Operations | Monitoring | ITSM | DevOps | Cloud

Implementing SLAs, SLIs, and SLOs in an observability suite is now business-critical. Over time, a company’s decision-makers can add a burdensome number of KPIs that force servers and other IT assets to devote excessive processing time to business intelligence. Eventually, the burden becomes so great that employees, managers, and executives start to complain about the system’s sluggishness. Developers know that they need to strike a balance between business needs and IT processes.

Some DBAs object to moving from on-prem (or self-hosted) to managed services. We hear you, but read this post to find out our side of the issue.

Over the past decade, businesses have flocked to the public cloud, with the promise of faster innovation, improved scalability — and of course, cost savings. Yet for many companies, the reality of cloud migration has been a different story. CFOs are blindsided by high costs and uncontrolled spending. Meanwhile, engineering teams struggle to justify and explain their spend — often frustrated that finance doesn’t understand, even when spend is growing healthily along with the business.

First, I’d like to say that pager duty isn’t something we should treat like chronic pain or diabetes, where you just constantly manage symptoms and tend to flare-ups day and night. Being paged out of hours is as serious as a fucking heart attack. It should be RARE and taken SERIOUSLY. Resources should be mustered, product cycles should be reassigned, until the problem is fixed.