What Is Data Center Analytics?

Data Center Analytics utilize a plethora of platforms to facilitate the concurrent use of multiple data sources, data collection methods, analytical, and presentation technologies.

These platforms may include big data, machine learning, mathematical modeling, and advanced analytics technologies to enhance data center operations (microsegmentation, network insights, network performance monitoring, network assurance, application performance monitoring, intelligent troubleshooting, IT ticket management, proactive remediation) functions with proactive, personal, and dynamic insights. 

Why it matters cisco data centers

Organizations are deploying applications in multiple public and private clouds, with more applications than ever. There are also more different classes of people and machines using these applications. 

As a result of containers, microservices, and serverless, developers are constructing these highly distributed application constructs with workload tiers and data services spread across hybrid IT spanning on-premises data centers and multiple public clouds. Because of these trends, multicloud data center operators are facing serious challenges, including:

These issues require network operators to have a high level of domain expertise and the ability to correlate complex IT environments to prevent or fix issues while upholding the infrastructure uptime to honor Service-Level Agreements (SLAs) with minimum disruptions.

So, what's happening?

In short, IT practitioners don't have the capacity to address these issues without sufficient automation tools. Here's why:

Tool fragmentation

Too many tools addressing siloed visibility use cases

Different protocols/mechanisms

Limited insights 

Low data fidelity that is not actionable

Lack of data correlation; don't get the full picture

No dataplane visibility

Inconsistent API architecture

Specialized knowledge required

Difficult to find root-cause issue, and often too late to react to it

But the tools we currently have are inadequate for today's complex networking environment.

The tools we do have are fragmented.

Which means the data we have offer limited insights.

Which leaves networking teams in a reactive posture, which is the opposite of what we want and what the business is demanding.

So how can we move forward? How can we maximize uptime, align with the business, and still have capacity for new projects and initiatives?