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Profiling

Continuous Profiling: A New Observability Signal

We’ve all grown used to logs, metrics and traces serving as the “three pillars of observability.” And indeed they are very important telemetry signals. But are they indeed the sum of the observability game? Not at all. In fact, one of the key trends in observability is moving beyond the ‘three pillars: One emerging telemetry type shows a particularly interesting potential for observability: Continuous Profiling.

Prefix Premium - Profile, Test & Fix Code As Your Write It

Like all of us today, I’m buying more and more products and services online. But even the slightest hiccup in my digital experience might cause me to switch vendors. Multiply that risk by millions – the result of digital commerce growing at an exponential rate – and it’s easy to see how bad user experiences could literally sink a company.

Continuous Performance Improvement of HTTP API

The following guest post addresses how to improve your services’s performance with Sentry and other application profilers for Python. Visit Specto.dev to learn more about application profiling and Sentry’s upcoming mobile application profiling offering. We’re making intentional investments in performance monitoring to make sure we give you all the context to help you solve what’s urgent faster.

Datadog on Profiling in Production

Depending on your chosen programming language and stack, you may have never used a profiler in production. The very idea of using a profiler in production for a web service may seem unrealistic, due to the amount of overhead involved. After all, aren’t profilers extremely computationally expensive to run? Despite a reputation for being computationally expensive, many programming languages have examples of profilers built to run in production. The importance of seeing how your application behaves in production is critically important to understanding how it performs in the real world.

Analyze Ruby code performance with Datadog Continuous Profiler

Ruby is an object-oriented programming language celebrated for its simple and easy-to-read syntax. It powers Ruby on Rails, the open source web development framework that streamlines common development tasks involved in building web applications. We’re pleased to announce that our Continuous Profiler, which provides low-overhead, code-level performance insights, is now generally available for Ruby applications.

Announcing the Preview of Splunk APM's AlwaysOn Profiling

For application developers and service owners who build and troubleshoot modern enterprise software, resolving production issues requires identifying poor performance across multiple networks, operating systems, servers, configs, and third party dependencies. When the problem is the code itself, code profiling helps identify service bottlenecks by periodically taking CPU snapshots, or call stacks, from a runtime environment.

Compare and optimize your code with Datadog Profile Comparison

Code profilers offer detailed insight into the efficiency of application code by measuring things like the execution time and resource utilization of a service. Datadog’s always-on, low overhead Continuous Profiler provides snapshots of code performance for a service that are tagged with key metadata (e.g., region, service, release), so you can easily identify and optimize inefficient code.

How to Troubleshoot Performance with a Visual Studio Profiler

Performance profilers mainly aid developers in analyzing the performance of applications. The purpose is to improve poorly performing sections of code that make up the functions of the application. When you say performance profilers, common names that come to mind are Visual Studio performance profilers and Prefix by Netreo. In this article, we will focus on the specific Visual Studio profiling tools for memory and CPU usage.