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Observability without Action is just Storage

Observability in software ops is key for proactive issue resolution, going beyond data collection to include decisive actions based on logs, metrics, and traces. Not acting on insights leads to reduced productivity and poor user experiences.

Observability is a crucial aspect of modern software operations, as it enables engineers to diagnose and debug issues quickly and proactively. So much so that there are many businesses and events that focus primarily on its framework and practices. We all want the ability to understand the internal state of a system by collecting and analyzing data from various sources, such as logs, metrics, traces, and events.

However, observability is NOT an end in itself. It is rather the first, albeit crucial, step in ensuring your applications & infrastructure are functioning as expected.

While many observability tools allow you to find issues, they don’t easily provide the ability to take actions against the alerts & data generated by the tools. Simply collecting and storing data without taking action is not only pointless, but also harmful for developer productivity and the user experience.

Observability is not just collecting data

Observability needs to encompass more than simply collecting data from various sources. It must include deriving insights. If you only collect data but don't use it to take actions, you're not achieving true observability. You're simply storing data.

An example of this is the common occurrence of stuck pods in Kubernetes clusters running stateful applications. Most observability tooling, even when set up properly, does not alert users that a pod is in a terminating state indefinitely. Forcing the operator to find out about this issue after an incident has been generated can lead to further escalation or even worse, lower customer satisfaction.

Here’s a real world analogy. Imagine you have a car that has a dashboard with various gauges and indicators. You can see the speedometer, fuel gauge, and other indicators. However, if you only look at these gauges, you won't get far. You need to use the information provided by these gauges to adjust your driving behavior, such as slowing down when you're running low on fuel.

Observability requires action to derive value

Today, the link between observability data and fast remediation is broken at the remediation stage. Operators have to cobble together a plethora of tooling to perform remediations for cloud providers, virtual machines vs Kubernetes, and even application type. This makes it difficult to efficiently respond to issues that your observability data might be raising and can ultimately result in tool fatigue.

Suppose you notice that the response time of a particular endpoint in your application is increasing or experiencing a high error rate. In either case, you need to investigate the root cause of the issue and fix it—not stand by and wait for it to happen again. By using the data collected from various sources, like logs, metrics, and traces as highlighted above, you can effectively diagnose the issue and take corrective action to avoid issues in the future.

Observability requires a feedback loop

Observability is not, and never will be, a one-time activity. It's an ongoing process that requires a feedback loop to drive continuous improvement. You need to continually monitor and analyze the data collected, implement changes based on that data, and evaluate the effectiveness of the actions taken.

You can’t simply deploy a fix for an issue and cross your fingers after determining the root cause. To ensure the issue is, in fact, actually resolved, you need to monitor the system's behavior. This will allow you to evaluate the effectiveness of your fix and determine any areas for improvement.

Start taking action

Observability requires action - plain and simple. You need to use the collected data to detect and fix issues, optimize performance, improve reliability, and enhance the user experience. Additionally, you need to continually monitor and analyze not only the data collected, but the effectiveness of the action taken.

Many DevOps tools detect incidents or assign them to the right person, but hardly anything actually helps fix them. Shoreline is changing that. Our solutions allow you to quickly build automations in hours (not weeks) to self-heal straightforward and repetitive issues so that your team can focus on innovation, not mundane work. And with our distributed debugging, you’ll be able to diagnose new incidents and implement repairs by running a single command across all your infrastructure.

Remember, observability without action is just storage. Stop simply collecting data and start taking action with Shoreline’s AI and automation platform. That way, you can extract more value from your observability data and drive continuous improvement for your organization.