Also known as application performance monitoring (APM), application monitoring tools track and analyze application performance. They monitor application metrics such as CPU usage, response times, error rates, and uptime. The tools also offer real-time insights to identify issues, improve user experiences, and optimize resources.
But are APM tools really necessary?
Why You Need An Application Monitoring Tool
Application monitoring tools are crucial for several reasons.
- Performance and availability. APM tools help ensure applications run smoothly and are available when needed. They also detect anomalies and potential issues before they impact users. This reduces downtime and maintains a positive user experience.
- Scalability and cost optimization. Cloud environments are dynamic, and APM tools help manage this complexity by scaling resources as needed. They track resource usage and identify underutilized assets, which can help optimize costs by shutting down or reallocating resources during low usage periods. This ensures that the application operates without incurring unnecessary costs.
- Security and compliance. APM tools provide visibility into potential vulnerabilities, allowing organizations to take proactive measures to secure their applications. This is particularly important in cloud settings where infrastructure spans multiple environments, making centralized monitoring essential for maintaining security and compliance.
- Operational efficiency. The tools automate monitoring tasks, reducing the need for manual work and boosting efficiency. They also offer analytics and reports, helping teams spot trends and make data-driven decisions to improve application performance and reliability.
Application Monitoring Tools For Different Use Cases
Here are some of the most common use cases for application performance monitoring.
- Response time monitoring. Tracks how long it takes for applications to respond to user requests.
- Uptime monitoring. Ensures the application is available and operational.
- Infrastructure monitoring. Monitors servers and hardware.
- Container monitoring. Tracks containerized application performance.
- Error rate monitoring. Monitors the frequency and types of errors occurring in the application.
- Resource usage monitoring. Measures CPU, memory, and other system resource usage.
- Transaction tracking. Follows specific transactions to identify bottlenecks.
- User experience monitoring. Analyzes user interactions and satisfaction.
- Log monitoring. Collects and analyzes logs for patterns and anomalies.
- Database performance monitoring. Tracks database queries and performance efficiency.
- Network performance monitoring. Measures network latency, throughput, and other network-related metrics.
- Security monitoring. Detects and addresses security threats within the application.
- DevOps support. Facilitates collaboration between DevOps teams for continuous integration, deployment, and monitoring.
Here are the best application monitoring tools to consider:
1. Datadog
Datadog is a monitoring and analytics platform for infrastructure, applications, and logs. Its Datadog Application Performance Monitoring (APM) offers visibility into your applications’ performance and health. It utilizes AI-powered code-level distributed tracing to monitor interactions from browser and mobile applications to backend services and databases.
Key Datadog features include:
- Faster detection and resolution of root causes
- Real-time end-to-end tracing
- Intelligent alerts and anomaly detection
- Automatic deployment tracking
- Network performance monitoring
- Synthetic monitoring
- Integration with popular DevOps tools
Datadog offers a range of performance monitoring services that can make pricing complex. Check out our article on managing Datadog costs with CloudZero.
2. New Relic
New Relic is an observability platform that helps developers and engineers monitor, debug, and improve their entire stack. Its code-level visibility provides detailed transaction data, including metrics, event data, transaction traces, SQL queries, and stack traces. This allows for quick identification and resolution of performance issues.
New Relic supports over 750 integrations with DevOps tools, cloud services, and infrastructure components.
Key New Relic features include:
- End-to-end tracing
- Supports real-user monitoring (RUM) and synthetic monitoring
- Optimizes resource usage
- Scalable architecture
- Monitors Kubernetes and microservices
- Serverless monitoring
- Log management
If you already use New Relic for observability and application monitoring and are looking for alternatives, consider these New Relic alternatives.
3. Dynatrace
Dynatrace monitors infrastructure across on-premises, cloud, and hybrid environments. It offers insights into server performance, network health, virtualization, microservices, and containers.
It also supports over 650 technologies, helping maintain optimal performance across the entire technology stack.
Key Dynatrace features include:
- Continuous auto-discovery and topology mapping
- Visual representation of application dependencies
- Integrated user-experience metrics
- Real user data and synthetic transaction monitoring
- Tracking of customer journeys end-to-end
- Database health metrics and SQL statement performance visibility
- Service-to-database dependency mapping
- AI-driven root cause analysis
4. SolarWinds AppOptics
SolarWinds is a full-stack visibility and monitoring platform. It manages IT applications, servers, networks, virtualizations, logs, and security information. Its SolarWinds AppOptics feature supports advanced performance monitoring with distributed tracing, live code profiling, and exception tracking.
