Performance engineering consists of the techniques applied during the life cycle of systems development, to make specific non-functional requirements for a performance like latency and memory usage are adequately met. In simple words, performance engineering is a part of agile processes and is used to spot performance issues in the development process in the early stages of development. Unlike QA, which takes place during the end of the product lifestyle, performance engineering oscillates side-by-side, which saves time and cost, which otherwise would have been there during the last-minute performance detection.

Role of Performance Engineering in business growth

Developing successful software programs is not restricted to writing bug-free code. With modern technologies making their way into software development, along with increasing customer expectations, the demand for high-performance, scalable, and user-friendly applications is on the rise. Performance engineering offers companies flexible solutions to automate various development processes and optimize their software performance. Here is how performance engineering can play a vital role in business growth.

#1. Stable and reliable UX

Performance engineering includes various questions regarding the speed, scalability, and stability of your project, to determine whether the process is being carried out as intended. This QnA is similar to the manufacturing inspection of physical processes, which determine whether the manufacturing process is being performed as intended or not. Talking about software development, performance engineering helps simulate user traffic, network responsiveness, and production loads to make sure the UX of your product is up to date and optimized efficiently.

#2. Reduced costs

Since performance engineering focuses on identifying inefficiencies in the earlier stages of the development process, it can have a significant impact on the final result. When your team runs regular tests at every step of the development process, it increases the opportunities for discovering an optimal design approach. If such ideas are discovered early in the process, it helps to avoid additional technology investments, which reduces the overall cost of the project. Moreover, performance engineering offers regular performance checking, which also reduces operational overhead costs, resource management costs.

#3. Product performance issues

It is essential to identify performance issues during the early stages of development to reduce overtime problems and overhead & resource management costs. Performance engineering enables you to do the same: identify potential impediments in your software and scalability issues before deploying the final product. In several cases, you might find the need to invest in new hardware solutions to maintain the integrity of your design.  Performance engineering makes sure you attain proper infrastructure, along with appropriate memory, disk space, CPU capabilities, and network configurations.

#4. Enhanced sustainability

Digital landscapes today are dynamic, and building scalable and sustainable applications is vital. Performance engineering offers virtual testing environments that enable you to test the scalability and long-term viability of your software. After running a series of tests, you can extract the reports to generate valuable insights for making better decisions. These reports can also help you create a roadmap and timelines to track and complete the short & long term goals of your project.

#5. Solutions used in performance engineering

Performance engineering and testing can offer tons of data to analyze, but it is essential to perform it effectively and efficiently. Here are a few performance engineering solutions that are used to test the performance of a project in its early stages.

#6. Tier-based engineering transaction

Load scripts contain ordered API calls or transactions in a standard performance test harness that represents the user workflow. For example, if your software is based on IoT, the transactions and logic behaviors of the script will represent a device. Engineering scripts include a single transaction, which targets a particular tier of the deployment process. With the help of engineering scripts, you can identify degradation in a transaction and can isolate that deployment tier. Although all deployments are unique, these three tiers can commonly encounter transaction problems.
● Web Tier: a static non-cached file
● App Tier: object is created but not forwarded to the database tier
● Database Tier: a query from the database

#7. Monitored KPIs

Front-end KPIs enable you to control the current capacity by correlating TPS, user load, error rate, and response time. If an application starts to degrade, monitored, KPIs can uncover the entire story behind the declining performance at a certain workload level. Two primary KPIs for every hardware or software servers include hit rates and free resources.
Some examples of monitorable hit rates are:
● Database: Queries per second
● Messaging: Enqueue/dequeue count
● Web server: Requests per second
● Operating system: TCP connection rate

Some examples of monitorable free resources are:
● App server: Free worker threads
● OS: CPU average idle
● Messaging: Enqueue/dequeue wait time
● Web server: Waiting for requests
● Database: Free connections in a thread pool

#8. Manual analysis

When it comes to performance analysis, manual scrutiny is crucial alongside automated data collection. Although automation is necessary to save time, performance results analysis, relevant data point separation, development of efficient solutions, and trend spotting: all require human input.

#9. Load ramp-up

Targeted workloads simplify the analysis process. Load ramp up commences by running ghost tests that check the system without hindering load-scripts. The ghost test does not include any real user or activity, but it is essential to determine whether monitored KPIs are collecting metrics or not.
After ghost test, move to single-user load tests where a single user is assigned to execute one engineering and single-user script each. For example, if you have 42 scripts, you will need 42 users executing the script at once. Lastly, you can create a concurrent user load scenario that enables the capture of three monitored KPI values per each load set.

The Bottom Line

Since technology is evolving and applications are continuing to grow, DevOps teams and developers need to utilize performance engineering tests. Performance engineering enables developers to spot performance issues in the early stage of product lifestyle and rectify upon them without inflicting additional overhead or resource management costs. To facilitate performance engineering, developers can utilize professional performance engineering tools that don’t only cover several technologies but promote flexible data collection and integration of developer tools as well.