Don't let the moniker of Infrastructure 2.0 fool you. Applications are an integral part of the new network equation.

jetNEXUS has a nice post entitled, “What does Application acceleration mean?” Aside from completely ignoring protocol acceleration and optimization (especially good for improving performance of those chatty TCP and HTTP-based applications) the author makes a point that should have been obvious but isn’t – compression is actually good for image heavy sites.

It’s true that images are technically already compressed according to their respective formats, so compression doesn’t actually do anything to the images. But a combination of browser rendering rules and client-side caching make the impact of compressing the base page significant on the overall performance of an image-heavy site.

Firstly, the images can't be displayed until the base page arrives at the client, so it follows that the quicker you can deliver the base page, the faster you can request the objects and the quicker the page can load.

Secondly, web sites and applications generally have a consistent look and feel. As such the effect of client side caching is significant. This means that most of the data that will be sent is compressible as most of the images are already saved at the client side.

This is definitely one of those insights that once it’s pointed out makes perfect sense, but until then remains an elusive concept that many of us may have missed. Understanding the way in which the client interprets the data, the HTML and all its components, means the ability to better apply application delivery policies such as those used for acceleration and optimization to the application exchange. Combined with the recognition that compression isn’t always a boon for application performance – its benefits and performance impact depend in part on the speed of the network over which clients are communicating – the application delivery process can be optimized to apply the right acceleration policies at the right time on the right data.

It may be necessary, however, for the application to take a more active role in deciding what acceleration policies should or should not be used, especially in the case where one of the primary factors is regarding the content of the response being returned. While an intermediary capable of inspecting the application data on ingress or egress is certainly able to intercept the data and inspect it to determine the number of images in the content, it would be more efficient for the application to participate in the process instead as it can provide that information without needing to inspect the data on every request.

This is yet another example of why it’s important to understand the application from end-to-end. In this case it’s not so much a matter of having components that are application-aware, but rather it’s important for those responsible for putting application delivery policies into place that need to understand the application end-to-end and be aware of its behavior at both endpoints: the client and the application. A dynamic infrastructure integrates the unique context available from application, the network, and the client to make more intelligent decisions regarding the delivery of the application. The application must be an active participant in this process in order to complete the delivery trifecta that will optimize and accelerate application delivery to users based on the context in which the request was made.

The application instance, which is almost certainly “hidden” behind an application delivery controller or load balancer and other network infrastructure components (firewalls) cannot “see” the speed of the network over which the user is requesting data, but the intermediary can. The application knows how many images are on a given page without requiring additional inspection and parsing. If the application can communicate that information to the application delivery controller, where the application acceleration policies will be applied, that data can be used as a factor in the optimization equation.

That’s one of the precepts of Infrastructure 2.0, that the endpoints collaborate just as the infrastructure collaborates to provide the information necessary to make the best decisions for delivery (security, acceleration, optimization, distribution) possible. It’s a matter of determining (1) where the policy should be applied, (2) what information is required to make the best-fit decision at the time the request was made, and (3) what component is the best source of each variable. In this case, the application is the best source of information regarding the make-up of the application while the application delivery component is the best source of information regarding the network. Combining the data into a single equation and deciding what policy to apply to each response will yield the greatest benefit for both the client and the organization in terms of efficient use of resources.

Anyone within enterprise IT who is using manual spreadsheets to track IP addresses needs to rethink their career strategy.  Change is coming.

Read more...

While almost everyone in the tech industry is talking about the promise of cloud computing very little dialogue focuses on the technology challenges that will need to be addressed (before enterprises fully embrace cloud computing).  And it is in that blue sky between cloud vaporware and day-to-day reality on the ground that new tech fortunes will be made and lost.

Read more...

The Virtualization and the Future of the Network webinar is now available for viewing on demand without having to register.  The webinar features Andreas Antonopoulos (Nemertes), Chris Hoff (Cisco), Mark Thiele (formerly VMware) and Rick Kagan (Infoblox).

Read more...

When VMware entered the production data center it was the beginning of a massive IT disruption with profound implications for careers, vendors and the next tech innovation cycle, driven by deep reductions in network operating expenses and equally uplifting increases in network flexibility and intelligence. 

VMware set the stage for the multibillion dollar system virtualization category by allowing operating systems and applications to be easily set up and moved on top of commodity server hardware.  They automated systems that had been requiring ever increasing amounts of manual labor as data centers grew ever more complex by creating an abstracting layer between software and hardware.

Read more...