209 articles · page 3 of 5
DevOps.com, Wednesday, April 29th, 2026
Explores how AI agents and vibe coding are transforming software engineering roles and the spectrum between declarative and imperative AI development approaches.
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DevOps.com, Tuesday, April 28th, 2026
It appears that GitHub has its hands full adjusting to the demands of scaling AI workloads. First, the company paused sign-ups for its Copilot subscription tiers in response to a wave of demand from agentic AI projects. Then it shifted to usage-based pricing to, again, better align revenue with the heavy compute demands of AI projects.
more → DevOps.com, Monday, April 27th, 2026
Building AI agents sounds straightforward until you actually do it. You need an agent to onboard a new employee. It has to create an Entra ID account, provision GitHub access, spin up cloud resources, create tasks in Azure DevOps, and send a welcome message in Teams. Five tools. Five different authentication models. Five different teams are managing those tools.
more → DevOps.com, Monday, April 27th, 2026
The Model Context Protocol (MCP) is moving faster than the developer community can keep up with, racing past its original design parameters and leaving teams scrambling to build clients that can match its pace. The result is an ecosystem where the protocol itself keeps shifting under everyone's feet, and where the tooling, conventions and security thinking that should accompany a foundational standard are still being figured out on the fly.
more → devops.com, Thursday, April 23rd, 2026
Operations in DevOps is not just about keeping systems up anymore. Teams now have to support faster releases, manage cloud-native environments, improve security, and keep services reliable at scale.
more → devops.com, Wednesday, April 22nd, 2026
The demos look super cool! An AI agent detects a failing deployment, rolls it back, opens a GitHub issue, and notifies Slack - all before the on-call engineer has finished reading the alert. If you've been following the DevOps tooling space over the last 18 months, you've probably seen some version of this pitch.
more → devops.com, Tuesday, April 21st, 2026
Grafana Labs announced AI agent integration, new observability platform, and Grafana 13 updates at GrafanaCON 2026.
more → devops.com, Monday, April 20th, 2026
Claude agents can automate repetitive DevOps tasks but cannot replace human judgment in complex production decisions.
more → devops.com, Friday, April 17th, 2026
The XZ Utils backdoor was a wake-up call, but the underlying problem it exposed has not gone away. Sophisticated adversaries are playing the long game, spending months or years earning trust within open source projects before introducing malicious code into libraries that sit at the foundation of modern software infrastructure.
more → devops.com, Thursday, April 16th, 2026
Waydev today revealed it has revamped its engineering intelligence platform to provide insights into how the adoption of artificial intelligence (AI) coding tools is impacting DevOps workflows. Company CEO Alex Circei said the overall goal is to make it easier for the leaders of software engineering teams to determine the return on investment (ROI) their AI coding tools are actually providing.
more → devops.com, Thursday, April 16th, 2026
There was once a trend toward becoming a full-stack software engineer. Today, full-stack engineers are not limited to UI (User Interface) and DB (Backend Databases), they are adapting to cloud-native applications, managing Infrastructure as Code (IaC), automating CI/CD pipelines and using tools like GitHub Actions, Docker, and Terraform.
more → devops.com, Tuesday, April 14th, 2026
For most of its short life, Claude has lived inside a chat window. You type, it responds. That model is changing fast.
more → devops.com, Wednesday, April 8th, 2026
Jules was just the beginning. Google's internally referenced 'Jitro' project signals a bigger shift - from task execution to outcome-driven development.
more → devops.com, Tuesday, April 7th, 2026
Various security issues do not appear during builds or staging tests. They emerge after deployment, when production traffic begins exercising real permissions, integrations and system states.
more → devops.com, Tuesday, April 7th, 2026
AI-assisted low-code platforms like VibeCode are generating a lot of excitement. They let users describe applications in natural language and produce working code quickly. This speed is impressive, but it raises questions for DevOps teams responsible for stability, security, and reliability.
more → devops.com, Tuesday, April 7th, 2026
A survey of 628 enterprise IT leaders conducted by the Futurum Group finds well over a third (36%) plan on spending more than $1 million on observability in 2026, with 7% planning to spend in excess of $5 million.
