Dynatrace

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. What is cloud monitoring? Best practices to consider. Define goals with a clear path to success. ” The post What is cloud monitoring?

Cloud 295

Cloud Monitoring Best Practices Infrastructure 295

Dynatrace

DECEMBER 15, 2022

To ensure resilience, ITOps teams simulate disasters and implement strategies to mitigate downtime and reduce financial loss. If malware, data corruption, or another security breach occurs, ITOps teams work with security teams to identify, isolate, and remediate affected systems to minimize damage and data loss. ITOps vs. AIOps.

Artificial Intelligence 246

Artificial Intelligence DevOps Hardware Virtualization 246

Dynatrace

JULY 6, 2020

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. See the health of your big data resources at a glance. Azure Front Door.

Azure 227

Azure Cloud Big Data Virtualization 227

Dynatrace

MARCH 14, 2022

The healthcare industry is embracing cloud technology to improve the efficiency, quality, and security of patient care, and this year’s HIMSS Conference in Orlando, Fla., AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 246

The Netflix TechBlog

JUNE 20, 2024

To handle errors efficiently, Netflix developed a rule-based classifier for error classification called “Pensive.” To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise.

Data Engineering 203

Data Engineering Engineering Entertainment Software Engineering 203

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. Dynamic approaches schedule block processing on the fly to maximise efficiency. ACM Computing Surveys, Dec.

Big Data 83

Big Data Open Source Processing Analytics 83

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. Alert fatigue and chasing false positives are not only efficiency problems. SecOps: Applying AIOps to secure applications in real time.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

The Netflix TechBlog

JULY 26, 2021

At Netflix Studio, teams build various views of business data to provide visibility for day-to-day decision making. With dependable near real-time data, Studio teams are able to track and react better to the ever-changing pace of productions and improve efficiency of global business operations using the most up-to-date information.

Big Data 255

Big Data Government Processing Analytics 255

DZone

DECEMBER 27, 2023

In this kickoff post, we delve into the intricacies of Apache Airflow and AWS EMR, a managed cluster platform for big data processing. Working together, they form the backbone of many modern data engineering solutions.

Best Practices 140

Best Practices Data Engineering Big Data Games 140

Scalegrid

FEBRUARY 8, 2024

Distributed storage systems like HDFS distribute data across multiple servers or nodes, potentially spanning multiple data centers, focusing on partitioning, scalability, and high availability for structured and unstructured data. By implementing data replication strategies, distributed storage systems achieve greater.

Storage 130

Storage Systems Big Data Azure 130

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 214

Processing Big Data Efficiency Engineering 214

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. All three sampling strategies are heavily used at Microsoft. VLDB’19.

Big Data 57

Big Data Analytics Latency Azure 57

The Netflix TechBlog

DECEMBER 21, 2020

We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits. This article will list some of the use cases of AutoOptimize, discuss the design principles that help enhance efficiency, and present the high-level architecture.

Storage 208

Storage Latency Efficiency Data Engineering 208

The Netflix TechBlog

FEBRUARY 16, 2021

As we expand offerings rapidly across the globe, our ideas and strategies around plans and offers are evolving as well. Operational Efficiency: The majority of the changes require metadata configuration files and library code changes, usually taking days of testing and service release to adopt the updates. What’s Next?

Mobile 214

Mobile Engineering Infrastructure Scalability 214

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. On the other hand, an append-only file ensures data safety by recording every write operation that modifies the dataset, allowing for complete data reconstruction in the event of a restart. Data transfer technology.

Cache 130

Cache Storage Architecture Scalability 130

Scalegrid

FEBRUARY 11, 2025

DBMS provides a systematic way to store, retrieve, and manage data, ensuring it remains organized and controlled. These systems are crucial for handling large volumes of data efficiently, enabling businesses and applications to perform complex queries, maintain data integrity, and ensure security.

Scalability 147

Scalability Database Storage IoT 147

The Netflix TechBlog

MARCH 2, 2021

I started working at a local payment processing company after graduation, where I built survival models to calculate lifetime value and experimented with them on our brand new big data stack. I was doing data science without realizing it. What best prepared you for your current role at Netflix?

Analytics 212

Analytics C++ Innovation Engineering 212

Scalegrid

JANUARY 10, 2025

They keep the features that developers like but can handle much more data, similar to NoSQL systems. Notably, they simplify handling big data flows, offer consistent transactions, and sustain high performance even when they’re used for real-time data analysis and complex queries.

Database 130

Database Scalability Best Practices Blockchain 130

All Things Distributed

JUNE 29, 2011

AWS also applies the same customer oriented pricing strategy: as the AWS platform grows, our scale enables us to operate more efficiently, and we choose to pass the benefits back to customers in the form of cost savings. Often customers are surprised about our strategy to help them drive their costs down.

AWS 83

AWS Retail Innovation Strategy 83

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” Isn’t it nice to uncover that in a simulated environment, where we can map out our risk mitigation strategies with calm, level heads?

Hardware 116

Hardware Storage Big Data Blockchain 116

Highly Scalable

MARCH 10, 2015

In this article we are trying to take a more rigorous approach and provide a systematic view of econometric models and objective functions that can leverage data analysis to make more automated decisions. were a subject of intensive research over the last century, if not longer. This framework resembles the approach suggested in [JK98].

Retail 152

Retail C++ Analytics Metrics 152

Testsigma

MAY 14, 2021

However, the primary goal of traditional testing and cloud-based testing remains the same i.e., to deliver high-quality and efficient software. Is there a possibility that moving testing to the cloud may lead to a change in the test strategy or foundation of testing? Cloud-based testing comprises cloud-based test automation as well.

Cloud 67

Cloud Testing Testing Tools Internet 67

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. This pattern should be broken.

Artificial Intelligence 70

Artificial Intelligence Social Media Logistics AWS 70

Tech News Gather

OCTOBER 7, 2023

In the ever-evolving landscape of business and marketing, where digital strategies often take center stage, it’s easy to overlook the enduring power of a simple phone call. Let’s explore why you should dedicate more thought and consideration to implementing a phone call tracking app in your business strategy.

Strategy 52

Strategy Big Data Scalability Games 52

Smashing Magazine

JULY 29, 2019

Read “ Efficiently load JavaScript with defer and async ” for more information. In Amazon’s case, there is room to make some big data savings on the desktop site and we shouldn’t get complacent just because the screen size suggests I’m not on a mobile device. This makes the script completely non-blocking. Large preview ).

Cache 99

Cache Mobile Google Network 99

Adrian Cockcroft

NOVEMBER 18, 2024

Paul Reed, Clean Energy & Sustainability, AWS Solutions, Amazon Web Services SUS101 | Advancing sustainable AWS infrastructure to power AI solutions In this session, learn how AWS is committed to innovating with data center efficiency and lowering its carbon footprint to build a more sustainable business.

AWS 98

AWS Energy Lambda Government 98

VoltDB

OCTOBER 17, 2024

Automotive manufacturers need real-time data for: Inventory Management The automotive supply chain is a complex network involving multiple suppliers, manufacturers, and distributors. Efficient supply chain management is crucial for minimizing production costs and meeting delivery schedules.

Automotive 52

Automotive IoT Energy Artificial Intelligence 52