Operations | Monitoring | ITSM | DevOps | Cloud

Routine vulnerability fixes are rarely difficult in isolation. The interruption that they cause is the problem: pick up the ticket, trace the dependency, update the package or image, regenerate files, run the checks, open the pull request, then return after deployment to close the loop. That repeated handoff was a good candidate for automation with agentic pipelines. The goal was simple: start the day with a tested pull request instead of another ticket to pick up.

Giordano “Gyo” Piazza, GitKraken’s Director of Engineering, has spent the past month heads down on the next version of Kepler. When he got on a call to talk through it, he skipped the changelog and went straight to the part he actually wanted to talk about: how agents show their work.

Database monitoring is the continuous tracking of a database's health, performance, and resource consumption, covering metrics like query latency, throughput, connections, and replication lag. In the AI era, it has expanded to include a fifth dimension: spend. Modern teams monitor not just whether the database is fast, but whether the workload it serves is worth what it costs to run. In May 2025, an engineer named Bohan Zhang stood up at PGConf.dev in Montreal and broke every scaling rule in the book.

Codex is OpenAI's terminal-based autonomous coding agent, bundled into ChatGPT plans and billed through token-based credits. Claude Code is Anthropic's terminal-based coding agent, sold through Claude subscriptions or the API. Codex is cheaper to enter; Claude Code is stronger on complex work. Both run $100 to $250 per developer monthly at active use.

Black Hat USA 2026 brought more than 20,000 people to Mandalay Bay in Las Vegas. We were there as a Platinum sponsor at booth 4208, and across two days on the business hall floor we had more than 750 conversations with security engineers and architects. Almost every one of them, whatever it started as, turned into a version of the same question: how do I know? How do I know whether a vendor's AI does what the banner says? How do I know what my agents are doing on the network?

TLDR: “Preview” isn’t a lightweight version of GA, and it isn’t a beta with a new name on it. It just changes the timing and access. You’ll see new JFrog capabilities the day they’re ready for real use, not the day they’re ready for a press release. We’re starting at swampUP 2026. As we know, AI has changed the speed of software development and delivery. Work that used to take three months now takes weeks.

AI is already good at writing SQL, which is why people keep asking whether AI agents will replace database IDEs. But letting an agent work on a production database is still a much bigger leap. In tests reported by BIRD, a text-to-SQL benchmark built from 95 real databases across 37 professional domains, human experts reached 92.96% execution accuracy. The best single-model entry reached 80.04% in June 2026. The model failed roughly one task in five; the humans, about one in fourteen.