Dynatrace

FEBRUARY 10, 2023

They now use modern observability to monitor expanding cloud environments in order to operate more efficiently, innovate faster and more securely, and to deliver consistently better business results. Further, automation has become a core strategy as organizations migrate to and operate in the cloud.

Efficiency 306

Efficiency Performance Analytics DevOps 306

The Netflix TechBlog

DECEMBER 21, 2020

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 208

Storage Latency Efficiency Data Engineering 208

The Netflix TechBlog

MARCH 4, 2025

Part 3: System Strategies and Architecture By: VarunKhaitan With special thanks to my stunning colleagues: Mallika Rao , Esmir Mesic , HugoMarques This blog post is a continuation of Part 2 , where we cleared the ambiguity around title launch observability at Netflix. The request schema for the observability endpoint.

Traffic 160

Traffic Strategy Entertainment Innovation 160

Dynatrace

MAY 8, 2023

This demand for rapid innovation is propelling organizations to adopt agile methodologies and DevOps principles to deliver software more efficiently and securely. And how do DevOps monitoring tools help teams achieve DevOps efficiency? Lost efficiency. 54% reported deploying updates every two hours or less.

DevOps 246

DevOps Efficiency Monitoring Infrastructure 246

Scalegrid

MAY 13, 2020

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

The Netflix TechBlog

NOVEMBER 12, 2024

After selecting a mode, users can interact with APIs without needing to worry about the underlying storage mechanisms and counting methods. Let’s examine some of the drawbacks of this approach: Lack of Idempotency : There is no idempotency key baked into the storage data-model preventing users from safely retrying requests.

Latency 247

Latency Cache Infrastructure Strategy 247

Scalegrid

FEBRUARY 24, 2025

This guide will cover how to distribute workloads across multiple nodes, set up efficient clustering, and implement robust load-balancing techniques. This decoupling is crucial in modern architectures where scalability and fault tolerance are paramount.

Best Practices 147

Best Practices Traffic Strategy Scalability 147

Dynatrace

OCTOBER 7, 2021

To get a better understanding of AWS serverless, we’ll first explore the basics of serverless architectures, review AWS serverless offerings, and explore common use cases. Serverless architecture: A primer. Serverless architecture shifts application hosting functions away from local servers onto those managed by providers.

Serverless 325

Serverless AWS Lambda Storage 325

Dynatrace

OCTOBER 4, 2022

Grail architectural basics. The aforementioned principles have, of course, a major impact on the overall architecture. A data lakehouse addresses these limitations and introduces an entirely new architectural design. This decoupling ensures the openness of data and storage formats, while also preserving data in context.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

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. What is a data lakehouse? How does a data lakehouse work? Data management.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

The Netflix TechBlog

SEPTEMBER 18, 2024

In this post, we dive deep into how Netflix’s KV abstraction works, the architectural principles guiding its design, the challenges we faced in scaling diverse use cases, and the technical innovations that have allowed us to achieve the performance and reliability required by Netflix’s global operations.

Latency 256

Latency Storage Cache Servers 256

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

OCTOBER 4, 2022

Several pain points have made it difficult for organizations to manage their data efficiently and create actual value. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. This approach is cumbersome and challenging to operate efficiently at scale.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

The Netflix TechBlog

SEPTEMBER 24, 2021

Table 1: Movie and File Size Examples Initial Architecture A simplified view of our initial cloud video processing pipeline is illustrated in the following diagram. Figure 1: A Simplified Video Processing Pipeline With this architecture, chunk encoding is very efficient and processed in distributed cloud computing instances.

Cloud 240

Cloud Media Storage Cache 240

Dynatrace

AUGUST 8, 2019

In short, over the last several months, we’ve completely rebuilt the architecture of the OneAgent installer for Windows. Smaller network and Dynatrace cluster storage footprint. The post Rebuilt OneAgent installer for Windows provides more efficient installation appeared first on Dynatrace blog.

Efficiency 164

Efficiency Network Storage Architecture 164

Dynatrace

OCTOBER 4, 2022

Further, these resources support countless Kubernetes clusters and Java-based architectures. In most data storage models, indexing engines enable faster access to query logs. But indexing requires schema management and additional storage to be effective, which adds cost and overhead. Cost-effective architecture.

Analytics 264

Analytics Storage Infrastructure Metrics 264

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. Despite initial investment costs, DBMS presents long-term savings and improved efficiency through automated processes, efficient query optimizations, and scalability, contributing to enhanced decision-making and end-user productivity.

Efficiency 147

Efficiency Storage Database Scalability 147

Dynatrace

SEPTEMBER 23, 2022

Organizations continue to turn to multicloud architecture to deliver better, more secure software faster. But IT teams need to embrace IT automation and new data storage models to benefit from modern clouds. Moreover, IT pros say that cloud architecture and data repositories thwart achieving better data insight.

Cloud 245

Cloud Artificial Intelligence Innovation Architecture 245

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 246

Analytics Infrastructure Storage Architecture 246

Dynatrace

MARCH 6, 2024

Kubernetes adds to the complexity of technology stacks Alongside the challenges of managing multicloud environments, IT and security teams struggle to maintain visibility into cloud-native architectures as Kubernetes continues to become the platform of choice for modern applications.

Analytics 246

Analytics Innovation Strategy Storage 246

Dynatrace

SEPTEMBER 28, 2020

Before we dive into the technical implementation, let me explain the visual concept of this “Global Status Page”: Another requirement for this status page was that it has to be lightweight, with no data storage at all. Getting the problem status of all environments has to be efficient. Lightweight architecture. js framework.

Storage 276

Storage Architecture Tuning Efficiency 276

The Netflix TechBlog

OCTOBER 8, 2024

In previous blog posts, we introduced the Key-Value Data Abstraction Layer and the Data Gateway Platform , both of which are integral to Netflix’s data architecture. Instead, we focus on addressing the challenge of storing and accessing extremely high-throughput, immutable temporal event data in a low-latency and cost-efficient manner.

Latency 235

Latency Storage Traffic Infrastructure 235

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. If you don’t have insight into the software and services that operate your business, you can’t efficiently run your business. Minimizes downtime and increases efficiency.

Infrastructure 246

Infrastructure Monitoring Virtualization Serverless 246

Dynatrace

OCTOBER 17, 2023

The rise of cloud-native microservice architectures further exacerbates this change. Dynatrace has developed the purpose-built data lakehouse, Grail , eliminating the need for separate management of indexes and storage. All data is readily accessible without storage tiers, such as costly solid-state drives (SSDs).

Retail 264

Retail Storage Best Practices Architecture 264

Dynatrace

JUNE 10, 2024

As a result, organizations are implementing security analytics to manage risk and improve DevSecOps efficiency. Security analytics must also contend with the multicomponent architecture of modern IT infrastructure. Dehydrated data has been compressed or otherwise altered for storage in a data warehouse. Read now!

Analytics 264

Analytics Network Open Source Hardware 264

High Scalability

SEPTEMBER 8, 2018

RISELabs , those wonderfully innovative folks over at Berkeley, have uplifted their Anna datatabase —a shared-nothing, thread-per-core architecture to achieve lightning-fast speeds by avoiding all coordination mechanisms—to become cloud-aware. What's changed ?

Storage 199

Storage Performance AWS Cloud 199

Dynatrace

JANUARY 11, 2023

Cloud storage monitoring. Teams can keep track of storage resources and processes that are provisioned to virtual machines, services, databases, and applications. Multicloud architectures, on the other hand, blend services from two or more private or public clouds — or from a combination of public, private, and edge clouds.

Cloud 295

Cloud Monitoring Best Practices Infrastructure 295

Dynatrace

JANUARY 4, 2024

It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration. Modern, cloud-native architectures have many moving parts, and identifying them all is a daunting task with human effort alone.

Government 263

Government Analytics Benchmarking Storage 263

The Morning Paper

MARCH 8, 2020

Building an elastic query engine on disaggregated storage , Vuppalapati, NSDI’20. For such workloads, shared-nothing architectures beget high cost, inflexibility, poor performance, and inefficiency, which hurts production applications and cluster deployments. joins) during query processing. Disaggregation (or not).

Storage 112

Storage Engineering Cache Serverless 112

Dynatrace

OCTOBER 14, 2022

All this is easier said than done because: Kubernetes-based dynamic architecture is becoming the norm. This allows you to create flexible and powerful log storage configurations on any level by utilizing the unique autodiscovery capabilities of Dynatrace OneAgent or a custom setup. Try it out yourself.

Storage 278

Storage Government Network Infrastructure 278

Dynatrace

OCTOBER 4, 2022

As a result, organizations need software to work perfectly to create customer experiences, deliver innovation, and generate operational efficiency. Traditionally, though, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Analytics 246

Analytics Software Software Storage 246

Dynatrace

SEPTEMBER 13, 2023

This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

AWS 305

AWS Efficiency Azure Cloud 305

The Netflix TechBlog

OCTOBER 27, 2020

At Netflix, we also heavily embrace a microservice architecture that emphasizes separation of concerns. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store. Figure 1 shows how we use Bulldozer to move data at Netflix. Moving data with Bulldozer at Netflix.

Latency 248

Latency Storage Big Data Tuning 248

Dynatrace

NOVEMBER 20, 2023

The first goal is to demonstrate how generative AI can bring key business value and efficiency for organizations. 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.

AWS 277

AWS Artificial Intelligence Cloud Analytics 277

Uber Engineering

AUGUST 14, 2019

Maintaining Uber’s large-scale data warehouse comes with an operational cost in terms of ETL functions and storage. In our experience, optimizing for operational efficiency requires answering one key question: for which tables does the maintenance cost supersede utility?

Efficiency 110

Efficiency Engineering Design Storage 110

Dynatrace

APRIL 8, 2024

This blog explores how vertically integrated risk management solutions that use AI and automation enable unparalleled visibility, control, and efficiency for risk management in banking. They can accomplish this all while delivering transformation efficiency and economies of scale for IT functions that maintain risk management infrastructure.

Analytics 246

Analytics Infrastructure Efficiency Technology 246

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Log analytics also help identify ways to make infrastructure environments more predictable, efficient, and resilient. Dynatrace news. What are logs?

Analytics 264

Analytics Monitoring DevOps Artificial Intelligence 264