The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Using network queue depths alone is enough to signal a large fraction of QoS violations, although smaller than when the full instrumentation is available. ASPLOS’19. Distributed tracing and instrumentation.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

JULY 6, 2020

Azure Virtual Network Gateways. Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure DB for PostgreSQL. Azure SQL Managed Instance. Azure HDInsight.

Azure 148

Azure Cloud Big Data Virtualization 148

ScaleOut Software

JULY 19, 2021

If a cyber network agent has observed an unusual pattern of failed login attempts, it needs to alert downstream network nodes (servers and routers) to block the kill chain in a potential attack. The list goes on. The Limitations of Today’s Streaming Analytics. A New Approach: Real-Time Device Tracking.

IoT 78

IoT Analytics Big Data Architecture 78

Scalegrid

MAY 13, 2020

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Greenplum Advantages.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

The Netflix TechBlog

SEPTEMBER 18, 2020

I bring my breadth of big data tools and technologies while Julie has been building statistical models for the past decade. They are continuously innovating compression algorithms to efficiently send high quality audio and video files to our customers over the internet. Is the benefit uniform, or do certain cohorts of members?—?such

Analytics 223

Analytics Education Innovation Engineering 223

Scalegrid

FEBRUARY 8, 2024

Handling Large Volumes of Data Distributed storage systems employ the technique of data sharding or partitioning to handle immense quantities of information. By breaking up large datasets into more manageable pieces, each segment can be assigned to various network nodes for storage and management purposes.

Storage 130

Storage Systems Big Data Azure 130

All Things Distributed

JUNE 26, 2016

AdiMap uses Amazon Kinesis to process real-time streaming online ad data and job feeds, and processes them for storage in petabyte-scale Amazon Redshift. Advanced problem solving that connects big data with machine learning. warehouses to glean business insights for jobs, ad spend, or financials for mobile apps.

AWS 90

AWS Cloud Healthcare Blockchain 90

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 100

Big Data Mobile Latency Database 100

Dynatrace

MAY 1, 2023

IT operations analytics is the process of unifying, storing, and contextually analyzing operational data to understand the health of applications, infrastructure, and environments and streamline everyday operations. ITOA collects operational data to identify patterns and anomalies for faster incident management and near-real-time insights.

Analytics 190

Analytics Artificial Intelligence Big Data Open Source 190

ScaleOut Software

NOVEMBER 24, 2020

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. The current telematics architecture also has inherent scalability issues in the form of network bottlenecks.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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 79

Artificial Intelligence Social Media Logistics AWS 79

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 Scalability Architecture 130

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 224

Cloud Monitoring Best Practices Infrastructure 224

The Netflix TechBlog

APRIL 29, 2019

Open Connect Open Connect is Netflix’s content delivery network (CDN). video streaming) takes place in the Open Connect network. The network devices that underlie a large portion of the CDN are mostly managed by Python applications. If any of this interests you, check out the jobs site or find us at PyCon. are you logged in?

Open Source 279

Open Source Network Infrastructure Big Data 279

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. It may have third-party calls, such as content delivery networks, or more complex requests to a back end or microservice-based application.

DevOps 198

DevOps Artificial Intelligence Healthcare Innovation 198

Dynatrace

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes.

Analytics 237

Analytics Artificial Intelligence Storage Serverless 237

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

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. Websites, mobile apps, and business applications are typical use cases for monitoring.

Artificial Intelligence 183

Artificial Intelligence Social Media Monitoring IoT 183

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. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

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.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 99

Hardware Storage Big Data Blockchain 99

The Morning Paper

SEPTEMBER 19, 2019

Could it be Analyzing efficient stream processing on modern hardware ? I don’t think so in this case, but this paper will take you down into the nitty-gritty of getting the best out of modern processors and networks, with up to two orders of magnitude single node throughput gains to be had. What’s their secret???

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

DECEMBER 12, 2018

We launched Edge Network locations in Denmark, Finland, Norway, and Sweden. Winning in this race requires that we become much more customer oriented, much more efficient in all of our operations, and at the same time shift our culture towards more lean and experimental. Telenor Connexion is all-in on AWS.

AWS 124

AWS Cloud Games Serverless 124

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

The Morning Paper

JUNE 23, 2019

We’ve seen similar high marshalling overheads in big data systems too.) Fetching too much data in a single query (i.e., If you decompose data across multiple keys to avoid this, you then typically run into cross-key atomicity issues. Over and above RTT times, the size of the data to be transferred also matters.

Cache 79

Cache Latency Google Lambda 79

Highly Scalable

JANUARY 31, 2012

It is worth noting that if MapReduce is used for sorting of the original (not intermediate) data, it is often a good idea to continuously maintain data in sorted state using BigTable concepts. In other words, it can be more efficient to sort data once during insertion than sort them for each MapReduce query.

C++ 144

C++ Network Ecommerce Processing 144

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. what is the cardinality of the data set)? bits per unique value.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Smashing Magazine

JULY 29, 2019

Many of us are lucky enough to be on mobile plans which allow several gigabytes of data transfer per month. Failing that, we are usually able to connect to home or public WiFi networks that are on fast broadband connections and have effectively unlimited data. As for mobile network connection type, 84.7% Mbps upload.

Cache 96

Cache Google Mobile Network 96

All Things Distributed

NOVEMBER 15, 2010

Now that our ability to generate higher and higher clock rates has stalled and CPU architectural improvements have shifted focus towards multiple cores, we see that it is becoming harder to efficiently use these computer systems. Driving down the cost of Big-Data analytics. Cluster Computer, Cluster GPU and Amazon EMR.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. These new offerings are organized on platforms or networks, and less so in processes.

Artificial Intelligence 77

Artificial Intelligence Technology Technology IoT 77

ACM Sigarch

NOVEMBER 1, 2019

Alongside more traditional sessions such as Real-World Deployed Systems and Big Data Programming Frameworks, there were many papers focusing on emerging hardware architectures, including embedded multi-accelerator SoCs, in-network and in-storage computing, FPGAs, GPUs, and low-power devices. Heterogeneous ISA. Final words.

Architecture 12

Architecture Hardware Cache Storage 12

Testsigma

FEBRUARY 12, 2021

The usage by advanced techniques such as RPA, Artificial Intelligence, machine learning and process mining is a hyper-automated application that improves employees and automates operations in a way which is considerably more efficient than conventional automation. Gartner’s 2020 projections first included the trend of hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node). Although such databases can be very efficient with counts and averages, some queries will be slow or simply non existent. Inserts are efficient for bulk inserts only. created_utc?? ?

Database 40

Database Analytics Blockchain Healthcare 40