Dynatrace

OCTOBER 17, 2023

In today’s data-driven landscape, businesses are grappling with an unprecedented surge in data volume. The rise of cloud-native microservice architectures further exacerbates this change. The data generated by applications to support operational teams has reached overwhelming proportions.

Retail 237

Retail Storage Best Practices Architecture 237

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 186

Performance DevOps Innovation Artificial Intelligence 186

High Scalability

JANUARY 11, 2022

Architecture. from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. High Level Design.

Design 334

Design Media Storage Logistics 334

DZone

SEPTEMBER 14, 2023

This data warehousing use case is about scale. From an architectural perspective, the system should be able to undertake real-time analysis of various formats of logs, and of course, be scalable to support the huge and ever-enlarging data size. Such a gigantic log analysis system is part of their cybersecurity management.

Analytics 124

Analytics Storage Architecture Scalability 124

InfoQ

DECEMBER 29, 2023

Zendesk reduced its data storage costs by over 80% by migrating from DynamoDB to a tiered storage solution using MySQL and S3. By Rafal Gancarz

Storage 133

Storage Scalability Database Technology 133

Scalegrid

JANUARY 8, 2024

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Exploring artificial intelligence in cloud computing reveals a game-changing synergy.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

JANUARY 22, 2024

While traditional AI relies on finding correlations in data, causal AI aims to determine the precise underlying mechanisms that drive events and outcomes. For example, machine learning can identify correlations in data and generate predictions, while causal AI determines which ones are the true drivers. Government.

Artificial Intelligence 207

Artificial Intelligence Healthcare Retail Government 207

VoltDB

JULY 10, 2018

Application State Management and Data-Driven Decision Making. This goal has been attempted to be addressed from the beginning of time: think of Object Oriented Programming, Service Oriented Architecture, Enterprise Service Bus and now Microservices. Data-driven decision making business logic. Real-World Example Problem.

Architecture 40

Architecture Scalability Ecommerce Latency 40

VoltDB

JULY 10, 2018

Application State Management and Data-Driven Decision Making. This goal has been attempted to be addressed from the beginning of time: think of Object Oriented Programming, Service Oriented Architecture, Enterprise Service Bus and now Microservices. Data-driven decision making business logic. Real-World Example Problem.

Architecture 40

Architecture Scalability Ecommerce Latency 40

Smashing Magazine

SEPTEMBER 28, 2022

Five Data-Loading Patterns To Improve Frontend Performance. Five Data-Loading Patterns To Improve Frontend Performance. Data loading patterns are an essential part of your application as they will determine which parts of your application are directly usable by visitors. But isn’t waiting for the data the point?

Performance 125

Performance Cache Servers Social Media 125

Dynatrace

JULY 29, 2021

Today’s digital businesses run on heterogeneous and highly dynamic architectures with interconnected applications and microservices deployed via Kubernetes and other cloud-native platforms. All this data is then consumed by Dynatrace Davis® AI for more precise answers, thereby driving AIOps for cloud-native environments.

Analytics 246

Analytics Open Source Serverless Architecture 246

The Morning Paper

AUGUST 29, 2019

Choosing a cloud DBMS: architectures and tradeoffs Tan et al., There’s a broad set of choices including where you store the data, whether you run your own DBMS nodes or use a service, the kinds of instance types to go for if you do run your own, and so forth. VLDB’19. The design space. Key findings. Query restrictions.

Architecture 76

Architecture Cloud Storage Serverless 76

All Things Distributed

JUNE 10, 2016

If you are looking for more examples there are the Lambda Serverless Reference Architectures that can serve as the blueprint for building your own serverless applications. Mobile Backend Serverless Reference Architecture. Real-time File Processing Serverless Reference Architecture. IoT Backend Serverless Reference Architecture.

Lambda 107

Lambda Serverless AWS Architecture 107

All Things Distributed

MAY 10, 2016

If you are looking for more examples there are the Lambda Serverless Reference Architectures that can serve as the blueprint for building your own serverless applications. Mobile Backend Serverless Reference Architecture. Real-time File Processing Serverless Reference Architecture. IoT Backend Serverless Reference Architecture.

Lambda 105

Lambda Serverless AWS Architecture 105

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. One option is to install OneAgent on that syslog server, which automatically discovers, instruments and sends the log data to the Dynatrace platform.

Strategy 180

Strategy AWS Open Source Transportation 180

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

FEBRUARY 10, 2023

Data proliferation—as well as a growing need for data analysis—has accelerated. According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations. Digital transformation shows no signs of slowing down.

Efficiency 276

Efficiency Performance Analytics DevOps 276

Dynatrace

DECEMBER 16, 2022

Data supports this need for organizations to flex and modernize. An open approach enables technologies to interoperate, whereas proprietary, legacy systems often create vendor lock-in and prevent interoperability and data integration. Teams make flawed decisions because they work with siloed data that provides an incomplete picture.

