Analytics Vidhya

JANUARY 25, 2022

Introduction In this article, we will be going through two concepts MLOps and DevOps. As you might be aware in DevOps we try to bring together […]. The post MLOps vs DevOps: Let’s Understand the Differences? We will first try to get through their basics and then we will explore the differences between them.

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IBM Journey to AI blog

JUNE 12, 2023

This requires a careful, segregated network deployment process into various “functional layers” of DevOps functionality that, when executed in the correct order, provides a complete automated deployment that aligns closely with the IT DevOps capabilities. appeared first on IBM Blog.

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Analytics Vidhya

MAY 30, 2022

Docker is a DevOps tool and is very popular in the DevOps and MLOPS world. This article was published as a part of the Data Science Blogathon. Introduction on Docker Docker is everywhere in the world of the software industry today. The post A Complete Guide for Deploying ML Models in Docker appeared first on Analytics Vidhya.

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Analytics Vidhya

JUNE 7, 2022

Introduction on Dockerfile This article contains about Dockerfile that we are commonly using in DevOps Engineering. DevOps is nothing but it is a set of practices that ensures systems development life cycle and provides continuous delivery with high software quality, that combines software […].

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Analytics Vidhya

MAY 21, 2022

Introduction on Docker Containers Networking The concept of DevOps culture in an IT-driven organization seeks to bring synergy between the development part of the application and operations. Docker is one of the critical tools being used by the DevOps community for providing complete […].

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IBM Journey to AI blog

SEPTEMBER 5, 2023

DevOps, open source and the mainframe Open-source software and DevOps share a common philosophy and technical underpinnings. DevOps is a mindset, a culture and a set of technical practices that foster better communication and collaboration across the software lifecycle. The key to this deep relationship? Open-source software.

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Analytics Vidhya

NOVEMBER 23, 2020

Introduction This article outlines the motivation behind MLOps, its relation to DevOps, The post MLOps – the Why and the What appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

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Analytics Vidhya

MARCH 2, 2023

And also Python is a flexible language that can be applied in various domains, including scientific programming, DevOps, automation, and web development. Introduction Setting up an environment is the first step in Python development, and it’s crucial because package management can be challenging with Python.

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Analytics Vidhya

OCTOBER 2, 2022

Many persons have barely finished digesting the meaning of DevOps, and here come a new term, MLOps. But, those who understand the meaning of the older term DevOps are on the safe side. So, if you know what’s DevOps and you […]. This article was published as a part of the Data Science Blogathon. Introduction MLOps?

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Flipboard

FEBRUARY 24, 2023

As indicated in my prior blogs Optimizing Cloud Costs for DevOps With AI-Assisted Kubernetes and Optimizing Cloud Costs for DevOps With AI-Assisted Orchestration, an AI-assisted Kubernetes orchestrator is needed to optimize cloud costs for DevOps, DevSecOps and SRE.

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Analytics Vidhya

JULY 28, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon ML + DevOps + Data Engineer = MLOPs Origins MLOps originated. The post DeepDive into the Emerging concpet of Machine Learning Operations or MLOPs appeared first on Analytics Vidhya.

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Analytics Vidhya

MARCH 21, 2022

Introduction I believe all you’re familiar with the terminology DevOps for these many years, this is the complete culture and process life cycle of CI/CD. This article was published as a part of the Data Science Blogathon.

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O'Reilly Media

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments.

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Analytics Vidhya

JUNE 13, 2024

LangSmith is a new cutting-edge DevOps platform designed to develop, collaborate, test, deploy, and monitor LLM applications. Introduction With the advancements in Artificial Intelligence, developing and deploying large language model (LLM) applications has become increasingly complex and demanding.

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databricks

SEPTEMBER 11, 2024

Personal Access Tokens (PATs) are a convenient way to access services like Azure Databricks or Azure DevOps without logging in with your password.

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Analytics Vidhya

FEBRUARY 2, 2022

Table of contents Overview Traditional Software development Life Cycle Waterfall Model Agile Model DevOps Challenges in ML models Understanding MLOps Data Engineering Machine Learning DevOps Endnotes Overview: MLOps According to research by deeplearning.ai, only 2% of the companies using Machine Learning, Deep learning have […].

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AWS Machine Learning Blog

MARCH 27, 2024

Although much of the focus around analysis of DevOps is on distributed and cloud technologies, the mainframe still maintains a unique and powerful position, and it can use the DORA 4 metrics to further its reputation as the engine of commerce. Using a Git-based SCM pulls these insight together seamlessly.

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Unite.AI

MARCH 7, 2025

It works alongside IT, DevOps, and SRE teams without requiring major infrastructure changes. Multi-agent AI workflows will enable seamless collaboration across IT, security, and DevOps, breaking down silos between departments.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Overview of Kubernetes Containers —lightweight units of software that package code and all its dependencies to run in any environment—form the foundation of Kubernetes and are mission-critical for modern microservices, cloud-native software and DevOps workflows.

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Marktechpost

APRIL 11, 2024

If you’re an LLM, you need Keywords AI’s unified DevOps platform. The post Meet Keywords AI: A Unified DevOps Platform to Build AI Applications appeared first on MarkTechPost. Key Takeaways The potential of LLM applications is enormous, but creating them is challenging.

