Operations | Monitoring | ITSM | DevOps | Cloud

Japanese organizations are focused on controlling costs and limiting complexity—and they might be getting ready to broaden their adoption at just the right time, according to analysis of a micro survey on observability recently conducted by Grafana Labs. Observability is an evolving space in Japan, and this is the first time Grafana Labs has run a Japanese version of our annual Observability Survey.

June 12, 2025. A date most of the Internet won’t remember — but anyone relying on Google Cloud will. In the span of minutes, a routine quota update snowballed into global disruption. APIs stopped responding. Dashboards stayed green. And across continents, teams scrambled to figure out if the problem was theirs — or Google's. It wasn’t a cyberattack. It wasn’t a datacenter fire.

TL;DR A Service Level Agreement (SLA) defines the required uptime for a service. An SLA uptime calculator helps convert uptime percentages into actual allowed downtime across different timeframes. This guide explains how these calculators work, why uptime matters, and how to monitor performance to meet SLA targets.

Everything comes at a cost — and observability is no exception. When we add metrics, logging, or distributed tracing to our applications, it helps us understand what’s going on with performance and key UX metrics like success rate and latency. But what’s the cost? I’m not talking about the price of observability tools here, I mean the instrumentation overhead.

Your code passes locally, CI is green, and the deploy goes through. Then production throws a 500, and the trace isn’t helpful. And here, event logs help. A log captures timestamped records of what the app did HTTP requests, DB queries, cache misses, retries, failures. These entries give you enough context to debug without reproducing the issue locally. Especially when dealing with distributed systems, logs are often the only consistent source of truth.

In most object-oriented languages, exceptions are an extremely powerful mechanism for dealing with unexpected situations that arise when running your code. PHP has supported robust exception handling since PHP 7.0. As you begin your programming journey, exceptions are a source of tremendous pain. Over time, you grow to appreciate the value they bring.

AWS gives you the power to scale, deploy, and innovate at speed. However, with that speed comes a good amount of complexity. Services multiply, resources balloon, and performance issues sneak in when you least expect them. That’s where monitoring comes in. But it isn’t about checking boxes on dashboards. It’s about getting the most value for every dollar you spend or, maximizing your return on investment (ROI) from AWS monitoring. So, how do you actually do that?