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Kubernetes : up and running : dive into the future of infrastructure
\"Kubernetes is here to stay. In just five years, this container orchestrator has radically changed the way developers and ops personnel build, deploy, and maintain applications in the cloud. The updated edition of this popular book explains how Kubernetes can help your company achieve new levels of velocity, agility, reliability, and efficiency-- whether you're new to distributed systems or have been deploying cloud native apps for some time\"-- Provided by publisher.
Book
Learn Kubernetes Security
Secure your container environment against cyberattacks and deliver robust deployments with this practical guide
Key Features
* Explore a variety of Kubernetes components that help you to prevent cyberattacks
* Perform effective resource management and monitoring with Prometheus and built-in Kubernetes tools
* Learn techniques to prevent attackers from compromising applications and accessing resources for crypto-coin mining
Book Description
Kubernetes is an open source orchestration platform for managing containerized applications. Despite widespread adoption of the technology, DevOps engineers might be unaware of the pitfalls of containerized environments. With this comprehensive book, you'll learn how to use the different security integrations available on the Kubernetes platform to safeguard your deployments in a variety of scenarios.
Learn Kubernetes Security starts by taking you through the Kubernetes architecture and the networking model. You'll then learn about the Kubernetes threat model and get to grips with securing clusters. Throughout the book, you'll cover various security aspects such as authentication, authorization, image scanning, and resource monitoring. As you advance, you'll learn about securing cluster components (the kube-apiserver, CoreDNS, and kubelet) and pods (hardening image, security context, and PodSecurityPolicy). With the help of hands-on examples, you'll also learn how to use open source tools such as Anchore, Prometheus, OPA, and Falco to protect your deployments.
By the end of this Kubernetes book, you'll have gained a solid understanding of container security and be able to protect your clusters from cyberattacks and mitigate cybersecurity threats.
What you will learn
* Understand the basics of Kubernetes architecture and networking
* Gain insights into different security integrations provided by the Kubernetes platform
* Delve into Kubernetes' threat modeling and security domains
* Explore different security configurations from a variety of practical examples
* Get to grips with using and deploying open source tools to protect your deployments
* Discover techniques to mitigate or prevent known Kubernetes hacks
Who this book is for
This book is for security consultants, cloud administrators, system administrators, and DevOps engineers interested in securing their container deployments. If you're looking to secure your Kubernetes clusters and cloud-based deployments, you'll find this book useful. A basic understanding of cloud computing and containerization is necessary to make the most of this book.
eBook
Learning Robotic Process Automation
Robotic Process Automation (RPA) enables automating business processes using software robots. Software robots interpret, trigger responses, and communicate with other systems just like humans do. Robotic processes and intelligent automation tools can help businesses improve the effectiveness of services faster and at a lower cost than current methods. This book is the perfect start to your automation journey, with a special focus on one of the most popular RPA tools: UiPath. Learning Robotic Process Automation takes you on a journey from understanding the basics of RPA to advanced implementation techniques. You will become oriented in the UiPath interface and learn about its workflow. Once you are familiar with the environment, we will get hands-on with automating different applications such as Excel, SAP, Windows and web applications, screen and web scraping, working with user events, as well as understanding exceptions and debugging. By the end of the book, you'll not only be able to build your first software bot, but also you'll wire it to perform various automation tasks with the help of best practices for bot deployment.
eBook
ROBOT: A Tool for Automating Ontology Workflows
Background
Ontologies are invaluable in the life sciences, but building and maintaining ontologies often requires a challenging number of distinct tasks such as running automated reasoners and quality control checks, extracting dependencies and application-specific subsets, generating standard reports, and generating release files in multiple formats. Similar to more general software development, automation is the key to executing and managing these tasks effectively and to releasing more robust products in standard forms.
For ontologies using the Web Ontology Language (OWL), the OWL API Java library is the foundation for a range of software tools, including the Protégé ontology editor. In the Open Biological and Biomedical Ontologies (OBO) community, we recognized the need to package a wide range of low-level OWL API functionality into a library of common higher-level operations and to make those operations available as a command-line tool.
