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A recent Gartner survey of enterprises indicated that user experience was the most important criteria when formulating application performance strategy. When user experience is reported as poor, discovering the cause of slow application transactions is paramount. But in today’s multi-tier, heterogeneous application architectures, it is challenging to determine what is causing a slowdown: is it the network, or the client, or the database query, or application processing, or an external web service call, etc.?
Monitoring and distributed tracing of business transactions provides clear visibility into which application tier is slowing down user access to applications and, in turn, affecting user experience.
Java application architectures have evolved to include several hardware and software tiers. Production applications involve multiple load balanced web servers, several tiers of Java application servers and middleware, backend databases, messaging servers, transaction processing engines and external services. And, many of these tiers are inter-dependent. Therefore, it can be extremely challenging to diagnose which tier is causing the transaction to be slow and why. IT operations and DevOps teams need answers to key questions, including:
eG Enterprise provides complete visibility into Java transaction processing in every tier that supports the application. Using byte code instrumentation, it tags every transaction and traces it through the presentation tier, business logic tier and data tier. Method invocations, processing times and any exceptions are captured in the Java tiers, and any calls to non-Java tiers and external services are also tracked. For database accesses, the queries executed and the execution times are reported.
Get complete visibility into distributed Java transaction processing, so you can clearly identify and solve slow application response issues:
eG Enterprise allows you to easily analyze transactions by breaking down request processing time hop by hop, as the transaction flows through each application tier. With this information, you can:
For situations where Java application slowness is caused by bottlenecks in the Java container or JVM layers, eG Enterprise provides in-depth monitoring for most popular Java containers (Tomcat, WebLogic, JBoss EAP, WildFly, WebSphere, Glassfish, etc.) and JVMs (Oracle, Sun, JRockit, etc.). Using these insights, you can:
Because user experience can be impacted by many factors outside of application performance, eG Enterprise goes far beyond identifying code level issues alone. Its universal monitoring technology provides visibility into every layer and every tier of the infrastructure that the Java application depends on.
A patented, virtualization-aware, root-cause diagnosis technology automatically discovers inter-dependencies between infrastructure tiers, correlates performance data across these tiers, and pinpoints the exact cause of issues. This eliminates guesswork and finger-pointing and enables IT operations teams, DevOps teams and developers to see exactly where the problem lies and where its effects are.
Distributed Application Transaction Tracing is a technique to monitor the flow of application requests as they move through the application delivery chain. It involves monitoring the entire journey of the request across your IT infrastructure, from front-end to middleware, message queues, backend services, external dependencies, and databases. p>
To track application transactions, Application Performance Monitoring (APM) and observability tools typically use bytecode instrumentation and a "tag and follow" approach, where requests are uniquely identified, and processing times are noted at each tier of the delivery chain. This information is aggregated to present simple topology or application dependency map views that clearly highlight application bottlenecks.
Site reliability engineers (SREs), IT Operations and Application developers (AppDev) can use distributed transaction tracing to identify and troubleshoot requests that experience high traffic surges, response time slowness, service latencies or errors. APM tools that leverage distributed tracing can reveal slow HTTP calls, sub-optimal database queries, slow method or function calls, exceptions or errors, and other issues.
Distributed tracing offers multiple and varied stakeholders such as SREs, DevOps, AppDev, helpdesk or support engineers, business owners and IT operations several benefits:
Easily comprehend the complexities of your application stack: As requests traverse the application, APM automatically builds an interactive topology map that visualizes these relationships without the need for manual configuration or additional instrumentation.
This provides end-to-end observability into all application components and dependencies, helping you quickly identify and troubleshoot issues. With intuitive topology and dashboards, you can easily comprehend the complexities of your application stack and delivery chain and ensure that there are no gaps or blind spots in your monitoring.
Understand service dependencies that may cause cascading issues: The end-to-end topology view or dependency map provided by distributed tracing allows SREs to have a comprehensive understanding of all service dependencies involved in each transaction. Such dependencies could be horizontal (between components of the same type) or vertical (between components of different types).
This big picture view can help SREs identify any performance bottlenecks that may arise due to dependencies between services. For example, sub-optimal SQL can have a cascading effect on several upstream services. By having this bird's-eye view, SREs can make informed decisions about where to focus their attention and optimize the system for maximum performance.
Reduce mean-time-to-resolve (MTTR) and empower even non-tech stakeholders like helpdesk: The individual timing information is aggregated to provide a comprehensive, end-to-end analysis of the overall time it takes to process the transaction. The APM and observability tool also correlates the captured transaction ID with other relevant metadata and service identification information.
This makes it easier for even non-technical helpdesk or support engineers to quickly triage all issues on the same APM and observability platform and avoid costly and time consuming “war rooms”. Instead, the helpdesk can forward the trouble ticket to the right stakeholder who can make any necessary optimization to resolve the issue.
A full-stack APM and observability tool can preempt the need for manual instrumentation by automatically discovering all the components in your IT infrastructure and enabling end-to-end tracing without any manual intervention. This saves valuable engineering time and reduces the chances of introducing bugs in your application.
Yes and no.
For transaction tracing to be enabled, there are two choices:
Both options enable the tracking of request flows and provide valuable insights for troubleshooting and performance analysis. Depending on your use case and available resources, you may consider alternative approaches, such as automatic APM solutions, which offer simplified instrumentation without the need for extensive code changes.
Distributed transaction tracing can introduce several overheads:
Transaction tracing can help detect a variety of problems in an application. Some common problems that can be detected through transaction tracing include:
These are some common prerequisites to consider for Java transaction tracing:
With an APM tool, all this is automatically made available to you out of the box.
Yes, transaction tracing can work even if multiple technologies are involved in an application, such as Java and .NET.
Automatic APMs offer comprehensive visibility by capturing trace information across different technologies, enabling a holistic view of request flow and transaction behavior. They enhance troubleshooting, facilitate efficient root cause analysis, ensure cross-platform compatibility, drive proactive performance optimization, and streamline collaboration among teams for improved system performance and reliability.
Agentless transaction tracing refers to gathering information about the flow of requests and responses across components in a distributed system without installing any software agent.
Several options exist:
In general, while agentless transaction tracing can provide visibility into the flow of requests and responses, it may have limitations compared to agent-based distributed tracing approaches.