LAS VEGAS, Dec. 3, 2019 /PRNewswire/ -- AWS re: Invent booth 3214 -- Opsani, the leading provider of AI-driven Continuous Optimization for cloud applications, today announced enterprises with services operating in the cloud are overspending by millions due to inefficiencies with their apps and runtime environments. The findings were recently uncovered in a poll conducted by Lead to Market of 100 companies that were verified as having a more than $5 million spend on annual cloud costs.
69 Percent of respondents report regularly overspending on their cloud budget by 25 percent or more, leading to a loss of millions on unnecessary cloud spend. Respondents were a mix of companies using the leading public clouds—AWS, Azure, and Google—internal clouds, and "others."
Gartner predicts that by 2022 overall cloud spend will reach more than $330 billion. Current estimates reveal that, even now, billions of this is the result of needless and wasted outlay. Why? Because resources are over-provisioned in order to buy peace of mind, and performance tuning is only happening in scenarios when an SLA isn't met, instead of continuously, as new code is released.
Of the poll respondents, 45 percent are releasing software in weekly, daily or hourly sprints. 65 percent of these companies plan on deploying their mainstream production applications on containers within the next 12 months. However, despite this trend toward DevOps and microservices, only 43 percent of respondents are confident their applications are running efficiently in the cloud, which leads to sub-par user experiences and over-paying for unneeded resources.
Modern enterprises are neglecting the post-release portion of the delivery pipeline—continuous optimization of live cloud apps and their environments. Survey respondents indicated that:
Polled companies were also asked what their biggest priorities were for DevOps moving forward. Options were: reducing cloud spend by more than 30 percent, improving application performance by more than 20 percent, or accelerating release cycles by more than 200 percent:
Opsani AI uses deep reinforcement learning (DRL), a specialized branch of AI to autonomously and continuously optimize live cloud apps and their environments. Continuous Optimization (CO) leverages neural networks and deep reinforcement learning to stop apps from wasting money. CO continuously examines millions of combinations of configurations and pinpoints the optimal combination of resources and parameter settings. With CO, it's possible to tweak and perfect those settings that are too complex to touch, so that infrastructure is tuned precisely to the workload and goals of the application.
As a result, DevOps teams run their apps with better performance to deliver the best user experience. However, 64 percent of poll respondents said they had limited to no ability to use AI tools for this process.
And overspending for cloud apps only goes up as services get traction. Take a company currently spending $50mm on the cloud. If it's growing at 20 percent year-on-year, the total cloud spend will be more than $372mm over the next five years. 20 percent of that $372mm is unnecessary spend--that's more than $60mm in overspend.
"Modern enterprises are using the cloud to reduce the costs of operating data centers, scale exponentially, bring value-added services online faster and more efficiently, and enjoy the flexibility of using resources as needed," said Ross Schibler, co-founder and CEO, Opsani. "But, operating in the cloud comes with costs that, if not managed continuously, can climb fast due to over provisioning and a lack of visibility into how live applications are affected by the CI/CD toolchain. Even small changes to live code disrupt tuned applications that lead to weak performance and higher costs. Opsani automates the optimization of live cloud apps to drop costs, deliver a better user experience, and free staff from mundane tuning work so they can bring more revenue-generating services online."
Opsani customers report more than 200 percent increases in performance per dollar, while saving up to 80 percent on their cloud spend—overnight.
Opsani AI proactively tunes resources like CPU and memory, middleware configuration variables like JVM GC type and pool sizes, kernel parameters like page sizes and jumbo packet sizes, and autoscalers; and application parameters like thread pools, cache timeouts and write delays.
Plugins for AWS, Azure, and GCP customers are available for GitHub, Terraform, Jenkins, Spinnaker, Wavefront, DataDog, SignalFX, Prometheus, Splunk and New Relic.
Go to https://opsani.com/product/ or meet them at AWS re: Invent Booth 3214
Opsani is the leading provider of AI-driven Continuous Optimization for cloud applications. visit https://opsani.com