Key SolarWinds features include:
- Native integration with AWS and Azure for cloud monitoring
- Monitors database performance
- Customizable dashboards and detailed reports for performance metrics
- Centralizes and analyzes log data for troubleshooting
- Monitors web applications through its Pingdom feature
- User experience monitoring
- Supports large-scale IT environments
- Flexible deployment options
5. AppDynamics
AppDynamics’ End User Monitoring (EUM) tracks web and mobile application performance. It includes Experience Journey Mapping to visualize user interactions and identify optimization opportunities. It also integrates with real-user monitoring (RUM) and synthetic monitoring to detect and resolve performance issues before they impact users.
Key AppDynamics features include:
- Real-time monitoring and diagnostics
- Integration with IT and DevOps tools
- Supports cloud-native, on-premises, and hybrid environments
- Visibility across all infrastructure layers
- Offers Business iQ to correlate application performance metrics with business outcomes
- Automatic discovery and mapping
6. HoneyComb
Honeycomb is an observability tool for DevOps and CI/CD processes. It features detailed insights into production systems, enabling fast debugging and incident resolution. Honeycomb integrates with CI/CD pipelines and supports automated tracing, real-time monitoring, and performance optimization.
Key HoneyComb features include:
- Real-time complex dependency mapping
- Distributed tracing
- Service Level Objectives (SLOs)
- Team collaboration tools
- OpenTelemetry integration
- Automated incident detection
- Timeline markers
7. Prometheus
Prometheus collects metrics from targets at set intervals and stores them as time series data. It uses PromQL for detailed analysis and adapts to infrastructure changes with dynamic target discovery. The multi-dimensional data model uses labels for flexible querying. Prometheus integrates with Grafana for custom dashboards and includes an alert manager for notifications based on thresholds. These features make Prometheus ideal for monitoring servers, databases, and cloud-native applications like Kubernetes.
Prometheus key features include:
- Data Storage
- Automatically discovers targets, simplifying configuration
- Easily scalable
- Open Source
8. Zabbix
Zabbix uses agents to collect metrics from servers, network devices, and applications. These agents measure performance, availability, and configuration while using minimal resources.
Zabbix also supports agentless monitoring via SNMP, IPMI, and HTTP protocols. This allows it to monitor a wide range of devices and applications. It automates the discovery of network devices and resources, making it easy to scale and manage large infrastructures.
Zabbix key features include:
- Automated discovery
- Data visualization
- High availability
- SSL-protected user access for robust security
- Scalability
- Supports API for custom integrations and automation
9. Instana
Part of IBM, Instana offers real-time visibility into servers, containers, and databases. It automatically uses AI-powered monitoring to discover and map applications, services, and infrastructure. It ensures precise tracking of performance and health across on-premise, cloud, and hybrid setups.
Instana agents collect detailed metrics every second, enabling rapid issue detection and resolution. The platform automates alerts and fixes. It links performance data and events to find root causes quickly.
Instana key features include:
- Distributed tracing
- Smart alert
- Service quality management
- Continuous deployment support
- Contextual insights
- Integration with DevOps tools
- Synthetic Monitoring
10. Splunk
Splunk supports real-time visibility into application performance and security by collecting and analyzing data from various sources. It links security incidents to performance issues, offering a complete view of the IT environment.
Using AI and machine learning, Splunk automates threat detection and alerting. It ingests data from logs, metrics, and traces, ensuring end-to-end visibility for identifying and mitigating threats.
Splunk key features include:
- NoSample™ architecture captures 100% of transaction traces without sampling
- OpenTelemetry-based instrumentation supports multiple programming languages
- AlwaysOn Code Profiling monitors CPU and memory usage for specific code
- Service Map visualizes services and their interactions
- Trace Analyzer stores and analyzes all traces for root cause identification
- Tag Spotlight analyzes service performance based on indexed span tags
- Business Workflows correlates related traces for monitoring transactions
- Built-in dashboards monitor service, endpoint, and system health
- Outlier Analyzer uses data science to uncover patterns in trace data
- Inferred Service Analysis detects services that are not instrumented but are involved in traces
11. Logz.io
Logz.io, with its ELK Stack and advanced analytics, mainly focuses on security monitoring. It uses rules, threat intelligence, and anomaly detection to find and address threats.
Logz.io Security Analytics combines security and operations, using the same data without extra setup. It handles logs from web servers, databases, and firewalls. It automatically parses and enriches them for accurate analysis.
Logz.io key features include:
- Service performance monitoring with aggregated R.E.D. metrics
- Real user monitoring
- Synthetic monitoring
- Cross-platform alerting for automatic issue notifications
- Distributed tracing
- Service map visualization to show data flow and dependencies
- Service overview dashboard centralizing telemetry data
- Anomaly detection
- Easy Connect for automated service discovery and data collection
- Data Optimization Hub to manage and reduce unnecessary data
12. Sentry
Sentry collects real-time data on application performance, identifying slowdowns and bottlenecks. It highlights transaction traces to reveal the path and time taken for operations.
