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 180

Cloud DevOps Open Source Retail 180

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 145

Azure Cloud Big Data Virtualization 145

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

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

Dynatrace

MAY 1, 2023

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Choose a repository to collect data and define where to store data.

Analytics 182

Analytics Artificial Intelligence Big Data Open Source 182

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

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 75

AWS Database Storage Scalability 75

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. Hybrid cloud combines an on-premises or private data center with public cloud infrastructure. What is cloud monitoring?

Cloud 217

Cloud Monitoring Best Practices Infrastructure 217

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 79

Artificial Intelligence Social Media Logistics AWS 79

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 253

Big Data Government Analytics Processing 253

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 189

DevOps Artificial Intelligence Healthcare Innovation 189

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 210

Processing Big Data Efficiency Engineering 210

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 203

Storage Latency Efficiency Data Engineering 203

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

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