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.
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.
In short, IT practitioners don't have the capacity to address these issues without sufficient automation tools. Here's why:
Too many tools addressing siloed visibility use cases
Some are old, and some are expensive
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?
To be successful, IT needs to be in a strategic partnership with business. Without this, it's impossible to efficiently help enable the changes necessary to help enable business growth. Cisco believes analytics enable IT professionals to turn raw data into actionable insights that they can use to drive business growth. When IT practitioners move to a proactive operations approach for their data center, both sides win.
As a key element of our Intent-Based Networking (IBN) strategy, we're delivering a powerful combination of data center analytics and automation capabilities — within and across domains — to help our customers simplify their network operations and attain the insights and assurance needed to continually evolve them.
Benefits to business:
1. Highest Operational Uptime and Outage Mitigation to meet SLAs/SLOs
2. OpEx (Operational Expenditure) Optimization and IT Strategic Agility Enhancement
3. Security Compliance and Assurance
Benefits to IT:
1. Faster remediation of issues while increasing agility
2. Allow engineers to focus on mission critical work
3. Greater confidence and less risk in operating your network
According to latest Gartner report "2019 Strategic Roadmap for IT Operations Monitoring."
To do this, IT needs a way to transform and get past install, provisioning and segmenting. In other words, IT needs a way to make “Day-2 Operations” easier. They need to be able to:
IT practitioners can do this through intent-based networking (IBN) and automation, which allows them to: