Opsani: AI-enabled Continuous Optimization for Cloud Applications

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Opsani

Ross Schibler, CEO, OpsaniRoss Schibler, CEO
When it comes to deploying applications to the cloud, most organizations today make a common mistake. They put more emphasis on the code rather than the run-time environment in terms of tuning parameters such as VM instance type, CPU shares, thread count, garbage collection and memory pool sizes. This restricts their ability to run applications in a faster and cost-efficient manner.

But, to be fair, tuning cloud applications while they run has grown beyond human scale--we need machines to do it better. The trillions of possible resources, middleware, and application parameter configurations can be integrated effectively—after identifying them correctly—into the CI/CD cycle by leveraging AI, and that’s where Opsani’s value proposition lies. Through its AI-driven Continuous Optimization application performance solution, the company delivers real-time, autonomous application tuning integrated into their clients’ CI/CD toolchain.

Using machine learning, Opsani automatically tunes the run-time parameters of its clients’ cloud applications in response to code, middleware, or environmental changes. Opsani takes the guesswork out of balancing requirements, cost, and performance by delivering a Continuous Optimization system that increases application performance and reduces cost. Further, Opsani’s system leverages machine learning to automatically adjust resource assignments and configuration settings. In the following conversation, Opsani’s CEO, Ross Schibler, shares insights on how the company empowers developers and operations with tools and services purpose-built for modern enterprise IT infrastructures.

Who are Opsani’s typical clients?

We work with clients in all industries, especially those companies with cloud-based apps that are running their service in either a VM or container-based environment. Our customers have a mature CI/CD pipeline in place and are frequently releasing new code. Most importantly, our typical clients have a desire to retain reliability and improve performance of their application while reducing their cloud spend.

Please elaborate on the underlying principles of the Opsani AI.

With our solution’s deployment in the cloud adoption pipeline, we can go beyond just the code and application layers as the Opsani neural net AI optimizes resource choices (CPU, memory), middleware configurations (JVM GC type/parameters, pool sizes), kernel parameters (page sizes, jumbo packet sizes), as well as application parameters (thread pools, cache timeouts, write delays), to find the best among the vast number of potential combinations.

The Opsani neural network learns from the intuition and characteristics of the application and how it ticks. This allows the solution to optimize the application with pinpoint accuracy for maximum efficiency gains which ultimately increases the performance to cost ratio.

We perform the initial optimization and then monitor the application performance and perform continuous optimization in response to changes in the application, middleware, or its environment. Further, we have internal APIs that help us to adjust parameters and measure the results.

How does Opsani AI continuously search for optimal settings and implement solutions? What are the benefits achieved by the clients?

The Opsani AI prioritizes the client’s KPIs and balances their optimization target between the highest performance and lowest cost. The efficiencies we find deliver a faster and better user experience while reducing resource costs. We built the Opsani AI to always fine-tune application performance that delivers our customers top and bottom line growth.

In fact, the neural network can find combinations of settings that humans may not even think of. In addition, we integrate with Kubernetes, Azure, Google Cloud Platform, and AWS and provide Plug-ins for Jenkins, Spinnaker, AppDynamics, Wavefront, Datadog, SignalFX, New Relic, Prometheus, and Terraform.

Please cite a case study where Opsani AI has enabled clients to overcome hurdles and attain desired outcomes.

One of the global leaders in family history and consumer genomics moved its operations to the cloud to enable it to scale with its customer base, and implemented CI/CD processes to facilitate faster feature rollout. However, with the rapid growth in both its user base and the range of products it provided, the company was hard-pressed to ensure that it was achieving optimum performance, efficiency, and customer experience via its cloud applications. Through the integration of Opsani AI, a new best practice was added to the client’s CI/CD toolkit—Continuous Optimization--which resulted in 230 percent performance per dollar gains and an average of more than 50 percent in cloud cost reduction.

What are some of the milestones that Opsani has achieved over the years?

The big moment came when we realized that the AI would tune applications not only faster, but way better than a human. The idea for Opsani’s AI came from watching autonomous cars navigate their environments. Autonomous cars use a neural network of sensors to ingest the ever-changing conditions around them, and then make the necessary corrections to keep the car moving safely. All of this happens autonomously.

We applied that concept to application optimization and tested our prototype AI on an in-house application. Opsani takes a little time to study the environment in which it is working, so we set the application and left for the night. The next day we expected to see maybe a 20 to 40 percent optimization, but the tool produced a 170 percent improvement. That was a ‘Eureka’ moment and the point at which we knew we had a business. Ever since then we’ve been saying to our customers, “come for the performance and stay for the cost-savings.” Approximately three-fourths of our clients achieve positive ROI within the same quarter they implement Opsani.

