Uptime. Downtime. Security protections. There are plenty of things to watch for, so an effective cloud monitoring strategy requires an organization to set some priorities.
- Adam Bertram
Published: 12 Jul 2021
Cloud infrastructure produces a mountain of data in real time. User activity fluctuates. Performance metrics shift abruptly. Faced with these continuous changes, how can an organization expect to gather the insights necessary to optimize its IT systems?
It is a genuine struggle to find and boost transparency, but there are ways to see more of what is happening within an enterprise IT environment. A effective cloud monitoring strategy can help unravel the mystery behind your services.
The key requirements are:
- proper tooling, sourced either externally or in-house;
- clear comprehension of your monitoring goals; and
- an understanding that cloud monitoring ultimately benefits all facets of a business.
Tools can help with these goals, but don't expect cloud monitoring to be as easy as marketers portray it to be. Experienced users are still needed at the helm, and a sound strategy is critical to success.
What are the different types of cloud monitoring?
Cloud monitoring is critical to system health and performance. Accordingly, different types of monitoring will suit different scenarios. Every cloud ecosystem has multiple moving parts, so there are different types of monitoring you can implement to keep things running smoothly:
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- Website performance. Traffic, resource usage, page availability and other performance metrics can tell an administrator how sites are loading versus expectations, how visitor counts or webpage elements impact overall browsing performance, and if SEO optimizations work as intended. A cloud service provider can capture these data points so you can compare them against established KPIs.
- Cloud storage. This measures remote storage operation, makes storage volume layouts observable and gives admins insights into smarter data organization. Storage monitoring can highlight inefficient capacity and processes as they occur, and also help reveal security holes. It's easier to capture this data while using third-party platforms.
- Databases. Tracking database requests, special queries, data integrity and user activity while an application continuously runs can reveal patterns that help admins make changes and plan upgrades.
- Virtual machines. This applies mainly to organizations that use an infrastructure service to extend computing capabilities. VM monitoring, like website or application monitoring, measures user activity, performance and individual infrastructure components.
- Virtual networks. This involves oversight and protection of firewalls, switches, routers and software-based load balancers. Network monitoring in real time can help IT teams assess networking performance and even uncover security concerns.
Why is cloud monitoring important?
Cloud monitoring opens a window into your cloud services' functionality at any given moment. If you know what takes place within a SaaS, PaaS, IaaS, FaaS or a cloud-hosting service, this empowers your teams. Keeping an eye on performance activity also can help providers and developers spot potential improvements that benefit end users, such as better resource allocation and load balancing changes. Cloud monitoring tools can also help position your services for scaled growth.
So, what can we monitor? The key indicators of ecosystem health are as follows:
- performance (throughput, latency, memory usage, response time, user capacity);
- reliability (uptime and downtime, average time between failures, time to repair, error handling);
- security (DDoS attack resistance, blast radii, access control, data protections); and
- costs and billing, which track estimated and accrued charges for cloud resources your workloads consume, to help keep your cloud usage and spending under control.
Keeping track of so many indicators might seem daunting. Monitoring tools enable you to pool application data into a centralized space, where the information is organized and discoverable by numerous stakeholders.
How does cloud monitoring benefit an organization?
Consider a modern automobile. Multiple systems and mechanical parts work in tandem, and diagnostic work for such complex systems and parts is a big undertaking. An onboard diagnostic system stores trouble codes and tracks real-time engine performance. Engineers can tweak these systems via programming changes.
Similarly, cloud monitoring reveals where problems lurk, so IT professionals can step in and act before those problems affect wider parts of the system and impact users. For example, if an app consumes too much memory or compute resources, IT staff can adjust resource provisioning. Active monitoring is immensely helpful, though retrospective logging can illuminate worrisome trends.
Unlike traditional services that are monolithic or bundled under one large codebase, microservices has its own code, resources and programmable logic. Developers run their applications within isolated containers that generate their own data and claim their own resource allocations. This gets complicated, especially at scale. Tracking the metrics can help alleviate growing pains.
Keep in mind that a cloud monitoring strategy doesn't just uncover problems -- it highlights what you're doing well, so you only devote attention to things that need improvement.
Greater visibility and a data-driven approach can accomplish the following advantages:
- Better performance. Raw metrics and organized infographics can provide clearer pictures of a system's performance, especially in a containerized environment. Knowledge about resource usage and allocation, and how application demand causes strain, can help teams optimize their deployments.
- Better security. User activity logs and RBAC tactics help admins tighten unauthorized access. Teams can measure the impacts of traffic to understand the potential severity of a DDoS attack. They also can regularly scan files and resources to prevent malware or other afflictions from gaining a foothold.
