What are the most effective ways to measure the reliability and availability of web applications?

When defining metrics and goals for your web application, consider the broader context of user experience and system performance. For error rates, not only track 4xx or 5xx HTTP status codes but also analyze specific error patterns to identify root causes and implement targeted improvements. Enhancing MTBF involves not only extending the time between failures but also conducting thorough post-failure analyses to prevent recurring issues. Likewise, minimizing MTTR requires efficient incident response and a well-defined recovery process. Lastly, achieving high availability involves optimizing infrastructure, implementing redundancy, and proactively addressing potential bottlenecks.

Ensuring the reliability but also the availability of web applications is crucial for providing a positive UX. From my perspective, here are some easy-to-understand ways to measure and improve these aspects: Uptime Monitoring: Calculate the percentage of time your website is accessible to make it more reliable and available. Response Time Analysis: Check the time it takes for pages to load or actions to complete. Design your system to handle failures without crashing. Geographic Redundancy:Ensure your website remains accessible even if one location has issues.

In assessing the reliability and availability of web applications, I find the percentage of 5xx errors (and occasionally 4xx errors) to be among the most effective metrics. These errors, particularly the 5xx series, are direct indicators of server-side issues, offering a clear view of the application's operational health. This metric is not only straightforward to measure and set up but also pivotal in identifying critical issues across various layers of the application. Another metric I prioritize is the number of logged errors. Anomalies in error logs often signal underlying problems that might not be immediately apparent through other indicators. For performance, I rely on the metrics used by Google Lighthouse (FCP, LCP, TBT, CLS).

Few more metrics that are useful to define and measure are 1) measure response time and latency, consistently low response time and latency are indicative of high performing and reliable application 2) measuring throughput - it measures no of transactions or requests are handled per second, and is also a good indicator of high performing web application 3) resource utilization - Monitoring CPU, memory, disk, and network usage can help in understanding if the application has sufficient resources to operate reliably and can also indicate potential bottlenecks. 4) user satisfaction - While more subjective, user feedback on the performance and availability of the web application can be a crucial metric to measure.

From my experience, a successful approach to monitoring web application reliability involves combining various tools. For instance, tools like Kibana provide in-depth log analysis, while Prometheus offers real-time metrics tracking. Furthermore incorporating tools like Grafana allows for the creation of comprehensive dashboards to visualize complex data, aiding in quicker decision-making. This combination allows for a holistic view of system performance, particularly in high-traffic situations. By employing these tools, teams can efficiently gather data, analyze trends, and promptly address issues, ensuring the web application remains reliable and available during critical times.

Its a vague topic and depending upon the size of your application , your approach may be different to tackle this. With all of the modern tools available for monitoring and error tracking, you can make use of a platform suitable for you to analyse and process real time insights. Out of many such platforms like New Relic, Sentry, Ray Gun, Datadog, Instabug, Dynatrace etc . You can google about them and find what (one or more) is/are suitable for your purpose/scale and platform. I have some experience using Ray gun on a web application. It was fantastic, It can log errors in real time before anyone can raise it and capture real time values of all the variables so its super easy to replicate and resolve bugs/issues.

Uptime monitoring through external services helps track the accessibility of the application, while response time analysis and error rate monitoring provide insights into performance and potential issues. Real User Monitoring (RUM) tools assess actual user experiences, and load testing simulates varying traffic scenarios. Capacity planning ensures infrastructure meets demand, and fault tolerance testing assesses the system's resilience. Incident response plans, log analysis, security monitoring, and automated testing contribute to a comprehensive strategy. Regular reviews and adjustments based on evolving usage patterns and technology changes are essential for continuous improvement in the performance of web applications.

I agree with most of the above one thing I believe is missing is the disaster recovery plan, you can't achieve reliability without having a plan to get back on your feet after a problem has occurred. While monitoring is the best thing you can do you can enhance this feature by automatically create tickets and make sure to add the proper critical level and follow up. The process of reliability depends how thorough are you with your SLA.

Inhouse solutions may may be custom-tailored to your needs, but are time-consuming and expensive to build and maintain. Therefore I now tend to use monitoring and logging services. Working with React, I've become especially fond of using Uptrends together with Sentry (with its React profiling plugin). Errors are bound to happen in production. These tools help you diagnose these issues and react (no pun intended) to them promptly.

One insightful approach I've observed involves integrating chaos engineering into regular testing routines. For instance, integrating tools like Chaos Monkey to randomly disable servers in a controlled environment. This simulates real-world scenarios, testing how well the application maintains performance and availability during unexpected disruptions. Such proactive testing not only assesses the system's resilience under stress but also helps in fine-tuning recovery processes and improving overall system robustness. This methodology is particularly effective in preemptively identifying and rectifying potential system vulnerabilities.

