Making the Right Choices with Cloud Monitoring Tools
Christina Harker, PhD
Marketing
The right monitoring tools are essential in identifying and resolving issues that can lead to downtime, performance degradation, and security threats, while also ensuring compliance and providing visibility into application infrastructure usage.
However, implementing effective cloud monitoring tools can be challenging, as it requires choosing the right tools that meet specific infrastructure needs, managing and analyzing large amounts of data generated by cloud applications and infrastructure, and integrating cloud monitoring tools with other tools and services used in the cloud environment.
In this article, we will discuss the importance of cloud monitoring and the technical challenges associated with selecting and implementing the right tools to ensure the smooth functioning of cloud infrastructure. We'll look at 3 possible paths: build/bring your own (BYO), provider managed services, and external managed services, and the advantages/disadvantages of each.
What are Cloud Monitoring Objectives?
Cloud monitoring is the process of gathering, analyzing, and reporting data related to the performance and behavior of cloud-based applications and the underlying infrastructure. A good cloud monitoring platform will take the vast amount of performance and behavior data emitted by cloud applications, and present it to engineers and stakeholders in a way that allows them to quickly understand how their applications are performing and to identify potential issues.
Monitoring: Performance Metrics and Basic Logs
Most engineers are familiar with the basic aspects of monitoring, which involve measuring static resource usage such as network bandwidth, CPU, RAM, and disk I/O. Monitoring also includes analyzing basic logs, which provide insights into events and issues occurring within the application and infrastructure.
By collecting these metrics and logs, cloud monitoring provides a general high-level overview of application performance. This information is crucial for identifying bottlenecks, diagnosing issues, and optimizing resource utilization. However, these static “snapshots” of data don’t tell the whole story about what’s actually going on inside an application, and how a user might be interpreting the perceived performance.
Observability: Holistic Understanding of Application Behavior and Performance
While monitoring focuses on gathering data related to resource usage and basic logs, observability goes a step further, aiming to provide a holistic understanding of application behavior and performance. Observability allows engineers to answer the question, "What happens during the lifecycle of a user request?" To achieve this, observability relies on more advanced metrics and data sources, including latency/response time, event-based logs, and distributed tracing.
Latency and response time metrics provide insights into how quickly user requests are processed, while event-based logs capture specific events and errors that occur during the request lifecycle. Distributed tracing enables engineers to follow the path of a request as it flows through various components of the application and infrastructure, helping to identify bottlenecks and performance issues at a granular level.
For modern software applications, it's essential to leverage both monitoring and observability; engineers need to have a detailed understanding of application performance and behavior both for maintaining good user experience, and for informing future design decisions.
Implement Your Own Cloud Monitoring
For organizations that decide to build their own (BYO) cloud monitoring, there are numerous open-source tools and platforms available, backed by extensive community support. One approach to building your own cloud monitoring system is to leverage projects from the Cloud Native Computing Foundation (CNCF). CNCF projects have the advantage of broad community support, use of accepted technical standards, and a cloud-first, platform-agnostic approach.
The CNCF hosts a variety of projects that can help build a robust and scalable cloud monitoring system. Some popular tools include:
Prometheus: A monitoring and alerting tool that collects and stores time-series data, mainly used for monitoring infrastructure and application metrics.
Grafana: A visualization and analytics platform that enables you to create interactive and customizable dashboards to visualize and analyze monitoring data.
Jaeger: A distributed tracing system for microservices-based architectures, designed to monitor and troubleshoot transactions in complex distributed systems.
OpenTelemetry: A set of APIs, libraries, and agents for capturing distributed traces and metrics, aimed at simplifying observability for cloud-native applications.
Fluentd: A log data collector that unifies data collection and consumption, providing a centralized and unified logging layer for your applications and infrastructure.
Logstash: Another log data processing pipeline tool, often used in conjunction with Elasticsearch and Kibana to create the ELK Stack, a popular log analysis platform.
Advantages of Implementing Your Own Cloud Monitoring
Cost: Building your own monitoring system using open-source tools is likely the lowest cost option compared to proprietary solutions.
Portability: CNCF tools can be deployed on any environment with compute resources, providing flexibility and reducing vendor lock-in.
Customization: By implementing your own cloud monitoring, you can design the system to meet your organization's specific requirements and constraints.
Disadvantages of Implementing Your Own Cloud Monitoring
Responsibility: When building your own monitoring system, you own the design, implementation, and administration end-to-end, which can be time-consuming and resource-intensive.
Complexity: Implementing and managing a comprehensive monitoring solution can be daunting, especially for small or inexperienced teams.
Focus: Building and maintaining a monitoring platform can divert resources and attention away from developing and improving your applications and services.
Organizations that decide to implement their own solution will have maximum flexibility and cost efficiency, but will have to deal with the administrative and technical complexity of owning the entire stack, end-to-end.
Implement Provider Cloud Monitoring
As an alternative to BYO is for organizations to utilize the built-in monitoring services provided by major cloud providers. Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) each offer comprehensive monitoring solutions for resources, logs, and tracing.
