Operations | Monitoring | ITSM | DevOps | Cloud

When your database performance degrades, diagnosing the root cause is rarely quick or straightforward. Your existing tools might surface metrics like CPU utilization, wait events, and query duration, but then leave you to correlate the data and identify what went wrong. Worse, what first appears to be the root cause can often just be a downstream effect of multiple interrelated issues.

Today, roughly 94% of enterprises are projected to use some form of cloud service, with 82% adopting hybrid models that combine cloud and on-premises infrastructure. By 2030, around 60% of all corporate data is expected to be stored in the cloud, highlighting a major shift away from traditional storage systems toward distributed, on-demand infrastructure. With such a huge amount of data, companies need a scalable, affordable, and secure method to store 1 PB.

Key takeaway: Granting AI agents unrestricted access to cloud infrastructure is an unacceptable security risk. Upsun provides a "zero-trust" framework by utilizing isolated, production-perfect preview environments that allow AI to be productive without the risk of a hallucinated production outage.

Drop a JAR on the JVM. Get distributed tracing, RxJava context propagation, log-trace correlation, and Vert.x internal metrics. No code changes. No Maven dependency. Java 8–21. Inside the design of last9/vertx-opentelemetry v2.3.4. Prathamesh works as an evangelist at Last9, runs SRE stories - where SRE and DevOps folks share their stories, and maintains o11y.wiki - a glossary of all terms related to observability.

Getting a certificate from a CA is a solved problem (ACME). Distributing it to the rest of your infrastructure is not. Your F5 has its own API. Your Palo Alto has a different one. Azure Key Vault is a third thing entirely, and the appliance in the back of the rack only has an SSH interface.

Focusing on GenAI and logs for IT efficiency Efficiency is everything for managing today’s digital systems. Technology is constantly transforming and expanding operations are driving an explosion in data. Consequently, data ingest and storage costs have soared. But it’s not just storage data costs that keeps teams behind.The challenge of managing all that observability data forces IT teams to choose between efficiency and the bottom line.

How to Draft, Customize, and Keep Service Level Agreements Defensible Most enterprises do not discover the weaknesses in their SLAs during the drafting process. They discover them during an incident review, a customer escalation, or a contract dispute, when the language that seemed reasonable at signing turns out to be too vague to measure, too broad to enforce, or disconnected from the operational data that would make it defensible.

A Practical Guide for Help Desk, IT Operations, and Enterprise SRE Teams A service level agreement template is only useful if it can be customized. The version that ships with your ITSM platform was designed to be generic enough to apply anywhere, which makes it precise enough to apply nowhere. The teams that maintain defensible SLAs are not the ones with the most sophisticated legal language.