IBM Journey to AI blog

MARCH 6, 2024

Software development is one arena where we are already seeing significant impacts from generative AI tools. A McKinsey study claims that software developers can complete coding tasks up to twice as fast with generative AI. A burned-out developer is usually an unproductive one.

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IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). Scope and focus AIOps methodologies are fundamentally geared toward enhancing and automating IT operations. AIOps and MLOps: What’s the difference?

Big Data 266

Big Data DevOps Automation Machine Learning 266

IBM Journey to AI blog

SEPTEMBER 17, 2024

It’s also revolutionizing the software development lifecycle (SDLC). And The evolution of the SDLC landscape The software development lifecycle has undergone several silent revolutions in recent decades. They can also build (and run) highly automated tests and perform quality and validation procedures.

Software Development 122

Software Development Generative AI DevOps Automation 122

IBM Journey to AI blog

NOVEMBER 13, 2023

Technical debt is a metaphor in software development that refers to the consequences of choosing a quick solution to a problem instead of a more comprehensive and responsible approach. Use frameworks: Frameworks are pre-established sets of libraries, tools and conventions that provide a foundation for developing software applications.

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AWS Machine Learning Blog

MARCH 27, 2024

In software engineering, there is a direct correlation between team performance and building robust, stable applications. The data community aims to adopt the rigorous engineering principles commonly used in software development into their own practices, which includes systematic approaches to design, development, testing, and maintenance.

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DevOps Generative AI Automation Software Development 118

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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Becoming Human

APRIL 19, 2024

In software development, staying ahead of the curve is vital for businesses that needs to deliver innovative and efficient solutions. The use of Generative AI is one of the most exciting technological developments that is changing the pattern for software development.

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IBM Journey to AI blog

MARCH 22, 2024

Quality Assurance (QA) is a critical component of the software development lifecycle, aiming to ensure that software products meet specified quality standards before release. QA encompasses a systematic and strategic approach to identifying, preventing and resolving issues throughout the development process.

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Automation DevOps IDP Software Development 241

Unite.AI

SEPTEMBER 30, 2024

AI quality assurance (QA) uses artificial intelligence to streamline and automate different parts of the software testing process. AI also automates test data generation, creating a wide range of test data that reduces the need for manual input. Automated QA surpasses manual testing by offering up to 90% accuracy.

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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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Unite.AI

JUNE 7, 2023

Can you discuss why enterprises should integrate application security early into the software development life cycle? DevSecOps, also known as “secure devops”, is the mindset that security is integrated throughout the entire SDLC, from requirements to architecture and design, coding, testing, release and deployment.

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IBM Journey to AI blog

MARCH 29, 2024

Monitoring and optimizing application performance is important for software developers and enterprises at large. OpenTelemetry and Prometheus enable the collection and transformation of metrics, which allows DevOps and IT teams to generate and act on performance insights. What is OpenTelemetry?

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IBM Journey to AI blog

FEBRUARY 6, 2024

This unified view gives administrators and development teams centralized control over their infrastructure and apps, making it possible to optimize cost, security, availability and resource utilization. Automation Automation tools are a significant feature of cloud-based infrastructure. What is a public cloud?

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Unite.AI

NOVEMBER 17, 2023

During the coding and testing phases, AI algorithms can detect vulnerabilities that human developers might miss. Below, I am listing several ways in which AI can assist developers in creating secure apps. Automated Code Review and Analysis AI can review and analyze code for potential vulnerabilities.

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IBM Journey to AI blog

FEBRUARY 29, 2024

This is managed by the container runtime—a software solution interacting with the OS to make the necessary room to run container images. Further, Kubernetes is an open-source system and encourages the avid participation of contributors (who oversee the project now), with each software provider putting its own spin on Kubernetes.

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Unite.AI

OCTOBER 18, 2024

As companies grapple with the complexities of cloud-native architectures, microservices, and the need for rapid deployment, IDPs offer a solution that streamlines workflows, automates repetitive tasks, and empowers developers to focus on what they do best – writing code.

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IBM Journey to AI blog

DECEMBER 19, 2023

This post expands on the topic and provides a maturity model and building blocks that help enterprises accelerate their software supply chain lifecycle in the ever-evolving landscape of enterprise cloud-native software development. We recommend a 4-stage roadmap for implementation, as shown in the figure below.

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IBM Journey to AI blog

JANUARY 26, 2024

At Instana, addressing our customers’ needs and creating a simple tool that is easy to use is fundamental to helping our DevOps and SRE teams reduce burnout rates, allowing them to excel in what they do best. We announced our action framework, where you can create new actions or reuse your existing automation (e.g.,

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Unite.AI

JUNE 19, 2024

MLOps, or Machine Learning Operations, is a multidisciplinary field that combines the principles of ML, software engineering, and DevOps practices to streamline the deployment, monitoring, and maintenance of ML models in production environments. ML Operations : Deploy and maintain ML models using established DevOps practices.

