SAP Observability in the Cloud: Four Essential Components

The disruptive effect of rapid technological innovations has redefined competition as we know it. So much so that standing still is equivalent to moving backwards in today’s digital economy. The sheer pace of change over the last decade has caused organizations to adopt cloud operating models for greater speed, agility, and flexibility.

While Cloud technology makes organizations more adaptable in a volatile business environment, the level of adaptability organizations realize through increased agility and flexibility is contingent on how well they adapt to operating in the Cloud. In other words, to optimize Cloud operating models, businesses need to change their people structures, processes, mindsets, and ways of working.

Beyond Traditional Monitoring

One particular area organizations must transform to optimize Cloud operations is application monitoring. Traditional monitoring solutions work by collecting data and identifying issues they are preconfigured to monitor. Simply stated, traditional monitoring solutions are designed to detect known or predictable failures. In the Cloud however, failures are much harder to predict.

Because Cloud environments are so complex, it is impossible for traditional monitoring solutions to know what to look for let alone cover all possible events. And without the ability to know what is happening in a Cloud environment at all times, it is impossible to have efficient operations. To optimize Cloud operations, businesses need a solution that can discover and address “unknown unknowns”. They need observability.

Observability, in a Cloud context, refers to software tools and practices for aggregating, correlating and analyzing a steady stream of performance data from an application and the infrastructure it runs on to effectively monitor, troubleshoot, and debug the application. While monitoring tells you whether a system works or not, observability will tell you why it is not working.

The benefits of observability are straightforward: organizations that implement observability in their Cloud environment have deeper visibility into their environments and faster, automated problem identification and resolution. In this article, we discuss four components SAP customers need in an observability solution to realize efficient Cloud operations.

Four Essential Components of SAP on Cloud Observability

One advantage of being on the Cloud is that everything is software. Since everything is software, everything can be observed. This fact has massive implications. If everything can be observed in an SAP on Cloud environment, stakeholders should know what is going on at all levels of their environment in real-time, have context to the data they are presented, be able to store operational data, and form predictions using the stored data. These capabilities encapsulate the four essential components of SAP on Cloud observability. Let’s examine each one closely.

1. SAP-Centric Semantics

An effective SAP on Cloud observability solution must present data in SAP-centric semantics stakeholders can understand. The challenge with many SAP on Cloud monitoring solutions is that they present data in cloud-centric semantics rather than SAP-centric semantics that is easy for users to understand.

Consider this example. You get an alert that says, “volume #4525 is approaching capacity”. As an SAP owner, it may take some time for you to figure out what this alert means. However, if that same data was presented as “load volume for S/4HANA production is approaching capacity”, you would be able to resolve the issue immediately. That is the value of implementing SAP-centric semantics in an observability solution. With SAP-centric semantics, organizations can accelerate SAP-related processes almost overnight.

2. SysOps, FinOps, and SecOps View

Most monitoring solutions only look at system health. When it comes to observing or monitoring an SAP on Cloud landscape, however, stakeholders want to know how their SAP system is performing from a system, cost, and security perspective.

To align with this requirement, an observability solution must provide real-time data on system operations (SysOps), financial operations (FinOps), and security operations (SecOps). With data from these three levels correlated in real-time and made accessible to stakeholders, they can flexibly query operational data from a system, finance, or security perspective and gain valuable insights, enabling them to be proactive rather than reactive when responding to issues.

3. Data Lakes: Store all your data forever

In the digital economy, data is like oil. The more businesses have, the more value they can extract. That said, it is in an organization’s best interest to store the data being generated in its observability solution indefinitely.

When it comes to cheaply storing all enterprise data for an indefinite period, a Cloud Data Lake is the perfect solution. Data lake solutions are appealing as they act as a place to temporarily store data without the need to transform the data first. When specific data is needed, it can then be queried and analyzed. With a Cloud Data Lake, businesses have a cheap and simply way to store and access all enterprise data.

4. Predictive Analytics

Predictive analytics uses current and historical data patterns to form accurate predictions. Because granularity and the historical length of stored data are the biggest strengths of data lake solutions, there is a synergy between predictive analytics and data lakes organizations must capitalize on.

If the copious amount of data in a data lake is like oil, predictive analytics can be likened unto a refinery that extracts value from the oil. With predictive analytics, businesses can use insights extracted from data lakes to optimize operational processes, improve production capacity and quality, and reduce risks.

A Value Chain of Operational Efficiency

From a holistic view, each of the four components we covered contributes to a value chain of operational efficiency. Stakeholders need to see what is going on at all operational levels of the SAP environment (system, finance, security), they need data from each level presented to them in a way they can understand to accelerate problem response, the steady follow of data within the SAP on Cloud environment needs to be stored, and the stored data needs to be refined to produce valuable insights. Implemented together within an SAP on Cloud observability solution, these four components can transform Cloud operations.