6 Ways to Reduce IT Costs Through Observability

Businesses need to growingly rely on complex IT systems to monitor, analyze, detect, and resolve issues proactively. Observability is an effective solution to these problems. It analyzes data generated by complex IT systems and enables IT teams to gain insights into how these systems behave and quickly identify and diagnose issues.

In this post, we will look at how observability can help reduce IT costs by optimizing engineering time, reducing the volume of downstream tools, lessening data storage costs, optimizing data sent to downstream tools, building an agile development culture, and decreasing incidents and outages.

What is Observability?

Observability refers to gaining insight into a system’s internal state by observing its external outputs or behaviors. In simpler terms, it’s the ability to see what’s happening inside a system from an outside perspective.

Observability is a primary concept in modern IT operations because it allows teams to understand the behavior of complex systems and processes. IT teams collect data from various sources, such as logs, metrics, traces, and events, to monitor the health and performance of the system in real-time.

Observability aims to make it easy for IT teams to diagnose and fix issues quickly. It can help them identify the root cause of problems and take the required corrective actions before they impact end-users by providing a complete picture of how a system behaves.

With the help of observability, IT teams can optimize resource utilization and plan for future capacity needs. By analyzing the data collected from observability tools, teams can gain insights into how resources are being used and where they can be optimized. That can reduce costs, avoid negligent security, and improve the overall efficiency of IT operations.

How to Reduce IT Costs With Observability

Let’s see how observability can help reduce IT costs.

1. Reduce Engineering Time

Remember that evaluating cost savings regarding data volumes and saving time to optimize data flow to your teams is essential. You will see significant increases in the productivity of your teams since you deliver the data you need downstream, and you’re sure that all of it is useful and actionable.

Mean Time to Detection (MTTD) and Mean Time to Resolution (MTTR) are the most common metrics that see decreases. Observability pipelines can be used to optimize engineer productivity and have impactful knock-on effects. You can optimize the time that your employers expend in identifying and fixing different problems and give them more time to concentrate on significant tasks, such as developing a new big product or improving current features.

In addition, the ability to reveal and eliminate issues quickly can save you millions as your Ops and IT teams keep a close eye on cyberattacks and system breakdowns, resulting in cumbersome data loss and leaks.

2. Optimize Volume to Downstream Tools

When using traditional observability data tools, one of the major hurdles is the high cost of ingesting and storing vast amounts of data. Historically, teams sent all their data to a SIEM or observability platform to guarantee quick access, query ability, and insights. However, with modern environments generating an explosion of data, these legacy methods contradict budgetary constraints.

Additionally, these tools offer a more complex way to filter or route data to other destinations, leading to potential overspending to access a limited amount of data. That puts teams in an unfavorable position, forcing them to choose between staying within budget or having sufficient observable surface area.

By implementing an observability pipeline, teams can evaluate each piece of data before sending it to downstream destinations, filtering or deduplicating data to eliminate useless data from their stream. That ensures that teams only pay for the required data and can derive value from it rather than incurring storage costs for all the data.

3. Lessen Data Storage Costs

In the current zero downtime era, monitoring system performance and ensuring it meets SLAs (service-level agreements) is critical. However, handling, storing, and reading the data involved presents a significant challenge in terms of cost. While having observability data is essential and considered a best practice, keeping only the necessary data can substantially reduce costs.

4. Reduce Data Sent to DownStream Tools

Starting to save by reducing data volumes sent to downstream tools is an easy first step, but it gets better with observability pipelines. You can choose where your data flows, so you don’t have to pay for the same data in multiple destinations.

However, you still need to retain some data types for compliance purposes. Previously, this meant routing all data to expensive legacy systems. But with an observability pipeline, you can segment compliance data and route it directly into cost-effective object storage, such as Amazon S3, bypassing more expensive platforms while ensuring historical data accessibility. This way, your team stays compliant, and you save your budget.

5. Build an Agile Development Culture

Observability tools enable you to swiftly detect and mitigate unnecessary resource usage, such as high CPU utilization before it negatively impacts users or applications. If an application on a server uses 100% of its CPU but only requires 50%, this can result from suboptimal code or algorithms. Identifying these issues can optimize your code and prevent future performance problems.

For software companies, responding to changing business requirements is essential. Application failures can cause significant losses and workplace accidents for your organization and its clients and partners. By using observability tools, you can monitor your system’s behavior from start to finish without writing code or restarting the app after an unexpected crash. Furthermore, you can track the duration of each request, allowing you to pinpoint the root cause of issues related to endpoints or microservices.

6. Decrease Incidents, Unplanned Work, and Outages

An IT department typically spends 30% of its time on non-value-added activities. However, observability tools can help to mitigate this by providing crucial visibility into the performance and availability of your applications.

With increased visibility, you can detect anomalies in your production systems (physical or virtual) before they turn into significant problems, reducing the number of incidents. That helps you quickly resolve issues before they impact your users or customers. By spotting patterns across your entire infrastructure, you can identify problems at the source rather than merely reacting to symptoms, helping your team find root causes faster and reducing unplanned work.

By detecting problems early on, you can take action before they impact your customers or users, reducing outages and ensuring that your systems are always up and running.

Conclusion

Observability is crucial in modern IT management, allowing organizations to understand complex systems and detect issues. By analyzing data generated by these systems, IT teams can improve performance, optimize resources, automate processes, identify cost savings, and enhance collaboration. Observability is essential in DevOps and SRE practices, emphasizing automation, collaboration, and continuous improvement.