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Description
Assessing the performance of production systems is widely recognized as a challenging task. Efforts to evaluate performance in testing environments often fail to capture the true strain present in a production setting. While micro-benchmarking certain components of your application can sometimes be done, it generally does not reflect the actual workload and behavior of a production system effectively. Continuous profiling of production environments serves as a valuable method for identifying how resources such as CPU and memory are utilized during the service's operation. However, this profiling process introduces its own overhead: to be a viable means of uncovering resource usage patterns, the additional burden must remain minimal. Cloud Profiler emerges as a solution, offering a statistical, low-overhead profiling tool that continuously collects data on CPU usage and memory allocations from your live applications. This tool effectively connects that data back to the specific source code that produced it, allowing for better insights into resource utilization. By utilizing such a profiler, developers can optimize their applications while maintaining system performance.
Description
Randoli serves as a comprehensive observability and cost management solution built on OpenTelemetry, specifically designed for Kubernetes, multicloud, hybrid, and AI/ML workloads. By consolidating essential elements such as infrastructure health, application performance, logs, metrics, traces, incidents, and cloud expenditures into a single control interface, it allows teams to move away from disparate tools and gain a unified view of system operations. Its federated architecture effectively decouples the control plane from the data plane, facilitating local telemetry analysis, relevant signal extraction, and on-demand data retrieval during investigations, all while minimizing ingestion and egress and ensuring data sovereignty is upheld. Randoli is capable of monitoring a wide range of components, including clusters, nodes, pods, workloads, services, dependencies, latency, errors, throughput, and resource utilization across diverse environments such as AWS, Azure, Google Cloud, OpenShift, and on-premises setups. Additionally, it leverages OpenTelemetry and eBPF for automatic, low-overhead instrumentation, which enhances filtering, telemetry enrichment, and real-time signal correlation, thus optimizing observability across the board. This innovative approach not only streamlines operational insights but also empowers teams to proactively manage performance and costs in their cloud infrastructures.
API Access
Has API
API Access
Has API
Integrations
Google Cloud Platform
Amazon Web Services (AWS)
Google Cloud Dataflow
Google Cloud Managed Service for Apache Spark
Google Compute Engine
Google Kubernetes Engine (GKE)
Kubernetes
Microsoft Azure
OpenTelemetry
Red Hat OpenShift
Integrations
Google Cloud Platform
Amazon Web Services (AWS)
Google Cloud Dataflow
Google Cloud Managed Service for Apache Spark
Google Compute Engine
Google Kubernetes Engine (GKE)
Kubernetes
Microsoft Azure
OpenTelemetry
Red Hat OpenShift
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$0.04 per hour
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Country
United States
Website
cloud.google.com/profiler/docs/about-profiler
Vendor Details
Company Name
Randoli
Founded
2017
Country
Canada
Website
www.randoli.io