Network automation is the use of IT controls to supervise and carry out every-day network management functions. It plays a key role in network virtualization technologies and network functions. The ...book starts by providing an introduction to network automation, SDN, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and reporting methodologies such as IPv6 migration, DC relocations, and interface parsing, all the while retaining security and improving data center robustness. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation including best practices in automation, ways to test automated networks using different tools, and other important techniques. By the end of the book, you will be well acquainted with the various aspects of network automation.
A pipeline is set up to build code, run tests, and securely deploy a newer version of the application. Manual errors are minimized or can be eliminated through automated pipelines thus providing ...developers with standardized feedback loops and facilitating rapid product iteration. This article introduces the entire automated CI/CD channel by deploying Jenkins, Ansible and Kubernetes cluster to host the updated version. The proposed approach provides an easy to implement automation methodology with high scalability and resiliency. The study aims to provide an approach for continuous integration (CI), continuous testing, and continuous delivery (CD) for automating compilation of source code, analysis, testing, deployment, and reports using build pipeline model.
With the advancement of network-based devices, resulting in communication networks also growing rapidly and becoming more complex, resulting in large and heterogeneous network architecture has ...brought a lot of challenges in network management. Therefore, managing the network has become an increasingly a challenge given the existing network architectures. In this study, we have investigated how network operators operate, maintain and secure telecommunications networks. The study has also investigated the effectiveness of Software Defined Networking (SDN) in improving network management. The study has also investigated how the architecture minimizes the challenges users face. To improve network management with SDN using the OpenFlow protocol, we created network topologies and configured devices using the graphical network simulator 3, Oracle VM VirtualBox Manager, and Mininet VM. Our approach implemented both Git and Ansible in a centralized network architecture to solve the problems facing existing network architectures with the rapid growth of network-based devices on the Internet. This research paper has shown how to use Ansible playbooks to manage your network and overcome the challenges you face. The simulation results shows that the proposed scheme performs better in terms of efficiency and flexibility than the traditional OpenFlow protocol. These improvements have been achieved through the separation of the control and data planes, allowing for more centralized network management and easier implementation of network policies.
A Survey of DevOps tools for Networking Shah, Jay; Dubaria, Dushyant; Widhalm, John
2018 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON),
2018-Nov.
Conference Proceeding
DevOps is a new methodology that combines developers and operations team to closely integrate people, processes and technology for an automated software delivery that is agile, scalable and ...cost-effective. DevOps delivery is a combination of two previous methods; agile software development and the collaboration between developments and operations team by changing the way we think to deploy an infrastructure through the entire product life-cycle, from the design through the production phase, we can deliver consistent and repeatable designs. By abstracting the configuration needed to launch server instances with specific configurations into consistently repeatable recipes or manifests, the entire technology stack becomes converged. In order to do this, both operation and development skills are required. We have GIT as source control tool, Ansible as configuration management, Jenkins as configuration integration, Vagrant as provisioning and Docker as containerization tool. With all these tools we can build an entire Continuous Integration and Continuous Delivery pipeline.
NetFlow is a Cisco proprietary protocol that can be useful other than network monitoring. It is available as an embedded system in most Cisco routers and switches. This protocol provides the ability ...to collect ingress and egress network traffic statistics that can be useful for detection of network anomaly and subsequent defense. It allows detection of unusual and suspicious network traffic conditions which can be characterized based on its communication behavior. Network automation such as ansible was used to automate the collection of the network traffic using NetFlow. Network anomaly was detected by comparing the baseline normal network operation from abnormal network operation.
Automation is critical to success in the world of DevOps. How quickly and efficiently an application deployment can be automated, or a new infrastructure can be built up, can be the difference ...between a successful product or a failure. Ansible provides a simple yet powerful automation engine. Beyond the basics of Ansible lie a host of advanced features which are available to help you increase efficiency and accomplish complex orchestrations with ease. This book provides you with the knowledge you need to understand how Ansible works at a fundamental level and leverage its advanced capabilities. You'll learn how to encrypt Ansible content at rest and decrypt data at runtime. You will master the advanced features and capabilities required to tackle the complex automation challenges of today and beyond. You will gain detailed knowledge of Ansible workflows, explore use cases for advanced features, craft well thought out orchestrations, troubleshoot unexpected behaviour, and extend Ansible through customizations. Finally, you will discover the methods used to examine and debug Ansible operations, helping you to understand and resolve issues.
