TL;DR — Key Takeaways Testing alone does not prove a release is production-ready. Business-critical systems also need data integrity, reconciliation, exception handling and operational approval. Production validation creates a formal release gate, ensuring issues, dependencies, evidence and sign-offs are resolved before deployment. The strongest model combines automation with business judgment, using repeatable workflows, documentation and targeted manual review for high-risk releases. In an enterprise environment, production failures are more often defined as testing failures, but they include other high-impact aspects, such as release readiness, data quality, exception handling and operational approval. However, the missing layer is not just about conducting…
Author: drweb
TL;DR — Key Takeaways Harness launched an agent-ready code repository and AI code review service designed to handle the higher volume of commits and pull requests generated by AI coding agents. The repository is built to support thousands of simultaneous pull requests and commits while maintaining search, history and diff performance across large repositories. DevOps teams can assign AI agents specific permissions, apply RBAC and OPA-based policies, and track agent activity separately from human developers. Harness today launched a code repository service that is specifically designed for DevOps teams that are relying on artificial intelligence (AI) agents to generate code.Martin…
AI coding agents are becoming part of everyday development work. Developers use them to find libraries, configure projects, troubleshoot installation problems, and set up new tools. An agent can search GitHub, read project documentation, and run commands without the developer having to work through every step manually.That convenience is creating another security concern for DevOps teams. An agent can encounter software and instructions during a task, decide that they are relevant, and act on them. A repository, README file or configuration file can therefore become part of the execution path.Recent attacks have shown how this can be abused. Malicious repositories…
I let AI recommend SQL Server indexes across a week of queries, measured every number before and after, and the result was not the one I expected to write about.I expected a comedy. I have read enough confident nonsense from chatbots about SQL Server to assume I would end up with a post full of terrible indexes and easy jokes.That is not what happened, and the actual answer is more useful.AI never connected to SQL Server or executed anything. I gave a general-purpose chat model one query at a time, manually reviewed its suggestions, and applied the candidates in a disposable…
How I used AI for this postChatGPT to generate images based on info specifically provided by me,including examples.Grammarly to catch grammar and sentence construction errors.I did a presentation on Vector Economics at EightKB, a popular SQL Server Internals conference, recently. The talk was well received. Among the follow up suggestions, one was about doing a blog series on DiskANN Algorithm – the algorithm created by Microsoft Research, documented here, and is used for vector index on SQL Server Vector Search.DiskANN is meant to help with searching a billion-vector dataset from a single machine using SSDs.Microsoft Research’s original work demonstrated a…
TL;DR — Key Takeaways Sonar launched SonarQube Hunter Agent to identify broken access control, business-logic vulnerabilities, and authentication or session-management issues across entire codebases. The AI agent traces how code and data move through an application, helping uncover flaws that traditional deterministic scanners may miss. Sonar says the tool can run investigations on demand and surface verified issues directly within DevSecOps workflows through CI/CD integrations. Sonar today made available an artificial intelligence (AI) agent designed to discover vulnerabilities and business logic flaws that pose the greatest risk to an organization should they be exploited.The SonarQube Hunter Agent first analyzes an…
Most people run dmesg once, see thousands of lines, and close the terminal. But that’s not really how you should use it. dmesg is one of the fastest diagnostic tools on Linux, and with the right options, you can quickly narrow down the exact information you need. The dmesg command reads the kernel ring buffer; a circular log where the Linux kernel records messages from the time the system boots. When the kernel detects hardware, loads a driver, recognizes a USB device, or encounters a disk or hardware-related error, those messages are typically written to this buffer. That makes dmesg…
Most people treat dnf as a drop-in replacement for yum and stop there. But that misses a lot of what makes DNF worth learning; automatic dependency resolution, transaction history with full undo support, module streams, and a plugin system that goes beyond what yum offered. DNF (Dandified YUM) has been the default package manager on Fedora since Fedora 22 (2015) and on RHEL since RHEL 8 (2019). It is used across RHEL 8/9/10, Rocky Linux, AlmaLinux, CentOS Stream, and Fedora. If you’re still typing yum on any of these systems, it is usually linked or aliased to DNF anyway. One…
TL;DR — Key Takeaways Confidence is not change control. Policy must be revalidated immediately before consequential actions. Idempotency prevents duplicate side effects when an agent workflow retries or resumes after an ambiguous failure. High-risk actions need stronger gates, combining approval, current policy, one controlled transmission and receipt verification. An AI agent that can call tools is not automatically an unsafe system. The dangerous move is smaller: Letting a workflow turn a recommendation into an external action without a durable decision record.That distinction matters in DevOps. An agent can sensibly summarize a failed deployment, draft a rollback plan or classify a…
Codex CLI is OpenAI’s coding agent that runs in your terminal, reads your files, and executes shell commands on your machine. In this guide, you’ll learn how to install it using curl or npm, sign in from a headless server, and configure sandbox modes before letting it work with anything important. It’s easy to install an AI agent, run it with all the guardrails turned off, and only check the sandbox settings after it has changed a configuration file you needed. Codex provides three sandbox levels along with a separate approval policy. The combination you choose determines what it can…