Observability Trends in Software Development Lifecycle

by Caleb Eghan

For developing and distributing software packages or products, infrastructure that provides developers and businesses with insight into code performance, vulnerabilities, and real-time assessment of system behaviour is required. In most cases, simply running your code or packages locally isn’t enough; they must also be able to adapt to any conditions and use cases, regardless of the environment in which they are hosted, where they are subject to multiple threats, vulnerabilities and possible downtime. 

This is why you require observability, which allows you to comprehend your deployed application or system at every stage through knowledgeably gathered data, enabling your team to make an informed decision.  The capacity to gauge a system’s internal conditions by looking at its outputs is known as observability. 

If the current state of a system can be determined solely from information from outputs, such as performance data, then the system is said to be “observable.” 

One of the early and most widely used methods by system engineers, software engineers, and organizations to gain an understanding of their deployment in a particular scenario is the use of logging. However, with the growing complexity of systems and cloud infrastructure, logging alone isn’t enough to understand your systems in detail. 

Thanks to sophisticated tools and services such as Cribl, Splunk, and honeycomb, just mention a few, that have been made available for observability, developers, system engineers, and organizations can now quickly advance beyond logging to real-time graphical insights on how a service is being consumed, vulnerability detections, and anomalies persisting in a specific time period.  

Here are  4 major observability trends organizations are adopting:

1. Initiating Observability at each stage of the software development lifecycle 

Currently, in most organization infrastructures, observability has been incorporated in every key step in software development. From development to testing and from deployment to maintenance, capturing performance and reviewing those performances has become a culture in many organizations.  For instance, software deployed in a testing environment might have a different performance from one deployed in a production environment. By incorporating observability, your team gets to understand what is causing the difference in performance and make an informed decision. This goes further to influence how developers write code and how infrastructures are built.  

2. Adopting a DevOps culture towards Observability 

DevOps observability adaptation is a growing trend that incorporates an agile process on how engineers review system performance and implement observability. In this sense, there is a continuous cycle toward observability integration that allows engineers and the entire organization to gain first-hand insight into system performance and behavior without having to wait for a disaster to occur. Adopting a DevOps culture towards observability gives your organization control over the time spent identifying an issue and focusing on the relevant performance issue at hand, saving the organization, engineers, and its customers a significant amount of time. 

 3. Collaborative Effort towards Observability: 

As infrastructure and deployment expand, organizations must segment the data they collect for observability purposes. This necessitates consistent team collaboration across multiple departments and groups, with data centralized for easy collaboration. In the case of multiple teams developing services that are consumed by other teams within the same organization. Observability is applied to each developed service. There is a need for a collaborative effort among teams in which each team analyses how their service is consumed by another team in order to better understand what informed decisions must be made to better serve consumers within the organization.  This collaborative effort gives room for data to be shared across teams and also helps each understand how the end user is consuming a given service within or outside the organization. It even goes above and beyond to assist the organization in areas where it has fallen short and help realize the expertise required to improve its deployment process. 

4. Usage-based pricing Impacting Observability Strategy 

As previously stated, the growing observability culture has introduced sophisticated tools and services to assist organizations in improving their observability process. The majority of these tools and services are priced on a consumption basis, making it difficult for organizations to fully utilize or benefit from the service. To stay within a given budget, most organizations end up compromising and restricting the use of certain features. Due to service provider usage costs, organizations end up analyzing only a fraction of the massive data captured from telemetry traces. This has an impact on the cost-cutting strategies used by organizations, causing them to miss out on the full benefit that an observability service or tool may provide. 

At RiverSafe, we assist organizations in incorporating observability across multiple vendors into their infrastructure, ensuring compliance and best practices. Assuring that the appropriate tools are consolidated while adhering to your organization’s culture and budget. 

By Caleb Eghan