Welcome, Polar Signals!
Observability is a cornerstone of effective systems management. If you can’t measure the internal state of a system — whether an airplane or piece of software — you’re essentially flying blind. It’s no surprise that observability is more difficult in the digital world. There’s no check-engine light, smoke detector, or other sensory output to tell you what’s going on. Instead, we’ve come to rely on manually instrumented data points across our software — the “three pillars” of observability (metrics, logs, and tracing).
In a cloud-native world, the very features that make software systems “simple” (abstractions, elasticity, composability) also make them less observable. Just like cloud displaced data centers and microservices replaced monoliths, serverless is causing another shift in the cloud landscape. This new architecture has exposed deficiencies in traditional observability tools which fall short in addressing the nuances of distributed architectures.
Enter Polar Signals, a company dedicated to transforming how we understand and optimize high performance systems. Polar Signals was founded in 2020 by Frederic Branczyk who was an early employee at CoreOS in their Berlin office and a key figure in the Prometheus and Kubernetes communities. Frederic experienced first hand the complexity of running, maintaining, and monitoring distributed systems, often building tools himself to address this.
Polar Signals is laser focused on “continuous profiling”. While this is not a new concept, its application in the context of Polar Signals is unique. By capturing detailed profiles of running programs, Polar Signals allows engineers to understand resource usage down to the function and line number. As of recently, they can also correlate traces with profiles to view usage data across all services. This granularity of data is hard to achieve with traditional observability tools.
To do this, Polar Signals leverages technologies like eBPF to collect data continuously, with minimal overhead, and zero instrumentation. Their flagship open-source product, Parca, has a simple deployment, no dependencies, and deep integration with Kubernetes. By focusing on continuous profiling, Polar Signals offers a new level of insight into system behavior.
Every company building and operating software can benefit from deeper insights into CPU usage, memory allocations, and overall system performance. Polar Signals allows developers to pinpoint exactly what parts of their code contribute to what resource usage. This not only facilitates cost optimization but also improves latency, directly contributing to better user experiences. With new AI-powered features, developers can also leverage Polar Signals to recommend code changes directly based on profiling data. It’s no surprise that some of the top teams in databases and systems are using Polar Signals.
At Spark, we love to invest in founders with a strong product focus, often during inflection points in a market. While observability is not new, Frederic and his team have taken a new lens to an old problem. With the ushering of new AI workloads, cloud costs and performance are at the forefront of companies’ priorities and Polar Signals has never been more important for understanding and optimizing these systems.
Today we are excited to share our investment in Polar Signals, with Spark Capital leading a $6.8M round with participation from existing investors (GV, Lightspeed, Haystack, Lorimer) and an incredible set of angels: Guillermo Rauch, Julius Volz, Monica Sarbu, Jimmy Zelinskie, Nikhil Benesch, and Erik Bernhardsson.
We couldn’t be more excited to partner with Frederic and the entire Polar Signals team (p.s. they’re hiring!). Welcome, Polar Signals!
