Enhancing the network performance of private or hybrid clouds means it's absolutely crucial to control cloud sprawl and how your company uses its cloud resources. Cloud environments are founded on virtualization, but they add features such as self-service and reporting or chargeback in order to provide easier, on-demand access to computing facilities. This alleviates much of the traditional everyday provisioning routine from IT staff, but it can easily allow wasted resources which, if left uncontrolled, lead to performance-impairing resource shortages. And every performance hiccup can affect your company's reputation among users.
Even when migrating or bursting workloads to public cloud providers, unrestrained use of the network and overprovisioning resources can choke critical applications and cause unnecessary public cloud costs over the long term.
Cloud monitoring and alerting tools can help prevent resource waste and application performance problems. However, today's cloud-based enterprises must implement the policies, guidelines and tools needed to track workload lifecycles. If old, unneeded or excessively provisioned workloads can be identified, they can also be relocated or removed -- freeing resources to ease contention, improve performance of remaining workloads, and lower capital and operating expenses.
Don't forget that public cloud computing resources are typically shared, so pay particular attention to the public cloud provider's service-level agreement (SLA). Understand service guarantees to know what the provider will do if it does not meet them, as well as how it will remedy the problem. Even when your own workloads are provisioned and are otherwise working properly, another unrelated workload on the same server might not, resulting in pesky I/O bursts that wind up disrupting your workload. This is known as the "noisy neighbor" effect -- which has affected even big-name cloud providers such as Amazon Web Services. Application performance monitoring (APM) tools may reveal this effect when a workload's performance varies while the underlying traffic to and from your workload does not.
About the author:
Stephen J. Bigelow is the senior technology editor of the Data Center and Virtualization Media Group. He can be reached at email@example.com
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