Results
ROBOT (a recursive acronym for “ROBOT is an OBO Tool”) is an open source library and command-line tool for automating ontology development tasks. The library can be called from any programming language that runs on the Java Virtual Machine (JVM). Most usage is through the command-line tool, which runs on macOS, Linux, and Windows. ROBOT provides ontology processing commands for a variety of tasks, including commands for converting formats, running a reasoner, creating import modules, running reports, and various other tasks. These commands can be combined into larger workflows using a separate task execution system such as GNU Make, and workflows can be automatically executed within continuous integration systems.
Conclusions
ROBOT supports automation of a wide range of ontology development tasks, focusing on OBO conventions. It packages common high-level ontology development functionality into a convenient library, and makes it easy to configure, combine, and execute individual tasks in comprehensive, automated workflows. This helps ontology developers to efficiently create, maintain, and release high-quality ontologies, so that they can spend more time focusing on development tasks. It also helps guarantee that released ontologies are free of certain types of logical errors and conform to standard quality control checks, increasing the overall robustness and efficiency of the ontology development lifecycle.
Journal Article
Unmanned aerial vehicles (UAVs): practical aspects, applications, open challenges, security issues, and future trends
Recently, unmanned aerial vehicles (UAVs) or drones have emerged as a ubiquitous and integral part of our society. They appear in great diversity in a multiplicity of applications for economic, commercial, leisure, military and academic purposes. The drone industry has seen a sharp uptake in the last decade as a model to manufacture and deliver convergence, offering synergy by incorporating multiple technologies. It is due to technological trends and rapid advancements in control, miniaturization, and computerization, which culminate in secure, lightweight, robust, more-accessible and cost-efficient UAVs. UAVs support implicit particularities including access to disaster-stricken zones, swift mobility, airborne missions and payload features. Despite these appealing benefits, UAVs face limitations in operability due to several critical concerns in terms of flight autonomy, path planning, battery endurance, flight time and limited payload carrying capability, as intuitively it is not recommended to load heavy objects such as batteries. As a result, the primary goal of this research is to provide insights into the potentials of UAVs, as well as their characteristics and functionality issues. This study provides a comprehensive review of UAVs, types, swarms, classifications, charging methods and regulations. Moreover, application scenarios, potential challenges and security issues are also examined. Finally, future research directions are identified to further hone the research work. We believe these insights will serve as guidelines and motivations for relevant researchers.
Journal Article
A robotic platform for flow synthesis of organic compounds informed by AI planning
Progress in automated synthesis of organic compounds has been proceeding along parallel tracks. One goal is algorithmic prediction of viable routes to a desired compound; the other is implementation of a known reaction sequence on a platform that needs little to no human intervention. Coley et al. now report preliminary integration of these two protocols. They paired a retrosynthesis prediction algorithm with a robotically reconfigurable flow apparatus. Human intervention was still required to supplement the predictor with practical considerations such as solvent choice and precise stoichiometry, although predictions should improve as accessible data accumulate for training. Science , this issue p. eaax1566 An automated synthesis platform conducts reactions on the basis of a human-devised workflow informed by a retrosynthesis algorithm. The synthesis of complex organic molecules requires several stages, from ideation to execution, that require time and effort investment from expert chemists. Here, we report a step toward a paradigm of chemical synthesis that relieves chemists from routine tasks, combining artificial intelligence–driven synthesis planning and a robotically controlled experimental platform. Synthetic routes are proposed through generalization of millions of published chemical reactions and validated in silico to maximize their likelihood of success. Additional implementation details are determined by expert chemists and recorded in reusable recipe files, which are executed by a modular continuous-flow platform that is automatically reconfigured by a robotic arm to set up the required unit operations and carry out the reaction. This strategy for computer-augmented chemical synthesis is demonstrated for 15 drug or drug-like substances.
Journal Article
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods
The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.
Journal Article