Traditional applications were built as static monoliths that were deployed and managed by IT. When a new application had to be deployed, IT would create a DNS entry for the application, allocate a virtual IP (VIP) and configure that VIP on a load balancer for the application to be discovered by other clients. In the best case scenario, this process took about 4-6 weeks. Enterprises have collectively recognized the inefficiencies in this throw-over-wall deployment hand-off of the application from developers to IT operations. There were no alternatives to this model in a data center dominated by purpose-built appliances owned by IT.
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Topics:
Microservices,
Application Services,
App Services 101,
Application Services 101
The Hardware Load Balancer Brick Wall Last month at Networked Systems Design and Implementation (NSDI) conference, Google lifted the covers off Maglev, their distributed network software load balancer (LB) [1]. Since 2008, Maglev has been handling traffic for core Google services like Search and Gmail. Not surprisingly, it's also the load balancer that powers Google Compute Engine and enables it to serve a million requests per sec without any cache pre-warming [2]. Impressive? Absolutely! If you have been following application delivery in the era of cloud, say over last 6 years, you would have noticed another significant announcement at Sigcomm ‘13 by the Microsoft Azure networking team. Azure runs critical services such as blob, table, and relational storage on Ananta [3], its home-grown cloud scale software load balancer on commodity x86, instead of running it on more traditional hardware load balancers. Both Google and Microsoft ran headlong into what can be best described as “the hardware LB brick wall”, albeit at different times and along different paths in their cloud evolution. For Google, it started circa 2008 when the traffic and flexibility needs for their exponentially growing services and applications went beyond the capability of hardware LBs. For Azure, it was circa 2011, when the exponential growth of their public cloud led to the realization that hardware LBs do not scale and forced them to build their own software variant. So, what is this “hardware LB brick wall” that these web-scale companies ran into?
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Topics:
ADC,
SDN,
Closed-Loop Application Delivery,
Architecture,
SSL,
Analytics,
Application Delivery Controller,
Microservices,
metrics,
Software Load Balancer
This article originally appeared in EnterpriseTech and was written by Doug Black. Containers have exploded through the bulkheads of market acceptance that most new technologies must slog through, crossing the chasm in only three years and transforming the way applications are deployed in data centers and in the cloud. The vast majority of major corporations around the world have either implemented, or at least tested, containers.
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Topics:
Microservices,
Containers
It’s been two weeks (since I joined Avi) or four Silicon Valley weeks! And if you imagine a proverbial “firehose”, I think it is safe to say Avi unleashes at least 10x more! So yes, these two weeks have been like a whirlwind for me.
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Topics:
OpenStack,
ADC,
SDN,
Avi Networks,
Application Delivery Controller,
Microservices
Today Avi Networks announced a new solution to enable enterprises to deliver production-ready microservices applications. Microservices architecture it seems is the tech world’s answer to applications that are “too big to fail.” Business disruptions caused by application downtimes have driven enterprises to find ways to break large applications into bite-sized components that can be independently deployed and updated without causing major outages. Light-weight container based infrastructure (e.g. Docker) along with resource and cluster management solutions such as Mesos are a natural fit for microservices applications. Assembling production-ready microservices applications requires a combination of infrastructure services, the application components themselves, and a range of application services.
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Topics:
ADC,
Docker,
Microservices,
Mesos,
Containers,
Service Fabric,
App Map
Grant Swanson
Swarna Podila
Chandra Sekar
