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. ” This data is excluded from storage, but teams can still gain value from data enrichment beforehand. Why perform exclusion at two points? Encryption.

Design 246

Design Storage Programming Analytics 246

Dynatrace

JUNE 6, 2023

Additionally, service meshes — such as those offered by Istio, Linkerd, and Consul Connect — help to manage internetwork communication at the platform layer using purpose-built application programming interfaces. Traditional storage solutions were not created to address these requirements, which are common among modern deployments.

Open Source 246

Open Source Storage Analytics Innovation 246

Dynatrace

APRIL 8, 2024

Collect data automatically and pre-processed from a range of sources: application programming interfaces, integrations, agents, and OpenTelemetry. Historically, IT infrastructure performance, IT security, data architecture, and data analytics, have been managed in disparate, unconnected silos deep within IT organizational structures.

Analytics 246

Analytics Infrastructure Efficiency Technology 246

Dynatrace

SEPTEMBER 30, 2021

Major cloud providers such as AWS offer certification programs to help technology professionals develop and mature their cloud skills. AWS Certified Data Analytics – Specialty: Highly knowledgeable data analytics pros who have already worked with AWS for some time should consider getting this certification. Data analytics.

AWS 246

AWS Best Practices Cloud Analytics 246

Dynatrace

OCTOBER 17, 2023

Dynatrace has developed the purpose-built data lakehouse, Grail , eliminating the need for separate management of indexes and storage. All data is readily accessible without storage tiers, such as costly solid-state drives (SSDs). No storage tiers, no archiving or retrieval from archives, and no indexing or reindexing.

Retail 264

Retail Storage Best Practices Architecture 264

Dynatrace

FEBRUARY 14, 2022

Building on its advanced analytics capabilities for Prometheus data , Dynatrace now enables you to create extensions based on Prometheus metrics. Dynatrace makes it radically simple to ingest all the monitoring data you need by integrating with a wide variety of platforms, applications, programming languages, and data formats.

Technology 246

Technology Technology Metrics Infrastructure 246

Dynatrace

DECEMBER 20, 2021

In practice, session recording solutions make use of the document object model (DOM), which is a programming interface for web pages and document. Improved analytic context. While data analysis tools such as Google Analytics provide statistics based on user experiences, they lack details about what the user is doing and experiencing.

Mobile 264

Mobile Website Analytics Cache 264

The Netflix TechBlog

MARCH 10, 2023

are stored in secure storage layers. Amsterdam is built on top of three storage layers. And finally, we have an Apache Iceberg layer which stores assets in a denormalized fashion to help answer heavy queries for analytics use cases. It is also responsible for asset discovery, validation, sharing, and for triggering workflows.

Strategy 261

Strategy Cache Analytics Storage 261

Dynatrace

DECEMBER 15, 2022

In this blog, we share three log ingestion strategies from the field that demonstrate how building up efficient log collection can be environment-agnostic by using our generic log ingestion application programming interface (API). In the “Storage and Logging” section, select “ awsfirelens ” as the log driver.

Strategy 245

Strategy AWS Open Source Transportation 245

Dynatrace

NOVEMBER 4, 2022

According to the survey, the key challenges CIOs face in unlocking greater value from observability data include the unavailability of data for analytics on demand (56%), inability to keep the data that is deemed critical in hot storage due to the cost (40%), and centralizing log management because it is difficult and time-consuming (35%). .

Government 147

Government Analytics Cloud Storage 147

Scalegrid

OCTOBER 7, 2019

The supported programming languages for PostgreSQL include.Net, C, C++, Delphi, Java, JavaScript (Node.js), Perl, PHP, Python and Tcl, but PostgreSQL can support many server-side procedural languages through its available extensions. We found that Java is the most popular programming language for PostgreSQL, being leveraged by 31.1%

Strategy 182

Strategy Cloud Java Open Source 182

All Things Distributed

DECEMBER 13, 2016

GoSquared provides various analytics services that web and mobile companies can use to understand their customers' behaviors. At re:Invent 2016 , AWS announced Greengrass (in limited preview), a new service designed to extend the AWS programming model to small, simple, field-based devices. Fraud.net is a good example of this.

AWS 155

AWS Cloud Artificial Intelligence IoT 155

Dynatrace

FEBRUARY 15, 2023

Additionally, its modern architecture delivers cost-effective storage and compute. As a result, teams benefit from low-cost cloud storage that provides access to all data and doesn’t require data rehydration. Teams can visualize an application’s vital signs, including its security posture. Site Reliability Guardian.

