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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

A New Console for Qovery

We rebuilt large parts of the Qovery Console: new navigation, overviews at every level, dark mode, and a modernized frontend architecture with TanStack Router and React Suspense. Rémi is a staff frontend engineer at Qovery. He writes about frontend architecture, developer experience, and building scalable UI systems for platform engineering tools. Théo is a senior product designer at Qovery.

The alerts worth your time. Resolved faster

It's 7am. An alert fired overnight. You open your monitoring solution, navigate to the alert, cross-reference the waits, check the query plans. Twenty minutes later: it should not have fired. You knew that before you started, but you had to check anyways. The feeling of being overwhelmed by alerts is real. And so is the cost. Thresholds set once and forgotten, firing on patterns that have been normal for months. The inbox fills. DBAs learn to ignore most alerts. The workaround becomes the workflow.

Why database governance in financial services is falling behind where it matters most

If anyone knows how to operate under scrutiny, it’s database teams within finance organizations. It’s a given considering the more rigorous compliance requirements and processes they must follow. But the 2026 State of the Database Landscape: Finance Edition reveals something more specific, and more uncomfortable, than the familiar story of regulatory pressure.

AI Found 18 OpenSSL Vulnerabilities. Now Your Team Has to Patch Them.

On June 9, 2026, the OpenSSL project released patches covering 18 vulnerabilities across its supported releases. The headline flaw, CVE-2026-45447, is rated high severity and has the potential for remote code execution. Not too long ago, a security advisory with 18 vulnerabilities would have been routine. Microsoft’s Patch Tuesday provided a predictable cycle, and organizations operated with the expectation of a meaningful remediation window. That model is under pressure.

dbForge: AI-Powered Multi-Database Tools for SQL Development & Management

dbForge is an AI-powered multi-database ecosystem for SQL development, database design, data management, testing, administration, reporting, and automation. In this video, you will see how dbForge helps database developers, DBAs, and technical teams reduce tool switching and work across SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, cloud databases, and on-premises environments from one connected ecosystem.

dbForge - AI-Powered Database Ecosystem for Developers & DBAs

Managing different databases, tools, and environments can slow down your workflow… but dbForge brings everything together. Work with SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, and cloud databases Use AI to generate, explain, fix, and optimize SQL queries Design, develop, test, manage, and automate databases Choose from dbForge Edge, dedicated Studios, standalone tools, and SSMS/Visual Studio add-ins.

PagerDuty Report Finds Two-Thirds (66%) of Office Professionals Have Used Unauthorized AI Tools at Work

Three-quarters of office professionals (75%) say they would be likely to look for a new job that offered better AI skills development, a figure that climbs to 80% at companies with $1 billion or more in revenue.

The Next Evolution of Infrastructure Observability

Operational visibility is becoming increasingly important as infrastructure teams are asked to support AI initiatives, automation goals, cost accountability, modernization efforts, and growing operational complexity at the same time. Most are expected to do it without expanding headcount, introducing additional risk, or rebuilding the environment from scratch. Those expectations are changing the role of infrastructure operations.

Tokenmaxxing: The AI Productivity Lie

Your best engineer spent 500,000 tokens last week. Nothing shipped. There's a name for it now: tokenmaxxing. Failed prompts, dead PRs, code that never reaches production — it looks like productivity, but it isn't. Most engineering leaders can't tell you what percentage of AI-generated code actually ships, or where the budget went. You should be able to say "that bug cost me $2,700 in tokens to fix.".