This document discusses high availability strategies for MySQL databases across multiple datacenters. It covers architectural considerations for hot/hot vs hot/cold configurations and disaster recovery approaches. The main sections explore replication techniques like MySQL replication and alternative schemes, application high availability mechanisms, and how Percona can help with high availability solutions and services.
This white paper describes the EMC Cloud Tiering Appliance (CTA). The CTA enables NAS data tiering, allowing administrators to move inactive data from high-performance storage to less-expensive archival storage, thus enabling cost-effective use of file storage. The CTA also facilitates data migration which moves data to new shares or exports.
Microsoft SQL High Availability and ScalingJustin Whyte
This is a white paper that I wrote that explores the different options for Microsoft SQL Server High Availability. I explain the pros and cons of each technology, as well as important considerations like RTO and RPO.
MoreVRP is a database performance monitoring and acceleration tool, and offers DBAs the capability to have real-time monitoring and resource management and control.
Find and fix SQL Server performance problems fasterSolarWinds
Great DBAs must be able to quickly identify problems with SQL Server instances. In this presentation, you will learn how to quickly identify where your problems are using tools such as:
*Dynamic Management Views
*Query Execution Plans
*Windows Performance Monitor
*Extended Events
*Third-party tools (including SolarWinds Database Performance Analyzer)
How to fix IO problems for faster SQL Server performanceSolarWinds
How do you determine the impact of I/O on poor performance? Learn the fundamentals of SQL Server storage and how it impacts performance, including:
*the difference between latency, throughput, IOPS, and how they relate
*performance characteristics of different storage solutions
*techniques for analyzing storage subsystem performance
*new features in SolarWinds Database Performance Analyzer that will help you more accurately pinpoint and resolve I/O issue
This white paper describes the EMC Cloud Tiering Appliance (CTA). The CTA enables NAS data tiering, allowing administrators to move inactive data from high-performance storage to less-expensive archival storage, thus enabling cost-effective use of file storage. The CTA also facilitates data migration which moves data to new shares or exports.
Microsoft SQL High Availability and ScalingJustin Whyte
This is a white paper that I wrote that explores the different options for Microsoft SQL Server High Availability. I explain the pros and cons of each technology, as well as important considerations like RTO and RPO.
MoreVRP is a database performance monitoring and acceleration tool, and offers DBAs the capability to have real-time monitoring and resource management and control.
Find and fix SQL Server performance problems fasterSolarWinds
Great DBAs must be able to quickly identify problems with SQL Server instances. In this presentation, you will learn how to quickly identify where your problems are using tools such as:
*Dynamic Management Views
*Query Execution Plans
*Windows Performance Monitor
*Extended Events
*Third-party tools (including SolarWinds Database Performance Analyzer)
How to fix IO problems for faster SQL Server performanceSolarWinds
How do you determine the impact of I/O on poor performance? Learn the fundamentals of SQL Server storage and how it impacts performance, including:
*the difference between latency, throughput, IOPS, and how they relate
*performance characteristics of different storage solutions
*techniques for analyzing storage subsystem performance
*new features in SolarWinds Database Performance Analyzer that will help you more accurately pinpoint and resolve I/O issue
Data deduplication is a hot topic in storage and saves significant disk space for many environments, with some trade offs. We’ll discuss what deduplication is and where the Open Source solutions are versus commercial offerings. Presentation will lean towards the practical – where attendees can use it in their real world projects (what works, what doesn’t, should you use in production, etcetera).
A presentation on best practices for J2EE scalability from requirements gathering through to implementation, including design and architecture along the way.
When it comes to backup and recovery, backup performance numbers rule the roost. It’s understandable really: far more data gets backed up than ever gets restored, and backup length is one of most difficult problems facing administrators today. But a reliance on backup numbers alone is dangerous. Recovery may not happen as frequently as daily backup but recovery is the entire reason for backup. Backing up because everyone does it isn’t good enough.
ClustrixDB 7.5 is the latest release of the only drop-in replacement for MySQL with true scale-out performance. The latest release of ClustrixDB is easier to use, provides more insight into the performance of the database and better utilizes hardware.
Featuring a brief overview of fault-tolerant mechanisms across various Big Data systems such as Google File system (GFS), Amazon Dynamo, Bigtable, Hadoop - Map Reduce, Facebook Cassandra along with description of an existing fault tolerant model
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...IJSRD
Big data is a popular term used to define the exponential evolution and availability of data, includes both structured and unstructured data. The volatile progression of demands on big data processing imposes heavy burden on computation, communication and storage in geographically distributed data centers. Hence it is necessary to minimize the cost of big data processing, which also includes fault tolerance cost. Big Data processing involves two types of faults: node failure and data loss. Both the faults can be recovered using heartbeat messages. Here heartbeat messages acts as an acknowledgement messages between two servers. This paper depicts about the study of node failure and recovery, data replication and heartbeat messages.
Lets face it: Distributed computing is hard. The truth is that most systems and vendor solutions work great under regular conditions, but what separates them is what happens when things go wrong. If you’re building a mission critical distributed system, you need to take the time to build infrastructure to test for failure. In this talk we’ll outline how we think about testing a distributed system, and share some real world experience in ferreting out issues before they become problems in production. We’ll provide a hands on overview of our test framework and show you how you too can be prepared.
Data deduplication is a hot topic in storage and saves significant disk space for many environments, with some trade offs. We’ll discuss what deduplication is and where the Open Source solutions are versus commercial offerings. Presentation will lean towards the practical – where attendees can use it in their real world projects (what works, what doesn’t, should you use in production, etcetera).
A presentation on best practices for J2EE scalability from requirements gathering through to implementation, including design and architecture along the way.