What does the future hold for Opsani?

Just like AI is enabling cars to function without human interference, using AI to autonomously tune applications will reduce human dependency and bring remarkable gains in cloud-based application performance and efficiency. Engineers’ time will be freed up to create new application features.

DevOps is changing, growing and becoming a strategic advantage. CI and CD will be joined by CO (Continuous Optimization) as the recognized best practices trifecta of DevOps. In the near future, we will be positioning Opsani to revolutionize the cloud optimization landscape, and inspire a transformation in DevOps culture.

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Opsani News

Opsani Secures $10 Million Series A Funding From Redpoint Ventures For AI-Driven Continuous Optimization Of Cloud Applications

REDWOOD CITY, Calif. - Opsani, the leading provider of AI-driven Continuous Optimization for cloud applications, announced the company has secured a $10 million Series A funding round led by Redpoint Ventures, with participation from early investors Zetta Ventures and Bain Capital. Satish Dharmaraj, Partner at Redpoint, will join the Opsani Board. The new funding will be used to scaleOpsani operations to tackle the projected $50 billioncloud spend market in 2020, which is projected to grow at 20 percent* year over year.

Modern DevOps has evolved for cloud environments. Savvy organizations employ a robust and effective continuous integration (CI) and continuous delivery (CD) toolchain that quickly and automatically sends safe new code to users. But up until now, DevOps hasn't been able to optimize the runtime environment—the complexity has grown beyond human scale. A simple five-container application can have more than 255 trillion hardware and software resources and basic parameter permutations. Applications run, but DevOps doesn't really know if they're getting the best performance and efficiency in their environments.

To address the problem, Opsani has added a new best practice to the CI/CD toolkit: automated continuous optimization (CO). CO uses artificial intelligence to autonomously optimize cloud applications and their infrastructure for maximum efficiency, performance for end-users, and cost savings. On average, Opsani customers experience more than a 200 percent increase in performance per dollar, getting more out of their applications while saving up to 80 percent on their cloud spend—overnight.

CO relies on systems that automatically adjust runtime parameters in response to performance and cost—even in ways people wouldn't consider—to optimize the trillions of possible combinations. As a result, companies quickly recognize dramatic cloud cost savings through increased efficiency, while most importantly, delivering a better experience to their end-users.

As one customer shares, "Ancestry is obsessed with our customers' experience and their journeys. That passion for their personal discovery and satisfaction drives us to continuously innovate and use cutting-edge technology to benefit our millions of users," said Russ Barnett, Chief Architect, Ancestry. "We're continuously growing and to support expansion, we invest in new products to ensure Ancestry's performance and efficiency are delivering maximum value. Opsani will allow us to maintain optimal performance of our cloud resources and gain visibility and control to manage costs in an increasingly complex environment."

Because it is constantly gathering new data, Opsani continuously uncovers new optimization solutions. Opsani reacts constantly to new traffic patterns, new code, new instance types, and all other key business metrics. With each new iteration, the system's predictions find the optimal solutions, and they're automatically promoted—no human intervention is needed. Infrastructure is tuned precisely to the workload and goals of the application—whether those goals relate to cost, performance, or some balance of the two.

"Redpoint has been successful in following its core philosophy of prioritizing and backing great teams, so getting behind Opasni carries that tradition forward. Ross and Peter are serial company builders and leaders, and they've again identified an unmet need that Opsani is uniquely positioned to service. Continuous Optimization of cloud-based applications completes the CI/CD toolset in DevOps," said Satish Dharmaraj, Partner, Redpoint Ventures.

"Using machine learning, Opsani automatically tunes applications for efficiency, best possible performance for end-users, and saves millions on cloud spend," Dharmaraj said. "This needs to be a new best practice for agile software teams. The savings Opsani delivers drops right to the bottom line while making the user experience consistently great, and that's a boon for the industry as a whole."

"Redpoint immediately saw the opportunity Company has to save companies millions against the soaring costs of cloud-first environments while creating the best possible experience for their applications' users," said Ross Schibler, CEO, Opsani. "They're keenly aware of how DevOps is changing, growing and becoming a strategic advantage, and with Redpoint's help, CI and CD will be joined by CO (Continuous Optimization) as the recognized best practices trifecta of DevOps."

Opsani integrates with AWS, Azure, Google Cloud Platform and Kubernetes. Plugins are available for GitHub, Terraform, Jenkins, Spinnaker, Wavefront, DataDog, SignalFX, Prometheus, Splunk and New Relic.



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