Remove Architecture Remove Big Data Remove Network Remove Storage
article thumbnail

Kubernetes for Big Data Workloads

Abhishek Tiwari

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. Storage provisioning.

article thumbnail

In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Interoperability with Hadoop. Pipelining.

Big Data 154
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is ITOps? Why IT operations is more crucial than ever in a multicloud world

Dynatrace

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. Additionally, they manage applications and services deployed on the network and provide secure access to authorized users. ITOps vs. AIOps.

article thumbnail

What is container orchestration?

Dynatrace

But managing the deployment, modification, networking, and scaling of multiple containers can quickly outstrip the capabilities of development and operations teams. This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. How does container orchestration work?

article thumbnail

The Need for Real-Time Device Tracking

ScaleOut Software

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention.

IoT 78
article thumbnail

What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
article thumbnail

What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data 321