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

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.

Software Development 103

Software Development Generative AI DevOps Artificial Intelligence 103

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.

Automation 241

Automation DevOps IDP Software Development 241

Marktechpost

DECEMBER 18, 2024

AI-powered tools have become indispensable for automating tasks, boosting productivity, and improving decision-making. From enhancing software development processes to managing vast databases, AI has permeated every aspect of software development.

Software Development 71

Software Development AI Tools DevOps Auto-complete 71

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.

DevOps 140

DevOps Software Engineer Data Scientist ML 140

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.

Automation 317

Automation AI AI DevOps 317

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?

DevOps 243

DevOps Software Development Automation Metadata 243

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?

DevOps 299

DevOps Automation Software Development Big Data 299

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.

DevOps 207

DevOps Automation Software Development 207

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.

Software Development 260

Software Development Automation DevOps Machine Learning 260

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.

DevOps 267

DevOps Software Development Artificial Intelligence Artificial Intelligence 267

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.

Artificial Intelligence 299

Artificial Intelligence Artificial Intelligence DevOps Automation 299

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.,

Automation 271

Automation DevOps Software Development Artificial Intelligence 271

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.

Automation 228

Automation DevOps Software Development 228

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.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

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.

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

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 172

Software Engineer Software Development Automation DevOps 172

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.

Chatbots 136

Chatbots Automation Machine Learning DevOps 136

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).

DevOps 289

DevOps Automation Software Development Generative AI 289

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 143

Software Development DevOps Big Data AI 143

Unite.AI

NOVEMBER 21, 2024

Archana Joshi brings over 24 years of experience in the IT services industry, with expertise in AI (including generative AI), Agile and DevOps methodologies, and green software initiatives. They support us by providing valuable insights, automating tasks and keeping us aligned with our strategic goals.

DevOps 147

DevOps Automation Responsible AI Software Development 147

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.

DevOps 308

DevOps Automation Software Development 308

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)?

DevOps 52

DevOps Artificial Intelligence Artificial Intelligence Machine Learning 52

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.

Machine Learning 78

Machine Learning DevOps Software Development Automation 78

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.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

Flipboard

NOVEMBER 24, 2023

This offering enables BMW ML engineers to perform code-centric data analytics and ML, increases developer productivity by providing self-service capability and infrastructure automation, and tightly integrates with BMW’s centralized IT tooling landscape. This results in faster experimentation and shorter idea validation cycles.

ML 152

ML DevOps Data Scientist ML Engineer 152

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?

Python 97

Python DevOps Machine Learning Data Science 97

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.

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

AWS Machine Learning Blog

OCTOBER 2, 2023

It is architected to automate the entire machine learning (ML) process, from data labeling to model training and deployment at the edge. Automating data labeling Data labeling is an inherently labor-intensive task that involves humans (labelers) to label the data. Let’s look at how to automate model building next!

DevOps 132

DevOps Automation Machine Learning Metadata 132

AWS Machine Learning Blog

OCTOBER 2, 2023

An MLOps pipeline allows to automate the full ML lifecycle from data labeling to model training and deployment. Implementing an MLOps pipeline at the edge introduces additional complexities that make the automation, integration, and maintenance processes more challenging due to the increased operational overhead involved.

DevOps 131

DevOps Automation ML Computer Vision 131

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.,

Automation 128

Automation DevOps Software Development Artificial Intelligence 128

AWS Machine Learning Blog

OCTOBER 2, 2023

In this post, we focus on how to automate the edge deployment part of the end-to-end MLOps pipeline. We show you how to use AWS IoT Greengrass to manage model inference at the edge and how to automate the process using AWS Step Functions and other AWS services. If you haven’t read it yet, we recommend checking out Part 1.

DevOps 131

DevOps Automation ML Machine Learning 131

IBM Journey to AI blog

AUGUST 2, 2023

Fact: All teams need access to the observability data The truth is that all teams— DevOps , SRE, Platform, ITOps and Development—need and deserve access to the data they want with the context of logical and physical dependencies across mobile, web, applications and infrastructure.

DevOps 176

DevOps Software Development Automation 176

Unite.AI

SEPTEMBER 4, 2024

System for Cross-Domain Identity Management (SCIM): This automation tool streamlines user provisioning and access control management across different domains and systems. Software Development and Code Management The native GitHub integration makes Claude a powerful ally for engineering teams.

DevOps 147

DevOps Large Language Models Automation Software Development 147

AWS Machine Learning Blog

NOVEMBER 27, 2024

For enterprises in the realm of cloud computing and software development, providing secure code repositories is essential. Amazon Bedrock offers a powerful solution by automating the process of scanning repositories for vulnerabilities and remediating them.

Generative AI 119

Generative AI Automation DevOps Prompt Engineer 119

AWS Machine Learning Blog

JULY 11, 2024

Agents for Amazon Bedrock automates the prompt engineering and orchestration of user-requested tasks. Through the interactive features of Agents for Amazon Bedrock, the automation of IaC generation not only streamlines the initial set up but also significantly improves ongoing operations like infrastructure management.

Data Ingestion 141

Data Ingestion DevOps Prompt Engineer Prompt Engineering 141

Marktechpost

AUGUST 30, 2024

On top of dealing with complicated documentation and software development kits (SDKs), existing cloud-native database services necessitate even more DevOps to orchestrate individual database instances: schema migrations, connection pooling, versioning across cases, etc.

DevOps 64

DevOps Software Development Automation Artificial Intelligence 64