10 Most Popular Tools to Monitor and Debug Serverless Applications

Shormistha Chatterjee
11 min readApr 2, 2024

--

10 Tools to Monitor and Debug Serverless Applications

Ensuring the seamless operation of serverless applications is crucial for delivering exceptional user experiences and maintaining high performance. This requires effective monitoring and troubleshooting tools that can identify issues, monitor performance metrics, and debug errors in real time. With the rapid adoption of serverless architecture, multiple tools have emerged to assist developers and DevOps teams in managing serverless apps efficiently. In this article, we’ll explore the top 10 tools that offer robust monitoring and debugging capabilities for serverless environments, helping organizations ensure optimal performance and reliability.

What Is Serverless Monitoring?

Serverless monitoring and debugging is the practice of tracking and scrutinizing the performance, availability, and behavior of serverless applications and functions. In a serverless architecture, apps are built and deployed as a collection of functions that run in response to events triggered by external sources, such as database changes, HTTP requests, or scheduled tasks. Serverless monitoring involves gathering metrics, logs, and other data points from these functions and services to confirm they are functioning as expected and to detect and troubleshoot any issues or anomalies that may arise. The main objective of serverless monitoring is to optimize the performance and reliability of serverless applications, improve resource utilization, and provide insights for continuous improvement and optimization.

Criteria for Assessing Serverless Monitoring Solutions

Evaluating serverless monitoring tools is crucial for ensuring the optimal performance, reliability, and efficiency of your serverless applications. The choice of monitoring solutions can significantly impact how well you can manage and optimize your serverless architecture. Here are some key criteria to consider when evaluating serverless monitoring tools.

  1. Scalability: An effective monitoring tool must be scalable to accommodate changing workloads and the increasing number of features, services, and events in serverless applications. It should seamlessly adjust to shifting workloads without compromising functionality.
  2. Real-time monitoring capabilities: Look for tools that offer real-time alerts and metrics to quickly identify and address emerging issues. Real-time monitoring provides complete visibility and minimal latency for effective troubleshooting and proactive management.
  3. Ease of integration: Choose monitoring tools that integrate easily with your serverless environment, supporting popular platforms and frameworks. Integration with existing DevOps and CI/CD pipelines is essential for streamlining the monitoring process within the development lifecycle.
  4. Customization options: Ensure that the monitoring tools offer customization options to tailor monitoring for serverless applications according to your specific needs. This includes defining custom metrics, setting up personalized alerts, and creating dashboards aligned with your performance indicators.
  5. Cost considerations: Understand the pricing model of the monitoring tools and evaluate how well it aligns with your budget. Consider factors such as features needed, data volume processed, and level of monitoring granularity required. Choose tools that offer transparent pricing and a balance between features and cost-effectiveness.

Top 10 Serverless Monitoring Solutions for 2024

Serverless monitoring solutions offer a seamless experience that enhances your overall operational efficiency. However, it’s important to note that not all tools are the same. We’ll delve into the features, advantages and disadvantages, practical applications, and pricing structures of our top 10 solutions.

Lumigo

Lumigo is a serverless monitoring platform designed for rapid troubleshooting. It provides real-time monitoring capabilities and interactive visual maps to analyze complex system behaviors, allowing for quicker issue resolution. Lumigo specializes in identifying critical paths and choke points to enhance application performance, improve efficiency, and reduce latency. The platform also tracks various scenarios and generates detailed data-driven reports.

Pros of Lumigo include support for various log and metric types, customizable dashboards, analytics management for capacity and demand, and a transparent cost structure.

However, Lumigo has some limitations such as a lack of audit trail support and the restriction to monitoring one cloud platform at a time.

Use cases for Lumigo include monitoring and debugging third-party APIs and managed services, investigating performance and cost-related issues, conducting end-to-end transaction path analysis, and performing root cause analysis.

Pricing Model

Four pricing tiers starting from USD 0 based on the number of traces, making it accessible for organizations of different sizes and needs.

