GitHub Steers Copilot Autofix Into Eye of AI Security Storm
GitHub has come forward with its new Copilot Autofix tool. This AI-driven software service is targeted at developers who need to address software vulnerabilities in code destined for traditional applications and inside those infused with an injection of new or existing breeds of AI.
Hello Henrik, Neuralogics’ Multi-Contextual Intelligence AI Engine
Neuralogics has followed the industry trend that sees technology vendors label their AI engines with a human name. With Salesforce Einstein, IBM Watson and Davis (that one’s Dynatrace) and even the possible inclusion of Waldo Search already with us, Neuralogics now joins the family with Henrik.
Say ‘No’ to ‘NoOps’: Why We Can’t Afford to Let AI Run Wild
As we anticipate the advancement of AI over the next decade, we must recognize that we are not equipped to grant these tools complete control.
Focus on Basics or Innovation? DevOps Success Requires Both
DevOps teams are experiencing a chasm between traditionalists and innovators — a rift that grows as pressure mounts for teams to leverage the latest advancements. Traditionalists are fighting to preserve the basics, to carry an appreciation for the early days of DevOps, and to not cut corners (look no further than CrowdStrike).
Survey: Usage of AI Rapidly Expands Once DevOps Teams Adopt
A survey of 504 DevOps professionals published today finds that 20% are now using artificial intelligence (AI) across all phases of the software development lifecycle (SDLC).
Global Survey Finds Testing as the Most Valuable AI Investment Across the Software Development Lifecycle
Tricentis report reveals AI-augmented DevOps tools will save teams over an estimated 40 hours per month—equivalent to an entire workweek AUSTIN, TEXAS – August 6th, 2024 – Tricentis, a global leader in continuous testing and quality engineering, today released the findings of its most recent AI report, “AI-augmented DevOps: Trends Shaping the Future.” This year’s research aims to understand […]
Survey Surfaces Wide Generative AI Adoption Among Software Engineers
A survey of 509 software engineers finds nearly three-quarters (72%) are leveraging generative artificial intelligence (AI) capabilities somewhere in a software development process, with nearly half (48%) reporting they use these tools every day.
DevOps for Machine Learning and Artificial Intelligence
DevOps for machine learning and artificial intelligence, known as MLOps, evolves to meet the demands of the AI landscape.
AI-Powered Solutions for Azure DevOps Pipelines
The integration of artificial intelligence (AI) into Azure DevOps pipelines transforms the manual software development and delivery process.
Survey Surfaces Troubling Signs of Software Supply Chain Insecurity
A survey of software engineering professions has uncovered disconcerting signs of software supply chain insecurity.
Pair of Surveys Surface Primary Developer Productivity Challenges
A survey of 900 developers finds well over two-thirds (69%) said developers are losing eight or more hours of their working week to inefficiencies created by, for example, technical debt, insufficient documentation and flawed build processes.
Survey Surfaces High DevOps Burnout Rates Despite AI Advances
The results of a survey of software developers and engineering professionals surfaces high DevOps burnout rates despite AI advances.
The Three Pillars of Modern API Management
If your company’s API management solution is multi-gateway, event-native and AI-forward, then you will be ahead of the competition in productivity and security.
Site Reliability Engineering State of the Union for 2024: Embracing Innovation and Efficiency in the Age of Generative AI
SRE practices are set to undergo significant transformations, driven by technological advancements and changing organizational needs.
SRE in the Age of AI
Site reliability engineering (SRE) is a concept introduced by Google in 2004 and since then it has been adopted by various leading software organizations. In its purest form SRE is what you get when you treat operations like it is a software problem. Industry-leading reports point out the strategic value that SRE offers to the […]
Datadog Extends Scope and Reach of Observability Platform
Datadog at its DASH 2024 conference added a bevy of tools and capabilities to streamline DevSecOps workflows, including integration with open-source OpenTelemetry agent software developed under the auspices of the Cloud Native Computing Foundation (CNCF) and the Datadog On-Call tool to optimize incident management workflows in a way that maintains context with observability data already collected.
Fostering an AI-Focused Engineering Team That Accelerates DevOps Maturity
An AI agent is a series of prompts that leverage AI to carry out a role within the engineering team, such as the business owner or tester.
Testing Agents: More than a Copilot
Copilots boost productivity for both use cases but are generally passive tools that must be fed precise requirements to get the desired results.
Sapient.ai Automation Platform Leverages AI to Create Unit Tests
Sapient.ai today launched a testing automation platform that makes use of artificial intelligence (AI) and automatically creates unit tests as the applications are developed.
Survey Surfaces Significant Adoption of AI Tools to Build Software
A global survey of 5,315 IT professionals that included 804 C-level executives and 1,439 security experts finds 39% of respondents reporting they work for organizations currently using artificial intelligence (AI) to build software.
JFrog Acquires Qwak to Meld MLOps and DevOps Workflows
JFrog today revealed it has acquired Qwak to add a machine learning operations (MLOps) platform to its existing portfolio of DevOps tools and platforms.
Can AI Replace DevOps Engineers ?
Let’s figure out what AI does well, where it falls short, and whether DevOps professionals should fear it and start re-skilling today.
Shreds.AI Launches LLM Platform Trained for Software Engineering
Shreds.AI today unveiled a namesake generative artificial intelligence (AI) platform based on a large language model (LLM) it trained to specifically automate software engineering tasks.