Monitor end-to-end performance beyond the last mile

Fine-grained monitoring tools for applications demanding the highest performance

Code-level profiling

Identify performance hotspots in the program code.

End-to-end tracing

Use distributed tracing to track critical execution paths in systems built across physical nodes, hardware platforms and coding languages.

Real-time performance metrics

Track and monitor key metrics and hardware counters responsible for overall system performance.

Error tracking & alerts

Get notified of errors produced by software crashes, hardware events and application exceptions that affect product performance.

Code-level profiling

Discover bloated code with automatic code profiling

Code-level profiling provides solutions to performance issues that other tools cannot offer. Whether your performance hotspots are in sensors, driver code, GPU code, computer vision algorithms, or machine learning models, profiling can pinpoint the bottleneck down to the function line number. Intuitive interface allows you to drill down modules to get per-function usage breakdowns.

  • Profile high-performance C/C++ applications to diagnose memory and CPU usage over its entire lifetime or a specific interval
  • Profile GPU code exclusively or alongside CPU execution, including per-stream NVIDIA CUDA kernels
  • Profile critical computer vision tasks that run on OpenCV and other CV frameworks
  • Profile deep learning models that run on Tensorflow, Pytorch, Keras and other deep learning frameworks

End-to-end tracing

Cloud-to-hardware tracing

Use distributed tracing to track and measure each step of any execution path and find the bottleneck in your code. Visualize the breakdown of critical tasks and operations by their execution times.

  • Multi-language support (C/C++, Python, Java, Javascript, Golang, Ruby, Node.js, and more)
  • High-precision nanosecond timestamps for hardware-layer tracing
  • Custom tags, metadata, and log messages for quick search and filtering
Real-time performance metrics monitoring

Monitor performance metrics down to hardware counters and registers

Real-time monitoring and logging of performance metrics, including the following:

  • Hardware performance counters (eg. CPU, GPU, RAM, SSD, SoC, FPGA, and more)
  • System metrics (eg. CPU load, memory usage, disk transfer rate, network throughput)
  • Deep learning metrics (eg. accuracy, AUC, logarithmic loss, confusion matrix, RMSE)
  • Application framework metrics (eg. Java, .NET, Redis, SQL, Apache, docker, and many more)

Use pre-defined or define custom alerts that trigger when metric values cross a particular threshold.

Error tracking & alerts

Get notifications of errors that are affecting performance

Track errors produced by software crashes, hardware events, application exceptions and alarms that cause service interruptions for your users. Errors can include any of the following:

  • Hardware errors (eg. CPU overheat, RAM ECC errors, disk CRC errors)
  • Software crashes (eg. segmentation fault, bus error, divide by zero)
  • Application exceptions (eg. Exceptions generated by C/C++, Go, Python, Java, Javascript, Golang, Ruby, Node.js)

Set pre-defined or create your custom alerts when a certain number of errors of a partitcular type is received.

Create world-class products to compete with the best of them

Manage top-to-bottom, end-to-end performance of your product
and create the most responsive, satisfying experience for your users.