ScaleOut Software

JUNE 22, 2020

In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

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. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

Analytics 202

Analytics Monitoring Artificial Intelligence DevOps 202

ScaleOut Software

JULY 14, 2021

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

IoT 52

IoT Azure Analytics Serverless 52

Dynatrace

OCTOBER 6, 2023

Buckets are similar to folders, a physical storage location. For example, a separate bucket could be used for detailed logs from Dynatrace Synthetic nodes. Debug-level logs, which also generate high volumes and have a shorter lifespan or value period than other logs, could similarly benefit from dedicated storage.

Artificial Intelligence 255

Artificial Intelligence Analytics Metrics Storage 255

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. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

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. Consider a simple example in which a message arrives signaling that a ventilator has been activated for a patient.

Logistics 52

Logistics Analytics Scalability Cloud 52

Dynatrace

APRIL 19, 2023

Enterprise data stores grow with the promise of analytics and the use of data to enable behavioral security solutions, cognitive analytics, and monitoring and supervision. For example, some security incidents have had a widespread, costly impact. . For example, credit card numbers are excluded by default.”

Design 184

Design Storage Programming Analytics 184

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

Dynatrace

AUGUST 24, 2020

But there are other related components and processes (for example, cloud provider infrastructure) that can cause problems in applications running on Kubernetes. Similarly, integrations for Azure and VMware are available to help you monitor your infrastructure both in the cloud and on-premises. Digital Business Analytics.

Analytics 234

Analytics Infrastructure AWS Operating System 234

Dynatrace

APRIL 21, 2022

Configuration API for AWS and Azure supporting services. You can now get a list of all AWS and Azure supporting services on your cluster, by current version, using the AWS credentials API and Azure credentials API respectively. Improved error handling for unexpected storage issues. (APM-360014). see Settings API.

Azure 209

Azure Metrics AWS Monitoring 209

Scalegrid

JANUARY 12, 2024

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. Storage is a critical aspect to consider when working with cloud workloads.

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

JANUARY 20, 2022

Azure supporting services (Synapse Analytics). RUM linking timeouts adjusted in transaction storage. (APM-341299). Resolved an issue that was causing alerts for infrastructure (for example, Host CPU) to be generated even when disabled. (APM-348563). Masking v1. Masking v2. See Available metrics. 5 (1 vulnerability).

Lambda 174

Lambda AWS Metrics Azure 174

Dynatrace

AUGUST 24, 2020

But there are other related components and processes ( for example, cloud provider infrastructure ) that can cause problems in applications running on Kubernetes. Similar ly, integrations for Azure and VMware are available to help you monitor your infrastructure both in the cloud and on-premises. . Conclusion.

Analytics 134

Analytics Infrastructure AWS Operating System 134

SQL Server According to Bob

DECEMBER 18, 2018

For example, if a flight booking reports that a seat has successfully been booked, then the seat will remain booked even if the system crashes.” – [link]. Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system. Patrick and Purvi doing performance and regression analytics.

Servers 90

Servers Media Cache Storage 90

O'Reilly

MAY 19, 2020

AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. But most Azure and GCP users also use AWS; the reverse isn’t necessarily true. In our AI adoption in the enterprise survey , for example, we had close to a 50/50 split between North America and the rest of the world.

Cloud 141

Cloud Serverless AWS Architecture 141

Abhishek Tiwari

NOVEMBER 3, 2018

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. Alternatively, you can upload output directory to cloud object/blob storage such as Amazon S3 or Azure Blob Storage and serve your site from there.

Systems 63

Systems Cache Website Network 63

ScaleOut Software

AUGUST 19, 2014

For example, consider a web server farm handling requests for web users or mobile apps. For example, when external requests from a web user are directed to different web servers, the user’s state has to be tracked independent of which server is handling the request. The Need to Keep It Simple.

Cloud 40

Cloud Azure Virtualization Scalability 40

ScaleOut Software

AUGUST 19, 2014

For example, consider a web server farm handling requests for web users or mobile apps. For example, when external requests from a web user are directed to different web servers, the user’s state has to be tracked independent of which server is handling the request. The Need to Keep It Simple.

Cloud 40

Cloud Azure Virtualization Scalability 40

Smashing Magazine

NOVEMBER 15, 2021

You can customize it to display information from sources like Google Analytics, GitHub, Feedly, shell command output, and more. For example, it’s been used to build several Node.js-based Storage is in plain text, includes Git-based versioning, wiki-style linking, color themes, and lots more. Require Node.js Large preview ).

Development 134

Development Google Storage Open Source 134

High Scalability

NOVEMBER 25, 2019

It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice.

Architecture 52

Architecture Cache Azure Storage 52