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

FEBRUARY 16, 2023

How do you get more value from petabytes of exponentially exploding, increasingly heterogeneous data? The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022.

Analytics 185

Analytics Innovation Metrics Database 185

DZone

JANUARY 20, 2023

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios. Do Not Be Misled Designing and implementing a scalable graph database system has never been a trivial task.

Scalability 201

Scalability Big Data Hardware Internet 201

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

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. However, this cannot be done without efficient, scalable data analytics.

Big Data 112

Big Data Analytics AWS Scalability 112

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. The strongest Kubernetes growth areas are security, databases, and CI/CD technologies. Java, Go, and Node.js

Open Source 342

Open Source Java Operating System Programming 342

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

JANUARY 11, 2023

As cloud and big data complexity scales beyond the ability of traditional monitoring tools to handle, next-generation cloud monitoring and observability are becoming necessities for IT teams. With agent monitoring, third-party software collects data and reports from the component that’s attached to the agent.

Cloud 222

Cloud Monitoring Best Practices Infrastructure 222

The Netflix TechBlog

OCTOBER 15, 2019

Part I: Overview Andreas Andreakis , Falguni Jhaveri , Ioannis Papapanagiotou , Mark Cho , Poorna Reddy , Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), caching (Memcached etc.),

Transportation 192

Transportation Architecture Processing Storage 192

Highly Scalable

MARCH 1, 2012

NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. Many techniques that are described below are perfectly applicable to this model.

Database 279

Database Ecommerce Efficiency Engineering 279

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., Seer uses a lightweight RPC-level tracing system to collect request traces and aggregate them in a Cassandra database. ASPLOS’19. Seer in action.

Big Data 45

Big Data Cloud Performance Hardware 45

Dynatrace

JULY 6, 2020

In addition to providing visibility for core Azure services like virtual machines, load balancers, databases, and application services, we’re happy to announce support for the following 10 new Azure services, with many more to come soon: Virtual Machines (classic ones). Effortlessly optimize Azure database performance.

Azure 147

Azure Cloud Big Data Virtualization 147

Scalegrid

MARCH 14, 2024

Implementing a hybrid cloud solution involves careful decision-making regarding application and data placement, migration strategies, and choosing compatible cloud service providers while ensuring seamless integration and addressing security and compliance challenges.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

ScaleOut Software

JULY 19, 2021

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. The following diagram illustrates a typical workflow. What’s missing in this picture?

IoT 78

IoT Analytics Big Data Architecture 78

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

All Things Distributed

SEPTEMBER 5, 2013

Over the past few years, two important trends that have been disrupting the database industry are mobile applications and big data. The explosive growth in mobile devices and mobile apps is generating a huge amount of data, which has fueled the demand for big data services and for high scale databases.

Big Data 100

Big Data Mobile Latency Database 100

Dynatrace

APRIL 11, 2023

Log4Shell required many organizations to take devices and applications offline to prevent malicious attackers from gaining access to IT systems and sensitive data. As a result, organizations need to be vigilant in identifying and addressing vulnerabilities to protect their systems and data.

Cloud 186

Cloud DevOps Open Source Retail 186

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Database tables.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

Dynatrace

JUNE 29, 2022

Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds. A hybrid cloud, however, combines public infrastructure and services with on-premises resources or a private data center to create a flexible, interconnected IT environment.

Infrastructure 181

Infrastructure Cloud Azure AWS 181

Dynatrace

SEPTEMBER 15, 2020

Stefano started his presentation by showing how much cost and performance optimization is possible when knowing how to properly configure your application runtimes, databases, or cloud environments: Correct configuration of JVM parameters can save up to 75% resource utilization while delivering same or better performance!

Performance 185

Performance Java Metrics Cloud 185

Percona

OCTOBER 18, 2023

release , we added support for physical backups and restores to significantly reduce Recovery Time Objective ( RTO ), especially for big data sets. However, the problem of losing data between backups – in other words, Recovery Point Objective (RPO) – for physical backups was not solved.

Best Practices 90

Best Practices Storage AWS Big Data 90

The Netflix TechBlog

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. With the latest Data Mesh Platform, data movement in Netflix Studio reaches a new stage.

Big Data 253

Big Data Government Analytics Processing 253

Percona

MARCH 15, 2023

We at Percona talk a lot about how Kubernetes Operators automate the deployment and management of databases. Operators seamlessly handle lots of Kubernetes primitives and database configuration bits and pieces, all to remove toil from operation teams and provide a self-service experience for developers.

Database 85

Database Big Data Processing Servers 85

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20. Emphasis mine ).

Cloud 104

Cloud Big Data Latency Architecture 104

Percona

JANUARY 19, 2023

Some startups adopted MySQL in its early days such as Facebook, Uber, Pinterest, and many more, which are now big and successful companies that prove that MySQL can run on large databases and on heavily used sites. For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant.

Open Source 86

Open Source Storage Database Big Data 86

Highly Scalable

MARCH 10, 2015

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods.

Retail 152

Retail C++ Analytics Metrics 152

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. And I’m sure we’ve all experienced frustration when an application crashes, is slow to load, or doesn’t load at all.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

DZone

MARCH 16, 2020

This article compares different options for the in-memory maps and their performances in order for an application to move away from traditional RDBMS tables for frequently accessed data. The migration will enable the application to quickly lookup in the map and vet the physician rather than querying the database table for vetting.

Cache 147

Cache Java Performance Database 147

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. And I’m sure we’ve all experienced frustration when an application crashes, is slow to load, or doesn’t load at all.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. Although such databases can be very efficient with counts and averages, some queries will be slow or simply non existent. count()?? ?

Database 40

Database Analytics Blockchain Healthcare 40

Dynatrace

MARCH 11, 2021

In the fourth part of the series, I’ll show you how I used Dynatrace’s raw problem and event data to find the best fit for optimized anomaly detection settings. I took a big-data-analysis approach, which started with another problem visualization. Statistically analyzing Dynatrace’s event and problem data.

Tuning 263

Tuning Architecture Monitoring Big Data 263

All Things Distributed

AUGUST 19, 2011

Job Openings in AWS - Senior Leader in Database Services. This week it is an opening for senior leaders with AWS Database Services. AWS Database Services is responsible for setting the database strategy and delivering distributed structured storage services to our AWS customers. Comments (). Contact Info. Werner Vogels.

AWS 77

AWS Database Storage Scalability 77

All Things Distributed

JANUARY 11, 2011

DROAM - Dreaming about Cheap Data Roaming. The one thing that I have always struggled with during my travels are the data plans of the cell phone companies. This international data mess has been a frequent conversation topic with fellow travelers and no one has a good, simple and reliable solution. Comments ().

Wireless 109

Wireless AWS Internet Internet 109

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 138

Cloud Big Data AWS Analytics 138

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152

DZone

MAY 14, 2020

The performance claims made and the hype surrounding the Graviton2 had us itching to see how our high-performance database would perform. We are, of course, referring to the Amazon EC2 M6g instances powered by AWS Graviton2 processors. The numbers were quite exciting with the AWS Graviton2 living up to the hype, we hope you enjoy!

AWS 130

AWS Benchmarking Database Performance 130