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Webinar: Understanding Disaster Recovery Options for SQL Server

May 24, 2019 by Jason Aw Leave a Comment

Understanding Disaster Recovery Options for SQL Server

Webinar: Understanding Disaster Recovery Options for SQL Server

Webinar: Understanding Disaster Recovery Options for SQL Server

Yes – you need a disaster recovery plan! Your SQL Server data depends on it.

On this webinar, Dave Bermingham, Microsoft Datacenter and Cloud MVP, explains the difference between Disaster Recovery, Business Continuity and High Availability and why each is a critical component for any business’ survival. Discover what key components should be included in your Disaster Recovery, Business Continuity plans and explore some of the tools available to help achieve your Disaster Recovery, Business Continuity goals.

Concerned about end of support for SQL Server 2008?  See how SIOS helps customers prepare for SQL Server 2008 EOS.

Filed Under: News posts Tagged With: Business Continuity, disaster recovery, disaster recovery - DR, High Availability, SQL Server

Webinar: Why Clustering for SQL Server High Availability?

May 24, 2019 by Jason Aw Leave a Comment

Why Clustering for SQL Server High Availability

Webinar: Why Clustering for SQL Server High Availability?

Webinar: Why Clustering for SQL Server High Availability?

When it comes to SQL Server high availability (HA), SQL Server Failover Cluster Instance (FCI) has been the standard since 1998 with the release of SQL Server 7. Dave Bermingham, Microsoft Cloud and Datacenter MVP and former Cluster MVP, reviews what clusters are, why you should use them for high availability, discusses SQL Server Failover Cluster Instance concepts and why it is an important part of your Mission Critical SQL Server deployment whether you run on-premises, in the cloud or in a hybrid cloud configuration.

Register Webinar: Why Clustering for SQL Server High Availability?

Filed Under: News posts Tagged With: Clustering, Failover Clusters, High Availability, SQL Server, SQL Server High Availability

Webinar: Best Practices for Migrating SQL Server 2008 to Azure

May 24, 2019 by Jason Aw Leave a Comment

Best Practices for Migrating SQL Server 2008 to Azure

Webinar: Best Practices for Migrating SQL Server 2008 to Azure

Microsoft announced that Extended Security Updates will be available for free in Azure for 2008 and 2008 R2 versions of SQL Server and Windows Server to help secure your workloads for three more years after the end of support deadline. That means if you are running SQL 2008 or 2008 R2 on-premises today and won’t have time to upgrade before the regular end of life of SQL Server 2008 and 2008 R2 on July 9th 2019, your best course of action to keep these systems secure would be to migrate those workloads into Azure. Microsoft Cloud and Datacenter MVP David Bermingham discusses best practices for moving standalone and clustered SQL Server 2008 instances into Azure to take advantage of these extended security updates.

See our SQL Server 2008 End of Support solution to help you maintain security and compliance for your SQL Server environments.

Register Webinar: Best Practices for Migrating SQL Server 2008 to Azure

Filed Under: News posts Tagged With: Azure Cloud, Cloud, High Availability, SQL Server

Subscribe to Data Informed The IT Shift from Computer Science to Data Science

November 13, 2017 by Jason Aw Leave a Comment

You may think that the words “artificial intelligence” or “machine learning” sound like trendy buzzwords. In reality, much of the hype about this technology is true. Unlike past periods of excitement over artificial intelligence, today’s interest is no longer an academic exercise. Now, IT has a real-world need for faster solutions to problems that are too complex for humans alone. This includes identifying the root causes of performance issues in virtual infrastructures.

Today, almost every large enterprise has virtualized part, or all, of their data centers. With virtualization, IT teams gain access to a huge variety and volume of real-time machine data they want to use to understand and solve the issues in their IT operations environments. However, the complexity of managing virtual IT environments is stressing out traditional IT departments. As a result, IT pros are discovering that the solution lies in the data and in the artificial intelligence-based tools that can leverage it.

