Dynatrace

FEBRUARY 12, 2024

Today’s organizations flock to multicloud environments for myriad reasons, including increased scalability, agility, and performance. However, these environments can drown enterprises in data, forcing them to adopt multiple tools and services to manage and secure it.

Analytics 171

Analytics Artificial Intelligence Engineering Technology 171

Dynatrace

NOVEMBER 7, 2023

Platform engineering is on the rise. According to leading analyst firm Gartner, “80% of software engineering organizations will establish platform teams as internal providers of reusable services, components, and tools for application delivery…” by 2026.

Engineering 262

Engineering DevOps Best Practices Infrastructure 262

Dynatrace

APRIL 18, 2024

DevOps and platform engineering are essential disciplines that provide immense value in the realm of cloud-native technology and software delivery. Observability of applications and infrastructure serves as a critical foundation for DevOps and platform engineering, offering a comprehensive view into system performance and behavior.

DevOps 180

DevOps Engineering Artificial Intelligence Infrastructure 180

The Netflix TechBlog

JANUARY 25, 2023

Scalable Annotation Service — Marken by Varun Sekhri , Meenakshi Jindal Introduction At Netflix, we have hundreds of micro services each with its own data models or entities. But there are more interesting cases where users want to store temporal (time-based) data or spatial data. Movie Entity with id 1234 has violence.

Scalability 283

Scalability Latency Media Architecture 283

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Several pain points have made it difficult for organizations to manage their data efficiently and create actual value.

Analytics 223

Analytics Artificial Intelligence Storage Serverless 223

Dynatrace

JULY 29, 2021

The complexity of such deployments has accelerated with the adoption of emerging, open-source technologies that generate telemetry data, which is exploding in terms of volume, speed, and cardinality. All this data is then consumed by Dynatrace Davis® AI for more precise answers, thereby driving AIOps for cloud-native environments.

Analytics 245

Analytics Open Source Serverless Architecture 245

Dynatrace

NOVEMBER 3, 2023

that offers security, scalability, and simplicity of use. While Python code can address most data acquisition and ingest requirements, it comes at the cost of complexity in implementation and use-case modeling. address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0:

Technology 236

Technology Technology Scalability Availability 236

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. Thus, Grail was born.

Artificial Intelligence 257

Artificial Intelligence Analytics Storage Architecture 257

Scalegrid

MAY 13, 2020

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

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. At Dynatrace Perform 2023 , Maciej Pawlowski, senior director of product management for infrastructure monitoring at Dynatrace, and a senior software engineer at a U.K.-based

Analytics 177

Analytics Infrastructure Storage Efficiency 177

DZone

OCTOBER 24, 2023

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

Analytics 267

Analytics Storage Infrastructure Scalability 267

Dynatrace

MAY 21, 2024

Data with context can improve your ability to deliver on your goals, modernize your organization, and accelerate business transformation. These outcomes are made easy through the platform’s unique ability to turn data into answers and action, in contextual, real-time, and cost-effective ways that were previously impossible.

Technology 193

Technology Technology Analytics Storage 193

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 176

Performance DevOps Innovation Artificial Intelligence 176

DZone

OCTOBER 1, 2023

Elasticsearch is an open-source search engine and analytics store used by a variety of applications from search in e-commerce stores, to internal log management tools using the ELK stack (short for “Elasticsearch, Logstash, Kibana”).

Open Source 257

Open Source Tuning Analytics Scalability 257

The Netflix TechBlog

MARCH 5, 2019

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. In the Reliability space, our data teams focus on two main approaches.

Infrastructure 182

Infrastructure Cloud Scalability AWS 182

Dynatrace

MAY 17, 2022

By taking advantage of native Kubernetes standards, Dynatrace Cloud Native Full Stack injection empowers you to precisely provide the data that your teams need in exceptionally fast and automated ways. These situations apply to organizations that are looking to: Onboard teams to Kubernetes observability data as quickly as possible.

Availability 305

Availability Scalability Cloud Metrics 305

Uber Engineering

SEPTEMBER 2, 2021

The team transforms Uber’s ideas into agile, global solutions by designing and implementing scalable solutions. One … The post Streaming Real-Time Analytics with Redis, AWS Fargate, and Dash Framework appeared first on Uber Engineering Blog.

Analytics 143

Analytics AWS Programming Scalability 143

DZone

NOVEMBER 27, 2023

An open-source distributed SQL query engine, Trino is widely used for data analytics on distributed data storage. Optimizing Trino to make it faster can help organizations achieve quicker insights and better user experiences, as well as cut costs and improve infrastructure efficiency and scalability.