more → devops.com, Tuesday, April 7th, 2026
When you ask an AI coding agent how to solve a problem, it reaches for code. That's not just a preference - code is how software teams actually ship and we have an ecosystem of essential tools and management systems: Version control, reviews, tests in CI, deploys and rollbacks.
more → devops.com, Tuesday, April 7th, 2026
Apica today updated its Ascent platform to add support for synthetic data that is increasingly being used by artificial intelligence (AI) agents to observe application environments.
more → devops.com, Monday, April 6th, 2026
The most dangerous assumption in quality engineering right now is that you can validate an autonomous testing agent the same way you validated a deterministic application. For the last decade, we wrote tests that expected input A to always produce output B, and we built entire CI/CD pipelines around that binary logic.
more → devops.com, Thursday, April 2nd, 2026
A survey of 712 IT professionals finds that programming languages and frameworks (49%), followed closely by ​databases and data technologies (46%), DevOps/GitOps/DevSecOps tooling (39%) and cloud and container technologies (38%) are the areas where open source software is most widely adopted.
more → devops.com, Thursday, April 2nd, 2026
AI is no longer a side experiment in software delivery. Gartner estimates that by 2028, three-quarters of enterprise software engineers will use AI code assistants, up from less than 10% in early 2023.
more → devops.com, Thursday, April 2nd, 2026
AI coding assistants can generate pull requests faster than most teams can review them, and that mismatch is creating a new kind of bottleneck across engineering organizations.
more → devops.com, Monday, March 30th, 2026
People are used to digital services operating immediately, across various places, devices and systems. Should something break down, it is usually obvious to those operating the system. The crucial element is how fast companies can recover, and the key metric for digital stability is called mean time to recovery (MTTR).
more → devops.com, Monday, March 30th, 2026
Apache Iceberg has effectively won the open table format conversation. AWS, Google Cloud, Microsoft, Snowflake, Databricks - every major platform has thrown its weight behind it.
more → devops.com, Wednesday, March 25th, 2026
Exponential growth in the adoption of digital businesses has compelled company leaders to look for new ways of developing and operating software.
more → devops.com, Wednesday, March 25th, 2026
Future Proofing the Foundation for AI-Ready Security Operations
more → devops.com, Wednesday, March 25th, 2026
Embedded software development has traditionally followed a different rhythm than mainstream software engineering.
more → devops.com, Wednesday, March 25th, 2026
DevOps has changed fast in the last decade. Scripts became pipelines. Pipelines became platforms. Now, AI agents in DevOps automation are leading the next wave.
more → devops.com, Tuesday, March 24th, 2026
AI didn't sneak into your stack and quietly sabotage a once-pristine DevOps pipeline. That story is comforting, but it's fiction. What's really happening is far less dramatic and a lot more uncomfortable.
more → devops.com, Wednesday, March 18th, 2026
Policy as code is usually framed as a compliance tool. It blocks insecure configurations, enforces internal standards, and helps teams prove they meet audit or regulatory requirements. That framing is accurate, but incomplete.
more → devops.com, Wednesday, March 18th, 2026
Arcjet today added an ability to detect and block risky prompts before they are shared with a large language model (LLM) embedded within an application. The Arcjet AI prompt injection protection capability is based on an LLM that the company has been specifically training to detect patterns indicative of risky prompts that can then be blocked using a runtime policy engine built using WebAssembly (Wasm).
more → devops.com, Monday, March 16th, 2026
When we think about sustainability in software, the conversation often revolves around efficient algorithms, optimized cloud usage, or energy-conscious infrastructure. Rarely do we consider observability, the practice that allows us to understand systems, maintain reliability, and troubleshoot issues, as part of the equation. Yet every metric collected, every log retained, and every dashboard query consumes energy. At scale, this translates into a measurable carbon footprint.
more → DevOps.com, Friday, March 13th, 2026
In the cloud-native ecosystem, velocity is everything. We built Kubernetes, microservices, and CI/CD pipelines to ship faster and more reliably.
