 2006, while Google revealed its first cloud service in 2007. Fast forward to 2020, when the pandemic boosted digital transformation efforts by around seven years (according to McKinsey), and the cloud has become a commercial necessity today. It not only facilitated the swift transition to remote work, but it also remains critical in maintaining company sustainability and creativity. Many can argue that the large-scale transition to the cloud in the 2010s was necessary to enable the digital-first experiences that remote workers and decentralized businesses need today. Multi-cloud and hybrid cloud setups are now the norm. According to Gartner, most businesses today use a multi-cloud approach to reduce vendor lock-in or to take advantage of more flexible, best-of-breed solutions. However, managing multi-cloud systems increases cloud complexity, and IT concerns, frequently slowing rather than accelerating innovation. According to 2022 research done by IntelligentCIO, the average multi-cloud system includes five platforms, including AWS, Microsoft Azure, Google Cloud, and IBM Red Hat, among others. Managing Multi-Cloud Complexities Like a Pro Your multi-cloud strategy should satisfy your company's requirements while also laying the groundwork for managing various cloud deployments. Creating a proactive plan for managing multi-cloud setups is one of the finest features that can distinguish your company. The five strategies for handling multi-cloud complexity are outlined below. Managing Data with AI and ML AI and machine learning can help manage enormous quantities of data in multi-cloud environments. AI simulates human decision-making and performs tasks as well as humans or even better at times. Machine learning is a type of artificial intelligence that learns from data, recognizes patterns, and makes decisions with minimum human interaction. AI and ML to help discover the most important data, reducing big data and multi-cloud complexity. AI and machine learning enable more simplicity and better data control. Integrated Management Structure Keeping up with the growing number of cloud services from several providers requires a unified management structure. Multiple cloud management requires IT time, resources, and technology to juggle and correlate infrastructure alternatives. Routinely monitor your cloud resources and service settings. It's important to manage apps, clouds, and people globally. Ensure you have the technology and infrastructure to handle several clouds. Developing Security Strategy Operating multiple clouds requires a security strategy and seamless integration of security capabilities. There's no single right answer since vendors have varied policies and cybersecurity methods. Storing data on many cloud deployments prevents data loss. Handling backups and safety copies of your data are crucial. Regularly examine your multi-cloud network's security. The cyber threat environment will vary as infrastructure and software do. Multi-cloud strategies must safeguard data and applications. Skillset Management Multi-cloud complexity requires skilled operators. Do you have the appropriate IT personnel to handle multi-cloud? If not, can you use managed or cloud services? These individuals or people are in charge of teaching the organization about how each cloud deployment helps the company accomplish its goals. This specialist ensures all cloud entities work properly by utilizing cloud technologies. Closing Lines Traditional cloud monitoring solutions are incapable of dealing with dynamic multi-cloud setups, but automated intelligence is the best at getting to the heart of cloud performance and security concerns. To begin with, businesses require end-to-end observability in order to see the overall picture. Add automation and causal AI to this capacity, and teams can obtain the accurate answers they require to better optimize their environments, freeing them up to concentrate on increasing innovation and generating better business results.

