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. With these goals in mind, two in-memory data stores, Redis and Memcached, have emerged as the top contenders.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

APRIL 20, 2023

Logs highlight observability challenges Ingesting, storing, and processing the unprecedented explosion of data from sources such as software as a service, multicloud environments, containers, and serverless architectures can be overwhelming for today’s organizations. Seamless integration.

Analytics 187

Analytics Infrastructure Storage Efficiency 187

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

Big Data 162

Big Data Government Open Source Storage 162

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. Website monitoring examines a cloud-hosted website’s processes, traffic, availability, and resource use. Cloud storage monitoring.

Cloud 220

Cloud Monitoring Best Practices Infrastructure 220

Dynatrace

FEBRUARY 16, 2023

The goal is to turn more data into insights so the whole organization can make data-driven decisions and automate processes. Grail data lakehouse delivers massively parallel processing for answers at scale Modern cloud-native computing is constantly upping the ante on data volume, variety, and velocity.

Analytics 186

Analytics Innovation Metrics Database 186

Dynatrace

MARCH 24, 2023

Container orchestration is a process that automates the deployment and management of containerized applications and services at scale. Container orchestration enables organizations to manage and automate the many processes and services that comprise workflows. How does container orchestration work? appeared first on Dynatrace news.

Infrastructure 186

Infrastructure Open Source Operating System Cloud 186

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? ITOps vs. AIOps.

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.

Traffic 339

Traffic Latency Tuning Systems 339

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention.

IoT 78

IoT Analytics Big Data Architecture 78

The Morning Paper

OCTOBER 26, 2020

Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. These two narratives of reference architecture and ingestion/indexing system are interwoven throughout the paper. Why do we need a new reference architecture?

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

JANUARY 16, 2023

Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments. Specifically, they provide asynchronous communications within microservices architectures and high-throughput distributed systems.

Open Source 343

Open Source Java Operating System Programming 343

The Netflix TechBlog

OCTOBER 15, 2019

Another thread or process is constantly polling events from the log table and writes them to one or multiple datastores, optionally removing events from the log table after acknowledged by all datastores. Thus, ensuring the atomicity of writes across different storage technologies remains a challenging problem for applications [3].

Transportation 192

Transportation Architecture Processing Storage 192

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

Percona

JANUARY 19, 2023

Compression: Compression is the process of restructuring the data by changing its encoding in order to store it in fewer bytes. There are many compression tools and algorithms for data out there. It can help us to save costs on storage and backup times. 1 mysql mysql 592K Dec 30 02:48 tb1.ibd ibd -rw-r --. ibd -rw-r --.

Open Source 86

Open Source Storage Database Big Data 86

The Netflix TechBlog

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. On the other hand, these optimizations themselves need to be sufficiently inexpensive to justify their own processing cost over the gains they bring.

Storage 203

Storage Latency Efficiency Data Engineering 203

All Things Distributed

JUNE 26, 2016

(previously known as Emdeon) uses Amazon SNS to handle millions of confidential client transactions daily to process claims and pharmacy requests serving over 340K physicians and 60K pharmacies in full compliance with healthcare industry regulations. . Seamless ingestion of large volumes of sensed data.

AWS 90

AWS Cloud Healthcare Blockchain 90

All Things Distributed

DECEMBER 8, 2016

It adopted Amazon Redshift, Amazon EMR and AWS Lambda to power its data warehouse, big data, and data science applications, supporting the development of product features at a fraction of the cost of competing solutions. Kik Interactive is a Canadian chat platform with hundreds of millions of users around the globe.

AWS 155

AWS Cloud Lambda Innovation 155

The Morning Paper

JUNE 23, 2019

Factor VI in the 12-factor app manifesto , “Execute the app as one or more stateless processes,” to be dropped and replaced with “Execute the app as one or more stateful processes.” session state that you want to survive an application process crash), and to keep the application server/services layer stateless.

Cache 79

Cache Latency Google Lambda 79

ACM Sigarch

NOVEMBER 1, 2019

This blog post gives a glimpse of the computer systems research papers presented at the USENIX Annual Technical Conference (ATC) 2019, with an emphasis on systems that use new hardware architectures. As a consequence, the vast majority of the papers in the past has usually focused on conventional X86 or GPU-accelerated architectures.

Architecture 12

Architecture Hardware Cache Storage 12

All Things Distributed

SEPTEMBER 6, 2013

Shell leverages AWS for big data analytics to help achieve these goals. Due to the exponential growth of the biology and informatics fields, Unilever needs to maintain this new program within a highly-scalable environment that supports parallel computation and heavy data storage demands.

Cloud 129

Cloud Energy AWS Healthcare 129

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. This allows quick answers to questions such as: “Show me the percentage shortfall in ventilators by state.”.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

For example, the parameters for a ventilator could include its identifier, make and model, current location, status (in use, in storage, broken), time in use, technical issues and repairs, and contact information. This allows quick answers to questions such as: “Show me the percentage shortfall in ventilators by state.”.

Logistics 52

Logistics Analytics Scalability Cloud 52

All Things Distributed

JULY 13, 2010

Customers with complex computational workloads such as tightly coupled, parallel processes, or with applications that are very sensitive to network performance, can now achieve the same high compute and networking performance provided by custom-built infrastructure while benefiting from the elasticity, flexibility and cost advantages of Amazon EC2.

Cloud 118

Cloud AWS Automotive Latency 118

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 processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

APRIL 27, 2011

To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Look inside a current textbook on software architecture, and youll find few patterns that we dont apply at Amazon.

Technology 151

Technology Technology AWS Storage 151

All Things Distributed

MARCH 28, 2011

The methods for accessing these objects is also rapidly changing; where in the past you needed a PC or a Laptop to access these objects, now many of our electronic devices have become capable of processing them. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. At werner.ly Syndication.

AWS 138

AWS Cloud Storage Internet 138

All Things Distributed

NOVEMBER 15, 2010

From financial processing and traditional oil & gas exploration HPC applications to integrating complex 3D graphics into online and mobile applications, the applications of GPU processing appear to be limitless. Because of its focus on latency, the generic CPU yielded rather inefficient system for graphics processing.

AWS 136

AWS Latency Programming Architecture 136