Microservices architecture is popular due to its scalability and flexibility. However, managing and troubleshooting distributed microservices-based systems can be challenging and time consuming. ...Auto-remediation of anomalies, that is the automated detection and root-causes generation and execution of repair scripts, can reduce the down-times and increase the availability of systems. This thesis will explore the potential and effectiveness of using large language models (LLMs) in auto-remediation. It will develop an auto-remediation framework to mitigate the effects of performance-based anomalies in self-adaptive microservice architectures. Multiple sample microservice applications as test-bed will be rigorously studied, and a dataset will be created to evaluate LLM-based codegeneration models using semantic, lexical, and correctness metrics in zero-shot and few-shot scenarios. Additionally, we will develop reliable prompts for automated Ansible runbook generation and assess their efficiency for orchestrating the auto-remediation process, including deployment, configuration changes, and system recovery to improve application reliability and operational efficiency.
Infrastructure as Code is the practice of developing and maintaining computing infrastructure through executable source code. Unfortunately, IaC has also brought about new cyber attack vectors. Prior ...work has therefore proposed static analyses that detect security smells in Infrastructure as Code files. However, they have so far remained at a shallow level, disregarding the control and data flow of the scripts under analysis, and may lack awareness of specific syntactic constructs. These limitations inhibit the quality of their results. To address these limitations, in this paper, we present GASEL, a novel security smell detector for the Ansible IaC language. It uses graph queries on program dependence graphs to detect 7 security smells. Our evaluation on an oracle of 243 real-world security smells and comparison against two state-of-the-art security smell detectors shows that awareness of syntax, control flow, and data flow enables our approach to substantially improve both precision and recall. We further question whether the additional effort required to develop and run such an approach is justified in practice. To this end, we investigate the prevalence of indirection through control and data flow in security smells across more than 15 000 Ansible scripts. We find that over 55% of security smells contain data-flow indirection, and over 32% require a whole-project analysis to detect. These findings motivate the need for deeper static analysis tools to detect security vulnerabilities in IaC.
System Hardening using CIS Benchmarks H, Ambika P.; Sujatha, G.
2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI),
2024-May-9
Conference Proceeding
Automated system hardening with Center for Internet Security (CIS) benchmarks is crucial for enhancing cybersecurity, and organizations face significant hurdles in this endeavor. Manual configuration ...is complex, errorprone, and time-consuming, making it difficult to scale as IT environments grow. The static nature of manual processes inhibits the ability to adapt quickly to evolving threats, leaving systems vulnerable. Resource limitations often hinder automation efforts, leading to incomplete or delayed compliance. Additionally, manual documentation and tracking of configuration changes present accountability challenges in incident response scenarios. To address these issues, organizations require an efficient and scalable solution for automating CIS benchmark compliance. Such a solution can streamline the hardening process, reduce errors, enhance security, and facilitate continuous monitoring and reporting, ensuring systems are fortified against both known and emerging threats.
In the evolving landscape of software development and system operations, the demand for automating traditionally manual tasks has surged. Continuous operation and minimal downtimes highlight the need ...for automated detection and remediation of runtime anomalies. Ansible, known for its scalable features, including high-level abstraction and modularity, stands out as a reliable solution for managing complex systems securely. The challenge lies in creating an on-the-spot Ansible solution for dynamic auto-remediation, requiring a substantial dataset for in-context tuning of large language models (LLMs). Our research introduces KubePlaybook, a curated dataset with 130 natural language prompts for generating automation-focused remediation code scripts. After rigorous manual testing, the generated code achieved an impressive 98.86% accuracy rate, affirming the solution's reliability and performance in addressing dynamic auto-remediation complexities.