Server Hypervisors

Article | May 18, 2023

Learn setting up a Docker and Kubernetes environment with the right considerations and choose the best-suited software from ten leading tools, softwares and platforms for your business needs. Contents The blog discusses how Kubernetes and Docker can boost software development and deployment productivity. In addition, it covers the benefits of the role of Kubernetes in orchestrating containerized applications and best practices for implementing these technologies to improve efficiency and streamline workflows. Docker and Kubernetes are both essential containerization ecosystem utilities. Kubernetes, an excellent DevOps solution, manages and automates containers' deployment and scaling, along with operating across clusters of hosts, whereas Docker is used for creating and operating containers. The blog covers tips to consider while choosing tools/platforms. It further enlists ten platforms providing Kubernetes and Docker, featuring their offerings. 1. Considerations While Setting Up a Development Environment with Kubernetes and Docker 1.1 Fluid app delivery A platform for application development must provide development teams with high velocity. Two factors contribute to high velocity: rapid application delivery and brief development cycles. Application platforms must support build processes that start with source code. The platforms must also facilitate the repetitive deployment of applications on any remote staging instance. 1.2 Polyglot support Consistency is the defining characteristic of an application platform. On-demand, repetitive, and reproducible builds must be supported by the platform. Extending a consistent experience across all languages and frameworks elevates the platform experience. The platform must support a native build process and the ability to develop and customize this build process. 1.3 Baked-in security Containerized environments are secured in a significantly different manner than conventional applications. A fundamental best practice is to utilize binaries compiled with all necessary dependencies. The build procedure should also include a directive to eliminate unnecessary components for the application's operation. Setting up a zero-trust architecture between platform components that orchestrate deployments significantly improves the workloads' security posture. 1.4 Adjustable abstractions A platform with paved paths and the flexibility to accommodate the requirements of software engineering teams has a greater chance of success. Open-source platforms score highly in this regard, particularly those with modular architectures that allow the team to swap out parts as they adjust. 2.Top Tips to Consider While Choosing Tools and Platforms for Kubernetes and Docker 2.1 Production-Readiness Configuring Kubernetes or Docker can be complex and resource-intensive. A production-ready platform will ensure having the necessary fully automated features without the need for configuration. Security is an essential aspect of production readiness. Additionally, automation is critical, as production readiness requires that the solution manage all cluster management duties. Automated backup, recovery, and restore capabilities must be considered. Also, ensure the high availability, scalability, and self-healing of the cluster's platform. 2.2 Future-Readiness As the cloud and software evolve, a system's hosting location may affect its efficacy. The current trend is a multi-cloud strategy. Ensure that the platform can support abstracting from cloud or data center providers and building a shared infrastructure across clouds, cloud regions, and data centers, as well as assist in configuring them if required. According to a recent study, nearly one-third of organizations are already collaborating with four or more cloud service providers. (Source: Microsoft and 451 Research) 2.3 Ease of Administration Managing a Docker or Kubernetes cluster is complex and requires various skill sets. Kubernetes generates a lot of unprocessed data, which must be interpreted to comprehend what's happening with the cluster. Early detection and intervention are crucial to disaster prevention. Identifying a platform that eliminates the issue of analyzing raw data is essential. By incorporating automated intelligent monitoring and alerts, such solutions can provide critical status, error, event, and warning data to take appropriate action. 2.4 Assistance and Training As the organization begins to acquire Kubernetesor Docker skills, it is essential to have a vendor that can provide 24/7 support and training to ensure a seamless transition. Incorrect implementation will add a layer of complexity to infrastructure management. Leverage automation tools that offer the support needed to use Kubernetes and Docker without the management burden. 3. 10 Tools and Platforms Providing Kubernetes and Docker 3.1 Aqua Cloud Native Security Platform: Aqua Security provides the Aqua Cloud Native Security Platform, a comprehensive security solution designed to protect cloud-native applications and microservices. Aqua offers end-to-end security for applications operating on Docker Enterprise Edition (Community Edition), protecting the DevOps pipeline and production workloads with complete visibility and control. It provides end-to-end security across the entire application lifecycle, from development to production, for both containerized and serverless workloads. In addition, it automates prevention, detection, and response across the whole application lifecycle to secure the build, cloud infrastructure, and operating workloads, regardless of where they are deployed. 3.2 Weave Gitops Enterprise Weave GitOps Enterprise, a full-stack, developer-centric operating model for Kubernetes, creates and contributes to several open-source projects. Its products and services enable teams to design, build, and operate their Kubernetes platform at scale. Built by the creators of Flux and Flagger, Weave GitOps allows users to deploy and manage Kubernetes clusters and applications in the public or private cloud or their own data center. Weave GitOps Enterprise helps simplify Kubernetes with fully automated continuous delivery pipelines that roll out changes from development to staging and production. Weaveworks has used Kubernetes in production for over eight years and has developed that expertise into Weave GitOps Enterprise. 