Akams Performance Summit Tailoring Google Dataproc
Tailoring the Google Dataproc to reduce Spark execution time and cut the bill

In this session at Performance Summit 2021 on September 30th, Luca Chiabrera (Head of Customer Success and Sales Engineering at Akamas) describes how Akamas ML-based optimization helps to tailor Google Dataproc to reduce Spark execution time and cut the bill. Dataproc is a

Akamas Google Dataproc Video
Optimizing Google Dataproc

Google Dataproc is a fully-managed service that hosts open-source distributed processing platforms such as Apache Spark, Presto, and Apache Hadoop on Google Cloud. Dataproc provides the flexibility to manage and configure clusters of varying size, on-demand. However, even with Dataproc users

Akamas faster spark jobs lower AWS costs blog
Wouldn’t it be nice to get faster Spark jobs and lower AWS costs?

Big data applications often offer relevant opportunities for gains both in terms of performance and of cost reduction. Typically, the underlying infrastructure – whether on-premise or on cloud – is both inefficient and over-provisioned to ensure a good performance vs

Akamas Solution Brief Spark
Autonomous Optimization for Apache Spark

The big data analytics market is growing fast, driven by the rapid increase in volume and complexity of enterprise data in virtually every industry. Leading among analytics engines and frameworks, Apache Spark features greater speed and scalability compared to many

Akamas Neotys Jurassic PAC Sparl optimization
Optimizing Spark costs on AWS with AI-powered tuning

During the Neotys Jurassic PAC 2020 virtual conference, Luca Cavazzana (Software Engineer at Akamas) explained how Akamas uses AI techniques to find the optimal configuration for Spark applications. He presented a study where Akamas tuned both Apache Spark parameters and EC2 cluster size, finding