Big Data profiling: enhance performance and optimize infrastructure costs

Identify bottlenecks and get dozens of tangible improvement recommendations

Big Data profiling and identifying bottlenecks

Run Big Data tasks with minimal infrastructure cost

Recommendations to optimize performance and infrastructure

Support of various Big Data technologies and programming languages

Big Data profiling and identifying bottlenecks

Integrating with Big Data jobs profiling OptScale analyzes inside and outside metrics to identify profiling issues and bottlenecks. Extensive Data job profiling is a complex process that depends on a defined hyperparameter set, hardware, or cloud resource usage. After the analysis, the engineering team can identify the bottlenecks to optimize performance and infrastructure.

Run Big Data tasks with minimal infrastructure cost

Infrastructure costs for running Big Data tasks depend on different factors such as the data size, the resources’ geographic location (network traffic between cloud regions could be paid), the complexity of the algorithms, and the specific configuration needs in data processing, for example, for GCP. OptScale is designed to optimize the cloud infrastructure, minimize costs, and ensure that resources are used efficiently.

Recommendations to optimize performance and infrastructure

By addressing the bottlenecks in the Big Data job profiling process, OptScale helps improve cloud infrastructure for better performance. OptScale highlights the issues and offers clear recommendations to optimize cloud usage. The recommendations include utilizing Reserved/Spot instances and Saving Plans, rightsizing and instance family migration, network traffic optimization, and IOPS inconsistencies that data transformations or model code inefficiencies can cause.

Support of various Big Data technologies and programming languages

OptScale is a solution for engineering teams using different big data technologies (such as Apache Hadoop or Apache Spark) and programming languages, that offers an opportunity to deliver OptScale to a wide range of companies. Moreover OptScale is built as an open-source platform to help businesses of any size improve Big Data job profiling by getting optimal performance and infrastructure costs.

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FinOps and MLOps

A full description of OptScale as a FinOps and MLOps open source platform to optimize cloud workload performance and infrastructure cost. Cloud cost optimization, VM rightsizing, PaaS instrumentation, S3 duplicate finder, RI/SP usage, anomaly detection, + AI developer tools for optimal cloud utilization.

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Optimize RI/SP usage for ML/AI teams with OptScale

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see RI/SP coverage
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