Optimizing App Performance in a Multicloud Stack
The cloud is increasingly where businesses live. This progression has only accelerated in recent years. Not only are businesses becoming more reliant on the cloud, the way in which many are using the cloud has also changed.
Whether it’s part of a multivendor strategy, a way to avoid lock-in, extra redundancy for security, developer preference, or for another reason, multicloud is becoming the new normal. For instance, if you’re using SaaS applications such as Salesforce or Office 365, then you’re already dependent on multiple clouds.
There are plenty of advantages to a multicloud strategy. But it brings businesses some challenges, too: a much more complex monitoring environment, lack of visibility, and performance variations across regions and cloud architectures. All of these challenges can impact end-user experience.
The caliber of customer relationships and the productivity of an organization’s workforce now depends on the quality of their digital experience. That digital experience in turn depends on an interlocking system of multiple clouds, distributed application architectures, and a complex web of APIs and third-party services.
This means there’s a lot of moving parts, and a lot that can go wrong. When it does, resolving the issue quickly is a priority. But the complexity that enables the services and capabilities we all rely on, paired with the lack of an end-to-end view of user experience, can make properly escalating and solving the problem a challenge.
The Cloud Migration Process Presents Its Own Unique Visibility Issues
Your situation might be different. Maybe you’ve resisted migrating essential company functions and data to the cloud precisely because of these concerns — the lack of control that comes with reliance on the public Internet and the lack of visibility into the cloud provider infrastructure.
For many companies, migrating to the cloud is a high-stakes operation. It can be like handing the crown jewels over for safekeeping. It’s not enough to be able to monitor everything after the transfer — you want visibility and testing capabilities before the transfer begins.
What’s needed is a way to benchmark impact on performance in pre-production environments. That way, enterprises can comfortably migrate despite giving up on control of apps, because they’re able to monitor and evaluate the process before it begins. The question is: How do you achieve that?
Multicloud Monitoring in Action
The challenge of multicloud monitoring is itself multipronged. There’s the need for safe, secure and smooth migration. There’s the overlapping complexity of multiple app infrastructures. There are regional performance variations to account for, plus visibility challenges across an environment that you don’t own.
All the while, end-to-end visibility into the entirety of the supply chain is critical in order to see, predict and optimize the digital experience that customers and employees have come to rely on.
Traditional monitoring tools flatline outside the perimeter of an enterprise, creating a visibility blind spot for multicloud deployments — and so native cloud monitoring isn’t sufficient. The network is the glue that binds all cloud communication — from the end user to the cloud, within the cloud, and between clouds. Calibrating performance in multicloud environments, therefore, requires an understanding of the hundreds of dependencies that flow between public and private ecosystems that power the application.
This means for a multicloud monitoring solution to be successful, it needs some key capabilities. It should be able to:
- Test app performance in one cloud, across clouds, and across regional pairs.
- Test connectivity, both over the public Internet and cloud providers’ private backbone networks.
- Use synthetic monitoring to see and benchmark end-to-end app performance in pre-production environments.
Multicloud architectures are complex and run across multiple hosting environments, regions and providers. To manage application performance in multicloud environments, it’s imperative to track interdependent connectivity and to have access to actual performance data — both to avoid the risk of false assumptions and to optimize the ultimate delivery of the digital experience.