Observability in code

An open source framework that makes it easy to understand the error rate, response time, and production usage of any function in your code.

Autometrics website

GitHub

languages we support

Features

fn create_user(
	db: &Database,
	id: u32,
	username: &str,
	email: &str
) {
    let user = User {
        id,
        username: username.to_string(),
        email: email.to_string(),
    };

    let mut db = db.lock().unwrap();
    db.insert(id, user);
}

Simplifies code-level instrumentation

Autometrics removes decision paralysis that comes with code instrumentation. Simply decide which functions are important and decorate them.

Autometrics enables you to understand your production system at one of the most fundamental levels: from the function.

Unified dashboards for code-level metrics

All metric data Autometrics generates has standard names, enabling you to use functional dashboards.

Grafana dashboard

SLOs and Alerts without YAML

Autometrics allows you to group instrumented functions in to SLOs and create useful alerts on them all while keeping the context in your application source code.

Built on top of popular open source libraries

Autometrics can be incrementally adopted with most open-source metrics libraries that you already use.

Graphs in your IDE

Easily explore your application's performance from your editor.

Easily explore your application's performance from within your editor.

VSCode extension

New

Spot faulty commits and deploys

Autometrics tracks your software versions and writes queries that can help pinpoint where and when issues were introduced

Why we built Autometrics

Metrics are useful

Metrics are a very effective way to assess how your code is actually performing in production. It’s cheaper, better to get high-level insights, and easier to alert or automate on than logs.

Code instrumentation is laborious

It is the last 10% of the work that takes 90% of the project time. It requires both manual labor to sprinkle instruments, and is full of naming pitfalls.

Querying is hard

Query-writing is still a field relegated to the few “wise-ones” to build dashboards for the rest of us.

Metrics are useful

Metrics are a very effective way to assess how your code is actually performing in production. It’s cheaper, better to get high-level insights, and easier to alert or automate on than logs.

Code instrumentation is laborious

It is the last 10% of the work that takes 90% of the project time. It requires both manual labor to sprinkle instruments, and is full of naming pitfalls.