Operations | Monitoring | ITSM | DevOps | Cloud

If you are leading technology strategy today, you face consequential choices about how to manage your enterprise telemetry. Your decisions determine not only where logs, metrics, traces, and events are stored, but also who controls how operational data is collected, shaped, governed, and put to work in an optimal way for the security, observability, analytics, and AI systems that power your business.

Like many modern software stacks, the incident.io platform is predominantly event-driven. For example, whenever you send us an alert, post a message to our agent on Slack, or update an entry in your Catalog - these are all events that then get enqueued on a message topic, meaning any of our downstream components that are interested in that event can subscribe and react asynchronously, such as sending a push notification or posting a reply to you in Slack.

When Nicole Forsgren, Margaret-Anne Storey, and their coauthors published "The SPACE of Developer Productivity" in 2021, they settled an argument the industry had been losing for years. Productivity is not one number, and it is not a proxy like commits or story points. It is multidimensional, and any attempt to flatten it into a single metric will mislead you. Most of what came after in developer productivity measurement builds on SPACE. SPACE and DRIVE were built for different jobs.

Leadership has stopped asking whether your team is using AI. They’re asking what you’re delivering with it. That’s a harder question, because most of the numbers teams have been reporting, adoption rate, seats activated, prompts run, don’t actually answer it.

For beverage companies, deploying a cooler at a retailer, restaurant, supermarket, or distributor is only the beginning of the asset lifecycle. Once coolers move outside company facilities, maintaining visibility becomes far more difficult. Operations teams need to know where each cooler is located, who is responsible for it, whether it has been transferred, if maintenance is required, and whether the equipment is being used effectively.

Here's a scene playing out in engineering teams right now. An engineer spends the weekend running four or five coding agents in parallel. Monday morning, a teammate opens their laptop to 53 changed files with 2000+ diffs and a message that says, more or less, "should be good to merge." Nobody asked for this much output. Nobody has time to review it properly. The team doesn't feel faster. It feels ambushed.