Dynatrace

APRIL 21, 2022

While applications are built using a variety of technologies and frameworks, there is one thing they usually have in common: the data they work with must be stored in databases. Now, Dynatrace has gone a step further and expanded its coverage and intelligent observability into the next layer: database infrastructure.

Database 244

Database DevOps Analytics Servers 244

Dynatrace

OCTOBER 4, 2022

Much of the software developed today is cloud native. However, cloud infrastructure has become increasingly complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence. User experience data.

Analytics 200

Analytics Software Software Storage 200

Dynatrace

APRIL 10, 2023

Managing cloud performance is increasingly challenging for organizations that spread workloads across a greater variety of platforms. And according to recent data from Enterprise Strategy Group, 59% of survey respondents indicated spending on public cloud applications would increase in 2023. ” Three years ago, Tractor Supply Co.

Cloud 179

Cloud Ecommerce Performance Retail 179

Dynatrace

DECEMBER 21, 2023

How can you reduce the carbon footprint of your hybrid cloud? Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. energy-efficient data centers—cloud providers—achieve values closer to 1.2. Is the solution to just move all workloads to the cloud? Want to learn more?

Cloud 218

Cloud Energy Best Practices Cache 218

Dynatrace

MAY 23, 2022

As a result, organizations are weighing microservices vs. monolithic architecture to improve software delivery speed and quality. Traditional monolithic architectures are built around the concept of large applications that are self-contained, independent, and incorporate myriad capabilities. What is monolithic architecture?

Architecture 203

Architecture DevOps Monitoring Programming 203

Dynatrace

APRIL 11, 2023

Today’s organizations face increasing pressure to keep their cloud-based applications performing and secure. Cloud application security remains challenging because organizations lack end-to-end visibility into cloud architecture.

Cloud 195

Cloud DevOps Open Source Retail 195

DZone

JUNE 11, 2020

It's challenging to troubleshoot issues in a distributed database because the information about the system is scattered in different machines. TiDB is an open-source, distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. Before version 4.0, Before version 4.0,

Database 246

Database Open Source Analytics Architecture 246

Scalegrid

JANUARY 11, 2024

What does it take to secure your cloud assets effectively? Cloud security monitoring is key—identifying threats in real-time and mitigating risks before they escalate. This article strips away the complexities, walking you through best practices, top tools, and strategies you’ll need for a well-defended cloud infrastructure.

Best Practices 130

Best Practices Cloud Monitoring Strategy 130

Dynatrace

JANUARY 31, 2024

Monitoring SAP products can present challenges Monitoring SAP systems can be challenging due to the inherent complexity of using different technologies—such as ABAP, Java, and cloud offerings—and the sheer amount of generated data. This is why Dynatrace is extending its observability capabilities for SAP with PowerConnect for SAP.

Java 198

Java Analytics Best Practices Monitoring 198

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 262

Cloud Azure Analytics AWS 262

Dynatrace

JUNE 9, 2023

They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. From a technical perspective, however, cloud-based analytics can be challenging. Cloud complexity leads to data silos Most organizations are battling cloud complexity.

DevOps 192

DevOps Analytics Storage Metrics 192

Dynatrace

APRIL 20, 2023

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. Logs are automatically produced and time-stamped documentation of events relevant to cloud architectures.

Analytics 196

Analytics Infrastructure Storage Efficiency 196

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. However, Redis, with its single-threaded architecture, may encounter bottlenecks with large numbers of concurrent connections.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

OCTOBER 4, 2022

These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. Further, these resources support countless Kubernetes clusters and Java-based architectures. where an error occurred at the code level.

Analytics 230

Analytics Storage Infrastructure Metrics 230

Scalegrid

FEBRUARY 8, 2024

At its core, a distributed storage system comprises three main components: a controller for managing the system’s operations, an internal datastore where information is held, and databases geared towards ensuring scalability, partitioning capabilities, and high availability for all types of data.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

JANUARY 31, 2024

Many organizations face significant challenges in pursuing their cloud migration initiatives, which often accompany or precede AI initiatives. Worse, the costs associated with GenAI aren’t straightforward, are often multi-layered, and can be five times higher than traditional cloud services. Service reliability.

Cache 212

Cache Azure Infrastructure Monitoring 212

Dynatrace

DECEMBER 8, 2020

Cloud-native technologies, including Kubernetes and OpenShift, help organizations accelerate innovation. Open source has also become a fundamental building block of the entire cloud-native stack. Why cloud-native applications, Kubernetes, and open source require a radically different approach to application security.