Tuning 162

Tuning Speed Performance Open Source 162

High Scalability

NOVEMBER 23, 2018

Here's some fancy FCC reverse engineering magic. Then please recommend my well reviewed (30 reviews on Amazon and 72 on Goodreads!) @KevinBankston : Ford's CEO just said on NPR that the future of profitability for the company is all the data from its 100 million vehicles (and the people in them) they'll be able to monetize.

Internet 174

Internet Internet Scalability Analytics 174

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 264

Efficiency Performance Analytics DevOps 264

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here could well be the future of data processing at Google. Because they had too many data processing systems! ;). VLDB’19. are divided.

Analytics 75

Analytics Latency Cache Google 75

Dynatrace

MARCH 29, 2023

With this Google Cloud Ready integration, Dynatrace ensures that AlloyDB for PostgreSQL users can now ingest metrics along with existing Google Cloud data. Through our partnership, customers can utilize Dynatrace alongside AlloyDB to gain more visibility and insights into data stored across databases and locations, including in AlloyDB.”

Google 209

Google Metrics Cloud Analytics 209

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

Scalegrid

MARCH 14, 2024

This approach allows companies to combine the security and control of private clouds with public clouds’ scalability and innovation potential. This combination allows for the fluid movement of data and applications across different environments, facilitating shared workloads seamlessly.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

NOVEMBER 17, 2020

OpenTracing data is seamlessly integrated by PurePath 4, which also unlocks more than 30 pre-instrumented technologies. On the right side you can see the connections to Istio instances that are sending data to the Envoy payment service. Investigate which calls led to a specific request. Waterfall visualization of all requests.

Analytics 151

Analytics Technology Technology Cloud 151

Percona

SEPTEMBER 14, 2023

However, modern business is very much dependent on analytical data. ClickHouse is a columnar database that handles analytical workloads quickly. I recommend you read our previous blog, Using ClickHouse as an Analytic Extension for MySQL , from Vadim to know more about this. The blog post contains the following topics.

Engineering 85

Engineering Database Servers Analytics 85

High Scalability

JANUARY 11, 2022

Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. 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. The MultiPart/Form-Data contains a series of parts.

Design 334

Design Media Storage Logistics 334

The Netflix TechBlog

JUNE 7, 2021

At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides flow data at scale for network insight. Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. What is BPF?

Network 325

Network Transportation AWS Cloud 325

Dynatrace

FEBRUARY 15, 2023

But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. 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 and automated workflows.

Code 201

Code DevOps Cloud Analytics 201

Dynatrace

APRIL 7, 2023

Streaming raises the default 6 MB hard limit to a 20 MB soft limit, adding greater scalability and flexibility to their applications. There is a new Lambda function handler signature that provides a stream object to which your function can write incoming stream data immediately, without waiting for any buffering as before.

Lambda 204

Lambda AWS Serverless Latency 204

Dynatrace

FEBRUARY 16, 2023

With increased scalability, agility, and flexibility, cloud computing enables organizations to improve supply chains, deliver higher customer satisfaction, and more. But the cloud also produces an explosion of data. And with that data comes the thorn to the cloud’s rose: increased complexity.

Artificial Intelligence 183

Artificial Intelligence Analytics Cloud Innovation 183

Dynatrace

OCTOBER 7, 2020

At the same time, you can now simply flip a switch to begin ingesting observability data from these tools into the Dynatrace platform, all while retaining your investment and increasing the value you get from Dynatrace. Open-source metric sources automatically map to our Smartscape model for AI analytics.

Open Source 247

Open Source Metrics Analytics Tuning 247

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

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Scalability Architecture 130

Dynatrace

FEBRUARY 15, 2023

Not only are these approaches difficult and costly to maintain, they also lack proper security and scalability. It empowers Dynatrace customers to use the same tools and technologies as Dynatrace engineers to develop new tailored apps. Boundless possibilities You now have unlimited possibilities to address any use case you can imagine.

Government 157

Government Serverless Analytics Metrics 157

Scalegrid

DECEMBER 21, 2023

In today’s data-driven world, the ability to effectively monitor and manage data is of paramount importance. Redis®, a powerful in-memory data store, is no exception. This ensures each Redis® instance optimally uses the in-memory data store and aligns with the operating system’s efficiency.

Strategy 130

Strategy Monitoring Latency DevOps 130

Scalegrid

JANUARY 12, 2024

Key Takeaways A cloud workload encompasses any application or service running on a cloud infrastructure, facilitating tasks ranging from basic functions to advanced data analysis with the help of resources like databases, collaboration tools, and disaster recovery systems. This applies to both virtual machines and container-based deployments.

Cloud 130

Cloud Virtualization Storage Efficiency 130