3.3 Mirantis Kubernetes Engine Mirantis provides the Mirantis Kubernetes Engine, a platform designed to help organizations deploy, manage, and scale their Kubernetes clusters. It includes features such as container orchestration, automated deployment, monitoring, and high availability, all designed to help organizations build and run their applications at scale. Mirantis Kubernetes Engine also includes a set of tools for managing the lifecycle of Kubernetes clusters, including cluster deployment, upgrades, and patching. It also has security scanning and policy enforcement features, as well as integration with other enterprise IT systems such as Active Directory and LDAP. 3.4 Portworx by Pure Storage Portworx's deep integration into Docker gives Portworx container data services benefits directly through the Docker Swarm scheduler. Swarm service creation brings the management capability of Portworx to the Docker persistent storage layer to avoid complex tasks such as increasing the storage pool without container downtime and problems like stuck EBS drives. Portworx is also a multi-cloud-ready Kubernetes storage and administration platform designed to simplify and streamline data management in Kubernetes. The platform abstracts the complexity of data storage in Kubernetes. Additionally, it serves as a software-defined layer that aggregates Kubernetes nodes' data storage into a virtual reservoir. 3.5 Platform9 Platform9 provides a powerful IDE for developers for simplified in-context views of pods, logs, events, and more. Both development and operations teams can access the information they need in an instant, secured through SSO and Kubernetes RBAC. The industry’s first SaaS-managed approach combined with a best-in-class support and customer success organization with a 99.9% consistent CSAT rating delivers production-ready K8s to organizations of any size. It provides services to deploy a cluster instantly, achieve GitOps faster, and take care of every aspect of cluster management, including remote monitoring, self-healing, automatic troubleshooting, and proactive issue resolution, around the clock. 3.6 Kubernetes Network Security Sysdig provides Kubernetes Network Security, a solution that offers cloud security from source to run. The product provides network security for Kubernetes environments by monitoring and blocking suspicious traffic in real time. It helps organizations protect their Kubernetes clusters against advanced threats and attacks. The product and Sysdig Secure offer Kubernetes Network Monitoring to investigate suspicious traffic and connection attempts, Kubernetes-Native Microsegmentation to enable microsegmentation without breaking the application, and Automated Network Policies to save time by automating Kubernetes network policies. 3.7 Kubernetes Operations Platform for Edge Rafay delivers a production-ready Kubernetes Operations Platform for Edge, streamlining ongoing operations for edge applications. It provides centralized multi-cluster management to deploy, manage, and upgrade all Kubernetes clusters from a single console across all edge nodes. In addition, it offers comprehensive lifecycle management, with which users can quickly and easily provision Kubernetes clusters at the edge, where cluster updates and upgrades are seamless with no downtime. Furthermore, the KMC for Edge quickly integrates with enterprise-class SSO solutions such as Okta, Ping One, and Azure AD, among others. Other features include standardized clusters and workflows, integration and automation, and centralized logging and monitoring. 3.8 Opcito Technologies Opcito provides simplified container management with efficient provisioning, deployment, scaling, and networking. Its application containerization expertise helps containerize existing and new applications and dependencies. Opcito is well-versed in leading container orchestration platforms like Docker Swarm and Kubernetes. While it helps choose the container platform that best suits specific application needs, it also helps with the end-to-end management of containers so clients can release applications faster and focus on innovation and business. The container management and orchestration services include: building secured microservices, Enterprise-scale Container Management and Orchestration, Orchestration, and Container Monitoring. 3.9 D2iQ Kubernetes Platform (DKP) D2iQ (DKP) enables enterprises to take advantage of all the benefits of cloud-native Kubernetes while laying the groundwork for intelligent cloud-native innovation by simplifying Kubernetes deployment and maintenance. It simplifies and automates the most difficult parts of an enterprise Kubernetes deployment across all infrastructures. DKP helps enterprises easily overcome operational barriers and set them up in minutes and hours rather than weeks and months. In addition, DKP simplifies Kubernetes management through automation using GitOps workflow, observability, application catalog, real-time cost management, and more. 3.10 Spektra Spektra, by Diamanti, a multi-cluster management solution for DevOps and production teams, provides centralized multi-cluster management, a single control plane to deliver everything needed to provision and manage the lifecycle of multiple clusters. Spektra is built to cater to business needs, from air-gapped on-prem deployments to hybrid and multi-cloud infrastructures. It also enables stretching resources across different clusters within the tenant. Furthermore, it allows you to move workloads and their associated data from one cluster to another directly from its dashboard. Spektra integrates with lightweight directory access protocols (LDAP) and Active Directory (AD) to enable user authentication and streamline resource access. In addition, it offers application migration, data mobility, and reporting. 4. Conclusion It is evident that Kubernetes and Docker can significantly boost software development and deployment productivity. By adopting appropriate containerization platforms and leveraging Kubernetes for orchestration, organizations can streamline workflows, improve efficiency, and enhance the reliability of their applications. Furthermore, following the tips to choose the tools or platform carefully can further improve productivity.

Article | April 17, 2020

Researchers have published the details of an investigation into CVE-2020-3952, a major vulnerability in VMware's vCenter that was disclosed and patched on April 9. The flaw was given a CVSS score of 10. CVE-2020-3952 exists in VMware's Directory Service (vmdir), which is a part of VMware vCenter Server, a centralized management platform for virtualized hosts and virtual machines. Through vCenter Server, the company says, an administrator can manage hundreds of workloads. The platform uses single sign-on (SSO), which includes vmdir, Security Token Service, an administration server, and the vCenter Lookup Service. Vmdir is also used for certificate management for the workloads vCenter handles.