Cloud 296

Cloud Open Source Internet Internet 296

Dynatrace

FEBRUARY 12, 2024

Because of this, it’s critical for organizations to have end-to-end visibility across on-premises, cloud, and hybrid deployments. Dynatrace® Clouds app. The new Dynatrace Clouds app enables seamless management of multicloud environments and provides insights across multiple cloud services in a single, integrated view.

Engineering 190

Engineering Development Infrastructure Cloud 190

Percona

MARCH 30, 2023

The use of open source databases has increased steadily in recent years. Past trepidation — about perceived vulnerabilities and performance issues — has faded as decision makers realize what an “open source database” really is and what it offers. What is an open source database?

Open Source 74

Open Source Database Storage Scalability 74

Dynatrace

JULY 6, 2020

With cloud deployments growing rapidly during the past few years and enterprise multi-cloud environments becoming the norm, new challenges have emerged, including: Cloud dynamics make it hard to keep up with autoscaling, where services come and go based on demand. Effortlessly optimize Azure database performance.

Azure 151

Azure Cloud Big Data Virtualization 151

The Netflix TechBlog

MARCH 5, 2019

All these micro-services are currently operated in AWS cloud infrastructure. Finally, provisioning our infrastructure itself is also becoming an increasingly complex task, so our data teams contribute to tools for diagnosis and automation of our cloud capacity management.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

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

All Things Distributed

NOVEMBER 15, 2016

QuickSight is a very fast, cloud-powered, business intelligence service for the 1/10th the cost of old-guard BI solutions. Along with data generated in the cloud, customers also have legacy data sitting in on-premises datacenters, scattered on user desktops, or stored in SAS applications. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152

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

APRIL 5, 2021

The growth of Azure cloud computing. Azure is a large and growing cloud computing ecosystem that empowers its users to access databases, launch virtual servers, create websites or mobile applications, run a Kubernetes cluster, and train machine learning models, to name a few examples. When not to use Azure Functions.

Azure 138

Azure Serverless IoT Lambda 138

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

The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. Several promising ideas were abandoned owing to the outsized work needed to overcome architectural limitations. The microservice architecture provides strong decoupling between services. 264, AV1, etc.).

Processing 229

Processing Media Latency Innovation 229

High Scalability

JANUARY 11, 2022

Architecture. We will use a graph database such as Neo4j to store the information. Additionally, we can use columnar databases like Cassandra to store information like user feeds, activities, and counters. Sample Queries supported by Graph Database. Sending and receiving messages from other users. High Level Design.

Design 334

Design Media Storage Logistics 334

All Things Distributed

OCTOBER 17, 2016

Now customers who have been requesting a second US East region have more infrastructure options for running workloads, storing files, running analytics, and managing databases. The Ohio Region is no different. Check out the Regional Products and Services page for the full list.

AWS 127

AWS Cloud Infrastructure Analytics 127

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

Percona

JUNE 23, 2023

Both MySQL and PostgreSQL do the basics very well From a high level, one relational database management system is pretty much like every other relational database management system. It does not follow the SQL Standard as closely as other databases, and some useful functions such as MERGE() are missing.

Database 119

Database Transportation Servers Cloud 119

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

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. Automation : Single load test executions can be repeated and tracked. The white box load testing project setup.

Testing 226

Testing Open Source Metrics Infrastructure 226

Dynatrace

JUNE 1, 2021

Causes can run the gamut — from coding errors to database slowdowns to hosting or network performance issues. Millions of lines of code comprise these apps, and they include hundreds of interconnected digital services and open-source solutions , and run in containerized environments hosted across multiple cloud services.

Monitoring 148

Monitoring Mobile Social Media Artificial Intelligence 148

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., ” For just the YouTube Analytics application, we’re looking at metrics like this, with a 99%-ile latency of 412ms: Embedded statistics use cases include the various counters such as views, likes, and subscriptions that are included in pages.

Analytics 75

Analytics Latency Cache Google 75

Tasktop

APRIL 30, 2019

Whether it’s a result of different teams or lines of business within the same company on separate instances, or even a merger or acquisition, you see different flavors of the multi-Jira architecture: Split across Jira server and Jira Cloud. Split across Jira Data Center and Jira Cloud instances.

Cloud 71

Cloud Servers Analytics Architecture 71

Percona

AUGUST 17, 2023

PostgreSQL is open source relational database management software. It’s used for data management (shocker), application development, and data analytics. In another survey, using multiple metrics for overall popularity, PostgreSQL ranks as the fourth most popular database management system ( DB-Engines, March 2023 ).

Open Source 78

Open Source Healthcare Social Media Database 78