Dynatrace

JANUARY 31, 2024

Organizations choose data-driven approaches to maximize the value of their data, achieve better business outcomes, and realize cost savings by improving their products, services, and processes. However, there are many obstacles and limitations along the way to becoming a data-driven organization. Understanding the context.

Analytics 189

Analytics Processing Transportation Storage 189

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 213

Analytics Storage Infrastructure Metrics 213

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

Government 193

Government Analytics Benchmarking Storage 193

Dynatrace

JUNE 25, 2020

Dynatrace Managed is intrinsically highly available as it stores three copies of all events, user sessions, and metrics across its cluster nodes. Our Premium High Availability comes with the following features: Active-active deployment model for optimum hardware utilization. Minimized cross-data center network traffic.

Availability 241

Availability Hardware Latency Traffic 241

Dynatrace

DECEMBER 5, 2023

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases.

Storage 161

Storage Healthcare Best Practices Speed 161

Dynatrace

OCTOBER 6, 2023

Grail: Enterprise-ready data lakehouse Grail, the Dynatrace causational data lakehouse, was explicitly designed for observability and security data, with artificial intelligence integrated into its foundation. Tables are a physical data model, essentially the type of observability data that you can store.

Artificial Intelligence 255

Artificial Intelligence Analytics Metrics Storage 255

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 261

Artificial Intelligence Analytics Storage Architecture 261

Dynatrace

APRIL 19, 2023

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 184

Design Storage Programming Analytics 184

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 28, 2023

Optimize cost and availability while staying compliant Observability data like logs and metrics provide automated answers, root cause detection, and security issues. Customer decisions about data retention are often determined by important security, privacy, and legal issues.

Analytics 206

Analytics Storage Infrastructure Metrics 206

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. What are the key advantages of DBMS?

Efficiency 147

Efficiency Storage Database Scalability 147

Dynatrace

SEPTEMBER 5, 2023

They handle complex infrastructure, maintain service availability, and respond swiftly to incidents. Predictive AI uses machine learning, data analysis, statistical models, and AI methods to predict anomalies, identify patterns, and create forecasts. This data-driven approach fosters continuous refinement of processes and systems.

Artificial Intelligence 257

Artificial Intelligence DevOps Analytics Engineering 257

Dynatrace

OCTOBER 14, 2022

Log data provides a unique source of truth for debugging applications, optimizing infrastructure, and investigating security incidents. This contextualization of log data enables AI-powered problem detection and root cause analysis at scale. Dynamic landscape and data handling requirements result in manual work.

Storage 219

Storage Government Network Infrastructure 219

Percona

FEBRUARY 10, 2023

ViewBlock , a blockchain explorer, uses the Percona Operator for MongoDB to store critical data. Today along with their team, we will see how pvc-autoresizer can automate storage scaling for MongoDB clusters on Kubernetes. In our lab we will use AWS EKS with a standard storage class. Note : If you use version 1.14.0

Storage 109

Storage Blockchain AWS Cloud 109

Dynatrace

JANUARY 31, 2024

I have ingested important custom data into Dynatrace, critical to running my applications and making accurate business decisions… but can I trust the accuracy and reliability?” ” Welcome to the world of data observability. At its core, data observability is about ensuring the availability, reliability, and quality of data.

DevOps 189

DevOps Analytics Airlines Metrics 189

Scalegrid

JULY 17, 2020

It is an open standard format which organizes data into key/value pairs and arrays detailed in RFC 7159. JSON is the most common format used by web services to exchange data, store documents, unstructured data, etc. You can also check out our Working with JSON Data in PostgreSQL vs. JSONB Patterns & Antipatterns.

Storage 321

Storage Database Efficiency Processing 321

Dynatrace

JANUARY 11, 2023

To stay competitive in an increasingly digital landscape, organizations seek easier access to business analytics data from IT to make better business decisions faster. As organizations add more tools, it creates a demand for common tooling, shared data, and democratized access. These technologies generate a crush of observability data.

Analytics 182

Analytics Strategy Storage Technology 182

Percona

JUNE 22, 2023

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. This guide provides an overview of what high availability means, the components involved, how to measure high availability, and how to achieve it. More in the following sub-section.)

Availability 107

Availability Database Open Source Hardware 107

The Netflix TechBlog

OCTOBER 28, 2021

Data Engineers of Netflix?—?Interview Interview with Pallavi Phadnis This post is part of our “ Data Engineers of Netflix ” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Pallavi Phadnis is a Senior Software Engineer on the Product Data Science and Engineering team.

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

Percona

JULY 7, 2023

With the average cost of unplanned downtime running from $300,000 to $500,000 per hour , businesses are increasingly using high availability (HA) technologies to maximize application uptime. Where a high availability design once worked well, it can no longer keep up with more complex requirements.

