#runtime-profile

CPU Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for general-purpose processor scheduling. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used CPU Runtime Profile when the service hit a compute ceiling, so the team could target optimization work before the workload scaled up.”

Cache Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for fast temporary data layer. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Cache Runtime Profile when the cache missed during peak traffic, so the team could target optimization work before the workload scaled up.”

Cluster Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for group of machines acting as one platform. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Cluster Runtime Profile when the cluster added a node pool, so the team could target optimization work before the workload scaled up.”

Container Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for packaged application runtime. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Container Runtime Profile when the image started on a new node, so the team could target optimization work before the workload scaled up.”

Edge Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for globally distributed runtime. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Edge Runtime Profile when the request arrived near a user, so the team could target optimization work before the workload scaled up.”

GPU Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for accelerated compute for parallel workloads. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used GPU Runtime Profile when the training job requested more memory, so the team could target optimization work before the workload scaled up.”

Memory Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for volatile runtime storage. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Memory Runtime Profile when the process approached its memory limit, so the team could target optimization work before the workload scaled up.”

Scheduler Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for placement of work onto resources. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Scheduler Runtime Profile when the cluster needed to place a job, so the team could target optimization work before the workload scaled up.”

Serverless Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for event-driven function execution. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Serverless Runtime Profile when the function received a traffic burst, so the team could target optimization work before the workload scaled up.”

Storage Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for persistent data and object access. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Storage Runtime Profile when the workload read a large dataset, so the team could target optimization work before the workload scaled up.”

Virtual Machine Runtime Profile is a compute performance record that shows how code uses CPU, memory, I/O, and time for isolated guest compute. It uses sampling, traces, and resource metrics so teams can target optimization work while keeping evidence, reliability, and public-safe operational boundaries clear.

“The platform engineering team used Virtual Machine Runtime Profile when the VM migrated hosts, so the team could target optimization work before the workload scaled up.”