Server Hypervisors
Article | May 18, 2023
Your ProtonVPN iOS app is now better equipped to fight censorship and offers more flexible connection options with the launch of OpenVPN for iOS. The OpenVPN protocol is one of the best VPN protocols because of its flexibility, security, and because it is more resistant to blocks. You now have the option to switch between the faster IKEv2 protocol and the more stable and censorship-resistant OpenVPN protocol.
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Server Virtualization
Article | May 17, 2023
SD-WANs are a critical component of digital transformation. Using software-defined networking (SDN) and virtual network functions (VNF) concepts to build and manage a wide area network (WAN) helps businesses successfully transition their infrastructure to the cloud by securely connecting hybrid multicloud architectures. But SD-WANs can do more than just facilitate a transition to the cloud —they make it faster and less expensive to expand your business.
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Virtual Desktop Strategies
Article | July 26, 2022
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.
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Virtual Desktop Tools
Article | July 7, 2022
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.
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