Operations | Monitoring | ITSM | DevOps | Cloud

An escalation protocol is the written rule set that says when an incident moves from the person holding it to the next level, who that next level is, how they get contacted and how long they have to respond. It sits underneath the escalation policy (the why) and above the contact matrix (the who), and it is the document the on-call engineer actually reads at 3 AM.

We’ve made a small but useful update to our Digital Signage integrations in StatusGator. You can now configure Allowed IP addresses for your digital signage integrations. This lets you restrict access to specific public IP addresses – for example, the network used by screens in your office, operations center, or other shared space. Simply add one or more IP addresses when configuring the integration, and StatusGator will limit access accordingly.

We are thrilled to announce an update to our Excel Add-ins, bringing expanded support for popular cloud services and databases. The release introduces new objects, fields, API capabilities, and authentication options for BigCommerce, FreshBooks, HubSpot, NetSuite, QuickBooks Online, Zoho CRM, Oracle, MySQL, and PostgreSQL.

SAP customers are navigating a period of significant change. Of course, there’s the transition to Cloud ERP and the scheduled end of standard support options for ECC in 2027 – these are well known. Basis professionals will be familiar with changes in support for Solution Manager and its components including monitoring and change management. Landscape Management has been formally discontinued after 2027. The natural assumption is Cloud ALM fills the gap.

Once you've published more than a handful of KPIs, you eventually need a way to summarize them. A total cost. An overall health status. An organization-wide SLA. Something that lets you answer the big questions without opening ten different dashboards. Summarizing those into a handful of KPIs usually feels straightforward. You add things together, average them, or collapse several statuses into one. The dashboard becomes easier to read, and nothing looks obviously wrong.

Most companies buy AI tools for developers and hope the impact shows up somewhere. A faster sprint. Fewer escaped bugs. Something. What they don’t have is a way to actually see it happening, which means adoption becomes a leap of faith instead of a measured bet. That’s the gap Kepler and GitKraken Insights close together, and it’s worth understanding as one story, not two separate product updates.

Someone on your team says "the Internet is slow." Twenty minutes later, IT finds out the Internet was never the problem. Maybe it was a laptop with a full RAM disk. Maybe it was an ISP outage two towns over that had nothing to do with your office. Misdiagnosing slow Internet wastes time. It sends you down the wrong fix path, like rebooting a router when the real issue is sitting on someone's desktop.

Effective incident response depends on having all of the context surrounding what’s happening. You have to understand your systems, services, architecture, and teams deeply enough to correctly interpret whatever alert just fired. Too often, that context doesn’t arrive packaged neatly in one place. Gathering and interpreting context correctly under time pressure is one of the most difficult parts of the job.

When our company pushed everyone to start using AI tools, I thought about what it would mean for my team. As a remote company, we are already challenged by the lack of organic human connection. Every connection is planned and takes effort, and now, AI adds another layer. People now spend part of their day collaborating with a tool rather than with a person, which can take away from the time we spend learning from each other.

AI is expensive because the model bill is only part of the cost. Three components set the floor: model subscriptions, per-token API pricing, and infrastructure. Three more make it move: adapting models to your business, catching and fixing errors, and rising energy and datacenter costs. Efficiency doesn't fix it, because cheaper AI gets used more, not less. Businesses are willing to spend on AI. Research from Deloitte found that in 2025, 85% of organizations increased their AI investments.