Dotcom-Montior

OCTOBER 6, 2021

Site reliability engineers are focused with creating scalable and reliable software systems, so this also includes ensuring that development work is efficient and reliable, so when the finished product is ready for production, there are no surprises. that are required to keep the software deployments live are running efficiently.

Engineering 67

Engineering DevOps Monitoring Google 67

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Logs can include data about user inputs, system processes, and hardware states. What is log analytics? Log monitoring vs log analytics.

Analytics 208

Analytics Monitoring Artificial Intelligence DevOps 208

Scalegrid

FEBRUARY 8, 2024

Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. This strategy reduces the volume needed during retrieval operations.

Storage 130

Storage Systems Big Data Azure 130

Dotcom-Montior

DECEMBER 8, 2021

By ITIL definition, the service desk may take the form of incident resolution or service requests, but whatever the case, the primary goal of the service desk to provide quick and efficient service. Software services still require physical devices and hardware for them to function. Problem Management. Asset Management.

Social Media 90

Social Media Monitoring Latency DevOps 90

Testsigma

JULY 3, 2021

More control: While performing on-premise testing, organizations have more control over configurations, setup, hardware, and software. Honestly, this is not time-effective at all if you’re aiming for efficiency and speed. If you configure a test environment and run into any errors, those will reflect in your test efficiency.

Cloud 57

Cloud Testing Storage DevOps 57

VoltDB

JUNE 29, 2017

However, increasing hardware capacity doesn’t really solve the problem, and it introduces new ones. If increasing hardware is the “work harder” answer to header bidding, then “work smarter” is the better option. DSPs and SSPs need to filter out low-value data quickly and cost-efficiently to free up capacity.

Performance 40

Performance Hardware Latency Infrastructure 40

VoltDB

JUNE 29, 2017

However, increasing hardware capacity doesn’t really solve the problem, and it introduces new ones. If increasing hardware is the “work harder” answer to header bidding, then “work smarter” is the better option. DSPs and SSPs need to filter out low-value data quickly and cost-efficiently to free up capacity.

Performance 40

Performance Hardware Latency Infrastructure 40

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. A data pipeline is a software which runs on hardware. The software is error-prone and hardware failures are inevitable. Data pipeline initiatives are generally unfinished projects.

Latency 63

Latency Analytics Scalability Engineering 63

All Things Distributed

DECEMBER 20, 2017

The benefit for customers: Authorized users can view this data and therefore manage their inventories across different sites, making the maintenance processes much more efficient. We need mechanisms that enable the mass production of data using software and hardware capabilities. This pattern should be broken.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

Scalegrid

DECEMBER 21, 2023

This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency. Command-Line Analysis Commanding the Redis CLI efficiently requires knowledge of every command’s function and how to decipher its output. It’s equally important to put preventative measures in place.

Strategy 130

Strategy Monitoring Latency DevOps 130

Smashing Magazine

JANUARY 15, 2019

how much data does the browser have to download to display your website) and resource usage of the hardware serving and receiving the website. It seems to have become more-or-less ubiquitous on the web for everyone to analyze what their website’s visitors do via tools like Google Analytics, KISSmetrics, Piwik, etc.

Website Performance 73

Website Performance Website Energy Performance 73

Scalegrid

DECEMBER 6, 2023

ScaleGrid’s comprehensive solutions provide automated efficiency and cost reduction while offering tailored features such as predictive analytics for businesses of all sizes. This includes being able to select the right hardware options for the job, enforcing desired safety measures, and having access to a variety of database software.

Database 130

Database Cloud Hardware Storage 130

Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

All Things Distributed

MARCH 13, 2017

Digitalization offers almost endless possibilities to communicate faster, work more efficiently, and be more creative – in real-time. Previously, the top priorities for IT departments were equipping data centers with hardware, purchasing software, and further developing proprietary software.

Social Media 84

Social Media Retail Automotive Innovation 84

Highly Scalable

AUGUST 20, 2013

The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. Thus, on a conceptual level, an efficient query engine in a distributed database can act as a stream processing system and vice versa, a stream processing system can act as a distributed database query engine. Pipelining.

Big Data 154

Big Data Processing Lambda Database 154

Dynatrace

FEBRUARY 23, 2022

IaC, or software intelligence as code , codifies and manages IT infrastructure in software, rather than in hardware. According to a Gartner report, “By 2023, 60% of organizations will use infrastructure automation tools as part of their DevOps toolchains, improving application deployment efficiency by 25%.”.

Serverless 264

Serverless Infrastructure Innovation DevOps 264

Dynatrace

JULY 11, 2023

By leveraging the Dynatrace Operator and Dynatrace capabilities on Red Hat OpenShift on IBM Power, customers can accelerate their modernization to hybrid cloud and increase operational efficiencies with greater visibility across the full stack from hardware through application processes.

Architecture 169

Architecture Availability Infrastructure Metrics 169

The Netflix TechBlog

APRIL 29, 2019

Such applications track the inventory of our network gear: what devices, of which models, with which hardware components, located in which sites. Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud.

Open Source 279

Open Source Network Infrastructure Big Data 279

Dynatrace

SEPTEMBER 29, 2021

Container technology is very powerful as small teams can develop and package their application on laptops and then deploy it anywhere into staging or production environments without having to worry about dependencies, configurations, OS, hardware, and so on. The time and effort saved with testing and deployment are a game-changer for DevOps.

