Sustainability

Optimizing Big Data 
workloads to reduce costs

Continuous and autonomous big data optimization solution reducing costs through improved performance

Reduce processing time and increase pipeline throughput to meet your SLAs

Big Data workloads are growing fast and becoming more expensive. By using Intel® Tiber™ App-Level Optimization, applications run more efficiently, with fewer wasted resources, faster time to completion, accelerated pipeline throughput, resulting in reduced costs.
Up to
45%
Compute cost reduction
Average of
31%
Processing time reduction
0
Code changes

See how it works

Reduced processing costs, optimized performance

Supports all infrastructure

Whether your systems are on-prem,
cloud-based or hybrid, Intel Tiber App-Level Optimization supports all infrastructure, including EMR, Dataproc, HDInsight, Cloudera, MapReduce, Spark, PySpark, and more.

Real time continuous orchestration

Avoid constant monitoring and benchmarking with autonomous, continuous optimization, tuning big data workloads to their unique cost-performance sweet spot.
Automatic | Full-stack | Scalable

Read more

Hit your Big Data workload targets

Reduce processing costs

across Spark, MapReduce, Kafka, and more

Meet your SLAs

with faster job completion time

Improve performance

by continuously optimizing application runtime and resource allocation

Unburden your R&D team

with continuous orchestration and zero code changes

Complete more jobs in less time

App-Level Optimization allows data science, data engineering and data analysis teams to improve performance
Yarn resource allocation

Optimized to improve cluster density and remove overprovisioning waste.

Spark dynamic allocation

Optimized dynamic allocation and removal of executors based on the job patterns and predictive idle heuristics.

Crypto & compression acceleration

Leveraging Crypto architecture, accelerators, and instruction sets for operations

Memory arenas optimization

Release of memory space and objects sizes to reduce allocation overhead

JVM runtime optimization

JNI overhead reduction, execution control flow and reflection overhead optimization

3 steps through just one init script

1. Install- 15 minutes

Start a free trial of Intel Tiber App-Level Optimization on your Big Data applications

2. Evaluate - 1 week

Let Intel Tiber App-Level Optimization autonomously learn the data application and workloads

03. Deploy - 15 minutes

Activate Intel Tiber App-Level Optimization and immediately experience data performance improvements