Network and application delivery paths.
An approach to measure health and network availability.
Os caminhos de entrega de aplicativos de hoje estão mais complexos do que nunca, geralmente incluindo conexões diretas com a Internet de escritórios remotos distantes. TruPath ™ , um núcleo patenteado da tecnologia de rede do AppNeta, é capaz de reverter rapidamente as filas de engenharia e exercitar qualquer caminho de rede ao seu nível máximo possível, fazendo isso com um mínimo absoluto de dados inseridos no caminho. Em seguida, ele aprende dinamicamente como um determinado caminho de rede será executado da perspectiva do aplicativo.
Usando a tecnologia de dispersão de pacotes, o TruPath ™ pode construir um conjunto completo de estatísticas de rede muito rapidamente, usando padrões especiais que detectam interferência de pacotes. O TruPath ™ foi projetado para funcionar em redes de produção, mantendo uma sobrecarga muito baixa. Ele investiga ativamente o caminho de rede especificado e gera uma ou mais distribuições de temporização de pacotes para esse caminho, obtendo precisão semelhante à inundação sem o impacto.
Package level visibility.
100% captures two real data and two packets on the network.
O AppNeta analisa os dados no nível do pacote de duas perspectivas: ativa e passiva. A metodologia ativa inclui o TruPath ™, que forma, envia e analisa respostas de pacotes pela rede, bem como nosso teste de transação sintética ativa para aplicativos baseados na web. A coleta passiva de pacotes e a subsequente análise de Deep Packet Inspection (DPI) revelam quais aplicativos estão atualmente em uso na rede.
A passive approach involves analyzing 100% packets in real time with an AppNeta monitoring point to identify and discover which applications are currently running on the network. AppNeta automatically categorizes and classifies traffic to show IT the percentages of allocation of your network capacity to recreational and business-critical applications. AppNeta then allows IT to drill down into granular data about the experience of specific desktop locations, applications and users. At a lower level, TCP retransmission taxes are only displayed together with network contributions and application latency.
Web Application Insight.
Synthetics of the Web for the performance of the application base line as it changes over time.
A good end-user experience is crucial for corporate IT, even when corporate networks transition to Cloud, SaaS and Internet Transformations. It is not enough to keep networks and applications running – IT now has to drive the success of these initiatives and ensure that users are not faced with continually slow or poorly performing applications, even (or especially) for applications that IT does not control, or seja. SaaS or cloud-hosted applications.
The synthetic monitoring of transaction transactions shows the performance trends of SaaS applications and networks on the web page. It emulates the paths and actions that users end up doing to experience an application. By running tests periodically, AppNeta can alert you when performance declines. Without synthetic products, the only way to know if a problem exists is if it really affects the user. AppNet active synthetics provide active intelligence without impact.
Abrasive flux dice.
Quem, when and what application traffic is on the network.
The combination of stream data and packet data allows AppNeta to identify thousands of applications in use on the network and target that network usage for specific hosts on the network. By analyzing flows by use, AppNeta can isolate specific conversations between origin and destination. This provides IT with useful information to solve problems by application, by local or by host.
The flow data we provide is enriched with automatic discovery and identification of applications to give your teams an understanding of the tools they are using at a greater capacity of the network. The routers and switches that flow normally do not enrich the data given in their own application identification without additional license requirements; And even when we do it, there is a material impact on the central performance of the hardware. Like AppNeta, this overhead is only 1-2 percent, because we compact the stream data for the express purpose of saving space during transmission.
