Why Continuous Availability Matters for Cloud Adoption
by Salvatore Salamone
Continuous availability and optimized performance are essential today. One way to ensure both is through the use of observability complemented with AIOps.
Nearly all companies are undertaking some form of cloud adoption these days. Efforts range from moving an app or workload to a cloud compute platform for the first time, melding cloud and on-premises activities into a hybrid cloud platform, or embracing cloud-native application architectures based on microservices and APIs. In all these variants, traditional tools that helped organizations ensure the performance and availability of their services and apps fail. Increasingly what’s needed are more modern tools that offer better observability and insights into what’s happening and an AI-based assist to help ensure continuous availability and stellar performance.
There are several issues at hand driving the need for modern tools. First, there is the increased complexity of cloud environments upon which organizations deploy applications and run their workloads.
Even a simple application such as providing a mobile front-end to a user’s account would involve backend elements maintained by the organization, a database on a public cloud, connectivity via the user’s provider, and any one of the major mobile operating systems. There are many inter-dependencies between the various elements, and the business has little control over most elements that could impact performance or availability. When a problem happens, it can take a great amount of time to determine the source of the outage. Modern observability tools using AIOps can help automate the root-cause analysis, accelerating the meantime to repair (MTTR) for an outage or other problem. This can significantly reduce the meantime to repair/recover.
Second, organizations can no longer be reactive, acting after a problem occurs. The traditional approach to IT management has been to wait for an angry call from customers or internal users about a service disruption or the poor quality of a service. AIOps offers a more predictive mode of operation. It enables a proactive approach that could spot, for example, an increase in dropped or re-sent packets and other indicators of poor performance and take corrective actions in real time.
Third, security is much more challenging when applications and services are delivered using multiple cloud elements, some of which are not under the control of an organization. With a modern observability tool, a security team could use AIOps to spot anomalies that are pre-cursors to an attack or activities that are indicative of a data breach. For example, AIOps might be used to alert the security team that an unusually large about of data is being sent out of the organization via a normally lightly used port.
Continuous availability is critical to meeting end-user expectations
Application performance and availability have always been important for any organization. Employees have certain expectations that the apps and services they need to get their job done will be available whenever they need them and they will perform well.
Similarly, any customer-facing application or service these days face even harsher user expectations. With people used to getting anything and everything instantly whenever they want it, there is very little intolerance for…
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