Analytics Vidhya

SEPTEMBER 14, 2022

Introduction DevOps practices include continuous integration and deployment, which are CI/CD. MLOps talks about CI/CD and ongoing training, which is why DevOps practices aren’t enough to produce machine learning applications. The post How is MLOps Different from DevOps? appeared first on Analytics Vidhya.

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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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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

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

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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DevOps Data Science Machine Learning 353

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

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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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 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

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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DevOps Data Science 288

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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DevOps Automation Generative AI Software Development 107

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

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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Machine Learning DevOps Data Science 284

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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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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DevOps LLM Large Language Models AI 107

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.

Big Data 266

Big Data DevOps Automation Machine Learning 266

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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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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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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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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DevOps ML Data Science 94

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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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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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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IBM Journey to AI blog

FEBRUARY 22, 2024

They upskilled 3,000 software engineers for DevOps and cloud-native technologies. With a co-created custom curriculum that is designed to supplement their standard DevOps and cloud native offerings to ensure the content aligned with the client’s new technology stack.

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DevOps Software Engineer 196

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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Flipboard

MARCH 27, 2023

Devops teams build their infrastructure as code, automate deployments with continuous integration/continuous delivery (CI/CD), and establish …

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DevOps Automation Big Data Machine Learning 168

AI News

JULY 11, 2024

Software development emerges as the most popular area for AI investment (59%), followed by quality assurance (44%) and DevOps and automation (44%). Investment in AI capabilities is substantial, with 93% of companies spending at least £100,000 in 2024, and 44% allocating £500,000 or more.

Software Development 292

Software Development Big Data DevOps AI 292

IBM Journey to AI blog

OCTOBER 3, 2023

Going beyond traditional APM solutions, IBM Instana extends observability to all teams, so anyone across DevOps , SRE , platform engineering, ITOps and development can get the data they want with the context they need. You’ll find automated full-stack visibility, one-second granularity and three seconds to notify.

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IBM Journey to AI blog

OCTOBER 17, 2023

This solution extends observability to a wide range of roles, including DevOps, SRE, platform engineering, ITOps and development. Instana Observability outperforms traditional application performance monitoring (APM) tools with one-second granularity and notifications delivered within three seconds.

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DevOps Auto-complete Automation Python 231

IBM Journey to AI blog

MAY 18, 2023

It’s also an evolution from the current “fat pipes” method (which doesn’t differentiate between applications) to one that aligns the network to the needs of the business, its users, and its developers, their CI/CD pipeline and DevOps cycles.

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IBM Journey to AI blog

MARCH 22, 2024

IBM® brings in all this through The IBM IGNITE Quality Platform (IQP), which is a DevOps-enabled single sign-on platform that leverages AI capabilities and patented methods to optimize tests.

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Automation DevOps IDP Software Development 241

IBM Journey to AI blog

DECEMBER 19, 2023

As practices like DevOps , cloud native , serverless and site reliability engineering (SRE) mature, the focus is shifting toward significant levels of automation, speed, agility and business alignment with IT (which helps enterprise IT transform into engineering organizations). Patterns (on paper) only as prescriptive guidance.

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DevOps Automation Software Development 207

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 […].

DevOps 143

DevOps Data Science 143

IBM Journey to AI blog

FEBRUARY 29, 2024

DevOps: The combination of microservices as an architecture and containers as a platform is a strong pairing and a common foundation for many teams that embrace DevOps and development environments as the way they choose to handle software development.

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