What does your model evaluation pipeline actually look like in production?
Offline evals, golden sets, LLM-as-judge, human review: what are you running before a model or prompt change ships, and what has caught real regressions?
In short
CI/CD covers the pipelines that build, test and deploy software automatically whenever code changes, and GitOps extends the idea by treating a Git repository as the record of what should be running. For buyers, pipeline speed, the security of the build itself, the cost of build minutes and how hard it would be to move pipelines elsewhere are the deciding factors.
Written by Techarda editors · Updated · How we work
The newest CI/CD and GitOps stories from the last 90 days. Each one opens with our summary and a link to the original source.
We are announcing a new logging feature that is now available in Python User-Defined Function (UDF) in BigQuery. Developers can now use Python’s standard logging library directly inside BigQuery UDFs to emit structured logs seamlessly into Cloud Logging, with zero external plugins or custom connectors required. While UDF logging enables a wide range of operational monitoring and debugging…
Snowflake's data team built an AI agent that diagnoses monitored pipeline failure and opens a proposed fix in under 16 minutes. Here's how.
When trusted packages are compromised, malicious code can quickly spread throughout and beyond developer environments. See how Wiz’s supply chain pipeline identifies compromised packages at publication, helping teams detect zero-day supply chain compromises in Wiz Defend before a CVE is published
Wiz CIRT responded to AI-driven attacks spanning cloud, Kubernetes, CI/CD, and identity. Learn how these attacks behave and how to detect them.
If you're a platform engineer, you've likely lived this: your team has assembled a toolchain for CI/CD, monitoring, security scanning, GitOps, and networking. Each tool does its specific job well, but over time, you realize you’re spending more hours maintaining the integrations between those tools than helping developers ship code. That's the real cost of tool sprawl. Yes, it’s increased…
You already have an AI assistant. It completes your code, explains code you didn’t write, and maybe even drafts a whole feature while you sip your coffee. An agent on GitLab picks up where your editor stops. The AI in your editor only knows what's open in your editor. It doesn't know that your merge request has been sitting in the queue for two days, or that your pipeline failed for the third…
AI-assisted coding is changing CI pipelines. Learn how Harness CI uses Cache, Build and Test Intelligence to reduce redundant work and speed up builds. | Blog
Overview On October 12, 2026, GitLab released 19.4.2 , 19.3.5 , and 19.2.8 to fix CVE-2026-97229 , an integer overflow in its CI/CD regular-expression handling. The issue was reported through HackerOne by joaxcar . GitLab assigned it a CVSS score of 10.0 and described possible code execution by an unauthenticated user. The advisory states that CVE-2026-97229 affects GitLab CE and EE from 19.2…
Showing the newest 60 of 122. The feed archive lists every story by month.
Stories say what companies announced. These threads are where people who work with CI/CD and GitOps compare notes.
Offline evals, golden sets, LLM-as-judge, human review: what are you running before a model or prompt change ships, and what has caught real regressions?
Sampling, tiered retention, OpenTelemetry pipelines, switching vendors? What cut the bill the most?
The active companies with the most CI/CD and GitOps stories in the last 90 days. It counts news coverage, not quality, market share or fit for your needs.
Where CI/CD and GitOps sits among the categories Techarda covers. Each hub shows who is active, and each guide sets out how to evaluate vendors.
Plain definitions of terms that come up in CI/CD and GitOps stories, from the Techarda glossary.
With continuous delivery every change is ready to release and a person decides when. With continuous deployment every change that passes the pipeline goes to production automatically.
An approach where the desired state of systems is declared in a Git repository and an agent keeps the running environment in line with it. Changes go through reviewed commits, which gives an audit trail and a simple rollback.
Pipelines hold credentials and can change production, so an attacker who compromises one can ship malicious code under your name. Short-lived credentials, signed build artefacts and locked-down build runners reduce that risk.
Stories are filed under topics automatically from their headline and summary, so the odd one may sit in the wrong place. Spotted one, or a topic we should add? Email engage@techarda.com. All topics.