Application performance monitoring software

Gain end-to-end visibility with distributed tracing

Code-level diagnostics to monitor application performance

Track metrics such as response time, throughput, requests, exceptions, etc. to enhance user experience and maintain system reliability.

Identify performance bottlenecks

• Detect application slowness: Identify slowdowns or time-consuming transactions that may frustrate users and take proactive measures to enhance performance. Pinpoint specific areas within the application or its infrastructure that are causing delays, such as database queries, API calls, or network latency.
• Detailed error reporting: Applications Manager provides detailed logs of exceptions, including stack traces, which help developers understand the context of the error and facilitate quicker resolution.
• Understand execution paths: Each trace provides insights into the sequence of operations that were executed during a request. Analyzing these paths helps teams understand where delays occur, whether in database calls, external API requests, or internal processing. Highlight inefficient code paths or algorithms that need optimization.
• Monitor exceptions and identify errors that occur within the application. Quickly diagnose and address issues before they escalate. Identify whether performance degradation is contributing to increased error rates. This correlation can guide optimization efforts.
• Highlight edge cases: Monitoring exceptions helps uncover edge cases that may not have been considered during development. Addressing these can enhance the robustness of the application.
• Identify system bottlenecks: A high number of exceptions in specific areas may indicate underlying bottlenecks or resource constraints that need to be addressed to improve overall system performance.
• Detect anomalies or spikes that may indicate underlying issues, such as service failures or increased error rates.
• Understand dependencies and diagnose performance issues that may arise from one component affecting others.

AI-powered root cause analysis

When performance issues arise, monitoring data throughput provides insights into whether the problem is related to insufficient bandwidth or other resource constraints. This aids in quicker diagnosis and resolution of issues.

• Historical data analysis: Keep track of exceptions over time and perform root cause analysis when issues arise. Detect patterns or recurring problems that need systemic solutions rather than one-off fixes.
• Post-mortem investigations: After significant incidents, having detailed exception logs aids in conducting thorough post-mortem analyses, helping teams learn from failures and prevent future occurrences.

Allocate resources effectively

• Take better scaling decisions: Assess whether your current infrastructure is sufficient for your application's needs. If certain components, services or traces are consistently slow under load or if throughput/response time is consistently high, you may need to scale resources (eg: add more servers or increase bandwidth) to accommodate user demand.
• Identify resource constraints: Understand whether performance issues are due to resource constraints (e.g., CPU or memory limitations) on specific components.
• Enhance cost efficiency: Optimize resource usage and ensure you are not over-provisioning or under-utilizing your infrastructure, leading to unnecessary costs.

Understand traffic patterns

• Track the number of requests and gauge user engagement with the application. Understand peak usage times and user behavior and take informed decisions on resource allocation and scaling.
• Identify trends, such as increased demand during specific periods or after marketing campaigns, enabling proactive adjustments to infrastructure.
• Correlate requests with response times and identify how increased traffic affects performance and pinpoint potential bottlenecks in the system.

Monitor error rates

Analyze requests alongside error rates (e.g., 4xx and 5xx responses) and identify issues in real-time. A sudden spike in requests with a corresponding increase in errors may indicate problems that need immediate attention.

Optimize application performance

Prioritize improvements

Get clear visibility into which components are underperforming and prioritize your performance optimization efforts on the most critical areas that impact user experience. For instance, if a particular API call consistently shows high response times, it can be optimized or refactored first.

Benchmark changes

Monitoring response times by component allows teams to benchmark the impact of changes made to the application. After implementing optimizations, they can compare the new metrics against historical data to assess improvement.

Capacity planning and forecasting

• Analyze resource requirements: Understand the volume of requests and determine whether the application can handle the expected load. Identify if it is approaching its capacity limits and plan for capacity needs effectively.
• Scale accordingly: Scale resources up or down based on demand and ensure that applications remain responsive under varying loads. Optimize cloud services or infrastructure costs and scale only when necessary.
• Trend analysis: Track data throughput over time and identify trends that inform capacity planning decisions. For example, if throughput is steadily increasing, it may indicate a need for future scaling or infrastructure upgrades.
• Predict peak usage: Historical data on throughput can help predict peak usage periods, allowing teams to prepare in advance by scaling resources or optimizing performance.

Improve user experience

Identify slow endpoints or services that may need optimization and enhance user experience by reducing wait times.

