Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence.

Cache 130

Cache Storage Scalability Architecture 130

DZone

JULY 29, 2019

These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on. One of the top trending open-source data storage that responds to most of the use cases is Elasticsearch.

Big Data 162

Big Data Government Open Source Storage 162

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

Dynatrace

JANUARY 11, 2023

With more organizations taking the multicloud plunge, monitoring cloud infrastructure is critical to ensure all components of the cloud computing stack are available, high-performing, and secure. Website monitoring examines a cloud-hosted website’s processes, traffic, availability, and resource use. Database monitoring.

Cloud 214

Cloud Monitoring Best Practices Infrastructure 214

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

JUNE 29, 2022

To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.

Infrastructure 172

Infrastructure Cloud Azure AWS 172

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 176

Analytics Innovation Metrics Database 176

The Netflix TechBlog

JUNE 7, 2021

Network Availability: The expected continued growth of our ecosystem makes it difficult to understand our network bottlenecks and potential limits we may be reaching. Flow Exporter The Flow Exporter is a sidecar that uses eBPF tracepoints to capture TCP flows at near real time on instances that power the Netflix microservices architecture.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

MARCH 24, 2023

Container orchestration is a process that automates the deployment and management of containerized applications and services at scale. This orchestration includes provisioning, scheduling, networking, ensuring availability, and monitoring container lifecycles. The post What is container orchestration?

Infrastructure 176

Infrastructure Open Source Operating System Cloud 176

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? What is ITOps? ITOps vs. AIOps.

Artificial Intelligence 191

Artificial Intelligence DevOps Hardware Virtualization 191

Dynatrace

JULY 6, 2020

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. We’re in a process of adding support for new cloud services in bulk. Azure Virtual Network Gateways.

Azure 144

Azure Cloud Big Data Virtualization 144

Dynatrace

JANUARY 16, 2023

That trend will likely continue as Kubernetes security awareness further rises and a new class of security solutions becomes available. Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments. This corresponds to an annual growth rate of +55%.

Open Source 333

Open Source Java Operating System Programming 333

The Netflix TechBlog

OCTOBER 15, 2019

Another thread or process is constantly polling events from the log table and writes them to one or multiple datastores, optionally removing events from the log table after acknowledged by all datastores. In Netflix the microservice architecture is widely adopted and each microservice typically handles only one type of data.

Transportation 192

Transportation Architecture Processing Storage 192

Dynatrace

APRIL 25, 2023

Exploratory analytics with collaborative analytics capabilities can be a lifeline for CloudOps, ITOps, site reliability engineering, and other teams struggling to access, analyze, and conquer the never-ending deluge of big data. These analytics can help teams understand the stories hidden within the data and share valuable insights.

Analytics 189

Analytics Big Data Media Operating System 189

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. CloudOps includes processes such as incident management and event management. The four stages of data processing. Analyze the data.

DevOps 185

DevOps Artificial Intelligence Healthcare Innovation 185

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?

Artificial Intelligence 201

Artificial Intelligence DevOps Innovation Metrics 201

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. If during the ticket handling another alert is raised this process repeats – but maybe with a different set of people who are working in parallel. The raw event data is available via API just like the problem data as well.

Tuning 260

Tuning Architecture Monitoring Big Data 260

High Scalability

APRIL 14, 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 Scalability Engineering 105

High Scalability

MAY 12, 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 102

Education Software Engineering Scalability Engineering 102

High Scalability

APRIL 28, 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 102

Education Software Engineering Scalability Engineering 102

ScaleOut Software

NOVEMBER 24, 2020

However, telematics architectures face challenges in responding to telemetry in real time. Current Telematics Architecture. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Challenges for Current Architectures.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

High Scalability

MAY 26, 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 100

Education AWS Software Engineering Scalability 100

All Things Distributed

JUNE 26, 2016

Today, I’m happy to announce that the Asia Pacific (Mumbai) Region is generally available for use by customers worldwide. Seamless ingestion of large volumes of sensed data. AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift.

AWS 90

AWS Cloud Healthcare Blockchain 90

All Things Distributed

DECEMBER 8, 2016

Today, I'm happy to share that the Canada (Central) Region is available for use by customers worldwide. The AWS Cloud now operates in 40 Availability Zones within 15 geographic regions around the world, with seven more Availability Zones and three more regions coming online in China, France, and the U.K. in the coming year.

AWS 155

AWS Cloud Lambda Innovation 155

Percona

JANUARY 19, 2023

Compression: Compression is the process of restructuring the data by changing its encoding in order to store it in fewer bytes. There are many compression tools and algorithms for data out there. It is available under a paid subscription. It was developed for optimizing data storage and access for big data sets.

Open Source 85

Open Source Storage Database Big Data 85

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source. Summing Up: Do More in Real Time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source. Summing Up: Do More in Real Time.

Analytics 52

Analytics IoT Lambda Big Data 52

The Netflix TechBlog

JULY 26, 2021

From the moment a Netflix film or series is pitched and long before it becomes available on Netflix, it goes through many phases. Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain.

Big Data 253

Big Data Government Analytics Processing 253

ScaleOut Software

APRIL 3, 2020

The real-time digital twin software tracks and updates this information using incoming messages whenever significant events affecting the ventilator occur, such as when it moves from place to place, is put in use, becomes available, encounters a mechanical issue, has an expected repair time, etc.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

The real-time digital twin software tracks and updates this information using incoming messages whenever significant events affecting the ventilator occur, such as when it moves from place to place, is put in use, becomes available, encounters a mechanical issue, has an expected repair time, etc.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

JULY 13, 2010

Today, I am very proud to be a part of the Amazon Web Services team as we truly make HPC available as an on-demand commodity for every developer to use. Additionally, many high-end HPC applications take advantage of knowing their in-house hardware platforms to achieve major speedup by exploiting the specific processor architecture.

Cloud 118

Cloud AWS Automotive Latency 118

The Netflix TechBlog

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 219

Infrastructure Big Data Transportation Architecture 219

Highly Scalable

MARCH 10, 2015

More specialized data mining applications like supply chain optimization and fraud detection are out of scope, as well as the implementation details of the data mining process (such as evaluation of model quality). This framework resembles the approach suggested in [JK98]. The model (2.1)

Retail 152

Retail C++ Analytics Metrics 152

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

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

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203

Storage Latency Efficiency Data Engineering 203

All Things Distributed

APRIL 27, 2011

To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Look inside a current textbook on software architecture, and youll find few patterns that we dont apply at Amazon.

Technology 151

Technology Technology AWS Storage 151