Understand your full-stack behavior with built-in visibility

Upsun provides built-in observability across infrastructure and applications, including metrics, Application Performance Monitoring (APM), and profiling.

Engineers can understand how applications behave in real environments without deploying or maintaining separate monitoring infrastructure.

What this enables

Observability and Profiling allow teams to understand application behavior through platform-level insights:

Detect performance bottlenecks and failures early
Understand how applications use resources over time
Debug issues in production-like environments with confidence

How it works

Infrastructure and service metrics

Upsun collects metrics for application containers and managed services such as databases and caches. Teams can track resource usage trends, identify saturation points, and correlate infrastructure behavior with application changes across environments.

Application performance monitoring

Built-in application performance monitoring for PHP and Python, via Blackfire, captures runtime behavior at the code level. Teams can identify slow requests, expensive queries, and inefficient execution paths. This data is tied directly to the running environment, not synthetic tests.

Profiling in real conditions

Upsun supports continuous profiling in production and development environments, including NodeJS, Go, Ruby, and Rust from the Console, with Blackfire-powered profiling for PHP and Python. Profiling data shows how functions and processes consume CPU and memory over time, helping teams pinpoint root causes without reproducing issues locally. Profiling can be enabled selectively to limit overhead as well.

What this solves

Blind spots in production

Without observability, teams rely on guesswork or user reports. Upsun provides direct visibility into application behavior as it runs.

Hard-to-reproduce performance issues

Many issues only appear under real traffic or data. Profiling in live environments makes these problems visible without complex setup.

Fragmented monitoring tools

Running separate tools for metrics, tracing, and profiling increases complexity. Upsun consolidates these capabilities into the platform.

Key capabilities

Infrastructure and service-level metrics per environment
Built-in APM for PHP and Python via Blackfire
Continuous and on-demand profiling for supported runtimes
Visibility across preview, staging, and production environments
Centralized access through console, CLI, and API
No separate stack required for built-in metrics, APM, and continuous profiling for supported languages

Full-stack visibility from container to code

Upsun’s integrated observability suite allows you to trace the exact path of a request, from the HTTP layer down to specific database queries or cache hits. Isolate the 20% of performance issues causing 80% of your application bottlenecks by analyzing real-time waterfall traces.

Continuous profiling: Identify functions that over-reserve resources or increase execution time within your application containers
Integrated performance testing: Define performance budgets and script automated tests that run on every deploy to block inefficient code.
Layered transaction monitoring: Track performance across the database, cache, and application layers to pinpoint exactly where latency occurs.

Enterprise considerations

Security and isolation

Observability data is scoped to your project and environments, with access governed by platform roles. Access is governed by platform permissions, and data does not leak across projects.

Operational overhead

Monitoring and profiling are managed by the platform. Teams do not need to deploy, upgrade, or maintain separate observability stacks.

Performance impact

Profiling and monitoring are designed to minimize runtime overhead and can be enabled selectively based on environment or use case. Allowing you to see the impact of changes before they go into production.

How teams use this in practice

Production debugging

An operations team investigates increased latency by reviewing APM traces for PHP or Python and profiling results directly from the production environment.

Pre-release validation

A team compares performance metrics between a preview environment and production to validate changes before deployment.

Capacity planning

Engineers are able to analyze long-term resource usage trends to inform scaling and cost optimization decisions.

Get started

Use Observability and Profiling to make data-driven decisions about performance, reliability, and scaling.

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