- Topographical understanding. Observability and clear views into an infrastructure's unique layout help teams understand how components are arranged. This knowledge makes it much easier to navigate the ecosystem during management tasks.
- Better cohesiveness. Cloud monitoring tools often pool human-readable data or charts into a centralized location. While this data was once segregated between teams, new databases can provide business value to all teams with one data set.
Cloud monitoring best practices
There are many ways to tackle cloud monitoring, but some consensus recommendations and best practices apply across most cases.
- Determine which metrics mean the most to your organization. What do you most want to accomplish through monitoring? Performance, security or reliability could take precedence over other areas. Many companies improve their services based on customers' preferences. For example, multiplayer gaming services might favor low latency and high capacity at the expense of security.
- Choose tooling based on core metrics. Sometimes a business gets too far ahead of itself and shops for a monitoring tool before it settles on a strategy -- which metrics to prioritize, which services you'll monitor and which providers you'll use. Consider your budget and technology stacks. Teams that maintain Docker-based applications have different needs than ones that conduct e-commerce. However, tools can't be all things to all teams. Every tool has strengths and shortcomings. Users might simply prefer one interface over another, everything else being equal. And keep in mind: There's no perfect monitoring tool.
- Numbers mean nothing without context. Establish a performance baseline to understand if your system is acting irregularly (or to spec). This will give you a point of comparison and normal operating range.
- Monitor the user experience. Users are everything, and services should exist to improve user outcomes. Enterprises often measure this with features, but user experience typically relies on reducing friction, such as frustration from crashes, service interruptions, errors or bottlenecks. Application performance monitoring (APM) tools can show how well an application behaves on user devices, through dashboards that paint a real-time picture of satisfaction, typically based on a calculated index or alternative measure. An organization can see how service-based events influence these ratings.
- Use your monitoring tool to improve testing procedures. Failures will occur at some point. Cloud monitoring continuously enables chaos testing for high-traffic applications and web services.
- Automate when possible. There's an adage in IT: If you perform a task more than once, automate it. Teams can offload key tasks onto their monitoring tool such as event-based responses, configuration changes, periodic health checks and timed reports. Automate administrative duties wherever possible to save time for more important tasks.
- Establish targeted alerting. Alerts that reach the right team members help immensely with issue remediation. Monitoring solutions can send messages via text, email or even via mediums such as Slack.
Cloud monitoring tools and dashboards
Real-time monitoring is powerful, but it can put demands on IT staff. Cloud service providers offer tools to assist with your monitoring efforts. For example, Microsoft Azure monitoring capabilities focus on specific areas of interest such as resource usage, cost optimization and network performance. AWS has similar tools for management and monitoring, as does Google Cloud.
Reliance on a cloud provider introduces some quirks into your monitoring process. Some tools provide unfettered visibility into all core metrics, while others can't tap into certain performance metrics or sensitive data due to lockdown.
Some monitoring tools are throttled to capture monitoring statistics only at certain intervals and not in real time. This may be inadequate, particularly for containerized environments because containers and pods can terminate or replicate at a moment's notice. Furthermore, sudden spikes in user activity impact resource utilization, which demands swift data capture.
Consider matching your hosting and tooling providers to provide a centralized monitoring experience without extensions. If you work with Amazon EC2, consider Amazon CloudWatch because its native compatibility provides unhindered data capture.
Examples of cloud monitoring tools
Hundreds of cloud monitoring tools, both closed and open source, exist on the market today. Providers differentiate with unique interfaces and task-specific dashboards to ensure that you focus on what matters most. These experiences are visually rich yet are tailored to prevent unwanted distractions. Some tools present monitoring data with graphs or lists, while others are more bare-bones with raw data and no visualization. A logging request with text-only output, for example, requires a user to dig deeper to extract meaningful insights.
The best cloud monitoring tool should engage and inform, and not prioritize superfluous data. It should align with your ecosystem's unique arrangement and requirements and your team's technology stack familiarity; integrations are also useful. Here are some noteworthy picks that you can use to monitor your cloud services:
- Raygun -- an APM tool that provides a simple, informative line graph that measures user happiness over 12-hour periods
- Datadog -- a cloud monitoring service that packages infrastructure, logging, network, user and security monitoring together
- AppDynamics APM -- a full-fledged monitoring platform that excels at monitoring containerized applications, either hybrid or full-cloud
- Amazon CloudWatch -- a popular infrastructure and application monitoring service that connects seamlessly to AWS components, pulling metrics from both the cloud and on-premises deployments
Without a doubt, cloud monitoring tools are indispensable to IT professionals. These tools are part of a cloud monitoring strategy, but they don't automatically solve your problems. Someone must know how to configure and deploy the tools, interpret incoming data and make decisions.
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