Search
10 articles for “workflow orchestration”
-
A Comprehensive Review of Durable State Persistence Techniques for Resilient API Calls in Kubernetes-Based Microservices
Abstract: Kubernetes lets teams scale microservices and replace pods almost without notice. The same design that makes clusters reliable creates an intractable problem for API calls that require multiple steps on multiple individual services. A pod can stop suddenly. Any progress retained only in the memory vanishes. The client is forced to start the whole thing over. Data that is left behind can end up inconsistent. Durable state persistence is a …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article
-
Workflow Streamlining Through Shell Programming: A Review of Automation Techniques, Best Practices, and Applications
Abstract: The rapid advancement of modern computing systems and the increasing complexity of information technology infrastructures have created a growing need for efficient automation and streamlined system administration. Among the various automation technologies available, shell programming remains one of the most practical, flexible, and widely adopted approaches for managing repetitive tasks and optimizing operational workflows in Unix-like operating systems. Shell scripts enable administrators and developers to automate command execution, coordinate system …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 · pp. 9–20 Read article
-
Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
-
Open-Source AI Agent Frameworks: A Comparative Performance Analysis
Abstract: The rapid growth of agentic AI has led to a diverse ecosystem of open-source frameworks for developing LLM-based agents. These frameworks differ in their approaches to state management, multi-agent coordination, tool orchestration, memory, and workflow execution. This paper presents a comparative analysis of prominent open-source AI agent frameworks, including LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and related systems. The study synthesizes a common architectural model to identify the core components …
Published in Journal of Open Source Developments · Vol. 13, Issue 2, 2026 · pp. 23–33 Read article
-
VeriSci—AI-Based Multi-Modal Research Assistant
Abstract: The exponential growth of scientific literature is a major bottleneck for academic researchers who want to efficiently discover, assess, and synthesize relevant scholarly knowledge. Traditional methods of literature review are heavily reliant on manual keyword searching, human screening, and subjective data extraction, making them time-consuming, susceptible to cognitive bias, and less effective as the tidal wave of information continues to grow. To overcome these limitations, this study introduces VeriSci, an …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 20–27 Read article
-
Applying Text Analysis Methods for Emotion Recognition
Abstract: This article presents a comprehensive study of sentiment analysis, a vital task in the realms of natural language processing (NLP) and artificial intelligence (AI). Sentiment analysis involves the extraction and classification of subjective information from textual data, determining whether the sentiment expressed is positive or negative. This paper investigates different approaches and methodologies used in sentiment analysis, encompassing machine learning models as well. Additionally, it discusses the challenges faced in …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 12–22 Read article
-
Advances in Shell Programming: Techniques, Tools, and Emerging Trends
Abstract: Shell programming has undergone a significant transformation, shifting from simple command-line interactions to a mature, versatile scripting environment that supports modern computing needs. Over time, shells such as Bash, Zsh, and PowerShell have expanded far beyond basic task execution, evolving into powerful tools capable of handling complex automation workflows, system configuration tasks, and cross-platform orchestration. These environments now offer improved error handling, stronger security features, integrated performance-monitoring options, and more …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
-
Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation (RAG), security analytics, and controlled tools used to support SOC teams. The proposed design uses specialized agents for alert triage, investigation, threat intelligence, detection engineering, response planning, and reporting, coordinated by an orchestration layer. Agents can collect evidence, summarize events, map behaviors to attack techniques, suggest hypotheses, and prepare response actions, but high-impact changes remain subject to human approval. The framework also emphasizes trustworthy operation through evidence citation, least-privilege access, policy gates, audit logs, prompt-injection resistance, privacy controls, and continuous evaluation. Electrical and electronics relevance is included through monitoring of Internet of Things devices, industrial control systems, programmable logic controllers (PLC), edge gateways, sensors, firmware, and operational technology (OT) networks. Recent research and industry practice indicate that large language models and autonomous agents can improve security workflow automation, while important limitations remain around hallucination, data leakage, adversarial manipulation, excessive agency, and model drift. The paper therefore treats the security copilot as an analyst augmentation layer rather than an unsupervised replacement for professional judgment.
Abstract: Security Operations Centers (SOCs) must interpret large volumes of alerts, logs, endpoint events, identity signals, threat intelligence, and cloud activity while responding quickly to incidents. Conventional automation reduces repetitive work, but it often depends on fixed rules and separate tools that still require analysts to assemble context manually. This review presents a practical framework for AI (Artificial Intelligence) agent-based security copilots that combine large language models, machine learning, retrieval-augmented generation …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 3, 2026 Read article
-
A Review of Shell Programming Applications in Blockchain and Web3 Infrastructure
Abstract: Shell programming has long been an essential tool for automation and system management, but its role in emerging technologies like Blockchain and Web3 infrastructure has become increasingly prominent. This review explores how shell scripting supports various processes within decentralized ecosystems, including node management, smart contract deployment, data synchronization, and continuous integration workflows. As blockchain networks scale in complexity, shell scripts provide efficient solutions for orchestrating automation, security audits, and distributed …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 3, 2025 Read article
-
AI-Powered Prompt-to-Production Platform for Automated React Application Generation and Cloud Deployment
Abstract: The proliferation of large language models (LLMs) has fundamentally altered the landscape of automated software engineering. However, a significant “deployment chasm” persists between the generation of code artifacts and their realization as production-grade cloud applications. Traditional workflows are marred by the “DevOps Tax”: the high operational overhead of environment configuration, dependency resolution, and infrastructure provisioning. This paper presents a novel, technically adept architecture that bridges this gap through a unified …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 · pp. 1–16 Read article