Autonomous Continuous Optimization for Big Data Workloads
- Reduce processing costs on Spark, MapReduce, Kafka, and more
- Improve performance by continuously optimizing application runtime and resource allocation
- Unburden your R&D team with continuous orchestration and ZERO CODE CHANGES
The next step in your big data journey starts here
Whether your systems are on-prem, cloud-based or hybrid Granulate supports all infrastructure:
& Hybrid cloud
How Can You Achieve Reduced CPU Utilization and Improved Processing Time?
YARN Resource Allocation
Optimize the allocation of your YARN resources 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
Leverage Crypto architecture, accelerators, and instruction set for operations.
Memory Arenas Optimization
PGO allocation and release of memory space and objects sizes to reduce allocation overhead
JVM Runtime Optimization
JNI overhead reduction, execution control flow and reflection overhead optimization