Dynatrace

FEBRUARY 15, 2023

Further, developers can build more agility into their processes with an intuitive, low-code approach to create custom, compliant, and intelligent data-driven apps and automation. This app also showcases AppEngine’s ability to unlock actionable insights from data through enrichment, visualization, and analytics.

Analytics 130

Analytics Storage Cloud Code 130

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. can enhance Redis by handling management tasks, backups, and scalability, facilitating global reach and easy cloud integration for global businesses.

Cache 130

Cache Storage Scalability Architecture 130

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 52

Analytics Social Media Serverless Cloud 52

Dynatrace

NOVEMBER 10, 2022

To take full advantage of the scalability, flexibility, and resilience of cloud platforms, organizations need to build or rearchitect applications around a cloud-native architecture. Taken together, these features enable organizations to build software that is more scalable, reliable, and flexible than traditionally built software.

Cloud 162

Cloud Architecture Serverless Infrastructure 162

Dynatrace

OCTOBER 17, 2023

As a result, IT organizations are overwhelmed as they strive to balance cost control processes with ensuring that their respective organizations have access to all the data required for their various use cases. Ingest and process. In contrast, answer-centric pricing simply charges customers when they query data. Transparency.

Retail 233

Retail Storage Best Practices Architecture 233

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. Safeguarding information privacy must be taken very seriously as any processing entrusted to outside suppliers could become a cause for concern.

Database 130

Database Cloud Hardware Storage 130

ScaleOut Software

SEPTEMBER 20, 2018

These are exciting times in the evolution of stream-processing. As we have seen in previous blogs , the digital twin model offers a breakthrough approach to structuring stateful stream-processing applications. It represents a big step forward for building stream-processing applications.

Programming 40

Programming IoT Java Analytics 40

Dynatrace

DECEMBER 15, 2022

While engaging the automatic instrumentation of the Dynatrace OneAgent makes log ingestion automatic and scalable , our customers have set up multiple other log ingestion methods. Fluentd is known for its flexibility and is also highly scalable, which makes it a good choice for high-volume environments. Log ingestion strategy no.

Strategy 177

Strategy AWS Open Source Transportation 177

HammerDB

FEBRUARY 25, 2021

However, it is crucial that the benchmarking application does not have inherent bottlenecks that artificially limits the scalability of the database. This is why the choice of programming language is so important from the outset. Top 10 Processes. and the following from TPROC-H. select top 100. where p_partkey = ps_partkey.

Programming 67

Programming Benchmarking Virtualization C++ 67

ScaleOut Software

JANUARY 28, 2021

Getting the COVID-19 crisis under control requires that we put in place an effective process for vaccine distribution so that the country can get to herd immunity as fast as possible. Its two core competencies are speed and scalability. Is vaccine distribution underserving certain regions or population groups?

Logistics 84

Logistics Airlines Analytics Ecommerce 84

ScaleOut Software

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Analytics methods can range from simple sequential code to machine learning algorithms or rules engines.

Processing 40

Processing IoT Programming Software Engineering 40

ScaleOut Software

MAY 4, 2018

Traditional stream-processing and complex event processing systems, such as Apache Storm and Software AG’s Apama , have focused on extracting interesting patterns from incoming data with stateless applications. Analytics methods can range from simple sequential code to machine learning algorithms or rules engines.

Processing 40

Processing IoT Programming Software Engineering 40

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 Analytics Big Data Architecture 78

Dynatrace

NOVEMBER 3, 2021

Monitoring , by textbook definition, is the process of collecting, analyzing, and using information to track a program’s progress toward reaching its objectives and to guide management decisions. Log entries describe events, such as starting a process, handling an error, or simply completing some part of a workload.

Monitoring 216

Monitoring Metrics DevOps Scalability 216

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. They’re often preferred for storing and processing business intelligence data by organizations that require fast SQL queries.

