Remove Availability Remove Big Data Remove Latency
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Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Overview At Netflix, the Analytics and Developer Experience organization, part of the Data Platform, offers a product called Workbench. Workbench is a remote development workspace based on Titus that allows data practitioners to work with big data and machine learning use cases at scale. We then exported the .har

Latency 211
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ScyllaDB Trends – How Users Deploy The Real-Time Big Data Database

Scalegrid

ScyllaDB offers significantly lower latency which allows you to process a high volume of data with minimal delay. percentile latency is up to 11X better than Cassandra on AWS EC2 bare metal. Nodes must be replaced if they are down, or dead, though a cluster can still be available when more than one node is down.

Big Data 187
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Understanding gRPC Concepts, Use Cases, and Best Practices

DZone

Because with the advent of cloud providers, we are less worried about managing data centers. Everything is available within seconds on-demand. This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests.

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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. Key challenges. Performance.

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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. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154
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The 6 Rules for Achieving (and Maintaining) High Availability

VoltDB

In the age of big-data-turned-massive-data, maintaining high availability , aka ultra-reliability, aka ‘uptime’, has become “paramount”, to use a ChatGPT word. So when they don’t get one, they ask again — and again… and again… We thus have two compelling reasons for why high availability is so important: 1.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

It provides a good read on the availability and latency ranges under different production conditions. The upstream service calls the existing and new replacement services concurrently to minimize any latency increase on the production path. Logging is selective to cases where the old and new responses do not match.

Traffic 344