GitLab stories
Banks risk repeating DevOps sprawl as DIY agentic AI pushes build costs above USD $1.4 million and delays production by up to 18 months.
Without stronger operational foundations, Asia Pacific firms risk turning new security tools into costly bottlenecks instead of productivity gains.
Mounting scrutiny over AI budgets is pushing software teams to prove whether the tools speed delivery enough to justify their cost.
Enterprises can now patch older open source software without disruptive upgrades, as IBM and Red Hat target stubborn vulnerability backlogs.
The designation underlines rising demand for cyber recovery and AI-era data protection as enterprises shift from backup alone to broader resilience.
The Serbian startup will use the cash to expand an open-source control plane that lets engineers supervise AI-driven production workflows safely.
Most organisations now use multiple AI coding tools, but many still cannot reliably trace, review or govern the code once it reaches production.
Regulators may soon demand proof of who did what as AI agents start opening merge requests in heavily audited development pipelines.
Enterprises could cut agent coding costs and compliance risks as the new releases add server-side repository access, audit tools and spend controls.
Regulated firms can now run GitLab's DevSecOps platform on Google Cloud with partner management, tighter data residency controls and new Gemini models.
Pressure to curb AI costs and improve returns is pushing Asia Pacific organisations towards multi-model deployment strategies across the software lifecycle.
Security teams can now apply the same rules to AI-generated code across development and deployment, as Salt broadens its platform to curb flaws earlier.
More than half of patched flaws in major DevOps tools were high or critical in 2025, putting software supply chains at greater risk.
The release gives security teams and developers new controls for credentials, merge requests and supply chain oversight as AI use grows.
The hire deepens BriefCatch's push into legal AI as firms demand tools that reduce citation errors and guard against hallucinations.
The new tools could let merchants sell inside AI apps and bill for token use in real time, while tightening fraud checks.
The release aims to curb a growing security risk as enterprises let autonomous agents into internal apps with broad human-style access.
Tech and software groups are most at risk as breaches, supplier access and stale credentials let attackers reach source code and customer data.
Software teams could catch regressions before release as the new verifier checks pull requests against live production behaviour inside existing workflow tools.
A free account could have let attackers alter Zapier-maintained packages and hijack logged-in users' browser sessions, researchers said.