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IBM Journey to AI blog

AUGUST 12, 2024

MLOps is a set of practices that combines machine learning (ML) with traditional data engineering and DevOps to create an assembly line for building and running reliable, scalable, efficient ML models. AIOPs enables ITOPs personnel to implement predictive alert handling, strengthen data security and support DevOps processes.

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Big Data DevOps Automation Machine Learning 266

Unite.AI

FEBRUARY 3, 2025

Just as teams of people collaborate to tackle challenges, AI agents can be organized to address non-trivial tasks in fields like DevOps, application development, or even financial technology. Agentic AI is a natural fit for any domain requiring complex problem-solving.

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Marktechpost

NOVEMBER 23, 2024

Gemini for DevOps Engineers This course teaches engineers to use Gemini to manage infrastructure. You will learn to prompt Gemini for application logs, create a GKE cluster, and explore build environments, with hands-on labs enhancing the DevOps workflow.

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DevOps Data Analysis Large Language Models Generative AI 108

Marktechpost

MAY 20, 2024

The post Bisheng: An Open-Source LLM DevOps Platform Revolutionizing LLM Application Development appeared first on MarkTechPost. By providing tools for both novices and experts and ensuring reliability and scalability for enterprise use, Bisheng is poised to play a significant role in the future of intelligent application development.

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IBM Journey to AI blog

OCTOBER 13, 2023

DevOps culture and collaboration Instana’s focus on fostering a Dev Ops culture and collaboration is another distinguishing factor. While New Relic offers similar capabilities, Instana’s AI-driven approach provides deep and actionable insights with minimal effort on the user’s end.

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IBM Journey to AI blog

JANUARY 10, 2024

Traditionally, applications and their hosting infrastructure align with DevOps and CloudOps. Typically, DevOps initiates requests, scrutinized by CloudOps, NetOps, SecOps and FinOps teams. However, rising costs due to diverse IT environments led to the emergence of FinOps, focusing on expense monitoring and control.

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Unite.AI

FEBRUARY 6, 2025

Key features include model cataloging, fine-tuning, API deployment, and advanced governance tools that bridge the gap between DevOps and MLOps. Designed with a developer-first interface, the platform simplifies AI deployment, allowing full-stack data scientists to independently create, test, and scale applications.

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Unite.AI

FEBRUARY 5, 2025

With AI-driven pentesting, businesses can shift left from DevOps to DevSecOps , seamlessly integrating security into their development workflows. Astra Security is designed to be the single source of security trust, ensuring that businesses can onboard vendors, integrate APIs, and expand their digital footprint without compromising security.

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Flipboard

FEBRUARY 24, 2025

Hrushikesh Deshmukh, Senior Consultant, Fannie Mae. Predictive monitoring is transforming enterprise operations by combining the latest technologies with strategic implementation. By preventing issues before they escalate through early detection, enhancement of reliability and better performance

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Towards AI

DECEMBER 26, 2024

Source: Image By Author As a Cloud Engineer, Ive recently collaborated with a number of project teams, and my primary contribution to these teams has been to do the DevOps duties required on the GCP Cloud. My main goal as a DevOps Cloud Engineer is to achieve four objectives. What are they?

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AWS Machine Learning Blog

JANUARY 23, 2025

About the Authors Muni Annachi , a Senior DevOps Consultant at AWS, boasts over a decade of expertise in architecting and implementing software systems and cloud platforms. He specializes in guiding non-profit organizations to adopt DevOps CI/CD architectures, adhering to AWS best practices and the AWS Well-Architected Framework.

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Automation DevOps Machine Learning ML 105

IBM Journey to AI blog

OCTOBER 16, 2023

They have become more important as organizations embrace modern development techniques such as microservices, serverless and DevOps, all of which utilize regular code deployments in small increments. Containerization helps DevOps teams avoid the complications that arise when moving software from testing to production.

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IBM Journey to AI blog

MAY 17, 2024

It identifies the technologies and internal knowledge that an organization has, how suited its culture is to embrace managed services, the experience of its DevOps team, the initiatives it can begin to migrate to cloud and more. A DevOps practice is being developed, bringing together cloud engineers and developer groups.

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Flipboard

DECEMBER 10, 2024

Technology operations (TechOps) is a broad topic that includes AIOps, SecOps, DevOps, FinOps, DataOps and so on. Sandeep Shilawat is a renowned tech innovator, thought leader and strategic advisor in U.S. federal markets. Generative AI (GenAI), armed with large language models (LLMs) and agentic AI,

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DevOps Large Language Models Generative AI AI 166

NVIDIA

DECEMBER 3, 2024

The certification exams and recommended training to prepare for them are designed for network and system administrators, DevOps and MLOps engineers, and others who need to understand AI infrastructure and operations.

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IBM Journey to AI blog

DECEMBER 1, 2023

The initial use of generative AI is often for making DevOps more productive. This enables IT operations and DevOps teams to respond more quickly (even proactively) to slowdowns and outages, thereby improving efficiency and productivity in operations.

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Towards AI

JANUARY 21, 2025

The project started with a clear objective: to build a functional MVP for a DevOps chatbot using AWS Bedrock… Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI.

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