• Maintain user trust: Frequent errors can lead to a poor user experience and decreased trust in the application. By monitoring exceptions and resolving them promptly, organizations can maintain a positive user experience.
• Error handling strategies: Effective monitoring allows teams to implement appropriate error handling strategies, such as user-friendly error messages or fallback mechanisms, which can improve user interactions during failure scenarios.
• Improve overall performance: By understanding which components are slow, organizations can work towards reducing overall response times, leading to a smoother and more responsive user experience. This is crucial for maintaining user satisfaction and engagement.

Assess and improve application performance with Apdex score

Identify slow endpoints or services that may need optimization and enhance user experience by reducing wait times.

• Understand how real users perceive application performance.
• Benchmark performance over time or against competitors.
• Identify which areas of the application are underperforming.

Visualize service interactions with automated maps

• Map dependencies: Get a visual representation of how different services within your application interact with each other. Understand the dependencies between services and easily identify how changes in one service can affect others.
• Track data flow: Clarify how requests are processed throughout the system to diagnose issues and optimize performance.
• Spot latency issues: Quickly identify which services are causing delays or performance bottlenecks. This enables targeted optimization efforts to improve overall application responsiveness.
• Analyze impact of changes: Assess the potential impact on other dependent services when changes are made to a service, facilitating better change management and risk assessment.
• Instant root cause analysis: Quickly trace the source of the problem by showing how services are interconnected. Accelerate troubleshooting efforts and reduce downtime.
• Contextual insights: By providing context around service interactions, these maps help teams understand not just where an error occurred, but also how it relates to other parts of the system.
• Get resource allocation insights: Understand the relationships between services and make informed decisions about resource allocation and scaling. If certain services are heavily relied upon, they can be prioritized for additional resources during peak usage times.
• Forecasting needs: Automated maps can help identify which services may require scaling based on usage patterns and dependencies, aiding in proactive capacity planning.

Integrate with real user monitor

Get a holistic view of application performance by combining APM and RUM data. This allows teams to gain a complete understanding of application performance from both server-side and client-side perspectives. APM focuses on backend metrics like response times and error rates, while RUM captures user interactions and experiences, providing a full picture of how applications perform in real-world scenarios.

• Identify how backend performance impacts user experience.
• Perform more effective root cause analysis. For example, if a slow page is detected in RUM, correlating it with backend performance metrics can help identify whether the issue is due to server-side processing or network latency.
• Prioritize optimizations based on real user impact rather than just backend metrics.
• Assess the impact on both backend performance and user experience simultaneously, ensuring that enhancements do not inadvertently degrade service quality.
• Align technical improvements with business goals and enhance overall value delivery.
• Get unified dashboards that provide a comprehensive view of application health and simplify reporting for stakeholders.

Improve security posture

• Discover abnormal activities: Detect DDoS attacks by looking for a sudden surge in requests. Identify anomalies or unusual activities that may indicate security breaches or misuse of the application.
• Identify vulnerabilities: By mapping out service interactions, organizations can better understand potential security vulnerabilities that may arise from dependencies between services. This insight allows for more effective risk management and mitigation strategies.
• Monitor data flow: Track sensitive data as it moves through various services, ensure compliance with data protection regulations, and enhance overall security monitoring.

Improve code quality

• After deploying updates or new features, get immediate feedback on how these changes affect overall performance and user experience.
• Development teams can track exceptions and receive continuous feedback on the quality of their code. Frequent exceptions may indicate areas that require refactoring or additional testing, leading to improved code quality over time.
• Detailed insights for developers: Get detailed insights into method calls, execution times, and resource allocations per thread. This aids developers in debugging complex issues that may not be apparent through standard logging.

Compliance and reporting

• Meet regulatory requirements: In industries with strict compliance requirements, monitoring exceptions can provide necessary documentation and reporting capabilities to demonstrate adherence to standards.
• Ensure compliance with Service Level Agreements (SLAs): Monitoring exception rates helps ensure compliance with SLAs related to application uptime and reliability, providing assurance to stakeholders.

Facilitate communication across teams

Foster better communication between development, operations, and business teams. Have a common understanding of performance issues and priorities across different stakeholders. Understand where performance challenges lie and what actions are being taken to resolve them.

Hybrid application infrastructure monitoring

Gain performance insights into your supporting infrastructure elements such as servers, databases, containers, virtual machines, etc. - both on premise and cloud native. Applications Manager supports over 150 enterprise technologies.