Operations | Monitoring | ITSM | DevOps | Cloud

SLA/SLO-driven monitoring aligns your observability strategy with business objectives by defining measurable service targets and implementing monitoring systems that track progress toward those goals. Service Level Agreements (SLAs) represent commitments to users, while Service Level Objectives (SLOs) are internal targets that ensure you meet those commitments with a safety buffer. In 2025, organizations running distributed systems need monitoring that goes beyond basic uptime checks.

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.

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.

Modern enterprises today often find themselves in a peculiar predicament: they are drowning in a deluge of telemetry data—including logs, metrics, and traces—yet paradoxically remain blind to what truly matters. Despite making substantial investments in observability tools, teams frequently find themselves reacting to incidents rather than proactively preventing them, with alerts flooding dashboards often devoid of critical context.

As data systems grow more complex and data becomes even more business-critical, teams struggle to detect and resolve issues that impact data quality, reliability, and, ultimately, trust. Engineers have to rely on manual checks and ad hoc SQL queries to catch data quality issues—often after teams relying on the data have noticed something has gone wrong.

On March 2, 2025, Firefly Aerospace made history. The company — a space services firm that offers safe, reliable, and economical access to space — completed the first fully successful lunar landing by a commercial provider with its Blue Ghost Mission 1. But behind the headlines and highlight reels was a team of dedicated engineers, years of preparation, and a mission control center outfitted with Grafana dashboards.

Log volume is exploding, costs are rising, and most teams are stuck duct-taping together short-term fixes. During our webinar, "Optimizing Log Management in Datadog: Cut Costs Without Losing Insights," we discuss how DevOps and engineering leaders are navigating the growing pains of observability, especially in environments where tools like Datadog are mission-critical but challenging to manage. Here’s a recap of the key takeaways.