Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

O'Reilly Software

JUNE 12, 2018

This meant a lot of time was spent on things like cycle time analysis, build pipeline design, test automation, and infrastructure automation. Back then, the most common pattern I saw for service-based systems was sharing a database among multiple services. And data was at the heart of the problem. How do you do that effectively?

Database 72

Database Cache Architecture Latency 72

ScaleOut Software

JULY 19, 2021

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. The following diagram illustrates a typical workflow.

IoT 78

IoT Analytics Big Data Architecture 78

Scalegrid

DECEMBER 21, 2023

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. Redis® Monitoring Essentials Ensuring the performance, reliability, and safety of a Redis® database requires active monitoring. Monitoring tools should also be considered when setting up your Redis® database.

Strategy 130

Strategy Monitoring Latency DevOps 130

Scalegrid

JUNE 4, 2020

ScaleGrid is a fully managed DBaaS that supports MySQL, PostgreSQL and Redis™, along with additional support for MongoDB® database and Greenplum® database. Along with many popular cloud providers, DigitalOcean also provides a Managed Databases service. So, which database service is right for your application? Single Node.

Database 230

Database Latency Benchmarking Performance 230

The Morning Paper

MARCH 10, 2020

This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system. The paper examines three different uses of RocksDB at Facebook: UDB , the underlying storage engine for the MySQL databases storing the social graph data.

Benchmarking 59

Benchmarking Storage Cache Open Source 59

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Job Openings in AWS - Senior Leader in Database Services.

AWS 85

AWS Storage Cloud Big Data 85

The Netflix TechBlog

JUNE 13, 2023

By collecting and analyzing key performance metrics of the service over time, we can assess the impact of the new changes and determine if they meet the availability, latency, and performance requirements. Our system doesn’t require strict consistency guarantees and does not use database transactions.

Traffic 279

Traffic Metrics Systems Strategy 279

Percona

DECEMBER 11, 2023

Here, we will discuss a notable new feature in Amazon RDS, the Dedicated Log Volume (DLV), that has been introduced to boost database performance. A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables.

AWS 100

AWS Benchmarking Performance Traffic 100

Scalegrid

JANUARY 12, 2024

Simply put, it’s the set of computational tasks that cloud systems perform, such as hosting databases, enabling collaboration tools, or running compute-intensive algorithms. Storage is a critical aspect to consider when working with cloud workloads. What is workload in cloud computing? Additionally.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

JANUARY 31, 2024

million” – Gartner Data observability is a practice that helps organizations understand the full lifecycle of data, from ingestion to storage and usage, to ensure data health and reliability. This reduces the demand for further data flow analysis tools and clears any hurdles to making data useable for DevOps automation use cases.

DevOps 193

DevOps Analytics Airlines Metrics 193

Percona

DECEMBER 26, 2023

This PoC demonstrates how to install and configure pg_stat_monitor in order to extract useful and actionable metrics from a PostgreSQL database and display them on a Grafana dashboard. Grafana database backend: Prometheus version 2.15.2+d This simplifies debugging and analysis processes by enabling users to execute the same query.

Benchmarking 125

Benchmarking Metrics C++ Database 125

Highly Scalable

SEPTEMBER 18, 2012

These developments gradually highlight a system of relevant database building blocks with proven practical efficiency. In this article I’m trying to provide more or less systematic description of techniques related to distributed operations in NoSQL databases. Read/Write latency. Data Placement. System Coordination.

Database 213

Database Latency C++ Scalability 213

All Things Distributed

JUNE 21, 2018

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167

Database AWS Games Latency 167

Dynatrace

DECEMBER 22, 2021

Metrics are measures of critical system values, such as CPU utilization or average write latency to persistent storage. Once teams centralize their telemetry data, an observability platform can provide analysis that enriches the value of the data. Observability platforms provide root-cause analysis.

Artificial Intelligence 177

Artificial Intelligence Metrics Architecture DevOps 177

All Things Distributed

AUGUST 20, 2015

Today, we are releasing a plugin that allows customers to use the Titan graph engine with Amazon DynamoDB as the backend storage layer. It opens up the possibility to enjoy the value that graph databases bring to relationship-centric use cases, without worrying about managing the underlying storage. Enter graph databases.

