Observability is increasingly important for platform engineers, with 32.8% prioritizing it according to the State of Platform Engineering Vol 4. The challenge lies not in finding tools, but in selecting those that provide both operational visibility and developer self-service. Effective observability helps teams understand why issues occur in complex systems like Kubernetes and microservices, rather than just highlighting that something is wrong. Companies report a 2.6x ROI from observability investments, and 63% plan to increase spending in the next two years, making tool selection a critical factor for maximizing this investment. Key criteria for evaluating observability tools include OpenTelemetry support, cost management, and developer self-service capabilities. OpenTelemetry is essential for ensuring that telemetry data remains consistent and portable. Tools that support OpenTelemetry natively facilitate ease of use and integration, while auto-instrumentation features help developers access observability without extensive setup. Cost management is also vital, as many teams face rising expenses in their observability efforts. Tools should provide transparent pricing and effective data lifecycle management to help teams avoid unexpected costs. The article evaluates ten observability tools, ranging from established players to emerging solutions. Datadog is strong for comprehensive monitoring but encourages proprietary agents, which may lead to higher costs. New Relic focuses on developer experience with a flexible query language. Dynatrace excels in AI-driven automation, suitable for large enterprises but may lean on proprietary solutions. Grafana Cloud is ideal for teams using Prometheus, offering vendor neutrality and straightforward cost optimization. Honeycomb emphasizes exploratory analysis for complex systems, while Lightstep specializes in high-volume trace data. Emerging options like Dash0 and SigNoz offer OpenTelemetry-native architectures with transparent pricing, making them appealing for teams aiming for composable observability solutions.