Data Science to the Rescue

As worldwide digital data levels continue to climb, companies are working to find the business value in their data, and to adapt their computer science strategies to the evolving data science market. Legacy management and monitoring tools used the same approach they used for physical server environments — that is, by looking at discrete silos (network, storage, infrastructure, application). They used multiple manually-set thresholds to focus on individual metrics — CPU utilization, memory utilization, network latency, etc., within each silo.

This threshold-based approach originated in a relatively static, well-understood physical server environment which has proven ineffective in handling the complexity of today’s virtual environments. Unlike their counterparts in physical server environments, components in virtual environments share host resources, creating complex, highly interdependent relationships between them. They are also highly dynamic, enabling IT to continually create and move workloads across VMs. IT pros can no longer make informed decisions using manual computer science approaches of yesterday and analyzing alerts from a single silo at a time. This is why companies are turning to “data science” approach that leverages sophisticated AI disciplines of machine learning and deep learning to get a holistic, automated solution to eliminate the time-consuming, manual process of problem-solving performance issues and optimizing virtual environments.

Machine Learning Analytics Tools Provide the Answers

Rather than monitoring individual metrics as threshold-based tools do, advanced machine learning-based solutions learn the complex behavior of interrelated components as they change over time. They can consider multiple metrics of related components simultaneously. As a result, they deliver much more precise, accurate information about virtual environments than either primitive machine learning tools or traditional threshold-based tools. Instead of creating “alert storms”, they identify the meaningful incidents associated with abnormal behavior at a specific time of day, week, month and year. And because machine learning is central to the design, there is no manual configuration required. Advanced machine learning solutions, can be up and running in minutes and learning behaviors immediately. As a result, this shift to a data-centric, behavior-based approach has major implications that significantly empower IT professionals. IT pros will always need domain expertise in computer science, but what analytical skills will IT need to become effective in this new AI-driven world?

Instead of spending their days reacting to and reworking application performance issues, IT will shift their focus from diagnosing problems to proactively predicting and avoiding them in the first place. Freed of the need to over-provision to ensure performance and reliability, they will be able to look for ways to optimize efficiency and spend their time focusing on the larger goals at hand. This allows IT to provide true business value, and work on projects that drive company objectives forward. Generally, that kind of value gives IT an important voice in senior management, bringing them into the decision making process and closing the gap between IT and operations. And as IT pros understanding and use of machine learning-based analytics tools advance, they will be on the forefront of building the foundation for automation and the future of the self-driving data center.

Jim’s Bio:

Jim Shocrylas is the Director of Product Management at SIOS.  Jim has more than 20 years in the IT industry, most recently as Portfolio Manager for EMC’s Emerging Technologies Division.

Filed Under: News and Events, News posts, Press Releases Tagged With: #AIOps, analytics, Artificial Intelligence, Machine Learning

MarketWatch: SIOS DataKeeper Cluster Edition Honored With Computer Technology Review’s Most Valuable Product (MVP) 2015 Award

May 26, 2015 by <a href="http://www.marketwatch.com/story/sios-datakeeper-cluster-edition-honored-with-computer-technology-reviews-most-valuable-product-mvp-2015-award-2015-05-26">MarketWatch</a> Leave a Comment

MarketWatchSIOS Technology Corp. (www.us.sios.com), maker of SAN and #SANLess clustering software products, today announced it received a Most Valuable Product (MVP) award for 2015 from Computer Technology Review for its SIOS DataKeeper(TM) Cluster Edition software.

As one of a select number of notable IT products receiving CTR’s MVP award, SIOS DataKeeper Cluster Edition was honored by CTR’s editorial panel based on rigorous judging criteria that included product innovation, functionality and affordability.

SIOS DataKeeper Cluster Edition software enables SANLess clustering for high availability and disaster protection in Windows Server Failover Clustering environments. It protects data in physical, virtual, and cloud environments and provides enterprise-class protection for all server workloads at a fraction of the cost of traditional shared-storage (SAN) based clusters.

View the Entire Article at MarketWatch

Filed Under: News and Events, News posts Tagged With: Awards, Computer Technology Review, SIOS DataKeeper Cluster Edition

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