When it comes to backup and recovery, backup performance numbers rule the roost. It’s understandable really: far more data gets backed up than ever gets restored, and backup length is one of most difficult problems facing administrators today. But a reliance on backup numbers alone is dangerous. Recovery may not happen as frequently as daily backup but recovery is the entire reason for backup. Backing up because everyone does it isn’t good enough.
ClustrixDB 7.5 is the latest release of the only drop-in replacement for MySQL with true scale-out performance. The latest release of ClustrixDB is easier to use, provides more insight into the performance of the database and better utilizes hardware.
Featuring a brief overview of fault-tolerant mechanisms across various Big Data systems such as Google File system (GFS), Amazon Dynamo, Bigtable, Hadoop - Map Reduce, Facebook Cassandra along with description of an existing fault tolerant model
Fault Tolerance in Big Data Processing Using Heartbeat Messages and Data Repl...IJSRD
Big data is a popular term used to define the exponential evolution and availability of data, includes both structured and unstructured data. The volatile progression of demands on big data processing imposes heavy burden on computation, communication and storage in geographically distributed data centers. Hence it is necessary to minimize the cost of big data processing, which also includes fault tolerance cost. Big Data processing involves two types of faults: node failure and data loss. Both the faults can be recovered using heartbeat messages. Here heartbeat messages acts as an acknowledgement messages between two servers. This paper depicts about the study of node failure and recovery, data replication and heartbeat messages.
Lets face it: Distributed computing is hard. The truth is that most systems and vendor solutions work great under regular conditions, but what separates them is what happens when things go wrong. If you’re building a mission critical distributed system, you need to take the time to build infrastructure to test for failure. In this talk we’ll outline how we think about testing a distributed system, and share some real world experience in ferreting out issues before they become problems in production. We’ll provide a hands on overview of our test framework and show you how you too can be prepared.
What is data replication? How many data replication types are there? How to perform data replication to protect from data loss in case of computer crashes?
We talk a lot about Galera Cluster being great for High Availability, but what about Disaster Recovery (DR)? Database outages can occur when you lose a data centre due to data center power outages or natural disaster, so why not plan appropriately in advance?
In this webinar, we will discuss the business considerations including achieving the highest possible uptime, analysis business impact as well as risk, focus on disaster recovery itself, as well as discussing various scenarios, from having no offsite data to having synchronous replication to another data centre.
This webinar will cover MySQL with Galera Cluster, as well as branches MariaDB Galera Cluster as well as Percona XtraDB Cluster (PXC). We will focus on architecture solutions, DR scenarios and have you on your way to success at the end of it.
Data Protection and Disaster Recovery Solutions: Ensuring Business ContinuityMaryJWilliams2
In today's digital landscape, data protection and disaster recovery are critical components of any robust IT strategy. This article delves into various solutions designed to safeguard your data against loss, corruption, and cyber threats. Explore the latest technologies and best practices for effective data protection, from backup strategies to comprehensive disaster recovery plans. To know more: https://stonefly.com/white-papers/data-protection-disaster-recovery-solution/
Shielding Data Assets: Exploring Data Protection and Disaster Recovery Strate...MaryJWilliams2
Delve into comprehensive data protection and disaster recovery strategies with our detailed PDF submission. Discover best practices, methodologies, and technologies to safeguard critical data and ensure operational continuity in the face of unforeseen events. Gain insights into designing resilient backup plans, implementing disaster recovery solutions, and mitigating risks effectively. Equip yourself with the knowledge needed to protect your organization's data assets and maintain business continuity. To Know more: https://stonefly.com/white-papers/data-protection-disaster-recovery-solution/
Some vignettes and advice based on prior experience with Cassandra clusters in live environments. Includes some material from other operational slides.
Streamlining Backup: Enhancing Data Protection with Backup AppliancesMaryJWilliams2
Explore the efficiency and reliability of backup appliances in safeguarding critical data with our informative PDF submission. Discover how organizations can leverage backup appliances to streamline backup processes, improve data resilience, and enhance disaster recovery capabilities. Gain insights into the features, benefits, and best practices for deploying backup appliances in diverse IT environments to ensure data availability and continuity. To Know more: https://stonefly.com/white-papers/data-availability-a-guide-to-backup-appliances-and-data-availability/
Why is Virtualization Creating Storage Sprawl? By Storage SwitzerlandINFINIDAT
Desktop and server virtualization have brought many benefits to the data center. These two initiatives have allowed IT to respond quickly to the needs of the organization while driving down IT costs, physical footprint requirements and energy demands. But there is one area of the data center that has actually increased in cost since virtualization started to make its way into production… storage. Because of virtualization, more data centers need "ash to meet the random I/O nature of the virtualized environment, which of course is more expensive, on a dollar per GB basis, than hard disk drives. The single biggest problem however is the signi!cant increase in the number of discrete storage systems that service the environment. This “storage sprawl” threatens the return on investment (ROI) of virtualization projects and makes storage more complex to manage.
Learn more at www.infinidat.com.
Atmosphere 2014: Switching from monolithic approach to modular cloud computin...PROIDEA
This presentation is to demonstrate, how the homogenous and centralized network architectures cease to operate efficiently and how limited are our abilities to respond to on-demand computing power in such cases. We will show you how to redesign monolithic storage architectures into modular systems, as well as how to migrate them to a scalable and flexible cloud environment.
Maciej Kuzniar - Founder and CEO of the project Oktawave. Passionate about technology related to the processing and data storage, having 10 years of experience working for enterprise customers (banks, telecoms, fmcg). Author of the concepts that support the development of tech startups and architectural solutions to ensure high HA and SLA for IT systems.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.