All Things Distributed

AUGUST 18, 2011

Werner Vogels weblog on building scalable and robust distributed systems. Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud.

Big Data 94

Big Data Analytics AWS Cloud 94

DZone

FEBRUARY 1, 2023

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2.

Azure 250

Azure Storage Big Data Analytics 250

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

DZone

JUNE 6, 2023

This can include the use of cloud computing, artificial intelligence, big data analytics, the Internet of Things (IoT), and other digital tools. One of the significant challenges that come with digital transformation is ensuring that software systems remain reliable and secure. This is where software testing comes in.

Artificial Intelligence 130

Artificial Intelligence Systems IoT Testing 130

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

JANUARY 13, 2022

The data platform is built on top of several distributed systems, and due to the inherent nature of these systems, it is inevitable that these workloads run into failures periodically. We have been working on an auto-diagnosis and remediation system called Pensive in the data platform to address these concerns.

Big Data 242

Big Data Infrastructure Metrics Games 242

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. The configuration of these devices is controlled by several other systems including source of truth, application of configurations to devices, and back up.

Open Source 280

Open Source Network Infrastructure Big Data 280

The Netflix TechBlog

OCTOBER 28, 2021

During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. I developed many batch and real-time data pipelines using open source technologies for AOL Advertising and eBay.

Data Engineering 181

Data Engineering Engineering Big Data Software Engineering 181

Dynatrace

APRIL 19, 2023

Business Insights is a managed offering built on top of Dynatrace’s digital experience and business analytics tools. The Business Insights team helps customers manage or configure their digital experience environment, extend the Dynatrace platform through data analytics, and bring human expertise into optimization.

Entertainment 237

Entertainment Analytics Healthcare Games 237

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. Like the development and design phases, these applications generate massive data volumes that offer relevant and actionable insights.

Artificial Intelligence 325

Artificial Intelligence Cloud Innovation Strategy 325

Dynatrace

JULY 6, 2022

While automating IT practices can save administrators a lot of time, without AIOps, the system is only as intelligent as the humans who program it. This kind of automation can support key IT operations, such as infrastructure, digital processes, business processes, and big-data automation. Big data automation tools.

Artificial Intelligence 246

Artificial Intelligence Tuning Strategy Big Data 246

Uber Engineering

APRIL 5, 2018

Three years ago, Uber Engineering adopted Hadoop as the storage ( HDFS ) and compute ( YARN ) infrastructure for our organization’s big data analysis.

Systems 109

Systems Big Data Storage Infrastructure 109

The Netflix TechBlog

JUNE 7, 2021

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. Network Availability: The expected continued growth of our ecosystem makes it difficult to understand our network bottlenecks and potential limits we may be reaching.

Network 327

Network Transportation AWS Cloud 327

Dynatrace

OCTOBER 25, 2022

Early implementations of NoOps were just ‘lift and shift’ efforts that replicated existing systems to the cloud. AIOps , a term coined by Gartner in 2016, combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination. Evolution of NoOps.

DevOps 246

DevOps Big Data Cloud Innovation 246

The Netflix TechBlog

JUNE 20, 2024

However, as the system has increased in scale and complexity, Pensive has been facing challenges due to its limited support for operational automation, especially for handling memory configuration errors and unclassified errors. Clark Wright, Staff Analytics Engineer at Airbnb, talked about the concept of Data Quality Score at Airbnb.

Data Engineering 206

Data Engineering Engineering Entertainment Software Engineering 206

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? Why is IT operations important?

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. tactical) in nature. Currently Iceberg sink is appended only.

Big Data 257

Big Data Government Processing Analytics 257

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Artificial Intelligence 254

Artificial Intelligence Social Media Monitoring IoT 254

Dynatrace

APRIL 11, 2023

Log4Shell required many organizations to take devices and applications offline to prevent malicious attackers from gaining access to IT systems and sensitive data. As a result, organizations need to be vigilant in identifying and addressing vulnerabilities to protect their systems and data.

Cloud 246

Cloud DevOps Open Source Retail 246

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Open source ER systems. ACM Computing Surveys, Dec. 2020, Article No. All of the discussed approaches require schemas.

Big Data 83

Big Data Open Source Processing Analytics 83

Dynatrace

MARCH 24, 2023

Containers enable developers to package microservices or applications with the libraries, configuration files, and dependencies needed to run on any infrastructure, regardless of the target system environment. This means organizations are increasingly using Kubernetes not just for running applications, but also as an operating system.

Infrastructure 246

Infrastructure Open Source Operating System Cloud 246

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 data warehouse is not designed to serve point requests from microservices with low latency.

Latency 252

Latency Storage Big Data Tuning 252

Dynatrace

AUGUST 10, 2021

She dispelled the myth that more big data equals better decisions, higher profits, or more customers. Investing in data is easy but using it is really hard”. The fact is, data on its own isn’t meaningful. Tricia quoted the statistic that companies typically use 3% of their data to inform decisions.

DevOps 246

DevOps Innovation Big Data Cloud 246

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. The four stages of data processing. This process continues until the system identifies a root cause. Two types of root cause.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

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 155

AWS Cloud Artificial Intelligence IoT 155

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. ICDE’16 (PowerDrill is a Google internal system).

Big Data 57

Big Data Analytics Latency Azure 57

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.” This contrasts stochastic AIOps approaches that use probability models to infer the state of systems. What is AIOps?

Artificial Intelligence 246

Artificial Intelligence DevOps Innovation Metrics 246

The Netflix TechBlog

MAY 26, 2020

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the Cloud Network Infrastructure to address the identified problems. These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines.

Network 154

Network Tuning AWS Traffic 154

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Monitoring 173

Monitoring Performance Social Media Artificial Intelligence 173

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Big Data Analytics Architecture 78

Scalegrid

FEBRUARY 11, 2025

Whether you need a relational database for complex transactions or a NoSQL database for flexible data storage, weve got you covered. Key Takeaways MySQL is a relational database management system ideal for structured data and complex relationships, ensuring data integrity and reliability.

Scalability 147

Scalability Database Storage IoT 147

All Things Distributed

APRIL 27, 2011

Werner Vogels weblog on building scalable and robust distributed systems. And while many of our systems are based on the latest in computer science research, this often hasnt been sufficient: our architects and engineers have had to advance research in directions that no academic had yet taken. All Things Distributed. Comments ().

Technology 129

Technology Technology AWS Storage 129

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

All Things Distributed

AUGUST 16, 2011

Werner Vogels weblog on building scalable and robust distributed systems. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics. AWS GovCloud (US) will be used by several of these agencies to help them with their Bigger-than-Big-Data needs.

AWS 90

AWS Government Big Data Cloud 90

All Things Distributed

AUGUST 22, 2011

Werner Vogels weblog on building scalable and robust distributed systems. Systems that make extensive use of caching almost all report a significant reduction in the cost of their database tier. Driving down the cost of Big-Data analytics. All Things Distributed. By Werner Vogels on 22 August 2011 07:40 PM.

Cloud 106

Cloud Cache AWS Storage 106

Scalegrid

MARCH 14, 2024

Understanding Hybrid Cloud Strategy A hybrid cloud merges the capabilities of public and private clouds into a singular, coherent system. This combination allows for the fluid movement of data and applications across different environments, facilitating shared workloads seamlessly. The tool must be compatible with your current systems.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130