AWS X-Ray

AWS X-Ray, an offering by Amazon, is a serverless monitoring tool that serves a different purpose compared to CloudWatch. While CloudWatch focuses on monitoring and collecting metrics from AWS resources and applications, AWS X-Ray is geared towards assisting developers in tracking requests across a distributed application. It helps identify performance issues, aids in debugging, and tracks performance bottlenecks. AWS X-Ray supports several programming languages such as Node.js, C#, Python, Java, Go, and Ruby.

Some advantages of AWS X-Ray include its native integration with AWS services, a robust feature set tailored for distributed applications, and support for in-cloud debugging.

On the downside, AWS X-Ray is limited to compatibility with AWS services only. It does not support tracing over the API gateway and asynchronous invocations, which could lead to performance errors in certain scenarios.

Use cases for AWS X-Ray include event monitoring and tracing, analyzing and debugging production and distributed applications with microservices architecture, applying sampling algorithms to determine which requests to trace, and using segments and subsegments to trace data content.

Pricing Model

AWS X-Ray offers a free tier for the first 100,000 traces recorded each month. For organizations requiring more traces, they can estimate the cost using the AWS pricing calculator to determine the most suitable pricing plan.

Amazon CloudWatch

Amazon CloudWatch, an AWS serverless monitoring tool, offers a comprehensive solution that seamlessly integrates with all AWS services. This tool is known for its real-time custom event creation and monitoring capabilities, utilizing machine learning algorithms for anomaly detection. By default, CloudWatch collects Lambda metrics but can also be configured to gather custom metrics related to terminations, volumes, thresholds, and more. The collected data is presented on customizable dashboards for easy analysis.

Pros of Amazon CloudWatch include easy setup of alerts, seamless integration with AWS services, real-time alerts and analytics, and a pay-as-you-go pricing model.

However, there are limitations to consider such as problematic integration with non-AWS vendors, lack of transaction tracking, limited search and filtering capabilities, and potentially unpredictable pricing at scale.

Use cases for Amazon CloudWatch include monitoring application performance with visual data and alarms, conducting root cause analysis, optimizing resources by setting custom thresholds, and testing website impact through evaluation of user requests, logs, analytics, and data.

Pricing Model

Offers a free tier with basic monitoring metrics and a paid tier via a pay-as-you-go model which can be calculated using the AWS pricing calculator.

Google Cloud’s Operations Suite (Formerly Stackdriver)

Google Cloud’s Operations Suite, formerly known as Stackdriver, is a comprehensive distributed application monitoring system offered by Google Cloud. It serves as Google’s counterpart to Amazon CloudWatch and comprises three main pillars: Cloud Monitoring, Cloud Logging, and Cloud Tracing. This suite provides real-time log management analysis, scalable metrics observability, a managed service for running and scaling Prometheus, and application performance management functionalities.

One of the significant advantages of Google Cloud’s Operations Suite is its multi-cloud compatibility, allowing users to monitor applications across different cloud environments seamlessly. Being a Google-supported tool, it offers extensive integrations with various Google Cloud services and tools.

However, some drawbacks include reported issues with customer support, limited query filtering criteria, and the absence of an alert policy feature.

Use cases for the Operations Suite include monitoring serverless infrastructure and applications, troubleshooting serverless applications using cloud ops tools, and optimizing application performance to reduce Mean Time to Recover (MTTR).

Pricing Model

Regarding pricing, the cost of using Google Cloud’s Operations Suite products is based on usage or data volume, and there are typically no upfront fees, with free data usage allotments available for users to get started.

Dashbird

Dashbird is an advanced real-time monitoring and alerting system designed specifically for AWS Lambda applications. It excels at detecting Lambda-specific issues like timeouts, memory problems, runtime errors, misconfigurations, and exceptions. Dashbird offers seamless integration with CloudWatch and supports multiple programming languages such as Python, Java, Node.js, and Go. Its primary goal is to optimize costs, enhance performance, and manage resources efficiently by providing insightful analytics for AWS accounts, services, and functions.