Open Source 79

Open Source Database Storage Scalability 79

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

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. This telematics architecture has evolved to handle ever increasing message rates (often reaching 2K messages per second), make up-to-the-minute information available to dispatchers, and feed offline analytics.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

HammerDB

JUNE 27, 2022

The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here. What programming languages does HammerDB use and why does it matter? As a result, HammerDB was able to scale beyond other database workload applications. Adoption by the TPC.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Tasktop

OCTOBER 20, 2020

Breaking down silos and seamlessly connecting and streamlining data and process flows are integral to finding new solutions, enhancing security, and creating personalized and engaging citizen experiences.” From AI to the cloud, to predictive analytics and innovative systems, there are few places that software isn’t impacting the government.

Government 105

Government Programming Metrics Software 105

The Netflix TechBlog

MAY 21, 2019

Partners across the globe leverage Netflix device certification process on a continual basis to ensure that quality products and experiences are delivered to their customers. The certification process involves the verification of partner’s implementation of features provided by the Netflix SDK. Detect a regression in a test case.

Testing 163

Testing AWS Lambda Network 163

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. Existing programming models make it too difficult to perform meaningful analysis in real time. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user.

Development 52

Development Analytics Database Programming 52

ScaleOut Software

MAY 6, 2020

Writing applications for streaming analytics can be complex and time consuming. Existing programming models make it too difficult to perform meaningful analysis in real time. This application cannot be implemented by most streaming analytics platforms. A database service to host state information for each user.

Development 52

Development Analytics Database Programming 52

Percona

JUNE 4, 2023

Introduction: MariaDB vs. MySQL The goal of this blog post is to evaluate, at a higher level, MariaDB vs. MySQL vs. Percona Server for MySQL side-by-side to better inform the decision making process. In addition, MariaDB provides optimal scalability options, making it ideal for growing workloads. Contact us to learn more!

Open Source 52

Open Source Servers Storage Scalability 52

ScaleOut Software

DECEMBER 10, 2019

In its usage in streaming analytics, a real-time digital twin hosts an application-defined method for analyzing event messages from a single data source combined with an associated data object: The data object holds dynamic, contextual information about a single data source and the evolving results derived from analyzing incoming telemetry.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

In its usage in streaming analytics, a real-time digital twin hosts an application-defined method for analyzing event messages from a single data source combined with an associated data object: The data object holds dynamic, contextual information about a single data source and the evolving results derived from analyzing incoming telemetry.

Code 52

Code Analytics Healthcare IoT 52

ScaleOut Software

DECEMBER 10, 2019

In its usage in streaming analytics, a real-time digital twin hosts an application-defined method for analyzing event messages from a single data source combined with an associated data object: The data object holds dynamic, contextual information about a single data source and the evolving results derived from analyzing incoming telemetry.

Code 52

Code Analytics Healthcare IoT 52

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 129

Cloud Energy AWS Healthcare 129

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

Dotcom-Montior

NOVEMBER 24, 2021

With the rapid advancements in web application technologies, programming languages, cloud computing services, microservices, hybrid environments, etc., This complexity is “hidden” to the end user, like how an API (Application Programming Interface) operates, whether that is an actual user or another computer. Scalability.

Systems 74

Systems Monitoring Hardware Network 74

Testsigma

JULY 13, 2021

Instead, it relies on natural language processing , drag-and-drop UI elements , artificial intelligence, self-healing capabilities etc. Code-based test automation needs a team that knows specific programming languages and framework knowledge on which testing will be done. Choosing a tool is not a textbook process.

Testing 52

Testing Artificial Intelligence Programming Code 52

All Things Distributed

AUGUST 16, 2011

Werner Vogels weblog on building scalable and robust distributed systems. The Cloud First strategy is most visible with new Federal IT programs, which are all designed to be â??Cloud This clears the path for agencies that have IT programs that need to be ITAR-compliant to start using AWS GovCloud (US) for these applications.

AWS 111

AWS Government Big Data Cloud 111