High Scalability

MARCH 30, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). Level up on in-demand technologies and prep for your interviews on Educative.io, featuring popular courses like the bestselling Grokking the System Design Interview.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

Percona

JANUARY 19, 2023

This may not be a huge problem for small tables, but for tables with millions of records, overprovisioning data types will only make the table to be bigger in size and performance, not the most optimal. Make sure you design the data types correctly while planning for the future growth of the table.

Open Source 87

Open Source Storage Database Big Data 87

ACM Sigarch

MAY 31, 2023

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. To maximize performance benefits, a thorough understanding of individual data objects (e.g.,

Latency 52

Latency Hardware Cache Architecture 52

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. Designing for Performance. High Performance Responsive Design. Responsive Web Design. Mobile First.

Performance 75

Performance Social Media Website Website Performance 75

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. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

Rigor

MAY 22, 2019

Big data is like the pollution of the information age. The Big Data Struggle and Performance Reporting. Alternatively, a number of organizations have created their own internal home-grown systems for managing and distilling web performance and monitoring data. The Value of Performance Monitoring Dashboards.

Big Data 76

Big Data Monitoring Performance Metrics 76

Testsigma

MAY 26, 2021

Scenario 4: Image-based data-driven testing. Photo management applications, e-commerce websites, search engines, healthcare, disaster monitoring, robotics, etc. No one wants spam emails, so spam detection algorithms have been designed to identify such spam emails. Example: Image classification algorithms. Example: email spam.

Testing 70

Testing Healthcare Performance Testing Website 70

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring. Application monitoring. Dynatrace news.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

O'Reilly

OCTOBER 21, 2019

He designed this new platform to be permission-less and free, an open space for creativity, innovation, and free expression that transcended geographic and cultural boundaries. Blockchains enable a permanent and tamper-proof record of a good’s journey from origin to ultimate destination that anyone in the community can monitor and audit.

Blockchain 52

Blockchain Social Media Innovation Internet 52

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. Once products and services are live, IT teams must continuously monitor and manage them. What is AIOps, and how does it work?

Artificial Intelligence 285

Artificial Intelligence Cloud Innovation Strategy 285

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing.

Processing 210

Processing Big Data Efficiency Engineering 210

All Things Distributed

JANUARY 19, 2011

To battle this complexity, developers who do not need control over the whole software stack often use development platforms that help them manage their application development, deployment and monitoring. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Driving down the cost of Big-Data analytics.

AWS 115

AWS Cloud Java Operating System 115

Dynatrace

AUGUST 10, 2021

Intelligent Observability includes the ability to not only monitor applications but gain actionable insights that can be used to transform services and create great customer experiences. She dispelled the myth that more big data equals better decisions, higher profits, or more customers. How can I make them better?

DevOps 246

DevOps Innovation Big Data Cloud 246

Dynatrace

JUNE 1, 2020

Application Performance Monitoring (APM) in its simplest terms is what practitioners use to ensure consistent availability, performance, and response times to applications. Websites, mobile apps, and business applications are typical use cases for monitoring. APM can be referred to as: Application performance monitoring.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” The second challenge with traditional AIOps centers around the data processing cycle. But what is AIOps, exactly? What is AIOps?

Artificial Intelligence 212

Artificial Intelligence DevOps Innovation Metrics 212

Scalegrid

MARCH 14, 2024

Workloads from web content, big data analytics, and artificial intelligence stand out as particularly well-suited for hybrid cloud infrastructure owing to their fluctuating computational needs and scalability demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option. Download report now!

Artificial Intelligence 208

Artificial Intelligence Storage Analytics Government 208

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. Python is also a tool we typically use for automation tasks, data exploration and cleaning, and as a convenient source for visualization work.

Open Source 279

Open Source Network Infrastructure Big Data 279

The Netflix TechBlog

FEBRUARY 16, 2021

However, with our rapid product innovation speed, the whole approach experienced significant challenges: Business Complexity: The existing SKU management solution was designed years ago when the engagement rules were simple?—?three three plans and one offer homogeneously applied to all regions.

Mobile 209

Mobile Engineering Infrastructure Scalability 209

The Netflix TechBlog

OCTOBER 18, 2022

by Jun He , Akash Dwivedi , Natallia Dzenisenka , Snehal Chennuru , Praneeth Yenugutala , Pawan Dixit At Netflix, Data and Machine Learning (ML) pipelines are widely used and have become central for the business, representing diverse use cases that go beyond recommendations, predictions and data transformations.

Java 202

Java Scalability Traffic Architecture 202

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

Highly Scalable

MAY 1, 2012

Let us start with a simple example that illustrates capabilities of probabilistic data structures: Let us have a data set that is simply a heap of ten million random integer values and we know that it contains not more than one million distinct values (there are many duplicates). what is the cardinality of the data set)?

Analytics 191

Analytics Traffic Big Data Efficiency 191

All Things Distributed

FEBRUARY 25, 2011

They also setup Auto Scaling, EC2 and RDS Security Groups, configure CloudWatch monitoring and alarms, and use SNS for notifications. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Driving down the cost of Big-Data analytics. Countdown to What is Next in AWS. Expanding the Cloud â??

AWS 121

AWS Cloud Scalability Storage 121

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. The DevOps workflow is strongly connected to continuous monitoring activities aimed to maximise the consistency of the product and eliminate corporate risk. Test Automation to better work in Agile Mode.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

Currently, an issue has been opened to make the “tailing” based on the primary key much faster: slow order by primary key with small limit on big data. At the same time, it was not originally designed that way. Let me know in the comments if you are using ClickHouse for this or similar projects.

Database 40

Database Analytics Blockchain Healthcare 40