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All Brawn and No Brain: Application Delivery Without Analytics

Ranga Rajagopalan
Posted on Jan 15, 2015, 11:00:00 AM

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Four factors are driving change in how applications are developed and deployed today.

First off, today’s users access applications and services from a plethora of devices in addition to their static desktops. They demand secure access from work, from home, and on the go – all with consistent and reliable performance.

Second, application architectures are evolving from traditional 2 / 3 tier models to distributed “microservices” architectures specifically to ensure efficient application delivery on mobile devices. This is exactly how applications at hyperscale companies such as EBay, Netflix, Twitter, and Amazon are architected.

Third, application deployment locations have changed. Applications may be deployed not only at on-premise enterprise datacenters but also at several public cloud locations such as AWS. In addition, applications may span multiple datacenters and clouds for redundancy and higher performance.

Finally, the efficacy of applications is now measured in terms of end-user engagement and satisfaction for both internal employees and external customers. As a result, end-user monitoring is critical for ensuring high quality service delivery and guaranteeing SLAs. Furthermore, the sprawl of microservices within and across clouds increases the need for improved visibility, monitoring, performance management, and security.

New world, new problems  

With the changing application architectures, deployment patterns, and flat IT budgets:

  • How do you guarantee the performance and safety of all your applications?
  • How do you monitor hundreds, if not thousands of applications out of the box (Batteries included!)?
  • How do you sift through and make sense out of millions of metrics and logs collected over months and years from your infrastructure devices?
  • How do you hunt for meaningful insights from hundreds of Gigabits - or even Terabits of traffic that traverse your infrastructure each day?
  • How do you proactively identify application performance issues even before they occur and stop reacting to appliance (and thereby application) outages?

Adding the brain to the brawn…

Because of the nature of its function as well as the strategic location it occupies, the ADC - application delivery controller (a.k.a load balancer) is uniquely positioned to bridge the gap between the end-user application experience and your infrastructure resources. Unfortunately, application delivery today is performed in a complete vacuum since ADCs (and load balancers) do not take any real-time user-to-app analytics or insights into consideration. By themselves, various analytics tools merely provide reports and dashboards that are interesting, but not really capable of automatically improving application performance and / or guaranteeing end-user experience.

The marriage of application delivery and real-time user-to-app analytics is therefore necessary to “close the loop” and guarantee end-user satisfaction. In other words, an analytics-driven ADC is the Holy Grail that can ensure ‘kumbaya’ between the IT admins and the DevOps engineers.

And that’s exactly what we engineered the Avi Networks’ analytics-driven Cloud Application Delivery Platform (CADP) to do! In addition to being a full-featured ADC, the Avi Networks CADP does the following:

  • Automatically base-lines thresholds for important metrics, allowing the ability to use the baseline information to predict anomalies even before they occur
  • Provides a single aggregate “Health Score” that identifies app performance, monitors resource utilization, and flags anomalous metrics for all apps across all locations
  • Includes tools that allow you to drill down into performance degradation issues - whether they are caused within the compute, the network, the user-device, or even the application itself
  • Provides a Google-like search index while logging analytics on application dimensions - thereby allowing you to search every transaction in real-time
  • Presents analytics and insights into client behavior, browsers, user locations, Operating Systems, etc.
  • Helps you predictively reduce MTBF (mean time between failures), instead of simply reducing MTTR (mean time to resolution)

The Avi Networks CADP combines a “best in class” ADC with the industry’s first streaming, real-time App Data Analytics architecture, which consists of a HyperScale Data collector / reducer and a clustered, scalable BigData Analytics Controller. With the integrated analytics capabilities described above it is the industry’s only self-correcting, “adaptive” application delivery platform that spans and serves every data center and cloud while you manage it as a single device.

As segments of a multi-part series, my next few blogs will accordingly dig deeper into the Avi Networks CADP, with specific details on each of the powerful analytics capabilities we built to ensure the industry’s first Closed-loop Application Delivery™ architecture.

In the world of application delivery, the analytics are the much-needed “brain” to accompany the brawn. Learn more at Inline Analytics and get hands-on with our analytics in action by clicking on the Try Avi link below.

Try Avi

Topics: ADC, Closed-Loop Application Delivery, CADP, Architecture, Analytics

  
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