3. Map out real traffic paths - Having visibility into specific areas of a distributed network that are problematic, as well as pertinent details that can help determine a root cause, results in more tangible and actionable information for the network you own and those of your providers. To achieve a more complete picture of how traffic is traversing the cloud network, it is essential to combine synthetic tests with ping and traceroute functionality. Now network teams can not only test the reachability of an endpoint or host through the cloud, but also use that data to determine the route or path of packet through a distributed network while measuring transit delays.
Another useful data point is Border Gateway Protocol (BGP) routing table information. BGP knits the Internet together by exchanging routing information between networks. And these routes determine how traffic flows to or from your apps and services. Layering this information into your diagnostic approach helps understand how routing configurations and changes impact reachability, latency, loss, jitter or other performance metrics.
4. Collaborate with SaaS and Cloud providers - When it comes time to work with your SaaS, ISP, and cloud providers, it helps to share your information, related visualizations and diagnostic information in an easily consumable way. That way, when a trouble ticket is generated, it is dealt with more quickly by the vendor or provider. Knowing exactly where a problem exists and the related cause analysis empowers teams to take immediate action and enable the responsible party take immediate action as well.
5. Get things right before deployment - With detailed visualizations and hop-by-hop metrics, it becomes possible to try out a routing change, plan for a new data center or test a roll out of a new application or SaaS service. Synthetic testing layered with contextual data and a detailed visual network topology allows teams to test performance and gain insight into initial infrastructure configurations, plan changes and understand their impact on cloud applications to get things right before deployment.
6. Continually monitor the performance of your network and its impact on applications – The same techniques and data sources that teams use to baseline performance and achieve optimal cloud configurations can also be used on an ongoing basis to ensure continued performance. Active monitoring with additional layered information allows organizations to constantly keep an eye on performance degradation to optimize end user experiences across their network.
The inclusion of visual analysis reduces mean time to troubleshoot and repair issues. As the Internet and cloud computing reshape the enterprise network, incorporating these new data sources, correlation of pertinent data points with a unified visualization is critical to the successful deployment and management of cloud applications and services.
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