Load testing is often a recommended step. Open source tools are available in the market. Additionally API testing with different validation scenarios has to be done so that we do not get error messages for certain scenarios

It is important to run the test suite for multiple days and analyse the failures. Simple load testing will not suffice as the web applications cause issues throughout the day. Performance Test tools which will run for days without overloading the application. For example Grinder is one of the tool which will reduce the load to the application if the response time is higher then it make sure the tests keep running throughout the day. This will help to identify the application issues when it is kept running for few days.

Testing your critical paths, and then expanding to as many scenarios as possible ensures that you’re not fixing the same problems twice. It also helps identify architecture issues much sooner than smashing your way through feature requests and seeing what happens.

The best way to start evaluating any web application is by knowing the health of it. Start testing it and record the results to know where we can improve/evaluate and use it.

In my opinion, creating clear, comprehensive reports is crucial. As engineers, we have a key responsibility: to translate the wealth of data we collect into insights that management can easily understand. Think of it as using a decoder to reveal the hidden treasures on a map. By presenting data in an accessible way, we empower management to make informed, data-driven decisions. It's about bridging the technical and business worlds, ensuring our application's performance is both transparent and actionable. It's a vital part of our role!

Answer for Non-IT PPL : Relavante on what they need and ready to use in anytime. Answer for IT PPL : You can summarize from previous answer of other ppl.it’s same! Also ensure you can translate technical lang and adjustment easy sentence to explain with suitable of background knowledge of each ppl.

This is a crucial stage for decision making, and not just about presenting numbers. Using various tools can identify areas of enhancement. Integrating feedback loops based on analysis enables continuous improvement cycles. Acting as a catalyst for overall success of whatever application being created

With the reports in hand, it's crucial to dive into analysis. Even seasoned engineers can fall into the trap of investing heavily in monitoring infrastructure without dedicating enough time to meaningful data analysis. - Ensure your findings are easily digestible for team members with diverse backgrounds. - Transform interesting insights into custom charts or reports and automate the monitoring process. - As you uncover valuable information, reevaluate your goals and metrics to guarantee alignment with your organization's overarching objectives.

Identify trends in user behavior, such as changes in page views or bounce rates. Report on the effectiveness of marketing and acquisition strategies. Evaluate page load times, server response times, and resource load times. Analyze the conversion rate and abandonment rate for key actions (e.g., sign-ups, purchases). Identify any patterns or factors influencing conversions. Summarize user feedback, comments, and reviews. Highlight positive feedback and address any common concerns or issues raised by users. Provide an overview of security incidents and their resolution. Report on the application's uptime/downtime and error rates. Review the application's compliance with accessibility standards. Address any issues raised by users.

Non-Reliable and Non-Available today sounds like a sin in this tech era. One must read online reviews, approach current users and get feedback before acquiring any service. Its time of accuracy and time-tight schedules, one can't afford non reliable solutions or incompetent softwares, be it rental or SAAS based. Most of our business targets are based on our data, which is gathered on our software tools. These 2 terms in software industry are vital in taking decisions. Most of the top players in industry have moved to cloud based infrastructure to assure availability. Companies are spending their heart out for reliable solutions. It's call of survival to be available always. If u are marked non reliable you will be non existent soon.

I think one should keep in mind below criteria - 1. Frequent monitoring 2. Performance improvement on certain milestones 3. User friendliness 4. Compliance adherence ????

Microservices architecture, renowned for its scalability and flexibility, presents distinctive monitoring challenges. Unlike monolithic setups, not all microservices are externally accessible, adding complexity to traditional monitoring. To tackle this, a tailored application-level monitoring system for the microservices environment becomes essential. For example, .NET Core's System.Diagnostics.Metrics classes can generate and publish the necessary data for internally deployed Prometheus or Grafana instances. This underscores the significance of utilizing platform-specific features to improve monitoring within microservices.

To measure reliability and availability of web applications, consider metrics such as uptime percentage, response time, and error rates. Conduct regular performance testing, monitor server health, and use tools like synthetic transactions to simulate user interactions. Additionally, track incidents, analyze root causes, and implement redundancy strategies for critical components. Regularly review and refine your monitoring and alerting systems to ensure prompt detection of issues.

A aplicabilidade de um health check na aplica??o é uma das maneiras de monitorar a disponibilidade da aplica??o. Recentemente implementei em uma WEB API, através de um endpoint público que verifica a conex?o com o banco de dados, validando também a disponibilidade do servidor de banco de dados. Utilizei o Application Insights da Microsoft.