Dynatrace

OCTOBER 4, 2022

Organizations need to unify all this observability, business, and security data based on context and generate real-time insights to inform actions taken by automation systems, as well as business, development, operations, and security teams. The next frontier: Data and analytics-centric software intelligence. Don’t reinvent the wheel.

Analytics 190

Analytics Software Software Storage 190

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 181

Analytics Storage Retail DevOps 181

Dynatrace

FEBRUARY 2, 2023

Exploding volumes of business data promise great potential; real-time business insights and exploratory analytics can support agile investment decisions and automation driven by a shared view of measurable business goals. Traditional observability solutions don’t capture or analyze application payloads.

Analytics 201

Analytics Metrics DevOps Storage 201

Dynatrace

SEPTEMBER 8, 2022

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. Comparing log monitoring, log analytics, and log management. These two processes feed into one another. Dynatrace news.

Systems 185

Systems Cloud Analytics DevOps 185

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. A log is a detailed, timestamped record of an event generated by an operating system, computing environment, application, server, or network device.

Analytics 208

Analytics Monitoring Artificial Intelligence DevOps 208

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

APRIL 8, 2024

Optimize the IT infrastructure supporting risk management processes and controls for maximum performance and resilience. The IT infrastructure, services, and applications that enable processes for risk management must perform optimally. If system failures occur, teams must resolve them quickly and resolutely.

Analytics 200

Analytics Infrastructure Efficiency Technology 200

Dynatrace

OCTOBER 4, 2022

Application and system logs are often collected in data silos using different tools, with no relationships between them, and then correlated in manual and often meaningless ways. Each process could generate multiple log entries, adding up to terabytes of data every day. A modern approach to log analytics stores data without indexing.

Analytics 220

Analytics Storage Infrastructure Metrics 220

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. It removes much of the guesswork of untangling complex system issues and establishes with certainty why a problem occurred. Fragmented and siloed data storage can create inconsistencies and redundancies. Timeliness.

Government 199

Government Analytics Benchmarking Storage 199

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. Ingest and process with Grail. Thus, it can scale massively. Retain data.

Artificial Intelligence 267

Artificial Intelligence Analytics Storage Architecture 267

Dynatrace

OCTOBER 7, 2020

Topology metrics are related to specific entities in your Smartscape topology (for example, the number of successful and failed batch jobs processed by a host). This gives you all the benefits of a metric storage system, including exploring and charting metrics, building dashboards, and alerting on anomalies.

Metrics 245

Metrics Analytics Storage Monitoring 245

Dynatrace

SEPTEMBER 5, 2023

Technology and operations teams work to ensure that applications and digital systems work seamlessly and securely. Predictive AI uses statistical algorithms and other advanced machine learning techniques to anticipate what might happen next in a system. Predictive analytics can anticipate potential failures and security breaches.

Artificial Intelligence 262

Artificial Intelligence DevOps Analytics Engineering 262

Dynatrace

JUNE 9, 2023

They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. From a technical perspective, however, cloud-based analytics can be challenging. All these steps and stages slow down processes, are error-prone, and introduce additional security risks.

DevOps 183

DevOps Analytics Storage Metrics 183

Dynatrace

OCTOBER 23, 2023

Microsoft Hyper-V is a virtualization platform that manages virtual machines (VMs) on Windows-based systems. It enables multiple operating systems to run simultaneously on the same physical hardware and integrates closely with Windows-hosted services. This leads to a more efficient and streamlined experience for users.

Efficiency 213

Efficiency Virtualization Hardware Performance 213

Dynatrace

JANUARY 18, 2023

Business events are a special class of events, new to Business Analytics; together with Grail, our data lakehouse, they provide the precision and advanced analytics capabilities required by your most important business use cases. Analytics without boundaries. Example business events from anywhere.

Analytics 227

Analytics Retail Storage Monitoring 227

Dynatrace

JANUARY 31, 2024

million” – Gartner Data observability is a practice that helps organizations understand the full lifecycle of data, from ingestion to storage and usage, to ensure data health and reliability. Data observability is crucial to analytics and automation, as business decisions and actions depend on data quality.

DevOps 194

DevOps Analytics Airlines Metrics 194

Scalegrid

JANUARY 12, 2024

Simply put, it’s the set of computational tasks that cloud systems perform, such as hosting databases, enabling collaboration tools, or running compute-intensive algorithms. In the realm of cloud-based business operations, there is an increasing dependence on complex information processing patterns. What is workload in cloud computing?

Cloud 130

Cloud Virtualization Storage Efficiency 130

DZone

SEPTEMBER 14, 2023

Such a gigantic log analysis system is part of their cybersecurity management. For the need of real-time monitoring, threat tracing, and alerting, they require a log analytic system that can automatically collect, store, analyze, and visualize logs and event records.

