Dynatrace

FEBRUARY 16, 2023

With increased scalability, agility, and flexibility, cloud computing enables organizations to improve supply chains, deliver higher customer satisfaction, and more. That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization.

Artificial Intelligence 193

Artificial Intelligence Analytics Cloud Innovation 193

Dynatrace

OCTOBER 6, 2023

ALLOW storage:buckets:read WHERE storage:bucket-name STARTSWITH "prod_infra_"; However, creating access policies solely on the bucket and table level is not scalable in a enterprise landscape, as one Dynatrace tenant can have a limited number of custom buckets.

Artificial Intelligence 261

Artificial Intelligence Analytics Metrics Storage 261

Dynatrace

NOVEMBER 20, 2023

Across the cloud operations lifecycle, especially in organizations operating at enterprise scale, the sheer volume of cloud-native services and dynamic architectures generate a massive amount of data. In general, generative AI can empower AWS users to further accelerate and optimize their cloud journeys. What is predictive AI? What is AIOps?

AWS 209

AWS Artificial Intelligence Analytics Cloud 209

Dynatrace

JANUARY 5, 2022

To do so we have successfully established AI-based White box load and resiliency testing with JMeter and Dynatrace, helping identify and resolve major performance and scalability problems in recent projects before deploying to production. Our customers usually involve us 2-4 weeks before the production release. a Jenkinsfile.

Testing 217

Testing Open Source Metrics Infrastructure 217

Dynatrace

OCTOBER 1, 2021

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their multi-cloud environments. Dynatrace news. As teams begin collecting and working with observability data, they are also realizing its benefits to the business, not just IT.

Metrics 363

Metrics Open Source Monitoring Infrastructure 363

High Scalability

JANUARY 11, 2022

Architecture. We have chosen this NoSQL based solution over relational databases as it provides the scalability to have hierarchies which go beyond two levels and extensibility due to the schema-less behavior of NoSQL data storage. Sending and receiving messages from other users. High Level Design. Streaming Data Model.

Design 334

Design Media Storage Logistics 334

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

Dynatrace

MARCH 24, 2023

Part of its popularity owes to its availability as a managed service through the major cloud providers, such as Amazon Elastic Kubernetes Service , Google Kubernetes Engine , and Microsoft Azure Kubernetes Service. Likewise, Kubernetes is both an enterprise platform and managed services with Red Hat OpenShift.

Infrastructure 186

Infrastructure Open Source Operating System Cloud 186

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. Vendors ScaleGrid provides the flexibility to select a suitable database architecture, minimizing worries of vendor lock-in. You are both captain and crew.

Database 130

Database Cloud Hardware Storage 130

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. However, real-time digital twins easily bring these capabilities within reach.

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

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. Scaleout StreamServer® DT was created to meet this need.

IoT 52

IoT Azure Analytics Healthcare 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. However, real-time digital twins easily bring these capabilities within reach.

Analytics 52

Analytics Social Media Serverless Cloud 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 Analytics Big Data Architecture 78

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. MaaSS for Cloud Architects: Deployment and Architecture Validations. Validate correct architecture, configuration and deployment by looking at Service Flow! 3 Log Analytics. Full-stack observability. End-to-end code-level tracing. Service mash insights. End-user monitoring.

AWS 127

AWS Monitoring Ecommerce Lambda 127

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

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

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

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. By avoiding the need to create or connect to complex databases and ship data to offline analytics systems, it can provide timely answers quickly and easily.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. By avoiding the need to create or connect to complex databases and ship data to offline analytics systems, it can provide timely answers quickly and easily.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

AUGUST 19, 2014

They also offer a powerful computing platform for analyzing live data as it changes and generating immediate feedback or “operational intelligence;” for example, see this blog post describing the use of real-time analytics in a retail application. The Need to Keep It Simple.

Cloud 40

Cloud Azure Virtualization Scalability 40

ScaleOut Software

AUGUST 19, 2014

They also offer a powerful computing platform for analyzing live data as it changes and generating immediate feedback or “operational intelligence;” for example, see this blog post describing the use of real-time analytics in a retail application. The Need to Keep It Simple.

Cloud 40

Cloud Azure Virtualization Scalability 40

ScaleOut Software

AUGUST 25, 2020

It also includes support for real-time aggregate analytics and visualization integrated with the real-time digital twin model to maximize ease of use.

Airlines 52

Airlines Mobile Analytics C++ 52

ScaleOut Software

AUGUST 25, 2020

It also includes support for real-time aggregate analytics and visualization integrated with the real-time digital twin model to maximize ease of use.

Airlines 52

Airlines Mobile Analytics C++ 52

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. Unfortunately, other than cost advantage Wordpress and Drupal have similar deficiencies i.e. legacy monolith architecture.

Systems 63

Systems Cache Website Network 63

High Scalability

NOVEMBER 25, 2019

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. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. SOA architecture based on REST APIs. Google cloud.

Architecture 52

Architecture Cache Azure Storage 52