Provider Cloud Monitoring Solutions
Every major cloud provider offers a collection of managed monitoring tools that are designed to integrate seamlessly with their respective infrastructure and services:
AWS: Amazon CloudWatch for monitoring resources, logs, and metrics, and AWS X-Ray for distributed tracing.
Azure: Azure Monitor for collecting, analyzing, and acting on telemetry data, and Azure Application Insights for application performance monitoring and diagnostics.
GCP: Google Cloud Operations Suite, which includes Monitoring, Logging, and Trace, provides an integrated monitoring, logging, and tracing solution.
Advantages of Implementing Provider Cloud Monitoring
Easier Integration: Provider monitoring solutions are designed to work seamlessly with their respective infrastructure and services, simplifying implementation and reducing the need for custom configurations.
Reliability: Cloud provider monitoring tools are managed services, which means the underlying infrastructure operations are managed wholly by the provider, reducing technical and operational burden on engineers.
Single-source Support: Provider cloud monitoring means a single source of support and technical assistance. Interoperability with the application resources is explicitly supported, and the same provider support staff can assist with both.
Disadvantages of Implementing Provider Cloud Monitoring
Cost: Cloud provider monitoring solutions are generally more expensive than open-source alternatives, which will drive cloud usage costs higher.
Opinionated Implementations: Provider monitoring solutions come with predefined configurations and implementations, which may not fully meet requirements. An organization may be forced to implement additional monitoring tools to fill in the feature gaps, further adding to cost and complexity.
Limited Interoperability: Integrating cloud provider monitoring solutions with external platforms or tools may be challenging, as their compatibility and support for third-party systems may be limited. Support options will be much more limited for third-party infrastructure and platforms.
Platform Lock-in: Relying on a specific provider's monitoring tools may lead to vendor lock-in, making it difficult to migrate to another platform or adopt a multi-cloud strategy in the future.
Utilizing the provider solutions offers quick, “batteries-included” implementation that can be attractive for certain use cases, but there are long-term considerations around cost and potential lock-in.
Implement Third Party Cloud Monitoring
Another approach to cloud monitoring is utilizing third-party Software as a Service (SaaS) platforms. These fully-featured external solutions provide state-of-the-art monitoring and observability tooling, covering a wide range of use cases and requirements.
Popular Third-Party Cloud Monitoring Platforms
There are several third-party cloud monitoring solutions available, each with its unique features and capabilities. Some of the most popular platforms include:
Datadog: A comprehensive platform that offers a broad selection of services for monitoring and observability.
Sentry: Focuses on application monitoring and error tracking. Classified as more of an observability tool, as it specifically focuses on internal application behavior at the code level.
New Relic: An Application Performance Monitoring (APM) platform that provides insights into application performance, infrastructure health, and user experience.
Honeycomb: A distributed tracing and observability solution designed for modern software architectures, such as microservices and serverless applications.
Splunk: A platform for searching, monitoring, and analyzing logs and text-based data.
Sumo Logic: A competitor to Splunk, also utilized for searching, monitoring, and analyzing logs and text-based data.
Advantages of Implementing Third-Party Cloud Monitoring
Built-in Integrations: Third-party monitoring platforms often include out-of-the-box integrations with major cloud providers, simplifying implementation and reducing the need for custom configurations.
Multi-Cloud Support: These platforms are designed to work across multiple cloud environments, making it easier to implement monitoring for multi-cloud architectures.
Cutting-Edge Features: As purpose-built monitoring and observability solutions, third-party platforms continuously evolve to include the latest features and capabilities. Contrast this with BYO solutions, which may require time-consuming upgrade cycles and downtime, as well as cloud provider monitoring, which tends to iterate less often and offer less features.
Disadvantages of Implementing Third-Party Cloud Monitoring
Cost: Third-party monitoring solutions are generally the most expensive option among the three and can often result in exponential cost growth as an application scales in usage.
Complex Implementation: While third-party platforms may offer easy integrations with major cloud providers, implementing them for more complex application architectures might still be challenging.
Opinionated Solutions: Like provider-based monitoring tools, third-party platforms may also come with inflexible configurations and implementations. Customers with incredibly high scale demands, specific technical requirements, or compliance and data custody issues may still be forced into building their own solutions.
Platform Lock-in: Relying on a specific third-party monitoring solution can lead to a different kind of vendor lock-in, making it difficult to migrate to another platform or switch providers in the future.
Choosing The Right Cloud Monitoring Solution Depends on Resources
Choosing the right path in cloud monitoring depends on an organization’s resources and objectives, as well as their overall timeline for implementation.
Organizations that have experienced staff and time as well as specific implementation needs would probably do best to take advantage of FOSS and CNCF tools to deploy their own solution. Leaner or less cloud-experienced teams that want everything to work fire-and-forget, all in one place should go with cloud provider tools, and avoid wasting precious development time on integration. Organizations that want to have the latest and greatest tools and aren’t as concerned with cost should reach for third-party monitoring solutions, although they should expect to spend a little more time with integrations.
The important takeaway is that with any of these choices, there are advantages and disadvantages. The complexity of modern cloud-first software applications highlights the need for organizations planning a cloud deployment to spend serious time and effort not just designing their software, but designing the best and most efficient way to run and monitor it.