The adoption of modern cloud-native distributed architectures has led to increased complexity in operating these systems, making observability a crucial practice. Observability helps engineering teams quickly identify and fix failures before they impact users, enabling frequent delivery of new features with confidence. A key requirement for observability is access to comprehensive telemetry about the system, which can be achieved through instrumentation. Open-source options like Prometheus exporters and OpenTelemetry instrumentation make it easier to instrument systems. Once a system is instrumented, storing and analyzing the generated telemetry becomes essential. The data layer is often the most complex component of an observability stack due to the large amounts of data being collected. To address this challenge, Timescale Cloud and Promscale are introduced as solutions for efficient storage and analysis of telemetry data. Timescale Cloud is a database cloud built on PostgreSQL and TimescaleDB, providing features like native columnar compression, flexible pricing plans with decoupled compute and storage, and downsampling capabilities through continuous aggregates. Promscale is an open-source observability backend built on PostgreSQL and TimescaleDB that automatically infers a schema to store metrics and traces, allowing analysis as if it were any other relational table in PostgreSQL. When used together, Promscale and Timescale Cloud provide a powerful ally for getting started in minutes, worry-free operations, native integration with Prometheus and OpenTelemetry, scalability, and the ability to deliver new features frequently and with confidence.