Scalegrid

FEBRUARY 8, 2024

This guide delves into how these systems work, the challenges they solve, and their essential role in businesses and technology. Distributed Storage Architecture Distributed storage systems are designed with a core framework that includes the main system controller, a data repository for the system, and a database.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This is simply not possible with conventional architectures. Data management.

Artificial Intelligence 214

Artificial Intelligence Storage Analytics Government 214

Dynatrace

JULY 6, 2020

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. Azure Batch. Azure DB for MariaDB. Azure DB for MySQL.

Azure 150

Azure Cloud Big Data Virtualization 150

Dynatrace

FEBRUARY 8, 2021

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Connecting data siloes requires daunting integration endeavors.

Cloud 261

Cloud Azure Analytics AWS 261

Dynatrace

NOVEMBER 20, 2023

While technologies have enabled new productivity and efficiencies, customer expectations have grown exponentially, cyberthreat risks continue to mount, and the pace of business has sped up. It’s being recognized around the world as a transformative technology for delivering productivity gains. What is artificial intelligence?

AWS 214

AWS Artificial Intelligence Analytics Cloud 214

Dynatrace

JANUARY 31, 2024

It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. Figure 1: Sample RAG architecture While this approach significantly improves the response quality of GenAI applications, it also introduces new challenges.

Cache 209

Cache Azure Infrastructure Monitoring 209

Scalegrid

JANUARY 8, 2024

Discover how AI is reshaping the cloud and what this means for the future of technology. AI algorithms embedded in cloud architecture automate repetitive processes, streamlining workloads and reducing the chance of human error. These services are tailored to meet various business requirements.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

FEBRUARY 16, 2023

That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. You have to get automation and analytical capabilities.” Throw in behavioral analytics, metadata, and real-user data. … We start with data types—logs, metrics, traces, routes.

Artificial Intelligence 199

Artificial Intelligence Analytics Cloud Innovation 199

Scalegrid

MARCH 14, 2024

The architecture usually integrates several private, public, and on-premises infrastructures. Key Components of Hybrid Cloud Infrastructure A hybrid cloud architecture usually merges a public Infrastructure-as-a-Service (IaaS) platform with private computing assets and incorporates tools to manage these combined environments.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. Modern observability technologies have helped enterprises identify software vulnerabilities such as Log4Shell in their environments.

Design 197

Design Storage Programming Analytics 197

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

SEPTEMBER 13, 2023

And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem.

AWS 252

AWS Efficiency Azure Cloud 252

Dynatrace

MARCH 24, 2023

Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services. This clinic will walk you through Dynatrace’s log monitoring and analytics capabilities, with a specific focus on Kubernetes and cloud-native architectures.

Infrastructure 191

Infrastructure Open Source Operating System Cloud 191

Dynatrace

FEBRUARY 12, 2024

These standards can be custom for specific teams, technologies, or criticalities. The new observability app for databases from Dynatrace was built to cater to all requirements of database administrators (DBAs), from swiftly assessing database availability and performance to delving into architectural intricacies for efficient troubleshooting.

Engineering 187

Engineering Development Infrastructure Cloud 187

Dynatrace

NOVEMBER 22, 2021

Serverless architecture enables organizations to deliver applications more efficiently without the overhead of on-premises infrastructure, which has revolutionized software development. These tools simply can’t provide the observability needed to keep pace with the growing complexity and dynamism of hybrid and multicloud architecture.

AWS 233

AWS Lambda Artificial Intelligence Serverless 233

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

Dynatrace

JANUARY 5, 2022

In recent years, customer projects have moved towards complex cloud architectures, including dozens of microservices and different technology stacks which are challenging to develop, maintain, and optimize for resiliency. Our solution to modernize this legacy approach is an approach we call white box testing. a Jenkinsfile.

Testing 223

Testing Open Source Metrics Infrastructure 223

Dynatrace

APRIL 22, 2022

When American Family Insurance took the multicloud plunge, they turned to Dynatrace to automate Amazon Web Services (AWS) event ingestion, instrument compute and serverless cloud technologies, and create a single workflow for unified event management. Step 2: Instrument compute and serverless cloud technologies. ski explains.

Cloud 173

Cloud Lambda Serverless AWS 173

High Scalability

JANUARY 11, 2022

Architecture. We can use cloud technologies such as Amazon Kinesis or Azure Stream Analytics for collecting, processing, and analyzing real-time, streaming data to get timely insights and react quickly to new information(e.g. Sending and receiving messages from other users. High Level Design. Streaming Data Model.

Design 334

Design Media Storage Logistics 334

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

Analytics 59

Analytics Social Media Ecommerce Serverless 59

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

O'Reilly

MAY 19, 2020

O’Reilly Learning > We wanted to discover what our readers were doing with cloud, microservices, and other critical infrastructure and operations technologies. AWS is far and away the cloud leader, followed by Azure (at more than half of share) and Google Cloud. All told, we received 1,283 responses. 10,000 or more employees.

Cloud 141

Cloud Serverless AWS Architecture 141

Dynatrace

JUNE 1, 2021

All these terms refer to related technology and practices. APM has rapidly expanded to encompass a broad range of technologies and use cases. Application architecture to gain insights into how application architecture changes impact performance and user experience. Why businesses need APM. What does APM do?

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

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

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. Their technology stack looks like this: Spring Boot-based Microservices. MaaSS for Cloud Architects: Deployment and Architecture Validations. Dynatrace’s PurePath technology brings us automatic end-to-end code level tracing without having to modify any code or configuration.

AWS 128

AWS Monitoring Ecommerce Lambda 128

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

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

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.

Database 130

Database Cloud Hardware Storage 130

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. To make this possible, the Azure-based streaming service hosts a real-time digital twin for each data source. What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

AUGUST 20, 2020

This blog post explains how a new software construct called a real-time digital twin running in a cloud-hosted service can create a breakthrough for streaming analytics. To make this possible, the Azure-based streaming service hosts a real-time digital twin for each data source. What Are Real-Time Digital Twins?

Cloud 52

Cloud Development Analytics Azure 52

ScaleOut Software

JUNE 22, 2020

For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing. The pace of these changes has made it challenging for server-based infrastructures to manage fast-growing populations of users and data sources while maintaining fast response times.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

For more than two decades, the answer to this challenge has proven to be a technology called in-memory computing. The pace of these changes has made it challenging for server-based infrastructures to manage fast-growing populations of users and data sources while maintaining fast response times.

Ecommerce 52

Ecommerce Cache Scalability IoT 52