Key advantages of Dashbird include its straightforward deployment process, comprehensive architecture observability, automated alerting system, and a powerful insights engine for detailed analysis.

However, there are limitations to consider, including limited integration with platforms beyond AWS Lambda, complexities in customization, lack of mobile support, and occasional service interruptions.

Use cases for Dashbird include AWS Lambda infrastructure monitoring, log management, X-ray tracing for performance analysis, and setting up alerts and alarms for critical events.

Pricing Model

Dashbird offers a pricing model with three tiers starting at USD 0, with costs varying based on the number of executions per month.

Epsagon

Epsagon is an advanced platform that offers automated data correlation, payloads, and end-to-end observability across various environments, empowering IT professionals to troubleshoot and resolve issues quickly and efficiently. The tool provides comprehensive visibility into containers, virtual machines, serverless systems, and more, eliminating the need for manual coding, labeling, training, or maintenance efforts. Epsagon leverages distributed tracing and sophisticated AI algorithms to identify expenses and monitor end-to-end performance effectively.

Some key advantages of Epsagon include its compatibility with any modern cloud environment, and extensive integrations with popular tools and services like EventBridge, Jira, GitHub, Serverless Framework, Slack, PagerDuty, Pulumi, and others. It also offers AI-based prediction and alerting capabilities, customizable dashboards for tailored monitoring, and automated tracing for cloud microservices.

However, there are some drawbacks to consider, such as a slight increase in code execution time, potential data fragmentation due to the lack of a general data framework, no optimization for mobile platforms, and limited support for multiple AWS accounts.

Use cases for Epsagon include automated tracing for cloud microservices, monitoring central processing unit (CPU) and memory utilization in containers, root cause analysis for issues, and instant observability with payload visibility.

Pricing Model

Epsagon offers a pricing model with three tiers starting at $0, providing up to 1K traces per month based on the selected plan.

Site24X7

Site24/7 is an integrated monitoring solution designed to cover website, application performance, server, network, and cloud monitoring needs. This comprehensive tool offers extensive visibility across various public cloud providers like AWS, Microsoft Azure, and GCP, as well as on-premises data centers leveraging hyper-converged infrastructure (HCI) technologies such as VMware and Nutanix. Site24/7 allows tech teams to create custom events or choose from a range of predefined scenario types for monitoring purposes, and it also comes with a mobile app for convenience.

Some advantages of Site24/7 include instant alerts for timely notifications, robust security tools for both internal and external monitoring of serverless applications, and an optimized mobile application for on-the-go monitoring and management.

However, there are a few drawbacks to note, such as challenges with the transaction recording process, the absence of browser recorder playback for recorders, and occasional interruptions in customer service.

Use cases for Site24/7 encompass public and private cloud monitoring, log management, network monitoring, and application performance management.

Pricing Model

Site24/7 offers a starter plan priced at $9 per month when paid annually, making it an accessible option for businesses looking to enhance their monitoring capabilities.

Thundra

Thundra is a robust platform offering a suite of features including tracing, profiling, monitoring, and alerting designed to assist administrators in effectively managing distributed services. It provides comprehensive observability for end-to-end serverless architectures, facilitates code-level time travel debugging, and offers automatic distributed tracing capabilities. Thundra also features a free live on-premises AWS Lambda debugger, ensuring that it doesn’t introduce additional latency to code execution.

Some advantages of Thundra include detailed monitoring of distributed systems, a wide range of automated alerting options, ease of setup, and no impact on code execution time.

On the downside, Thundra may have complex configuration options, making it less suitable for smaller environments. Additionally, it has a steep learning curve, requiring users to invest time in learning its intricacies.

Use cases for Thundra include automating tracing and serverless monitoring, time travel debugging, integrating alerts and actions with workflows and systems, and real-time automation of security and compliance control configuration, enforcement, and verification.

