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Best practices for defining a cloud monitoring strategy

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.

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 robust 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.

Why bother with cloud monitoring?

Cloud monitoring opens a window into how your services are functioning at any given moment. There is tremendous value in knowing what takes place within a SaaS, PaaS, IaaS, FaaS or a cloud hosting service. Monitoring practices not only empower your teams, they can spur product improvements that benefit end users. Cloud monitoring tools can also help position your services for scaled growth.

So, what can we monitor? These are key indicators of ecosystem health:

  • Performance (throughput, latency, memory usage, response time, user capacity);
  • Reliability (uptime and downtime, average time between failures, time to repair, error handling); and
  • Security (DDoS attack resistance, blast radii, access control, data protections).

Keeping track of so many indicators might seem daunting, but monitoring tools pool your application data into one centralized space -- discoverable by numerous stakeholders, and laid out in rich, organized ways.

How cloud monitoring benefits an organization

Consider a modern automobile. Multiple systems and mechanical parts work in tandem, and -- because these are complex systems and parts -- diagnostic work 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.

Cloud monitoring works in a similar fashion, revealing where problems lurk. IT ops professionals can step in and act before those problems affect wider parts of the system, which could become evident to users. For example, if an app consumes too much memory or compute resources, IT staff can improve provisioning. Active monitoring helps immensely here, though retrospective logging can illuminate worrisome trends.

Services of old were monolithic or bundled together under one large codebase. With microservices, each service has its own code, its own resources and its own programmable logic that differentiates it from its cousins. Developers run their applications within isolated containers, which generate their own data and claim their own resource allocations. This gets complicated, especially at scale.

An expanded services suite introduces complexity, but tracking the metrics can help alleviate growing pains.

Keep in mind that monitoring isn't only about problems. A cloud monitoring strategy should lead you to uncover what you're doing well; that way, you'll know not to devote attention to something that really doesn't need it.

Best practices in a cloud monitoring strategy

As a first priority, decide what you most want to accomplish through monitoring. Performance, security or reliability could take precedence over other areas. Determine which metrics mean the most to your organization.

Choose tooling based on core metrics. 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. This approach doesn't necessarily follow best practices, but it exists.

Sometimes a business gets too far ahead of itself and begins shopping for a monitoring tool before it settles on a strategy. It's critical to know which metrics to prioritize, which services you'll monitor and which providers you'll use. Be sure to consider your budget and technology stacks. What kind of company are you? Teams that maintain Docker-based applications, after all, will have very different needs than ones that conduct e-commerce.

It's important to note that tools can't be all things to all teams. Each will have its shortcomings. Each will have its strengths. Users might simply prefer one interface over another, everything else being equal. And keep in mind: There's no perfect monitoring tool.

Monitor the user experience. Users are everything, and services should exist to improve user outcomes. We often measure this with features, though the user experience relies on reducing friction. That includes frustration stemming from crashes, service interruptions, errors or bottlenecks.

Application performance monitoring (APM) tools can show us how well applications behave on user devices. APM dashboards paint a real-time picture of satisfaction -- usually through a calculated index or alternative measure. We can thus see how service-based events influence these ratings.

Automate when possible. If you perform a task more than once, as is often said, automate it. Teams can offload key tasks onto their monitoring tool, such as event-based responses, configuration changes, periodic health checks and timed reports. Any administrative task that can be automated saves time for other pursuits.

Cloud monitoring tool and dashboards

Cloud service providers offer tools to assist with your monitoring efforts. Through its Azure portfolio, for example, Microsoft offers monitoring capabilities focused on specific areas of interest, such as resource usage, cost management and network performance. Plenty of similar tools are available from AWS, and Google Cloud has made efforts to boost its management and monitoring offerings as well.

Reliance on a cloud provider introduces some quirks into your monitoring process. Some provide unfettered visibility into all core metrics, while others keep certain data locked down.

Not every tool excels at real-time data capture, either. Some monitoring tools are throttled, meaning they can only capture monitoring statistics at certain intervals. This may be inadequate.

Say you use Docker and want a hassle-free tool for monitoring your containers. While some tools may require modifications to your Docker images, the ideal tool might leave them untouched. What if you work with Amazon EC2? It would be wise to consider Amazon CloudWatch, which, because of its native compatibility, provides unhindered data capture. When you match your hosting and tooling providers, you can gain a centralized monitoring experience without extensions.

Tools present monitoring data in various ways. Some use graphs, some lists, and others are more bare bones. An ideal tool should be engaging and informative without prioritizing superfluous data.

As an example, Raygun's APM tool provides a simple, informative line graph that measures user happiness over 12-hour periods.

APM graph from Raygun
Raygun’s APM graph, organized by colored categorization and approval percentage.

Makers of cloud monitoring tools set themselves apart by offering unique interfaces. They also bring a number of task-specific dashboards, which ensures that you'll focus on what matters most. These experiences are visually rich, yet are tailored to prevent unwanted distractions. Real-time monitoring is powerful but can put demands on a staff.

Without a doubt, cloud monitoring tools have become indispensable for IT professionals. These tools are part of a cloud monitoring strategy, but they don't automatically solve your problems. Someone still needs to know how to interpret incoming data and make decisions. Also, tools require some degree of configuration before they are usefully deployed.

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