Analytics 130

Analytics Storage Cloud Code 130

Dynatrace

NOVEMBER 17, 2020

With these release candidate APIs available, instrumentation for web frameworks, storage clients, and much more can be built. For instance, we are working on OpenTelemetry metrics exporters for popular programming languages which will automatically tap into metrics exposed via OpenTelemetry instrumentation.

Open Source 207

Open Source Software Engineering Government Java 207

All Things Distributed

MAY 18, 2010

Expanding the Cloud - Amazon S3 Reduced Redundancy Storage. Today a new storage option for Amazon S3 has been launched: Amazon S3 Reduced Redundancy Storage (RRS). This new storage option enables customers to reduce their costs by storing non-critical, reproducible data at lower levels of redundancy. Comments ().

Storage 64

Storage Cloud AWS Scalability 64

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 63

Programming IoT Java Analytics 63

All Things Distributed

NOVEMBER 15, 2010

We believe that making these GPU resources available for everyone to use at low cost will drive new innovation in the application of highly parallel programming models. General Purpose GPU programming. But with the third generation interfaces, the true power of General Purpose GPU programming was unlocked. From CPU to GPU.

AWS 125

AWS Programming Latency Architecture 125

Scalegrid

JANUARY 12, 2024

Storage is a critical aspect to consider when working with cloud workloads. High availability storage options within the context of cloud computing involve highly adaptable storage solutions specifically designed for storing vast amounts of data while providing easy access to it. What is an example of a workload?

Cloud 130

Cloud Virtualization Storage Efficiency 130

All Things Distributed

SEPTEMBER 6, 2013

Shell leverages AWS for big data analytics to help achieve these goals. Unilever – Unilever R&D program intended to accelerate the company’s scientific progress through improved access to global information. Shell''s scientists, especially the geophysicists and drilling engineers, frequently use cloud computing to run models.

Cloud 102

Cloud Energy AWS Healthcare 102

Scalegrid

MARCH 28, 2024

This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. It uses a hash table to manage these pairs, divided into fixed-size buckets with linked lists for key-value storage. Redis Database Management with ScaleGrid ScaleGrid.io

Cache 130

Cache Storage Architecture Scalability 130

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

All Things Distributed

JANUARY 19, 2011

Flexibility is one of the key principles of Amazon Web Services - developers can select any programming language and software package, any operating system, any middleware and any database to build systems and applications that meet their requirements. Driving Storage Costs Down for AWS Customers. Comments (). At werner.ly Syndication.

AWS 99

AWS Cloud Java Scalability 99

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. All the tedious tasks such as storage, backups, and configuration are managed by an attentive crew so that you can concentrate on making your vacation special.

Database 130

Database Cloud Hardware Storage 130

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Big Data Analytics Architecture 78

The Netflix TechBlog

MAY 21, 2019

There are several problems efficient test scheduling could help us solve: Quickly detect a regression in the integration of the Netflix SDK on a consumer electronic or MVPD (multichannel video programming distributor) device. The data can be truncated after each execution and offloaded to a long-term storage for further analysis.

Testing 163

Testing AWS Lambda Network 163

Percona

MARCH 30, 2023

Further, open source databases can be modified in infinite ways, enabling institutions to meet their specific needs for data storage, retrieval, and processing. Non-relational databases: Instead of tables, non-relational (NoSQL) databases use document-based data storage, column-oriented storage, and graph databases.

Open Source 106

Open Source Database Storage Scalability 106

ScaleOut Software

SEPTEMBER 20, 2018

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.

Programming 40

Programming IoT Java Analytics 40

All Things Distributed

MARCH 24, 2011

The TNW team is doing a great job in getting an excellent program together that draws an audience from around the world, not just Europe, and there is an interesting mix of startups, enterprises, investors and media attending. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway.

AWS 75

AWS Internet Internet Storage 75

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

HammerDB

JUNE 27, 2022

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. What programming languages does HammerDB use and why does it matter? Adoption by the TPC. Derived Workloads.

Benchmarking 63

Benchmarking Open Source C++ Cache 63

VoltDB

JUNE 26, 2024

Using real-time streaming data and analytics, manufacturers can optimize workflows in the moment, reducing bottlenecks and minimizing downtime. Using predictive analytics, manufacturers can anticipate potential quality issues before they occur, allowing for proactive adjustments.

IoT 52

IoT Analytics Artificial Intelligence Energy 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

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