Pricing Model

Thundra offers a variety of pricing models including a free trial, freemium, and subscription plans starting at USD 0 with options to scale based on monthly invocations, making it accessible to a wide range of users and organizations.

Google Cloud Monitoring

Google Cloud Monitoring, an integral component of Google Cloud’s operations suite, offers automated dashboards designed to collect metrics seamlessly for Google Cloud services. This tool stands out for its ability to support multi-cloud and hybrid environments, making it a versatile choice for diverse infrastructure setups. Some of its notable features include service-level objective (SLO) monitoring, managed metrics specifically tailored for Kubernetes and virtual machines, and effortless integration with Google Cloud services without requiring additional instrumentation.

One of the major advantages of Google Cloud Monitoring is its provision of automatic metric collection dashboards right out of the box for Google Cloud services. This feature streamlines the monitoring process and provides valuable insights into performance metrics, events, and metadata, aiding in trend identification and issue prevention.

However, it’s worth noting that being a relatively new product, Google Cloud Monitoring may still lack some advanced features and may have user interface (UI) issues. Users have reported occasional false positives in alerts, which can be a concern for some scenarios.

The tool finds application across various use cases, including scaling monitoring through its managed service for Prometheus, monitoring API usage, tracking Compute Engine virtual machine (VM) instances, and implementing site reliability engineering (SRE) practices for digital transformation initiatives.

Pricing Model

In terms of pricing, Google Cloud Monitoring follows a model with no upfront fees, allowing users to utilize free data usage allotments to get started. For detailed pricing information, users can refer to the official pricing guide provided by Google Cloud. No upfront fees to start using the free data usage allotments.

New Relic

New Relic is a comprehensive observability platform renowned for its in-depth code-level analysis of entire serverless architectures. The tool’s intuitive dashboards present performance data of cloud services, making troubleshooting seamless with extensive documentation. New Relic boasts support for over 100 built-in integrations, real-time alert creation, and efficient log management, covering a wide range of languages including Java, Node.Js, Python, Go,.NET, PHP, and Ruby, and even offers a native C/C++ agent.

One of the standout features of New Relic is its ease of installation, making it accessible for users looking to dive into performance and availability monitoring. The platform also stands out for its dynamic alerts and the ability to provide granular monitoring across various infrastructure aspects, application layers, and customer-side layers.

However, it’s important to note that New Relic may have a steep learning curve, and the full subscription can be pricey, which might be a consideration for some users.

New Relic finds applications across diverse use cases, including performance and availability monitoring, AWS Lambda monitoring, observability into cloud-managed functions, and viewing the correlated performance of serverless services within the stack in a unified interface.

Pricing Model

Regarding pricing, New Relic follows a usage-based model, with specific details available for users to explore in depth.

Wrapping Up

Adopting and accepting a serverless architecture brings accessibility and cost-efficiency to application development. Monitoring and debugging serverless applications is crucial for ensuring their optimal performance, scalability, and reliability. Such tools offer a variety of features such as real-time monitoring, comprehensive analytics, automated alerting, and integration with cloud platforms. By leveraging these tools, developers and DevOps teams can effectively manage their serverless architectures, identify and resolve issues promptly, optimize resource utilization, and deliver better user experiences.

Choosing the right monitoring and debugging tool depends on factors like the specific needs of your application, the cloud platform you are using, budget considerations, and the level of customization and automation required. It’s essential to evaluate each tool’s pros and cons, pricing models, and compatibility with your existing infrastructure before making a decision.

Ultimately, adopting the right monitoring and debugging practices and utilizing the best tools for serverless applications can lead to improved operational efficiency, reduced downtime, cost savings, and overall better performance of your serverless ecosystem.

--

--

Shormistha Chatterjee
Shormistha Chatterjee

Written by Shormistha Chatterjee

Dzone Contributor| Blogger| Co-author | Sr. Writer| Silent observer on Medium, reads every day and love to write.