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qovery

Base44 vs Lovable: Which AI App Builder Should You Use in 2026?

Jun 23, 2026 By Mélanie Dallé In Qovery
Base44 vs Lovable compared: features, backend, pricing, popularity, and which AI app builder fits your use case - plus how to take either prototype to production on infrastructure you control. Melanie leads content at Qovery. She covers platform engineering trends, Kubernetes operations, FinOps, and the tools that help engineering teams ship faster.
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cortex

What is an AI software factory?

Jun 23, 2026 By Ganesh Datta In Cortex
Ask a software engineer what they do and the answer, for years, has been some version of "I write code." That assumption is unwinding fast. AI agents can now write code, review pull requests, run tests, and ship to production, and they're taking on a fast-growing share of that work. As agents absorb more of the execution, the human role shifts.
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coroot

Observability on Windows, before eBPF is production-ready

Jun 23, 2026 By Nikolay Sivko In Coroot
No large enterprise runs a single stack. A shiny new Kubernetes cluster sits right next to a Windows Server box that has quietly run the billing system for a decade without missing a beat. Both keep the business running. Both deserve the same visibility. Linux runs most server workloads, and Coroot grew up there. Our open-source node-agent uses eBPF to collect metrics, logs, traces, and profiles, with no code changes. But "most" is not "all".
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Inside the Buyer's Decision: Governance, Trust, and Production-Ready Agentic AI

Jun 23, 2026 By Resolve In Resolve
Why do so many AI pilots succeed in testing but fail to reach production? In this webinar, Resolve and IT leaders from RisePoint explore one of the biggest challenges facing enterprise AI adoption today: trust. While organizations are investing heavily in AI agents and automation, many initiatives stall before deployment due to governance concerns, compliance requirements, risk management, and lack of operational visibility.
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Stop Token Maxing The Future of Al Budget Management

Jun 23, 2026 By Harness In Harness
The era of token maxing is over. When Claude Fable 5 launched last week at $10/$50 per million tokens - double the price of Opus 4.8 - it was a clear reminder that the most powerful model isn't always the right model. Not every task needs the Ferrari. The fastest way to burn your Al budget is sending every request to the most expensive model by default. The real question for the next phase of Al cost management isn't "can this model do the job?" — it's "is it the right model for the job?".
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ScienceLogic

How High-Performance IT Organizations Prevent SLA Exposure Before It Becomes a Customer Disruption

Jun 23, 2026 By ScienceLogic In ScienceLogic
Over the past decade, significant progress has been made in incident detection and response across enterprise IT environments. Observability platforms, event correlation engines, and AIOps capabilities have measurably reduced mean time to detection and mean time to resolution. Operational teams are better equipped to identify anomalies, triage alerts, and coordinate remediation across increasingly complex architectures.
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jfrog

Stop Treating Coding Agent Plugins Like Settings: Introducing Agent Plugins Repositories

Jun 23, 2026 By Adam Browning In JFrog
Your developers install agent plugins every day: pulling from unmanaged GitHub repos, copying Cursor commands out of Slack, pointing Codex at a personal Git fork. Each of those is a new, uncontrolled distribution channel inside your software development lifecycle, and your platform team has zero visibility into any of it. A plugin is not a preference file. It is executable software, and right now it’s arriving on developer machines with no versioning, no provenance, and no audit trail.
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datadog

How to migrate feature flags without breaking production

Jun 23, 2026 By Anthony Rindone In Datadog
Feature flag migrations have a reputation problem. Ask anybody who’s been through one before and you’ll hear the stories, usually from someone still a little frustrated about a bad cutover, with a postmortem or two to show for it. The reputation is mostly undeserved. While the risks are real, they’re well understood and easily controlled. Getting a migration right doesn’t require a big coordinated effort.
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