Operations | Monitoring | ITSM | DevOps | Cloud

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.

An employee's notice period is the highest-risk window for data theft. How to detect and stop SharePoint and Microsoft 365 data exfiltration by departing staff in 2026.

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.

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.

How many times should your service desk solve the same problem before it becomes shared knowledge? A senior agent on a 14-person service desk we worked with last quarter had answered the same question four times in two days for four different employees. The solution was already documented but buried in a wiki nobody could find. That is exactly the gap ITSM knowledge management is designed to close.