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.

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

AIOps (or “AI for IT operations”) uses artificial intelligence so that big data can help IT teams work faster and more effectively. As AI becomes increasingly important to care delivery, the healthcare sector is pursuing a national strategy for AI. Gartner introduced the concept of AIOps in 2016.

Healthcare 246

Healthcare Artificial Intelligence Innovation Strategy 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. This strategy has increased the Studio Tech Solutions team performance and stability.

Big Data 255

Big Data Government Processing Analytics 255

The Netflix TechBlog

JUNE 20, 2024

To address this, we propose developing an intelligent agent that can automatically discover, map, and query all data within an enterprise. This “Enterprise Data Model/Architect Agent” employs generative AI techniques for autonomous enterprise data modeling and architecture.

Data Engineering 203

Data Engineering Engineering Entertainment Software Engineering 203

Dynatrace

APRIL 11, 2023

Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture. As organizations migrate applications to the cloud, they must balance the agility that microservices architecture brings with the complexity and lack of transparency that can also come with it.

Cloud 246

Cloud DevOps Open Source Retail 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. Achieving autonomous operations. The great promise of AIOps is to automate IT operations — or achieve autonomous operations.

DevOps 246

DevOps Artificial Intelligence Healthcare Innovation 246

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

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 Architecture Scalability 130

Scalegrid

FEBRUARY 11, 2025

Key Takeaways MySQL is a relational database management system ideal for structured data and complex relationships, ensuring data integrity and reliability. MongoDB stores data as JSON documents, presenting a flexible approach compared to the structured tabular format used by MySQL.

Scalability 147

Scalability Database Storage IoT 147

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 214

Processing Big Data Efficiency Engineering 214

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

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

All Things Distributed

AUGUST 19, 2011

AWS Database Services is responsible for setting the database strategy and delivering distributed structured storage services to our AWS customers. This team is constantly rethinking the assumptions behind how traditional databases were built and constantly working on building the right database architectures suited for the Cloud environment.

AWS 65

AWS Database Storage Scalability 65

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. Information Architecture. Web Performance Daybook-Volume-2. The Art of SEO. Site speed & SEO go hand in hand.

Performance 75

Performance Social Media Website Website Performance 75

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. In addition, this approach is more tailored for both structured as well unstructured data sets. Classic ETL. Challenges.

Big Data 40

Big Data Retail Storage Google 40

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. RE94] Grouplens: an open architecture for collaborative filtering of netnews, P. PZ07] Content-based Recommendation Systems, M.

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

DECEMBER 20, 2017

Marketers use big data and artificial intelligence to find out more about the future needs of their customers. Also, trade with data contributes more to global growth than trade with goods. Therefore, IT has never been more important for strategy than it is now – not only for us, but for every company in the digital age.

Artificial Intelligence 70

Artificial Intelligence Social Media Logistics AWS 70

ACM Sigarch

APRIL 8, 2019

Computer architecture is an important and exciting field of computer science, which enables many other fields (eg. big-data processing, machine learning, quantum computing, and so on). For those of us who pursued computer architecture as a career, this is well understood. Why is that? Should we be alarmed as a community?

Architecture 74

Architecture Open Source Hardware Software Engineering 74

Adrian Cockcroft

NOVEMBER 18, 2024

Discover data sources to gain insights into your resource efficiency and environmental impact, including the AWS Customer Carbon Footprint Tool and proxy metrics from the AWS Cost & Usage Reports. This lightning talk explores how companies can cut costs and carbon emissions through architectural best practices and workload optimization.

AWS 98

AWS Energy Lambda Government 98