Operations | Monitoring | ITSM | DevOps | Cloud

By the time an IoT device shows up in an incident review, it has usually already done its damage. Not the dashboard-gap kind. These devices are load bearing. They sit in the control path of substations, haul trucks, pump stations and cold rooms, so when they go blind the blast radius gets measured in tripped relays, spoiled stock, and unplanned outages rather than in missing datapoints.

Tracing is one of the richest observability signals, but it's also noisy and susceptible to data bloat. In a busy system, the vast majority of traces describe the same healthy, fast, successful request over and over, so most organizations downsample their traces to cut costs. But that approach has consequences, since the sampling strategy you choose determines whether you get a faithful picture of your whole system, or just a smaller, blurrier copy of your busiest endpoints.

A customer reports that checkout failed twice before they gave up, then stops replying to the support thread. What do you actually have to work with? A timestamp, a browser string, and a description written by someone who was not looking at the console. Session replay answers the question that ticket cannot. It rebuilds that single visit in the browser and plays it back step by step, so the click that failed, the field that rejected input, and the script error that fired alongside it appear in sequence.

How many privacy requests is your organization working on right now, and how many of them are still inside their legal deadline? The answer usually lives in several places at once. Shared mailboxes hold some, web forms hold others, and legal keeps a tracker of its own. That scattering is the problem. A CCPA request carries a hard statutory deadline and a documentation duty behind it, yet privacy work is the one regulated workload in most organizations that never entered the service management system.

You may be familiar with web card skimming, where a fraudster replaces the payment iframe on an ecommerce site with a fake version designed to intercept payment details or divert a transaction. However, there’s another variation that, while not new, is something we encounter far less often. It was highlighted this week during a call from an ecommerce vendor: redirection fraud. In this scenario, the attack starts much earlier in the customer journey.

Summary A new async Rust client for InfluxDB. Built for the edge gateways, embedded systems, and high-throughput ingest pipelines where Rust already runs. Table of Contents Time series data shows up wherever the physical world meets software. A satellite constellation streams altitude, power, and thermal telemetry from every spacecraft on every pass. A factory floor running on Industry 4.0 principles instruments every line, every motor, every batch.

AI agents are only as effective as the context they can access. The problem is that most of that context lives outside your observability platform.

Most companies will tell you they’re customer-obsessed. Fewer can point to the actual mechanism. At GitKraken, it isn’t a quarterly survey or a roadmap council. It’s a Slack channel where developers vent about their Git workflow, and the desktop team is already in there reading it.

Visualize branches and commits, manage parallel work and agents, and run your entire Git workflow from one view. AI changed how code gets written. It also changed what developers spend their time doing. Today, developers are reviewing AI-generated changes, coordinating parallel work across branches and worktrees, cleaning up commit history, resolving conflicts, and getting everything ready to merge.

CFEngine 3.29.0 changes how storage promises treat a filesystem that is already mounted. A promise for an unmounted filesystem now mounts only that filesystem instead of all unmounted filesystems, edit_fstab actively maintains the file system table entry to keep it aligned with the promise even when the filesystem is already mounted, and an unmount promise acts only on the explicitly promised filesystem.