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IBM Journey to AI blog

AUGUST 11, 2023

MLOps, which stands for machine learning operations, uses automation, continuous integration and continuous delivery/deployment (CI/CD) , and machine learning models to streamline the deployment, monitoring and maintenance of the overall machine learning system. How to use ML to automate the refining process into a cyclical ML process.

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Data Science DevOps Machine Learning Data Scientist 170

AWS Machine Learning Blog

MARCH 10, 2025

The use of multiple external cloud providers complicated DevOps, support, and budgeting. Automated deployment strategy Our GitOps-embedded framework streamlines the deployment process by implementing a clear branching strategy for different environments. The system also enables rapid rollback capabilities if needed.

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Flipboard

DECEMBER 26, 2023

Software development is currently undergoing a profound transformation, marked by a quiet yet remarkable surge in advanced automation. This impending …

Software Engineer 171

Software Engineer Software Development Automation DevOps 171

AWS Machine Learning Blog

OCTOBER 16, 2024

The company developed an automated solution called Call Quality (CQ) using AI services from Amazon Web Services (AWS). Machine learning operations (MLOps) Intact also built an automated MLOps pipeline that use Step Functions, Lambda, and Amazon S3. Amazon DynamoDB is used in this architecture to control the limits of the queues.

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Machine Learning Data Scientist Deep Learning DevOps 86

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.

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AWS Machine Learning Blog

MAY 1, 2024

This post demonstrates how to build a chatbot using Amazon Bedrock including Agents for Amazon Bedrock and Knowledge Bases for Amazon Bedrock , within an automated solution. Solution overview In this post, we use publicly available data, encompassing both unstructured and structured formats, to showcase our entirely automated chatbot system.

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AWS Machine Learning Blog

MARCH 21, 2025

However, by using Anthropics Claude on Amazon Bedrock , researchers and engineers can now automate the indexing and tagging of these technical documents. By automating the indexing and tagging of technical documents, these powerful models can enable more efficient knowledge management and accelerate innovation across a variety of industries.

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Artificial Corner

MARCH 6, 2025

For decades, every new automation tool has raised the same question: "Will it replace developers?" It can automate repetitive coding and speed up development, but it can’t design systems or decide what to build—those high-level responsibilities are still firmly in human hands (for now). Hype or Reality?

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IBM Journey to AI blog

APRIL 4, 2024

cloud servers, data storage , networking capabilities, automation , software, data analytic tools)—with the security and control of on-premises IT infrastructure. SaaS, or Software-as-a-Service , is on-demand access to ready-to-use software apps (e.g., Adobe Creative Suite, Slack).

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Pickl AI

APRIL 17, 2023

How can a DevOps team take advantage of Artificial Intelligence (AI)? DevOps is mainly the practice of combining different teams including development and operations teams to make improvements in the software delivery processes. So now, how can a DevOps team take advantage of Artificial Intelligence (AI)?

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IBM Journey to AI blog

NOVEMBER 2, 2023

When it comes to modern IT infrastructure, the role of Kubernetes —the open-source container orchestration platform that automates the deployment, management and scaling of containerized software applications (apps) and services—can’t be underestimated.

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Mlearning.ai

JUNE 16, 2023

Increase your productivity in software development with Generative AI As I mentioned in Generative AI use case article, we are seeing AI-assisted developers. SDLC stages Let’s review software development lifecycle first. Then software development phases are planned to deliver the software.

Software Development 52

Software Development Generative AI ChatGPT Prompt Engineer 52

Pickl AI

APRIL 1, 2025

Collaborating with DevOps Teams and Software Developers Cloud Engineers work closely with developers to create, test, and improve applications. Learn a Programming Language Coding is essential for automating cloud tasks and managing infrastructure efficiently.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

The technical sessions covering generative AI are divided into six areas: First, we’ll spotlight Amazon Q , the generative AI-powered assistant transforming software development and enterprise data utilization. You’ll leave with practical skills to supercharge your application development!

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Becoming Human

MAY 11, 2023

Machine learning operations, or MLOps, are the set of practices and tools that aim to streamline and automate the machine learning lifecycle. MLOps projects are projects that focus on implementing machine learning operations best practices into a company’s existing software development and deployment process.

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The MLOps Blog

JANUARY 23, 2023

Just so you know where I am coming from: I have a heavy software development background (15+ years in software). Lived through the DevOps revolution. Came to ML from software. Founded two successful software services companies. If you’d like a TLDR, here it is: MLOps is an extension of DevOps.

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Pickl AI

JANUARY 30, 2023

Data Automation: Automate data processing pipelines and workflows using Python scripting and libraries such as PyAutoGUI and Task Scheduler. A Software Developer Uses Python: Backend Development : Python finds applications in developing server-side applications and APIs. How to Make a Career in Python?

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Heartbeat

FEBRUARY 1, 2023

MLOps is a highly collaborative effort that aims to manipulate, automate, and generate knowledge through machine learning. We also have software engineers who are in charge of creating and maintaining the facilities and tools required to deploy and operate machine learning models. Learn more lessons from the field with Comet experts.

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