Atualizámos a nossa política de privacidade. Clique aqui para ver os detalhes. Toque aqui para ver os detalhes.
Ative o seu período de avaliaçõo gratuito de 30 dias para desbloquear leituras ilimitadas.
Ative o seu teste gratuito de 30 dias para continuar a ler.
Baixar para ler offline
LinkedIn has evolved from serving live traffic out of one data center to four data centers spread geographically. Serving live traffic from four data centers at the same time has taken the company from a disaster recovery model to a disaster avoidance model, where an unhealthy data center can be taken out of rotation and its traffic redistributed to the healthy data centers within minutes, with virtually no visible impact to users.
As LinkedIn transitioned from big monolithic applications to microservices, it was difficult to determine capacity constraints of individual services to handle extra load during disaster scenarios. Stress testing individual services using artificial load in a complex microservices architecture wasn’t sufficient to provide enough confidence in data center’s capacity. To solve this problem, LinkedIn leverages live traffic to stress services site-wide by shifting traffic to simulate a disaster load.
Michael Kehoe and Anil Mallapur discuss how LinkedIn uses traffic shifts to mitigate user impact by migrating live traffic between its data centers and stress test site-wide services for improved capacity handling and member experience.
LinkedIn has evolved from serving live traffic out of one data center to four data centers spread geographically. Serving live traffic from four data centers at the same time has taken the company from a disaster recovery model to a disaster avoidance model, where an unhealthy data center can be taken out of rotation and its traffic redistributed to the healthy data centers within minutes, with virtually no visible impact to users.
As LinkedIn transitioned from big monolithic applications to microservices, it was difficult to determine capacity constraints of individual services to handle extra load during disaster scenarios. Stress testing individual services using artificial load in a complex microservices architecture wasn’t sufficient to provide enough confidence in data center’s capacity. To solve this problem, LinkedIn leverages live traffic to stress services site-wide by shifting traffic to simulate a disaster load.
Michael Kehoe and Anil Mallapur discuss how LinkedIn uses traffic shifts to mitigate user impact by migrating live traffic between its data centers and stress test site-wide services for improved capacity handling and member experience.
Parece que você já adicionou este slide ao painel
Você recortou seu primeiro slide!
Recortar slides é uma maneira fácil de colecionar slides importantes para acessar mais tarde. Agora, personalize o nome do seu painel de recortes.A família SlideShare acabou de crescer. Desfrute do acesso a milhões de ebooks, áudiolivros, revistas e muito mais a partir do Scribd.
Cancele a qualquer momento.Leitura ilimitada
Aprenda de forma mais rápida e inteligente com os maiores especialistas
Transferências ilimitadas
Faça transferências para ler em qualquer lugar e em movimento
Também terá acesso gratuito ao Scribd!
Acesso instantâneo a milhões de e-books, audiolivros, revistas, podcasts e muito mais.
Leia e ouça offline com qualquer dispositivo.
Acesso gratuito a serviços premium como Tuneln, Mubi e muito mais.
Atualizámos a nossa política de privacidade de modo a estarmos em conformidade com os regulamentos de privacidade em constante mutação a nível mundial e para lhe fornecer uma visão sobre as formas limitadas de utilização dos seus dados.
Pode ler os detalhes abaixo. Ao aceitar, está a concordar com a política de privacidade atualizada.
Obrigado!