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Enhancing the Availability of Important but Non-Critical Applications

Cassius Rhue
SIOS Technology

For mission-critical applications, it's often easy to justify an investment in a solution designed to ensure that the application is available no less than 99.99% of the time — easy because the cost to the organization of that app being offline would quickly surpass the cost of a high availability (HA) solution. In a 2022 survey from ITIC, 44% of respondents from mid-sized and large enterprises said that a single hour of unexpected downtime could cost more than $1 million.

But not every application warrants the investment in an HA solution with redundant infrastructure spanning multiple data centers or cloud availability zones. Many of the applications in an organization fall into a category perhaps best described as important-but-non-critical applications. If these applications go offline, even for an extended period of time, they're not likely to impact your business to the tune of $1M per hour. But downtime may be costly in other ways. You may need to redirect IT resources from other projects to bring them back online. Your employee productivity and satisfaction may take a hit, leading to lower customer satisfaction. Your reputation may suffer.

So how can you reduce the risk of unexpected downtime without investing in an HA solution?

The answer actually has two parts. One is simple: constant vigilance, enabled through the use of application monitoring tools that monitor all aspects of the application execution environment — from the underlying characteristics of the hardware to the allocation of resources and the management of process threads. Because these tools are designed with application awareness, they can both identify conditions that are out of bounds for the application and ignore conditions that are, in fact, normal for the application, even though a monitoring solution that lacks application awareness might flag that condition as problematic.

The second part of the answer, though, is just as important: incorporate application-aware automation. There are any number of monitoring tools that can keep your IT personnel apprised of the performance of distinct aspects of the application stack. When these tools detect an issue, though, they typically send an alert to the IT team, which then needs to review the alert, determine what to do, and then perform some action to resolve the problem (if, in fact, the alert really does indicate a problem). If the application-aware monitoring tools were also able to respond — appropriately and automatically — to detected problems, then you could enhance the performance and reliability of these important-but-non-critical applications without placing any additional burdens on your IT team.

Such application-aware solutions for automated monitoring and maintenance of your important-but-non-critical systems are available. By monitoring for problems that might be minor in the near term but more problematic in the long term, they can proactively help you avoid application downtime. For example, they might detect and automatically restart an application service that is not performing as expected. If that doesn't improve the situation, the solution might restart the entire application (or reboot the entire server) — all without operator intervention. These tools can bring a problem to the attention of an operator — if it's a problem that the tool cannot resolve on its own — but because these tools are designed to be application aware and have been designed to execute an appropriate response automatically, they can proactively do the right thing without having to request an intervention from your IT personnel.

By remaining vigilant and monitoring all aspects of the application environment, these solutions can ensure that your important-but-non-critical applications remain accessible and operational at a much higher level of availability than you would otherwise achieve through a combination of hope and benign neglect. You won't have a guarantee of 99.99% availability as you would if you were running your applications on an HA infrastructure spanning multiple data centers or cloud availability zones, but for a fraction of the cost of an HA infrastructure you can enhance the availability of these applications in a way that is commensurate with their importance to your employees, customers, and reputation.

Cassius Rhue is VP of Customer Experience at SIOS Technology

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Enhancing the Availability of Important but Non-Critical Applications

Cassius Rhue
SIOS Technology

For mission-critical applications, it's often easy to justify an investment in a solution designed to ensure that the application is available no less than 99.99% of the time — easy because the cost to the organization of that app being offline would quickly surpass the cost of a high availability (HA) solution. In a 2022 survey from ITIC, 44% of respondents from mid-sized and large enterprises said that a single hour of unexpected downtime could cost more than $1 million.

But not every application warrants the investment in an HA solution with redundant infrastructure spanning multiple data centers or cloud availability zones. Many of the applications in an organization fall into a category perhaps best described as important-but-non-critical applications. If these applications go offline, even for an extended period of time, they're not likely to impact your business to the tune of $1M per hour. But downtime may be costly in other ways. You may need to redirect IT resources from other projects to bring them back online. Your employee productivity and satisfaction may take a hit, leading to lower customer satisfaction. Your reputation may suffer.

So how can you reduce the risk of unexpected downtime without investing in an HA solution?

The answer actually has two parts. One is simple: constant vigilance, enabled through the use of application monitoring tools that monitor all aspects of the application execution environment — from the underlying characteristics of the hardware to the allocation of resources and the management of process threads. Because these tools are designed with application awareness, they can both identify conditions that are out of bounds for the application and ignore conditions that are, in fact, normal for the application, even though a monitoring solution that lacks application awareness might flag that condition as problematic.

The second part of the answer, though, is just as important: incorporate application-aware automation. There are any number of monitoring tools that can keep your IT personnel apprised of the performance of distinct aspects of the application stack. When these tools detect an issue, though, they typically send an alert to the IT team, which then needs to review the alert, determine what to do, and then perform some action to resolve the problem (if, in fact, the alert really does indicate a problem). If the application-aware monitoring tools were also able to respond — appropriately and automatically — to detected problems, then you could enhance the performance and reliability of these important-but-non-critical applications without placing any additional burdens on your IT team.

Such application-aware solutions for automated monitoring and maintenance of your important-but-non-critical systems are available. By monitoring for problems that might be minor in the near term but more problematic in the long term, they can proactively help you avoid application downtime. For example, they might detect and automatically restart an application service that is not performing as expected. If that doesn't improve the situation, the solution might restart the entire application (or reboot the entire server) — all without operator intervention. These tools can bring a problem to the attention of an operator — if it's a problem that the tool cannot resolve on its own — but because these tools are designed to be application aware and have been designed to execute an appropriate response automatically, they can proactively do the right thing without having to request an intervention from your IT personnel.

By remaining vigilant and monitoring all aspects of the application environment, these solutions can ensure that your important-but-non-critical applications remain accessible and operational at a much higher level of availability than you would otherwise achieve through a combination of hope and benign neglect. You won't have a guarantee of 99.99% availability as you would if you were running your applications on an HA infrastructure spanning multiple data centers or cloud availability zones, but for a fraction of the cost of an HA infrastructure you can enhance the availability of these applications in a way that is commensurate with their importance to your employees, customers, and reputation.

Cassius Rhue is VP of Customer Experience at SIOS Technology

Hot Topics

The Latest

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 ...

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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 ...

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