more → DevOps.com, Friday, March 13th, 2026
A global survey of 700 software engineering practices published this week finds that thanks to increased reliance on artificial intelligence (AI) coding tools, well over a third (35%) are either achieving daily or more frequent product deployments, with 36% deploying software multiple times per week. However, more than half (51%) also noted AI-generated code leads to deployment problems at least half the time.
more → DevOps.com, Thursday, March 12th, 2026
Most platform teams aren't deciding whether they'll run across multiple clouds. They already are, or they'll be soon. The real question is how to migrate critical systems without turning on-call into a guessing game.
more → DevOps.com, Thursday, March 12th, 2026
If you are of a certain age, you remember the old StarKist commercials. Charlie the Tuna would swim up proudly announcing that he had 'good taste.' The StarKist fisherman would shake his head and deliver the punchline: Sorry, Charlie, StarKist wants tuna that tastes good. Meaning they didn't want tunas with good taste, only ones that tasted good.
more → DevOps.com, Thursday, March 12th, 2026
As AI coding tools accelerate software delivery, they are also intensifying a problem DevOps and SRE teams have been dealing with for years: the unchecked growth of observability data.
more → DevOps.com, Tuesday, March 10th, 2026
An analysis of 2,000 organizations worldwide finds that historically lower performing software engineering teams are seeing nearly a 50% improvement in lead time to delivery, a four times greater rate of improvement over higher performing teams that have adopted AI coding tools.
more → DevOps.com, Monday, March 9th, 2026
For years, most low-code platforms have focused on one primary challenge: efficiency. The goal was to help teams build applications faster and with less effort, reducing manual coding, speeding up iterations, empowering non-developers, and enabling apps to be created in just a few clicks. That focus delivered real value, but it's no longer enough.
more → DevOps.com, Monday, March 9th, 2026
Operations teams have been battling alert fatigue for a very long time now. We saw monitoring systems multiply while cloud-native architectures increased system complexity. Every new microservice, dependency, and API introduced another stream of signals for folks to contend with.
more → DevOps.com, Friday, March 6th, 2026
Following a $50 million funding round, GitGuardian CEO Eric Fourrier discusses why secrets security is becoming a much bigger problem in the age of AI-generated code and autonomous agents.
more → DevOps.com, Thursday, March 5th, 2026
A global survey of 820 IT decision makers and DevOps practitioners finds that half of respondents (53%) report that developers in the age of artificial intelligence (AI) are now authoring more tests directly.
more → DevOps.com, Tuesday, March 3rd, 2026
The transition from experimental AI prototypes to production-grade DevOps agents hinges on one critical discipline that most teams overlook: context engineering.
more → devops.com, Friday, February 27th, 2026
Artificial intelligence has shortened the timeline for software development from months to days. But according to new research, that acceleration is creating significant risks for security and compliance issues.
more → devops.com, Friday, February 27th, 2026
Harness today revealed that it will make available a set of open source tools for testing the resiliency of applications that are based on a chaos engineering platform the company gained with the acquisition of LitmusChaos.
more → devops.com, Thursday, February 26th, 2026
Open Policy Agent (OPA) is a policy engine that streamlines policy management across your stack for improved development, security and audit capability.
more → devops.com, Thursday, February 26th, 2026
Continuous integration and continuous development (CI/CD) pipelines have transformed the practice of delivering software, resulting in higher quality and faster results. This is the way in which the infrastructure that supports CI/CD enables teams to shift left many test and verification tasks.
more → devops.com, Thursday, February 26th, 2026
Researchers from Georgia Tech have found that the supply chain for threat intelligence data is susceptible to adversarial action, and proposed a method to improve data sharing that they think will make it stronger.
more → devops.com, Wednesday, February 25th, 2026
On Monday, Anthropic published a blog post about using Claude Code to modernize COBOL. IBM's stock dropped 13% - its worst single-day loss since October 2000. Bloomberg reported the decline put IBM on track for a 27% drop in February, its worst monthly slide since at least 1968.
more → devops.com, Wednesday, February 25th, 2026
Software engineering leaders have invested heavily in generative AI coding assistants for over two years-and for good reason. For many teams, the productivity gains appear significant. I hear the same story in conversations with leadership at dozens of enterprises: thanks to AI, developers complete tasks faster, write more code, and spend less time on boilerplate activities.
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