Analytics 124

Analytics Storage Architecture Scalability 124

Dynatrace

NOVEMBER 20, 2023

Effectively automating IT processes is key to addressing the challenges of  complex cloud environments. Relying on manual processes results in outages, increased costs, and frustrated customers. But, as resources move off premises, IT teams can lose visibility into system performance and security issues. What is AIOps?

AWS 208

AWS Artificial Intelligence Analytics Cloud 208

High Scalability

JANUARY 11, 2022

The streaming data store makes the system extensible to support other use-cases (e.g. System Components. The system will comprise of several micro-services each performing a separate task. There are two major processes which gets executed when a user posts a photo on Instagram. Fetching User Feed.

Design 334

Design Media Storage Logistics 334

Dynatrace

FEBRUARY 10, 2023

In what follows, we explore some key cloud observability trends in 2023, such as workflow automation and exploratory analytics. From data lakehouse to an analytics platform Traditionally, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs.

Efficiency 275

Efficiency Performance Analytics DevOps 275

Scalegrid

JANUARY 8, 2024

Key Takeaways AI integration in cloud computing increases operational efficiency by automating processes, optimizing resource allocation, and improving scalability, leading to cost savings and allowing IT teams to concentrate on strategic initiatives.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

OCTOBER 6, 2023

Buckets are similar to folders, a physical storage location. Debug-level logs, which also generate high volumes and have a shorter lifespan or value period than other logs, could similarly benefit from dedicated storage. Suppose a single Grail environment is central storage for pre-production and production systems.

Artificial Intelligence 261

Artificial Intelligence Analytics Metrics Storage 261

Dynatrace

OCTOBER 17, 2023

Moreover, the system lacks flexibility, imposing strict schemas that administrators and developers must adhere to avoid additional costs. Dynatrace has developed the purpose-built data lakehouse, Grail , eliminating the need for separate management of indexes and storage. Ingest and process.

Retail 236

Retail Storage Best Practices Architecture 236

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

Dynatrace

AUGUST 21, 2023

Traditional monitoring approaches worked fine when an operator was tasked with tracking a simple, static system,” wrote Ali Siddiqui in “ How to harness the power of observability, AIOps and automation.” They need to automate manual tasks, streamline processes, and invest in new technologies. during 2021–2026.

Analytics 145

Analytics Innovation Infrastructure Scalability 145

Scalegrid

JANUARY 20, 2020

Follower clusters are a ScaleGrid feature that allows you to keep two independent database systems (of the same type) in sync. Here are a few critical ways in which it differs from replication: You can control how frequently the destination system syncs from source – once a week, once a day, or even less frequently.

Analytics 185

Analytics Storage Database Systems 185

Scalegrid

DECEMBER 21, 2023

With these essential support systems in place, you can effectively monitor your databases with up-to-date data about their health and functioning status at all times. 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

MARCH 14, 2024

Understanding Hybrid Cloud Strategy A hybrid cloud merges the capabilities of public and private clouds into a singular, coherent system. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. We will examine each of these elements in more detail.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

JANUARY 22, 2024

That’s why causal AI use cases abound for organizations looking to build more reliable and transparent AI systems. Understanding complex systems Causal AI holds great importance for achieving full-stack observability in complex systems. More generally, causal AI can contribute to explainable and fair AI systems.

Artificial Intelligence 207

Artificial Intelligence Healthcare Retail Government 207

Scalegrid

MARCH 28, 2024

This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. It uses a hash table to manage these pairs, divided into fixed-size buckets with linked lists for key-value storage. step in to simplify this task.

Cache 130

Cache Storage Scalability Architecture 130

The Netflix TechBlog

OCTOBER 28, 2021

During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics. I also built online serving systems and microservices powering Walmart’s e-commerce. At this conference, I also got to know my current team: Consolidated Logging (CL).

Data Engineering 173

Data Engineering Engineering Big Data Software Engineering 173

Dynatrace

APRIL 19, 2023

When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration. Enterprise data stores grow with the promise of analytics and the use of data to enable behavioral security solutions, cognitive analytics, and monitoring and supervision.

Design 191

Design Storage Programming Analytics 191

DZone

DECEMBER 14, 2021

Metadata synchronization (sync) is a core feature in Alluxio that keeps files and directories consistent with their source of truth in under-storage systems, thus making it simple for users to reason the data retrieved from Alluxio. Meanwhile, understanding the internal process is important in order to tune the performance.

Design 244

Design Storage Tuning Systems 244

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. Grail buckets function like folders in a file system.

Storage 166

Storage Healthcare Best Practices Speed 166

The Netflix TechBlog

OCTOBER 19, 2020

which is difficult when troubleshooting distributed systems. Reconstructing a streaming session was a tedious and time consuming process that involved tracing all interactions (requests) between the Netflix app, our Content Delivery Network (CDN), and backend microservices. Stream Processing: to sample or not to sample trace data?

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

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