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How to Improve Cloud Computing with Performance Monitoring

Keith Bromley

According to a webinar presented by Viavi, 6 Steps for Maintaining Control in the Cloud, a survey was conducted by Gartner Research with IT engineers that had moved workloads to the cloud. The results showed that approximately 53% of respondents were blind as to what happens in their cloud network and 79% were dissatisfied with the monitoring data that they get about their cloud network. This lack of proper monitoring data leads to a lack of ability to accurately understand what your network is doing and how well it is/is not performing.

In a previous blog, I talked about how to get visibility into cloud networks and resolve the first part of the problem. This included why visibility was important and how to accomplish it. Once you have that information, the next thing you need to understand is the performance of your cloud network so that you can answer important questions. This includes:

How will the network handle the application data that you currently have?

Is the current contracted work space enough?

Will you encounter performance problems and need to upgrade the CPU and memory in a hurry before you get more user complaints?

Here are three suggestions to help you:

■ Test your cloud network for adequate capacity before you migrate from your current on-premises solution

■ Monitor your cloud and on-premises networks during the migration process

■ Continually verify that your cloud provider is delivering upon the contracted SLA

To get the answers you want, the first thing you will want to do is to insert virtual taps into your cloud network so that you get the proper monitoring data you need.

The second thing you will want to do is create a proactive cloud monitoring solution. Basically, this is a monitoring solution that uses software agents and probes that you can place across your cloud and physical infrastructure.

With a proactive monitoring solution, you can use visibility technology to actively test your solution before migration, during migration, and after migration. For instance, you can pre-test the network with synthetic traffic to understand how the solution will perform against either specific application traffic or a combination of traffic types. The synthetic traffic provides you the network and/or application loading of a "busy hour" and the flexibility to perform evaluations during the network maintenance window.

Once the migration starts, you can measure the ambient latency, throughput, and performance problems on a per-hop basis within the network to see how it is performing. This lets you analyze both your on-premises solution as well as your cloud solution. This can be especially important if you have a hybrid solution right now, and are in the (often multi-year) process of transitioning from the physical to the virtual (cloud) world. A proactive testing and monitoring approach gives you the confidence that your new application rollouts will be successful in either network.

Proactive monitoring also allows you to perform SLA validation during business hours, since it is not service disrupting. This allows you validate the SLA performance at will. The information gathered can then be used to inform management about which goals are being met. If goals are not being met, you can use the impartial data you have collected and contact your vendor to have them either fix any observed network problems, or give you a discount if they are failing to meet agreed upon SLAs.

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How to Improve Cloud Computing with Performance Monitoring

Keith Bromley

According to a webinar presented by Viavi, 6 Steps for Maintaining Control in the Cloud, a survey was conducted by Gartner Research with IT engineers that had moved workloads to the cloud. The results showed that approximately 53% of respondents were blind as to what happens in their cloud network and 79% were dissatisfied with the monitoring data that they get about their cloud network. This lack of proper monitoring data leads to a lack of ability to accurately understand what your network is doing and how well it is/is not performing.

In a previous blog, I talked about how to get visibility into cloud networks and resolve the first part of the problem. This included why visibility was important and how to accomplish it. Once you have that information, the next thing you need to understand is the performance of your cloud network so that you can answer important questions. This includes:

How will the network handle the application data that you currently have?

Is the current contracted work space enough?

Will you encounter performance problems and need to upgrade the CPU and memory in a hurry before you get more user complaints?

Here are three suggestions to help you:

■ Test your cloud network for adequate capacity before you migrate from your current on-premises solution

■ Monitor your cloud and on-premises networks during the migration process

■ Continually verify that your cloud provider is delivering upon the contracted SLA

To get the answers you want, the first thing you will want to do is to insert virtual taps into your cloud network so that you get the proper monitoring data you need.

The second thing you will want to do is create a proactive cloud monitoring solution. Basically, this is a monitoring solution that uses software agents and probes that you can place across your cloud and physical infrastructure.

With a proactive monitoring solution, you can use visibility technology to actively test your solution before migration, during migration, and after migration. For instance, you can pre-test the network with synthetic traffic to understand how the solution will perform against either specific application traffic or a combination of traffic types. The synthetic traffic provides you the network and/or application loading of a "busy hour" and the flexibility to perform evaluations during the network maintenance window.

Once the migration starts, you can measure the ambient latency, throughput, and performance problems on a per-hop basis within the network to see how it is performing. This lets you analyze both your on-premises solution as well as your cloud solution. This can be especially important if you have a hybrid solution right now, and are in the (often multi-year) process of transitioning from the physical to the virtual (cloud) world. A proactive testing and monitoring approach gives you the confidence that your new application rollouts will be successful in either network.

Proactive monitoring also allows you to perform SLA validation during business hours, since it is not service disrupting. This allows you validate the SLA performance at will. The information gathered can then be used to inform management about which goals are being met. If goals are not being met, you can use the impartial data you have collected and contact your vendor to have them either fix any observed network problems, or give you a discount if they are failing to meet agreed upon SLAs.

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 ...