Optimizing Application Response Time to Enhance Enterprise Performance
With mobile devices gradually taking over the corporate world, the emphasis on mobile applications is higher than ever. Companies are focused on creating or purchasing the best possible applications that match their requirements. Although the creation of an application is a challenging task in itself, bigger obstacles appear when the application is in use. One of the main concerns when monitoring the performance of an application is the application response time. Response time-delays will stall both employ and system performance and thus the productivity of the unit, which adversely affects the organization as a whole.
A lot of factors contribute to this time delay or latency. Chief amongst them are lack of processors/systems, slow servers, smaller database and slower network services to name a few. Although these challenges are quite difficult to overcome, there are methods to tackle them and improve the application response time.
One of the first things a company should consider is bringing visibility into the entire application stack. This will allow them to identify the bottlenecks and rectify them. Guess work is eliminated. To achieve this Application Response Measurement (ARM) should be employed. ARM is an open standard used for monitoring and diagnosing performance bottle necks, which tells the administrator what is causing the delay. Armed with this information, an organization can employ those methods that can rectify the detected issue. Companies can also consider referencing historical baselines. By establishing historical baselines, it will be easy for the organizations to compare the performance of the application at different time periods. By reading the results, it becomes simpler to detect the bottlenecks at the early stages and solve the issues.
After bottleneck identification, organizations usually opt for application scalability. Although it is the best available method in helping eliminate problems and accelerating application response time, there are certain issues which either do not require the use for scaling or cannot be solved through scaling. One major issue is the traffic within the server which leads to slower data delivery, and hence latency. To overcome this problem, certain platforms incorporate Data Path Acceleration Architecture (DPAA) within their platform. The DPAA addresses performance related requirements in a system. This architecture, as the name suggests, helps in the faster movement and delivery of data. Only when issues like this have been dealt with, and the latency eliminated, should the organization consider scaling.
Scaling is the ability of a computer application to perform well even after its volume is increased to match user needs. For scaling an application, organizations have to distribute the load across multiple servers, enabling parallel processing. Scaling is generally of two types:
• Scaling up—In case of scaling up, companies add computing resources like better processors and more memory to a single server, making the data centre more powerful.
• Scaling Out—Scaling out is where firms add more nodes to a system. It is effectively adding more computers that have enough computing power to support large data centers.
Companies generally refer to it as load balancing. It is a technique in which the work which is usually done by one computer is split between multiple computers so that the work is done faster.
As it can be seen, through scaling, the processing power of the server is drastically increased, which in turn increases the response time and hence enhancing the performance of the application. Furthermore, organizations also consider using flexible bandwidth and determining the average least network traffic times. By doing so, they will be able to deliver the data much faster than normal. Additionally, the flexible bandwidth can identify and contain junk traffic, making the delivery faster for the important traffic. Companies can also maximize rapid access to frequently used files, similar to using cache memory in the system.
They can also consider purchasing advanced acceleration techniques and consoles. Companies like F5 and ManageEngine provide platforms which help monitoring and overcoming performance bottlenecks.