Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? Performance.

Artificial Intelligence 191

Artificial Intelligence DevOps Hardware Virtualization 191

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Scalegrid

FEBRUARY 8, 2024

Their design emphasizes increasing availability by spreading out files among different nodes or servers — this approach significantly reduces risks associated with losing or corrupting data due to node failure. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

JULY 6, 2020

In addition to providing visibility for core Azure services like virtual machines, load balancers, databases, and application services, we’re happy to announce support for the following 10 new Azure services, with many more to come soon: Virtual Machines (classic ones). Azure Virtual Network Gateways. Azure Batch.

Azure 144

Azure Cloud Big Data Virtualization 144

ACM Sigarch

MAY 31, 2023

Introduction Memory systems are evolving into heterogeneous and composable architectures. Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. The recently announced CXL3.0

Latency 52

Latency Hardware Cache Architecture 52

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. This data is also periodically uploaded to a data lake for offline batch analysis that calculates key statistics and looks for big trends that can help optimize operations.

IoT 78

IoT Analytics Big Data Architecture 78