Application Performance Management (APM) analyses the performance of software applications in this age of information technology.
APM ensures that the customer receives services up to the defined level and discovers application performance issues. Different categories, such as load time and application reaction time, can be used to monitor or track application performance.
Applications are growing increasingly complicated and distributed as technology advances. As a result, monitoring an application’s performance is required in order to deliver improved end-user satisfaction.
What is Apache Kafka?
Apache Kafka is a platform for event-streaming. It’s a scalable, dependable, and safe approach to build asynchronous (or event-driven) APIs.
A client programme waits for a response when it sends a request to a RESTful, GraphQL, SOAP, or other synchronous API. When using asynchronous APIs, neither the client nor the server requires a response. The event-driven architecture is implemented using such APIs.
Pom.xml is a file which gives details about the configuration and project used by Maven for a project. You can also change the grade file to POM file through gradle build. Moreover, it’s a trusted platform that can be deployed to function different distributed systems.
Why Monitor Kafka?
Apache Kafka is primarily used to convey massive amounts of real-time data (also known as data-in-motion) in a number of formats. It’s most commonly used to collect data over time and location, between servers and even data centers, with dependable categorization and storage. Kafka is used in two ways.
- Create real-time data pipelines that reliably gather, stream, and transform data between systems.
- Algorithms and analytics are used to process streams of real-time data.
Kafka clusters are divided into three parts to accomplish this: producers, consumers, and brokers. Go through our elaborate guide to explore the use cases and learn more about the Kafka architecture. A broker is a server that executes the Kafka software, and your Kafka cluster can include one or more brokers. Data is published by producers to subjects, which are then processed by the brokers in your cluster. Finally, consumers pay attention to data given to these issues and pull it on their own timetable to use.
Performing tools for monitoring consumer application
1. Traceview
It was previously known as Tracelytics, which was bought by AppNeta and is now owned by SolarWinds.
SolarWinds was founded in 1999 and is based in Texas. It employs more than 150 people and generates $429 million in revenue.
It’s a web application performance monitoring tool. It gives you a thorough understanding of the programme thus beginners can learn Kafka updations, features, and improve the end-user experience, and is a very cost-effective performance monitoring tool.
Features:
- Java,.NET, PHP, Ruby, Python, and other languages are supported by Traceview.
- It keeps track of web and SaaS apps.
- Traceview allows for code-level performance monitoring.
- With a real-time user monitoring system, it solves the problem.
- It provides online, email, and phone help.
2. Conduktor
For Conduktor to access the metrics, you can enable JMX or Jolokia access in your Cluster Configuration.
JMX
JMX is a standard protocol for exposing metrics in Java programmes. Because Apache Kafka is a Java application, it naturally provides a plethora of JMX metrics.
Jolokia
Jolokia is a solution that allows you to retrieve JMX metrics using a simple HTTP request by exposing an HTTP server.
It is frequently launched as a Java agent from within the main Java programme. Jolokia starts an HTTP server on a customizable port when it starts up.
Conduktor has only recently begun to harness the measurements’ full potential. They’re currently working on exposing common metrics as graphs so you can monitor them and be notified if anything seems off.
3. Datadog
To optimize your application, Datadog APM allows you to examine and identify dependencies, remove bottlenecks, reduce latency, track mistakes, and improve code efficiency.
Distributed traces are integrated with browser sessions, logs, profiles, synthetic tests, process-level data, and infrastructure metrics to provide complete insight into the health of your application across all hosts, containers, proxies, and serverless operations.
Features
- In one integrated platform, seamlessly connect application performance to logs and underlying infrastructure metrics.
- Tracing without Boundaries: Search and analyze all traces in real time (no sampling) and keep only the ones that matter to you with tag-based rules.
- Continuous Profiling: With low effort, analyze code-level performance throughout your entire stack, identify your most resource-intensive methods (CPU, memory, etc.) using tags, and correlate it with relevant requests and traces.
- Synthetics and Real User Monitoring (RUM): Measure and enhance the speed and end-user experience of your front-end application in real time or by replicating controlled browser and API tests, and link them to relevant traces, logs, and infrastructure data.
- Watchdog uses machine learning to detect irregularities and prevent alert fatigue.
- Reduce resolution time and deploy features faster by navigating apps easily using the Service Map and other out-of-the-box dashboards and visualizations.
- Datadog aggregates data and events across your whole DevOps stack with over 450+ turn-key connectors.
4. ManageEngine
ManageEngine Applications Manager is a feature-rich application performance monitoring solution designed for today’s complex and dynamic situations. It provides detailed insight into the performance of business-critical applications, both in the data center and in the cloud. It’s easy to set up and utilize.
Features
- For Java, .NET, PHP, Node.js, and Ruby applications, agent-based monitoring with byte-code instrumentation and code-level diagnostics is available.
- For multi-page end-user workflow simulation, synthetic transaction monitoring from multiple geographical locations is used.
- Over a hundred apps and infrastructure parts are supported out of the box.
- Monitor hybrid cloud, virtual, and container technologies like Kubernetes and Docker in great detail.
- Automated application discovery, tracing, and diagnostics let you find and fix the source of problems faster (ADTD).
- Machine learning-enabled analytics can help you predict future resource use and growth.
Users in 5000+ enterprises worldwide utilize Application Manager in various roles such as IT Operations, DBAs, DevOps engineers, Site Reliability Engineers, application developers, application owners, Cloud Ops, and so on.
5. Sematext APM
Sematext APM gives real-time end-to-end visibility into web application performance by monitoring individual and business operations to identify your application’s slowest and under-performing components. It facilitates faster troubleshooting and enhances the user experience.
Features:
- View real-time interactions between applications and underlying components, databases, and external services.
- Anomalies can be discovered in real time, before they affect the end user.
- Get code-level visibility to find the source of performance problems and shorten the time it takes to fix them.
- The ability to track and filter database operations, as well as slow SQL, in order to identify the most time-consuming transactions.
- Pointcuts to order (for JVM).
- The Sematext AppMap displays inter-component communication, including throughput, latency, and error rates, among other things.
Conclusion
In this article, we can understand how Kafka testing is done and the tools used for monitoring consumer applications.
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