Open Source 301

Open Source Traffic DevOps Cloud 301

HammerDB

JUNE 27, 2022

It enables the user to measure database performance and make comparative judgements about database hardware and software. The TPC designed benchmarks for transaction processing (OLTP) and analytics (OLAP) and anyone can run these benchmarks, have them audited by the TPC and published on the official benchmark rankings.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Dynatrace

OCTOBER 1, 2021

In these modern environments, every hardware, software, and cloud infrastructure component and every container, open-source tool, and microservice generates records of every activity. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

Dynatrace

OCTOBER 28, 2020

This enables organizations to innovate faster, collaborate more efficiently, and deliver more value with dramatically less effort. There’s a more efficient way with Dynatrace. And even Digital business analytics. Read below to see what you get with the Dynatrace platform.

Monitoring 146

Monitoring Systems Infrastructure Cloud 146

Dotcom-Montior

NOVEMBER 24, 2021

Software and hardware components are autonomous and execute tasks concurrently. A distributed system comprises of a variety of hardware and software components with different operating systems and technologies, meaning the processors are separate and independent of each other. State is distributed through the system. Concurrency.

Systems 74

Systems Monitoring Hardware Network 74

O'Reilly

NOVEMBER 28, 2023

That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure. Several respondents also mentioned working with video: analyzing video data streams, video analytics, and generating or editing videos. It’s good to see issues like safety and security near the top of the list.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

Dynatrace

DECEMBER 20, 2019

There’s a more efficient way with Dynatrace! You can’t keep pace by simply upgrading to the latest hardware and updating to the latest release twice a year. AppMon is still the best-in-class second-generation APM solution, but it requires you to instrument each process manually and pick the corresponding agent technology.

Infrastructure 134

Infrastructure Cloud Government Monitoring 134

The Morning Paper

SEPTEMBER 19, 2019

Could it be Analyzing efficient stream processing on modern hardware ? Hyper Dimension Shuffle describes how Microsoft improved the cost of data shuffling, one of the most costly operations, in their petabyte-scale internal big data analytics platform, SCOPE. for machine generated emails sent to humans). What’s their secret???

Blockchain 46

Blockchain Hardware Google Analytics 46

Percona

DECEMBER 14, 2022

Online analytical processing , OLAP : Online analytical processing applications enable users to analyze multidimensional data interactively from multiple perspectives which consist of three basic analytical operations: . But while eminently capable of performing OLAP, it’s not quite as efficient. consolidation (roll-up).

Database 92

Database Analytics Storage Processing 92

HammerDB

FEBRUARY 25, 2021

For the TPROC-H workload this is all we need the queries are long-running analytics queries so once executed on the database do not need to wait for the benchmarking client. However, having the application logic in the client is even worse because you are sacrificing key database efficiencies of prepared statements. select top 100.

Programming 67

Programming Benchmarking Virtualization C++ 67

All Things Distributed

JULY 14, 2015

In traditional database architectures, database engines often run a small search engine or data warehouse engines on the same hardware as the database. Also, you can choose to program post-commit actions, such as running aggregate analytical functions or updating other dependent tables.

Database 167

Database Lambda AWS IoT 167

Abhishek Tiwari

DECEMBER 27, 2017

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. Apache Arrow's in-memory columnar layout is specifically optimized for data locality for better performance on modern hardware like CPUs and GPUs.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

O'Reilly

OCTOBER 11, 2022

Andrew Ng , Christopher Ré , and others have pointed out that in the past decade, we’ve made a lot of progress with algorithms and hardware for running AI. Our current set of AI algorithms are good enough, as is our hardware; the hard problems are all about data. But the gain in efficiency would be relatively small.

Games 116

Games Healthcare Processing Retail 116

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. General Purpose GPU programming.

AWS 136

AWS Latency Programming Architecture 136

The Morning Paper

SEPTEMBER 12, 2019

SQL provides a declarative programming interface, below which the system itself can figure out the most effective execution plans based on data size and statistics, layout, compute hardware etc. Declarative recursive computation on an RDBMS… or, why you should use a database for distributed machine learing Jankov et al., VLDB’19.

Network 44

Network Database Programming Hardware 44

Alex Russell

JANUARY 30, 2024

HTML, CSS, images, and fonts can all be parsed and run at near wire speeds on low-end hardware, but JavaScript is at least three times more expensive, byte-for-byte. Predictably, they are over-represented in analytics and logs owing to wealth-related factors including superior network access and performance hysteresis."

Performance 90

Performance Network Mobile Speed 90

O'Reilly Software

APRIL 4, 2018

A message-oriented implementation requires an efficient messaging backbone that facilitates the exchange of data in a reliable and secure way with the lowest latency possible. It enables unbounded scalability as more commodity or specialized hardware can be seamlessly added to existing clusters. Build on the shoulders of giants.

Architecture 80

Architecture Scalability Google Operating System 80

All Things Distributed

JANUARY 18, 2012

DynamoDB frees developers from the headaches of provisioning hardware and software, setting up and configuring a distributed database cluster, and managing ongoing cluster operations. Additional request capacity is priced at cost-efficiently hourly rates as low as $.01

Scalability 167

Scalability Database Ecommerce Latency 167

Alex Russell

JULY 14, 2021

Hardware access APIs, notably: Geolocation. Standard tools, analytics packages, and feature availability dashboards do not make mention of IABs, and the largest WebView IAB promulgators (Facebook, Pinterest, Snap, etc.) Basic navigation and window management features to (e.g. Web OTP (for easier/faster sign-in). Web Bluetooth.

Google 121

Google Mobile Engineering Internet 121