Operations | Monitoring | ITSM | DevOps | Cloud

AI writes code in seconds, but delivery still takes days

The pitch for AI coding was speed. Claude Code, Copilot, Cursor, whatever you’re running, they all generate business logic faster than you can review it. That part is real. But look at what happens after the code gets written and the numbers get ugly. CircleCI’s 2026 State of Software Delivery Report found AI drove a 59% increase in average throughput.

PostgreSQL 19 Release: New Features, Release Date, and Upgrade Notes

With PostgreSQL 19 on the horizon, query planning could get smarter thanks to new query tools and faster maintenance. The release is still a few months away, but Beta 1 already shows where PostgreSQL is headed. Released on June 4, 2026, PostgreSQL 19 Beta 1 previews most of what’s planned for the final release.

Top Security Data Pipeline Platforms in 2026: The Comprehensive Guide

The security data pipeline platform has become the most strategically important layer in the modern SOC, and in the last twelve months, the largest security vendors have paid to own it. CrowdStrike acquired Onum for $290 million, SentinelOne acquired Observo AI for $225 million, and Palo Alto Networks acquired Chronosphere for $3.35 billion. The layer that sits between your data sources and your security tools now decides what every downstream tool receives, at what cost, and in what shape.

Claude Code Monitoring at Scale: Gateways and Routing With OpenTelemetry

Chelsea and I recently wrote a guide on how we monitor Claude Code usage internally with Bindplane. TLDR; We remotely manage a Bindplane Distribution of the OpenTelemetry Collector (BDOT) that runs on every engineer's laptop. This setup is great, but it has one downside. Sending to Google Cloud Monitoring, Swarmia, and any other destination directly from an engineer’s laptop is limited to local processing. You can’t get the benefit of centralized routing and processing on a gateway.

Boost Is Now In Public Preview

Today, we’re excited to announce that Boost is moving out of beta and into public preview. After months of building, breaking, and rebuilding inside JFrog’s own R&D organization, Boost is ready for the world. If you are currently running into token limits, unpredictable costs, or runaway usage from AI agents, Boost was built for you. It has already helped our teams reduce token spend while maintaining performance.

5 AT&T Email-to-Text Alternatives to Improve MTTR in 2026

On June 17, 2025, AT&T permanently shut down its email-to-text and text-to-email gateway. Emails sent to @txt.att.net and @mms.att.net stopped reaching phones, and any automated workflow that relied on that address went dark overnight (AT&T support) . For IT Ops, MSPs, facilities and energy ops and incident response teams, this was not a minor inconvenience.

Business intelligence plugins for Grafana: A support update

In January, we announced that Grafana Labs had assumed maintenance of the business intelligence (BI) plugins created by Volkov Labs, and committed to a six-month maintenance period. Today, we’re sharing an update: we're extending our maintenance commitment through the end of 2026. As announced earlier this year, that commitment includes maintaining compatibility with recent Grafana releases while handling bug fixes, security updates, and community contributions on a best-effort basis.

What I got wrong about ClickHouse as a Kafka Person

Kafka is brilliant at moving events around, but sooner or later someone wants to actually query those events, perhaps aggregations, dashboards, or ad-hoc analytics over billions of rows. That is where ClickHouse comes in. It's the option for when stream processing is more than you need, but warehouse query latency is more than you'll tolerate.

Building AI SRE Agents, Part 1: Start Local, Break Things, Learn Fast

The first stage of AI SRE maturity is a laptop, a throwaway cluster, and zero production access. Here’s how to set it up, and what to watch for. AI SRE (Site Reliability Engineering) agents are AI-powered systems that automate the most time-consuming parts of incident response: triaging alerts, correlating logs and metrics, generating root-cause hypotheses, and proposing remediation steps.