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. What is your favorite project?

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

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. The processing mode – traditional batch (with or without budget constraints), or incremental. Block processing.

Big Data 83

Big Data Open Source Processing Analytics 83

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 238

Big Data Infrastructure Metrics Hardware 238

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 111

Big Data Analytics AWS Cloud 111

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. VLDB’19. Approximate query support.

Big Data 57

Big Data Analytics Latency Azure 57

Dynatrace

JULY 6, 2022

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

Dynatrace

OCTOBER 25, 2022

NoOps is a concept in software development that seeks to automate processes and eliminate the need for an extensive IT operations team. But it might also result in the entire software development process falling apart. Early implementations of NoOps were just ‘lift and shift’ efforts that replicated existing systems to the cloud.

DevOps 217

DevOps Big Data Cloud Innovation 217

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 Analytics Big Data Architecture 78

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?

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

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

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

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. To achieve these AIOps benefits, comprehensive AIOps tools incorporate four key stages of data processing: Collection. Aggregation.

Artificial Intelligence 284

Artificial Intelligence Cloud Innovation Strategy 284

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 186

Cloud DevOps Open Source Retail 186

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. Container orchestration is a process that automates the deployment and management of containerized applications and services at scale.

Infrastructure 186

Infrastructure Open Source Operating System Cloud 186

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.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

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 325

Network Transportation AWS Cloud 325

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

Scalegrid

MARCH 28, 2024

Redis can be configured to optimally utilize both RDB and AOF persistence methods optimally, achieving a balance between speed and data safety while minimizing the impact on response times due to its child process handling for disk writes. Data transfer technology. Cube or box Block chain of abstract financial data.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

AUGUST 10, 2021

Dynatrace CMO Mike Maciag talked about the dangers of “status quo” and failing to get where you need to go because of loyalty to legacy APM software, or hanging onto outdated processes. On the other hand, every single step you take towards intelligently observing data across your organization brings increasingly greater rewards.

DevOps 246

DevOps Innovation Big Data Cloud 246

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 212

Artificial Intelligence DevOps Innovation Metrics 212

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications – including your customers and employees. User Experience and Business Analytics ery user journey and maximize business KPIs.

Artificial Intelligence 180

Artificial Intelligence Social Media Monitoring IoT 180

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. User Experience and Business Analytics ery user journey and maximize business KPIs.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Current Telematics Architecture.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Testsigma

SEPTEMBER 8, 2021

In IT, however, the cloud means a lot more than just streaming media on the system. If I consider current times, it has become a core concept in development, management, analytics, and also – automation testing. Apart from cloud testing, you can also download various other testing modules on the system. Key Features.

Cloud 76

Cloud Testing AWS Testing Tools 76

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

What’s missing is a flexible, fast, and easy-to-use software system that can be quickly adapted to track these assets in real time and provide immediate answers for logistics managers. Within seconds, the software performs aggregate analysis of this data for all real-time digital twins.

Logistics 52

Logistics Analytics Scalability Cloud 52

The Morning Paper

SEPTEMBER 19, 2019

” Crusher is a Google system for automatically discovering email templates (e.g. It handles an order of magnitude more throughput than a prototype built on a stream processing engine. Could it be Analyzing efficient stream processing on modern hardware ? for machine generated emails sent to humans). What’s their secret???

Blockchain 46

Blockchain Hardware Google Analytics 46

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. Many changes are rendered through automated testing. Hyperautomation. IoT Test Automation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

All Things Distributed

AUGUST 16, 2011

Werner Vogels weblog on building scalable and robust distributed systems. ITAR is the International Traffic in Arms Regulatory framework which stipulates for example that data must be stored in an environment where physical and logical access is restricted to US Persons. Government and Big Data. All Things Distributed.

AWS 111

AWS Government Big Data Cloud 111

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Analytical databases are optimized for a low number of slow queries.

Database 40

Database Analytics Blockchain Healthcare 40

All Things Distributed

DECEMBER 20, 2017

For example, Kärcher, the maker of cleaning technologies, manages its entire fleet through the cloud solution "Kärcher Fleet" This transmits data from the company's cleaning devices e.g. about the status of maintenance and loading, when the machines are used, and where the machines are located. More than mere support.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

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. CDC events can also be sent to Data Mesh via a Java Client Producer Library.

Big Data 253

Big Data Government Analytics Processing 253

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data. Applications.

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

AUGUST 17, 2011

Werner Vogels weblog on building scalable and robust distributed systems. Amazon S3 is much more than just storage; the network and distributed systems infrastructure to ensure that content can be served fast and at high rates without customers impacting each other, is amazing. Driving down the cost of Big-Data analytics.

Servers 126

Servers Social Media AWS Website 126