Database 134

Database Logistics Availability Social Media 134

The Netflix TechBlog

NOVEMBER 2, 2021

This enables us to use our scale to increase throughput and reduce latencies. Here, based on the video length, the throughput and latency requirements, available scale etc., Similar to chunk-based encoding , the VQS workflow consists of chunk-based quality calculations, followed by an assembly step. The workflow is initiated.

Media 171

Media Innovation Metrics Latency 171

The Morning Paper

SEPTEMBER 10, 2019

Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. That’s hard for many reasons, including the differing trade-offs between throughput and latency that need to be made across the use cases. Reporting and dashboarding use cases (e.g.

Analytics 75

Analytics Latency Cache Google 75

ScaleOut Software

JULY 14, 2021

The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes. Acting as a switchboard for incoming and outgoing messages, Azure IoT Hub forms the core of these capabilities. Azure digital twins serve a different purpose.

IoT 52

IoT Azure Analytics Serverless 52

All Things Distributed

APRIL 9, 2015

AWS has been offering a range of storage solutions: objects, block storage, databases, archiving, etc. Amazon EFS is a fully-managed service that makes it easy to set up and scale shared file storage in the AWS Cloud. With Amazon EFS, there is no minimum fee or setup costs, and customers pay only for the storage they use.

Lambda 122

Lambda Cloud IoT AWS 122

The Morning Paper

JANUARY 26, 2020

Second, Reverb enables speculative bug fix analysis … Third, Reverb supports wide-area debugging for applications whose server-side components use event-driven architectures. Reverb also take a snapshot of the client’s local storage (e.g. The problem. cookies) at the start of logging.

Programming 86

Programming Servers Network Latency 86

Dynatrace

AUGUST 5, 2019

It covers these key areas: Technology & Dependency Analysis. Resource consumption & traffic analysis. Database & functional migration. Remember: This is a critical aspect as you do not want to migrate a service and suddenly introduce high latency or costs to a system that you forgot about having a dependency with!

Cloud 31

Cloud Traffic Database Network 31

Adrian Cockcroft

NOVEMBER 11, 2019

Collecting some critical metrics at one second intervals, with a total observability latency of ten seconds or less matches the human attention span much better. For systems that are latency sensitive, creating two independent ways to succeed is an important technique for greatly reducing the 99th percentile latency.

Latency 52

Latency Engineering Systems Hardware 52

Adrian Cockcroft

NOVEMBER 11, 2019

Collecting some critical metrics at one second intervals, with a total observability latency of ten seconds or less matches the human attention span much better. For systems that are latency sensitive, creating two independent ways to succeed is an important technique for greatly reducing the 99th percentile latency.

Latency 53

Latency Engineering Systems Hardware 53

All Things Distributed

NOVEMBER 15, 2010

For example, the most fundamental abstraction trade-off has always been latency versus throughput. Modern CPUs strongly favor lower latency of operations with clock cycles in the nanoseconds and we have built general purpose software architectures that can exploit these low latencies very well. Where to go from here?

AWS 136

AWS Latency Programming Architecture 136

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce. Case Study. References.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Alex Russell

APRIL 29, 2021

Chrome has missed several APIs for 3+ years: Storage Access API. For heavily latency-sensitive use-cases like WebXR, this is a critical component in delivering a good experience. The lesson for performance analysis is, as always, that one must always double-and-triple-check to ensure you're actually measuring what you hope to. ??.

Media 145

Media Games Education Engineering 145

Alex Russell

MARCH 6, 2021

A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. Sadly, data on latency is harder to get, even from Google's perch, so progress there is somewhat more difficult to judge. The Moto G4 , for example.

Performance 124

Performance Network Cache Metrics 124

Smashing Magazine

JANUARY 6, 2020

Treo Sites provides competitive analysis based on real-world data. Estimated Input Latency tells us if we are hitting that threshold, and ideally, it should be below 50ms. Large preview ). For high-pressure points like animation, it’s best to do nothing else where you can and the absolute minimum where you can't.

Performance 145

Performance Cache Network Metrics 145