cloud optimization

We created a survey to ask our consumers about their cloud to gain insight into how we can provide the best possible solution to our customers. 270 people responded in the tech community of all different job titles and cloud providers. This survey gave us lots of valuable insight into how companies are using the cloud for their business and their pain points, which is where we come in. 

We decided it would be helpful to pull some of the questions people left for us on our survey to educate people on Opsani, our software, and where we fit in the cloud computing space. 

If you participated in the survey, thanks so much! Hopefully, this blog will help answer some of your questions and give you a clear understanding of our solution! 

What is the accuracy of the data analysis?

With data analysis, sophisticated application configuration analysis requires parsing through enormous decision trees and testing multiple settings to discover performance, reliability, and cost minima and maxima. The trick is to conduct this analysis without falling into the trap of any local maxima or minima.

Humans are notoriously bad at parsing giant decision trees. This results from cognitive bias, time pressures, and “intuition” all get in the way of finding the right solution.

Machine’s do not have the same limitation as humans, but that is not to say that they *always* find the right answer. What we can say, with significant confidence, is that Opsani’s Machine Learning algorithms vastly outperform humans by 5-10X. 

So, how accurate is our data analysis? It is much more accurate than what you would expect from human “experts.”

Can customer information be kept safe?

Opsani relies on RED metrics. RED metrics are not PII. We do not need and do not store any PII information such as MAC addresses, IP addresses, or other unique identifiers or hashes that describe any of our customers’ workloads. And, as soon as we make our adjustments and communicate our analysis back to the customer, we purge the requisite RED metrics.

In other words, customer data is kept safe with Opsani because we do not rely on any sensitive customer data. What you do not have, you cannot lose.

How do you utilize AI for cloud optimization?

Opsani COaaS maximizes cloud workload performance and efficiency using the latest AI and Machine Learning to continuously reconfigure and tune with every code release, load profile change, and infrastructure upgrade. We accomplish this while integrating easily with either a single app or across your service delivery platform while also scaling autonomously across 1000’s of services.

For a deeper understanding, check out our whitepaper or watch our webinar Using ML to Optimize All Applications Across the Delivery Platform.

How are you different from other Cloud providers?

We are not a cloud provider. We are instead a tool to manage the cloud. We are different from other cloud optimization tools because other vendors run experiments, but no one is doing it autonomously where it systematically learns and gets better every time. Other products are just a reactive system instead of determining what configuration works best. 

What vulnerability scanning features (if any) are embedded into your product?

None

Does your cloud optimization solution work for different deployment options?

Opsani Team is designed for managing Kubernetes settings. Then, once you upgrade to Opsani Enterprise, we will work with you to integrate with your deployment platform, such as Harness or Argos. 

How does Opsani cloud optimization enhance performance?

When you deploy Opsani, you define your app’s service-level objectives (SLOs). Opsani AI helps you reach your SLOs by finding and implementing the best configurations. Continuous Optimization as a Service (COaaS) will rightsize your resources to continuously and autonomously tune workloads with sophisticated AI algorithms. In addition to COaaS, OLAS (Opsani Learning AutoScaler) extends COaaS with autonomous, intelligent autoscaling that automatically learns traffic periodicity, trends, and burst behavior.

Check our webinar How to Use COaaS & OLAS for Optimal Application Performance

Why can’t cloud optimization be done manually?

 It’s impossible to keep modern applications in optimal performance by human effort – they are way too complex. For example, a three-service app with just two parameters each has combinations in the trillions. That is why you need AI to do this work – This is what Opsani has built.

For more information on why cloud optimization can’t be done manually, check out this 1 min clip Why manual tuning is obsolete.

What’s the easiest way to save money?

The easiest way is to rightsize your application for the performance that you need. This can be done by efficiently allocating your cloud resources as well as autoscaling.

Do I need to deploy Kubernetes to use your products?

No, you don’t. Opsani Team assumes Kubernetes, but Opsani Enterprise works with any cloud workload.

What are your product features and capabilities, and how would it help with ROI?

Our product is Opsani Dev, Team, and Platform. For a visual breakdown of our product, click this page!

In terms of how our product will help with ROI, Opsani enables companies to reduce cloud costs by up to 80% while increasing performance by up to 210%. If you would like an example of how Opsani has improved our customer’s cloud applications, check out our customer success story with ancestry!

How can your solution be used with Kubernetes-native technologies such as Horizontal Pod Autoscaler and Cluster Autoscaler?

The Opsani Learning Autoscaler (OLAS) is a drop-in replacement for the Kubernetes Horizontal Pod Autoscaler (HPA). Unlike HPA, OLAS provides predictive and proactive autoscaling. Using machine learning, OLAS learns the traffic patterns of your service and scales up just ahead of time to ensure enough pods are ready to take the increased traffic. When traffic subsides, OLAS quickly scales down to reduce cloud costs. To learn more, check out our whitepaper Juice Kubernetes performance with Opsani Learning Autoscaler or blog Optimize Beyond Your Horizontal Pod Autoscaler.

What’s cloud optimization? Is that kind of automation?

Our cloud optimization is not only automated but autonomous. Automation is doing the same task over and over. It’s very predictable. For example, a piece of code will always do the same thing with the same input. Think about it in the way of putting your car on autopilot; your car knows to stay in the lane or slow down when it needs to. Autonomy is learning and doing a different action in the same environment. Instead of putting your car on autopilot, your car learns traffic is bad at a specific time and will take a different route.

What is fully autonomous Optimization?

The significant difference between autonomy and automation is that applications can think for themselves. Instead of just doing the same task over and over again, these machines are thinking and predicting based on based learnings for the best possible outcome. For more info on the difference between autonomous and automation, check out our blog The Future is Autonomous, Are You Ready?

I would like to explore more on Kubernetes. Do you have any insight?

We have several different resources available when it comes to Kubernetes. We have resources where you can learn about Opsani Kubernetes cost optimization and just general Kubernetes tips and best practices.

Here is our webinar, Quick Start for Opsani Kubernetes Optimization. We also have a whitepaper Using Saturation Optimization to Improve Application Performance on Kubernetes, a guide, The Essential Guide to K8s Optimization.

We also have articles for Kubernetes best practices such as How to Monitor Kubernetes with Prometheus, Five Ways to Run Kubernetes on AWS, Instrumenting Kubernetes with Envoy for Application Performance Metrics, Kubernetes Cost Optimization Best Practices, Kubernetes Node Affinities Best Practices, How to Manage Requests and Limits for Kubernetes, 10 Kubernetes Performance Tuning Tips and Best Practices, Kubernetes Best Practices & Cloud Cost Optimization, Kubernetes Best Practices: Seven Optimization Tips, What is Kubernetes?

Do you provide just bare metal or even Kubernetes? If Kubernetes, what version do you support?

We suggest that you virtualize your bare metal server or run containers on it to get the most use out of it. Of course, you will need to orchestrate your VMs or containers. Opsani can optimize both, although it is much easier to integrate us into Kubernetes. You can deploy us on Kubernetes 1.14 or later.

Conclusion 

We hope we answered all your questions about Opsani, but if not, feel free to contact us! We are always happy to discuss our product or if you need some resources in the cloud computing space. If you are interested in setting up a free trial with us, click here