Momento this week emerged from stealth to launch an elastic Serverless Cache platform that promises to improve the performance of applications running on databases deployed in the cloud while simultaneously reducing costs.
Fresh from raising $15 million in seed funding, Momento CEO and co-founder Khawaja Shams said Serverless Cache gives IT teams access to a serverless computing framework for accessing cache memory that can be used to improve the interactivity of applications.
Cache is, of course, already widely employed to improve the performance of applications running on databases in the cloud. However, organizations today are required to provision excess cache memory to address performance workload peaks. That approach, over time, conspires to increase the total cost of cloud computing, he noted.
A serverless cache makes it possible to more easily share an elastic pool of memory that can be invoked in seconds via an application programming interface (API) that is itself invoked by adding five lines of code to an application. The Momento cache service can then handle millions of transactions per second that can be spread across multiple applications, said Shams.
The Momento Serverless Cache service also automatically manages hot-keys, maintains high cache hit rates and keeps tail latencies low.
Organizations that are already using Momento on either the Amazon Web Services (AWS) or Google Cloud Platform (GCP) include CBS, NTT Docomo and Wyze Labs, Shams said.
In general, there’s a lot more scrutiny of cloud costs in the wake of the economic downturn, noted Shams. More IT teams are starting to take note of the fact that various cloud-native platforms enable them to more efficiently consume cloud resources, he added.
The simple truth is that far too many organizations are managing cloud resources in much the same way they managed on-premises IT environments. Capacity is being dedicated to virtual machines to ensure application availability with even less regard for cost because the perception is that the cloud makes it easy to throw hardware resources at any issue. The challenge is the bill for those cloud resources tends to add up at the end of every month. Cloud database services, in fact, are among the most expensive to consume, noted Shams.
It’s not clear how much organizations will optimize the consumption of cloud resources in the weeks and months ahead, but it’s clear more supervision is going to be required. Organizations have historically let developers provision resources in the name of agility with little to no regard for cost. Now that finance teams are looking to, at the very least, make sure cloud resources are optimally consumed, there will undoubtedly be more reviews of cloud spending patterns.
In the meantime, many organizations may also decide to accelerate the rate at which they are embracing cloud-native technologies to optimize that spending. One of the more compelling attributes of Kubernetes clusters and serverless computing is they make it easier to scale compute resources up and down as required to eliminate the need to overprovision cloud infrastructure. The challenge, of course, is that the cost of acquiring and mastering those technologies remains significant.