Operations | Monitoring | ITSM | DevOps | Cloud

Top tips is a weekly column where we highlight what’s trending in the tech world and share ways to stay ahead. This week, let's look at a few ways you can become an essentialist at work. It's easy to fill up our calendar with tasks that may not be impactful, but we end up feeling falsely accomplished. This happens to us more often than we realize, and the antidote to this is to be an essentialist.

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.

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.

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.

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.

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.

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.

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.

Modern infrastructure teams are expected to deliver cloud-like speed, consistency, and reliability, even when their workloads run on physical servers. Bare metal remains essential for many environments: private clouds, Kubernetes clusters, AI infrastructure, edge sites, regulated platforms, and large Ubuntu estates. But operating physical infrastructure at scale is difficult when provisioning, patching, monitoring, and lifecycle management are handled by disconnected tools and manual processes.

This is a follow-up to Sergiy’s post Errors, traces, logs, metrics: when to reach for what. Modern observability platforms, like Sentry, give developers a lot of choice. For a given problem, should you use traces, profiles, metrics, logs? If you take away one thing from this post, I hope it’s this: when in doubt, start by adding a few targeted log lines.