Sentry also tracks errors and exceptions with detailed reports, including stack traces and context, to understand root causes. By linking performance issues and errors to specific releases, Sentry enables targeted improvements.
Sentry key features include:
- Error tracking
- Customizable alerts
- Release tracking
- Issue management
13. Elastic APM
Elastic APM is a tool in the Elastic Stack for monitoring user experience through real user monitoring (RUM). It tracks page load times, interaction delays, and error rates, helping teams identify and fix performance issues.
Elastic APM uses Google’s Core Web Vitals, covering loading performance, visual stability, and interactivity. This ensures high website performance, improving user satisfaction and search engine rankings. It also integrates with Elastic’s observability suite to correlate logs, metrics, and traces, giving a full view of application performance and user experience.
Key Elastic APM features include:
- Distributed tracing
- Automatic instrumentation
- Error tracking
- Service maps
- Customizable dashboards
- Transaction sampling
- APM agents
- Real-time monitoring
- Environment-specific metrics such as development, staging, and production
14. SignalFx
Now part of Splunk, SignalFx supports performance monitoring with real-time visibility into application and infrastructure metrics. It tracks and analyzes performance data. Users can detect anomalies, set alerts, and visualize metrics through interactive dashboards.
With SignalFx, organizations can monitor system health and performance. This allows quick identification and resolution of issues, maintaining optimal performance
SignalFx key features include
- High-resolution metrics collects and analyzes metrics in real-time with second-level granularity
- Advanced analytics, which utilizes machine learning to detect anomalies and predict performance issues
- Distributed tracing
- Intelligent alerting enables sophisticated alerting mechanisms based on dynamic thresholds and historical data
- Scalability
- Service maps
15. Raygun
Raygun’s Real User Monitoring (RUM) gives insights into user interactions with web and mobile applications. It tracks performance metrics like page load times, session details, and errors in real-time. By capturing these metrics, Raygun identifies performance issues affecting the user experience. RUM shows a detailed breakdown of load times, helping developers find and address slowdowns quickly. This monitoring resolves issues before they affect users, boosting satisfaction and performance.
Key Raygun features include:
- Tracks individual user experiences and errors
- Detailed error reports, including stack traces, environment data, and more
- Integrates with popular tools such as Slack, GitHub, JIRA, and more
- Monitors the impact of new deployments on application stability
- Configurable alerts
- Robust API for custom integrations
The above tools enable organizations to gain deep visibility into the performance of their applications. However, there is a major concern when it comes to application monitoring. Cost management.
How To Manage Application Monitoring Costs With CloudZero
Application monitoring generates vast amounts of data, leading to higher operational costs. The tools collect metrics, logs, and traces, requiring significant storage and processing power, especially in dynamic cloud environments. High scalability and sophisticated analytics further increase costs.
CloudZero can help with its robust cost management solutions. The platform helps businesses understand, control, and optimize their spending on application monitoring by:
Integration with application tools
CloudZero integrates Datadog, New Relic, and more to allow organizations to correlate performance data with cost data.
For example, CloudZero’s integration with Datadog offers detailed cost allocation and analysis. It allows users to visualize and explore their Datadog spend without needing tags.
It also allocates costs using metrics such as cost per feature, product, microservice, team, and more. These enable granular cost control and optimization of running application monitoring.
Kubernetes cost visibility
Monitoring Kubernetes (K8s) involves tracking the performance of nodes, pods, and containers. Platforms like Prometheus, Datadog, and New Relic support Kubernetes monitoring by providing metrics, logs, and performance insights.
CloudZero integrates with Kubernetes to manage costs by providing visibility into spending. It breaks down costs by namespaces, pods, and clusters, integrating this data with overall cloud costs.
Additionally, it offers analytics to visualize Kubernetes spending in relation to business objectives, aiding in better financial planning and resource management.
CloudZero also:
- Offers real-time visibility into cloud spending to detect and address cost anomalies promptly
- Sends automated alerts for unusual spending patterns to prevent budget overruns
- Analyzes historical spending data to forecast future costs and optimize budget planning
- Recommends optimization strategies for better resource use and cost savings
- Integrates with major cloud providers, AWS, Azure, and Google Cloud, for comprehensive cost tracking
- Implements cost management policies to ensure compliance and control over cloud spending
to see CloudZero in action.
The Cloud Cost Playbook
The step-by-step guide to cost maturity
