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5 Myths about Cloud HA and DR

Jerry Melnick

Enterprises are moving more and more applications to the cloud. The use of cloud computing is growing, and by 2016 this growth will increase to become the bulk of new IT spend, according to Gartner, Inc. 2016 will be a defining year for cloud as private cloud begins to give way to hybrid cloud, and nearly half of large enterprises will have hybrid cloud deployments by the end of 2017.

While the benefits of the cloud may be clear for applications that can tolerate brief periods of downtime, for mission-critical applications, such as SQL Server, Oracle and SAP, companies need a strategy for high availability (HA) and disaster recovery (DR) protection. While traditional SAN-based clusters are not possible in these environments, SANless clusters can provide an easy, cost-efficient alternative.

According to Gartner, IT service failover automation provides end-to-end IT service startup, shutdown and failover operations for disaster recovery (DR) and continuous availability. It establishes ordering and dependency rules as well as IT service failover policies. The potential business impact of this emerging technology is high, reducing the amount of spare infrastructure that is needed to ensure DR and continuous availability, as well as helping ensure that recovery policies work when failures occur, thus improving business process uptime.

Separating the truths and myths of HA and DR in cloud deployments can dramatically reduce data center costs and risks. In this blog, I debunk the following five myths:

Myth #1 - Clouds are HA Environments

Public cloud deployments, particularly with leading cloud providers, are high availability environments where application downtime is negligible.

The Truth - Redundancy is not the same as HA. Some cloud solutions offer some measure of data protection through redundancy. However, applications such as SQL Server and file servers still need additional configuration for automating and managing high availability and disaster recovery.

Myth #2 - Protecting business critical applications in a cloud with a cluster is impossible without shared storage

You cannot provide HA for Windows applications in a cloud using Windows Server Failover Clustering (WSFC) to create a cluster because it requires a shared storage device, such a SAN. A SAN to support WSFC is not offered in public clouds, such as Amazon EC2 and Windows Azure.

The Truth - You can provide high availability protection for Windows applications in a cloud simply by adding SANless cluster software as an ingredient and configuring a WSFC environment. The SANless software synchronizes local storage in the cloud through real-time, block level replication, providing applications with immediate access to current data in the event of a failover.

Myth #3 ­ Remote replication isn’t needed for DR

Applications and data are protected from disaster in the cloud without additional configuration.

The Truth - Cloud providers experience downtime and regional disasters like any other large organization. While providing high availability within the cloud will protect data centers from normal hardware failures and other unexpected outages within an availability zone (Amazon) or fault domain (Azure), data centers still need to protect against regional disasters. The easiest solution is to configure a multisite (geographically separated) cluster within a cloud and extend it by adding an additional node(s) in an alternate datacenter or different geographic region.

Myth #4 - Using the cloud is “all or nothing”

The Truth - Companies can use the on-premise datacenter as its primary datacenter and cloud as the hot standby DR site. DR configurations can be assembled from a single on-premise server that includes a remote cluster member hosted in the cloud. Or, the on-premise configuration could be a traditional SAN based cluster that includes a remote cluster member hosted in a cloud. Both approaches are very cost effective alternatives to building out a separate DR site, or renting rack space in a business continuity facility.

Myth #5 - HA in a cloud has to be costly and complicated

The Truth - A cluster for high availability in a cloud can be easily created using SANless clustering software with an intuitive configuration interface that lets users create a standard WSFC in a cloud without specialized skills. SANless clustering software also eliminates the need to buy costly enterprise edition versions of Windows applications to get high availability and added disaster protection or as described in Myth 4, to eliminate the need to build out a remote recovery site.

Jerry Melnick is COO of SIOS Technology.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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5 Myths about Cloud HA and DR

Jerry Melnick

Enterprises are moving more and more applications to the cloud. The use of cloud computing is growing, and by 2016 this growth will increase to become the bulk of new IT spend, according to Gartner, Inc. 2016 will be a defining year for cloud as private cloud begins to give way to hybrid cloud, and nearly half of large enterprises will have hybrid cloud deployments by the end of 2017.

While the benefits of the cloud may be clear for applications that can tolerate brief periods of downtime, for mission-critical applications, such as SQL Server, Oracle and SAP, companies need a strategy for high availability (HA) and disaster recovery (DR) protection. While traditional SAN-based clusters are not possible in these environments, SANless clusters can provide an easy, cost-efficient alternative.

According to Gartner, IT service failover automation provides end-to-end IT service startup, shutdown and failover operations for disaster recovery (DR) and continuous availability. It establishes ordering and dependency rules as well as IT service failover policies. The potential business impact of this emerging technology is high, reducing the amount of spare infrastructure that is needed to ensure DR and continuous availability, as well as helping ensure that recovery policies work when failures occur, thus improving business process uptime.

Separating the truths and myths of HA and DR in cloud deployments can dramatically reduce data center costs and risks. In this blog, I debunk the following five myths:

Myth #1 - Clouds are HA Environments

Public cloud deployments, particularly with leading cloud providers, are high availability environments where application downtime is negligible.

The Truth - Redundancy is not the same as HA. Some cloud solutions offer some measure of data protection through redundancy. However, applications such as SQL Server and file servers still need additional configuration for automating and managing high availability and disaster recovery.

Myth #2 - Protecting business critical applications in a cloud with a cluster is impossible without shared storage

You cannot provide HA for Windows applications in a cloud using Windows Server Failover Clustering (WSFC) to create a cluster because it requires a shared storage device, such a SAN. A SAN to support WSFC is not offered in public clouds, such as Amazon EC2 and Windows Azure.

The Truth - You can provide high availability protection for Windows applications in a cloud simply by adding SANless cluster software as an ingredient and configuring a WSFC environment. The SANless software synchronizes local storage in the cloud through real-time, block level replication, providing applications with immediate access to current data in the event of a failover.

Myth #3 ­ Remote replication isn’t needed for DR

Applications and data are protected from disaster in the cloud without additional configuration.

The Truth - Cloud providers experience downtime and regional disasters like any other large organization. While providing high availability within the cloud will protect data centers from normal hardware failures and other unexpected outages within an availability zone (Amazon) or fault domain (Azure), data centers still need to protect against regional disasters. The easiest solution is to configure a multisite (geographically separated) cluster within a cloud and extend it by adding an additional node(s) in an alternate datacenter or different geographic region.

Myth #4 - Using the cloud is “all or nothing”

The Truth - Companies can use the on-premise datacenter as its primary datacenter and cloud as the hot standby DR site. DR configurations can be assembled from a single on-premise server that includes a remote cluster member hosted in the cloud. Or, the on-premise configuration could be a traditional SAN based cluster that includes a remote cluster member hosted in a cloud. Both approaches are very cost effective alternatives to building out a separate DR site, or renting rack space in a business continuity facility.

Myth #5 - HA in a cloud has to be costly and complicated

The Truth - A cluster for high availability in a cloud can be easily created using SANless clustering software with an intuitive configuration interface that lets users create a standard WSFC in a cloud without specialized skills. SANless clustering software also eliminates the need to buy costly enterprise edition versions of Windows applications to get high availability and added disaster protection or as described in Myth 4, to eliminate the need to build out a remote recovery site.

Jerry Melnick is COO of SIOS Technology.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...