Innovation 196

Innovation Software Software Cloud 196

The Netflix TechBlog

MAY 4, 2023

When undertaking system migrations, one of the main challenges is establishing confidence and seamlessly transitioning the traffic to the upgraded architecture without adversely impacting the customer experience. This blog series will examine the tools, techniques, and strategies we have utilized to achieve this goal.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

MARCH 24, 2023

Problems include provisioning and deployment; load balancing; securing interactions between containers; configuration and allocation of resources such as networking and storage; and deprovisioning containers that are no longer needed. How does container orchestration work? The post What is container orchestration?

Infrastructure 186

Infrastructure Open Source Operating System Cloud 186

Dynatrace

JANUARY 16, 2023

The study analyzes factual Kubernetes production data from thousands of organizations worldwide that are using the Dynatrace Software Intelligence Platform to keep their Kubernetes clusters secure, healthy, and high performing. Through effortless provisioning, a larger number of small hosts provide a cost-effective and scalable platform.

Open Source 343

Open Source Java Operating System Programming 343

Dynatrace

NOVEMBER 2, 2020

IT infrastructure is the heart of your digital business and connects every area – physical and virtual servers, storage, databases, networks, cloud services. This shift requires infrastructure monitoring to ensure all your components work together across applications, operating systems, storage, servers, virtualization, and more.

Infrastructure 200

Infrastructure Monitoring Virtualization Serverless 200

The Netflix TechBlog

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 203

Storage Latency Efficiency Data Engineering 203

Percona

DECEMBER 4, 2023

Percona software is designed for peak performance, uncompromised security, limitless scalability, and disaster-proofed availability. It is the most stable, scalable, and secure open source MySQL distribution based on Percona Server for MySQL. Release highlights include: Docker images are now available for x86_64 architectures.

Open Source 84

Open Source Azure Servers Programming 84

Percona

JUNE 30, 2023

Kubernetes provides many benefits, such as automation and scalability, but it also introduces new complexities when it comes to managing databases. IT teams must ensure high availability, scalability, and security, all while ensuring that their PostgreSQL clusters perform optimally. What is better in version 2 compared to version 1?

Availability 98

Availability Open Source Azure Hardware 98

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. better cluster resource utilization.

Big Data 63

Big Data Storage Benchmarking Hardware 63

ScaleOut Software

JULY 19, 2021

Today’s streaming analytics architectures are not equipped to make sense of this rapidly changing information and react to it as it arrives. Incoming data is saved into data storage (historian database or log store) for query by operational managers who must attempt to find the highest priority issues that require their attention.

IoT 78

IoT Analytics Big Data Architecture 78

Abhishek Tiwari

JULY 12, 2018

Building data pipelines can offer strategic advantages to the business. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects. In this post, we will discuss why you should avoid building data pipelines in first place.

Latency 63

Latency Analytics Scalability Engineering 63

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

Percona

AUGUST 17, 2023

It’s used for data management (shocker), application development, and data analytics. PostgreSQL has powerful and advanced features, including asynchronous replication, full-text searches of the database, and native support for JSON-style storage, key-value storage, and XML. What is PostgreSQL used for?

Open Source 82

Open Source Healthcare Social Media Database 82

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Grail architectural basics.

Artificial Intelligence 267

Artificial Intelligence Analytics Storage Architecture 267

Dynatrace

DECEMBER 5, 2023

Without observability, the benefits of ARM are lost Over the last decade and a half, a new wave of computer architecture has overtaken the world. ARM architecture, based on a processor type optimized for cloud and hyperscale computing, has become the most prevalent on the planet, with billions of ARM devices currently in use.

Efficiency 266

Efficiency Architecture Energy Monitoring 266

Percona

DECEMBER 27, 2023

In our conversations with developers and engineers during the conference, we confirmed the CNCF GItOps Microsurvey data – 91% are already using GitOps. While integrating AI and machine learning into cloud-native architectures, there’s an increasing demand from users for AI to be open and collaborative.

Cloud 84

Cloud Open Source Strategy Best Practices 84

The Netflix TechBlog

MAY 21, 2019

In our quest to be objective, scientific, and inline with the Netflix philosophy of using data to drive solutions for intriguing problems, we proceeded by leveraging machine learning. Likewise it has very low requirements on the initial amount of training data. which allows fast deployment times and rapid scalability.

Testing 163

Testing AWS Lambda Network 163

All Things Distributed

OCTOBER 17, 2016

The Ohio Region launches with three AZs so that customers can create high-availability environments and architect for fault tolerance and scalability. Data transfer between the Ohio Region and the Northern Virginia Region is priced the same as data transfer between AZs within either of these regions.

AWS 127

AWS Cloud Infrastructure Analytics 127

Dynatrace

APRIL 20, 2023

Modern organizations ingest petabytes of data daily, but legacy approaches to log analysis and management cannot accommodate this volume of data. based financial services group, discussed how the bank uses log monitoring on the Dynatrace platform with an emphasis on observability and security data.

Analytics 187

Analytics Infrastructure Storage Efficiency 187

Dynatrace

SEPTEMBER 17, 2019

Some vendors have just bolted on individual capabilities which often leads to six data silos. PostgreSQL & Elastic for data storage. MaaSS for Business: Data per SaaS-Tenant. The Business teams therefore built a set of dashboards that contain the data they want to see. REDIS for caching.

AWS 127

AWS Monitoring Ecommerce Lambda 127