Availability 83

Availability Open Source Architecture Database 83

Dynatrace

JULY 31, 2020

Cloud-based solutions typically aren’t a viable option or enterprises that have strict security or privacy policies that require their data to be maintained on-premise. Dynatrace Managed now available on the Google Cloud Platform. Dynatrace news. How to set up Dynatrace Managed on Google Cloud Platform. Prerequisites.

Cloud 202

Cloud Availability Azure Google 202

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 179

Performance DevOps Innovation Artificial Intelligence 179

Dynatrace

APRIL 24, 2024

To transparently manage expectations and maintain trust with our customers, we expanded the Dynatrace SLA beyond accessing the user interface to cover the full range of relevant product categories, such as processing and retaining incoming data, accessing and working with data, and triggering automations.

Azure 233

Azure Infrastructure Metrics AWS 233

DZone

JUNE 4, 2019

NVMe Storage Use Cases. NVMe storage's strong performance, combined with the capacity and data availability benefits of shared NVMe storage over local SSD, makes it a strong solution for AI/ML infrastructures of any size. There are several AI/ML focused use cases to highlight.

Storage 100

Storage FinTech Artificial Intelligence Performance 100

Dynatrace

NOVEMBER 4, 2022

A new Dynatrace report highlights the challenges for government and public-sector organizations as they increasingly rely on cloud-native architectures—and a corresponding data explosion. This shift makes it harder to monitor, observe, and analyze data across a distributed technology stack. .

Government 147

Government Analytics Cloud Storage 147

Percona

OCTOBER 10, 2023

This is not a general rule, but as databases are responsible for a core layer of any IT system – data storage and processing — they require reliability. Availability solutions – Advanced backups, including physical backups and point-in-time recovery that are not available to MongoDB Community Edition.

Availability 99

Availability Servers Database Open Source 99

DZone

JUNE 3, 2019

Using local SSDs inside of the GPU node delivers fast access to data during training, but introduces challenges that impact the overall solution in terms of scalability, data access, and data protection.

Storage 100

Storage Performance Network Scalability 100

Scalegrid

JANUARY 19, 2024

When a MongoDB rollback happens, it can cause trouble to your data integrity and system consistency. Understanding how to address a rollback is critical for minimizing potential data loss and maintaining seamless operations. The consequences of rollbacks are significant and should not be underestimated.

Database 130

Database Network Servers Monitoring 130

Dynatrace

FEBRUARY 15, 2023

Teams can now use an observability platform to unify operations, business, and development data to gain automatic, precise answers about cloud environments and user experience. As a result, these leaders can ask different questions of the same data. Additionally, its modern architecture delivers cost-effective storage and compute.

Analytics 130

Analytics Storage Cloud Code 130

Dynatrace

SEPTEMBER 7, 2022

Dynatrace and the Dynatrace Intelligent Observability Platform have added support for the newly introduced Amazon VPC Flow Logs to Amazon Kinesis Data Firehose. This support enables customers to define specific endpoint delivery of real-time streaming data to platforms such as Dynatrace. What is VPC Flow Logs? Why Dynatrace?

Traffic 208

Traffic AWS Network Cloud 208

Percona

FEBRUARY 1, 2023

PostgreSQL is a fantastic database, but if you’re storing images, video, audio files, or other large data objects, you need to “toast” them to get optimal performance. This post will look at using The Oversized-Attribute Storage Technique (TOAST) to improve performance and scalability.

Storage 90

Storage Scalability Strategy Performance 90

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 179

Analytics Innovation Metrics Database 179

Dynatrace

JULY 11, 2023

But observability data (traces) can fill in the blanks to reveal useful evidence of possible exploitation, as proved by our analysis of the MoveIT vulnerability using Dynatrace. When exploiting the vulnerability, attackers can gain remote code injection capabilities in the MOVEit server and modify or steal sensitive data from its database.

Database 153

Database Government Games Servers 153

Scalegrid

FEBRUARY 1, 2024

Regarding MySQL backups , knowing how to secure your data is crucial. Dive in to uncover the essentials of different backup types, command-line tools, and strategic practices for robust data protection. MySQL is a popular open-source relational database management system for online applications and data warehousing.

Best Practices 130

Best Practices Storage Strategy Database 130

Percona

JULY 24, 2023

PBM) introduced a GA version of incremental physical backups , which can greatly impact both the recovery time and the cost of backup (considering storage and data transfer cost). Contact me through any channels (we do have our Jira open to the Community, my email is available in the footnote, and I am present on LinkedIn).

Availability 76

Availability Open Source Strategy Storage 76

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

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