Systems need to be failure proof
The best advice from Anish Behanan at @Capgemini about reliability? Every system needs to be failure proof.
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New Devart Python Connectors Add Broader Compatibility and Stronger Security
We are thrilled to announce a major update to our Python Connectors line. The release adds support for Python 3.14, PostgreSQL 18, MySQL 9, and MariaDB 12, introduces modern authentication and security options, and delivers notable performance gains across several connectors.
How IT teams can finally break free from manual AD management
If there’s one thing every IT leader can agree on, it’s this: Manual Active Directory (AD) management never ends. There’s always one more access request, one more approval chain, and one more audit reminder flashing on your screen. By the time you’ve closed your last ticket of the day, there’s already another one waiting. For many teams, 2025 became the year of “we’ll automate next quarter.” But next quarter came and went without any automation.
OTel Updates: Declarative Config - A Steadier Way to Configure OpenTelemetry SDKs
Application configs change over time, often in small ways that are easy to miss. They may start simple — a few environment variables, one exporter, nothing unexpected. As your instrumentation grows, you add rules for filtering health check spans, adjust sampling based on attributes, or introduce environment-specific resource settings. Each change makes sense on its own. But months later, the picture can look different across dev, staging, and production.
Managing Alerts: Car Alarms and Smoke Alarms
Building and shipping an application is exciting, you watch your idea come alive and reach users. But once it’s out there, your real job begins: keeping it alive. An app in production isn’t just code running, it’s a living system. It needs monitoring to stay healthy and alerting to warn when something’s off. But there’s a catch: too few alerts, and you’ll miss real issues; too many, and you’ll drown in noise.
The Outage Anxiety Test: Can You Answer These 3 Questions In Under 10 Minutes?
On Oct. 20, the Internet woke up and seemingly chose violence. For more than 12 hours, Amazon Web Services (AWS) went down. From banking platforms to hospital communications to mobile ordering apps, digital services came to a screeching halt. The cause? Two programs are trying to write a DNS entry simultaneously, failing, and leaving the entry blank. Thus began the incredibly costly failure cascade.
AI And Sustainability: Measuring The Impact Of The Generative AI Boom
Before 2022, Alex Hanna worked on Google’s Ethical AI team. Today, she’s the director of research at the Distributed AI Research Institute, a transition sparked by Google’s handling of a paper exposing AI’s growing environmental footprint. So, how bad is it, really? That depends on who you ask. Take Jesse Dodge, a senior research analyst at the Allen Institute for AI. Jesse told NPR that a single ChatGPT query can use as much electricity as keeping a light bulb on for 20 minutes.
Rovo AI: Create Work Items from Loom | Demo Den | Atlassian
Ever wish you could turn a quick Loom recording into Jira work items without all the manual typing? Now you can! In this Demo Den episode, Pierre walks through a new Rovo AI feature that automatically converts your Loom videos into actionable Jira work items. Whether you're recording bug reports, feature requests, or project updates, Rovo handles the data entry for you. What Pierre covers: Turning Loom videos into work items with Rovo How it works in your AI-enabled Jira instance.
Why AI Coding Assistants Fail (And How to Fix Them)
Why do developers stop using AI coding assistants? According to Carnegie Mellon research, the top reason is unhelpful suggestions. Tabnine's Principal Architect John Feeney explains how context transforms AI coding tools from generic to genuinely useful. Learn the 4 Cs framework for maximizing AI assistant value: Context (workspace indexing), Connection (repo integration), Coaching (rules-based guidance), and Customization (fine-tuning). Discover how Retrieval Augmented Generation (RAG) helps AI understand your codebase, not just open source patterns.
Building dbRosetta Using AI: Part 1 of Many
Like many of you, over the last couple of years, I’ve been using AI, or, well, let’s just name it appropriately, Large Language Models (LLM), as a part of my job. I’ve also used it in my hobby. With it, I’ve generated snippets of code, tested data conversions, even built a small database for a presentation. However, to date, I haven’t tried doing everything through the LLM. Now, I’m going to.