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Curated Engineering Insights

How to Control DevOps Observability Costs to Maximize ROI

Apr 5, 2023 11:56:34 AM

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How to Control DevOps Observability Costs to Maximize ROI_1

While observability is an increasingly crucial part of DevOps-based software development, the associated costs are growing faster than infrastructure costs. IT organizations today face the challenge of balancing innovative observability strategies with maintaining sustainable business models.

Companies that invest in new technologies, for instance, DevOps observability tools, run into the problem of realizing a positive Return on Investment (ROI). Ideally, the costs of cloud adoption must consist of two cost channels growing parallelly and proportionately - one cost area is that of DevOps tools integration, and the other area involves infrastructure costs.

The 2022 Observability Forecast by New Relic discovered that 35.6% of respondents ranked budget-friendly pricing as highly crucial in an observability tool, and the provision to leverage a single license metric was mentioned by 30.7% of respondents.

In this article, we will delve into the various strategies that companies can embrace to enable stronger control over the costs of DevOps observability adoption.

What is DevOps Observability?

DevOps observability is highly essential for application development as it helps developers and other stakeholders to gain granular visibility to pinpoint the root cause behind any malfunction. As cloud application development environments are highly complex and layered, having a reliable observability tool is important for deciphering and pinpointing where exactly things have gone wrong.

More often than not, there are thousands of compute instances running simultaneously in any modern cloud app environment, and keeping track of individual operations can only be done through DevOps automation tools for observability. As more software development approaches are increasingly employing microservices, getting to the exact point of failure is getting ever more complicated.

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Despite the minor pitfalls, at the end of the day, the increase in DevOps adoption is a good thing as it helps software development teams speed up their delivery timelines. Regular deployments of application packages and components in the respective environments lead to greater scope for risk in the system. Debugging and diagnosing the system effectively is carried out with close attention to continuous integration and deployment strategies.

DevOps Observability is the one-stop solution for all the above problems that lead to the breaking of code or the final application not being up to par. Moreover, the DevOps tools enable the automation of certain tasks along the Software Development Lifecycle (SDLC) for tangible business outcomes. The entire volume of data generated by the app environment is put into its proper context by DevOps observability tools.

DevOps Observability Pipeline-realkinetic

Image: Observability Pipeline

Source: realkinetic.com

DevOps Observability ensures that the DevOps teams are always fully aware of what is going on across the software development workflow and multiple environments. Here are the primary components that enable DevOps Observability: 

Event Logs: Actions or occurrences in an environment or software development workflow are recorded in specific types of files known as event logs. Different types of event logs such as system-related, application-specific, or security-based logs are stored for different areas such as systems, databases, and cloud environments.

Metrics: When it comes to the visibility of the performance of a system or an approach, DevOps metrics are employed. These are specific data points representing the performance of the software development pipeline that help spot bottlenecks quickly and remediate them accordingly. 

Traces: These observability tools provide a view into the flow of the overall application, even in distributed systems such as microservices and containers. A distributed trace moves through the various parts of the application and records and compares the time it takes to process a request or which parts of the application triggered the error in question.

How to Determine the Cost of Observability

Software engineering enterprises pursuing a reliable growth factor must consider the immense capability of observability. However, there is the pitfall of inflated costs associated with adopting robust observability tools. The costs of DevOps observability greatly depend on aspects such as the pricing model, the business model, the type of software ecosystem utilized, and so on. Here are those aspects discussed in detail:

1) Business Models: Based on how the application is structured, the development environment is either determined as an on-premise or a software-as-a-service (SaaS) business model, or sometimes a hybrid model combining the two is the one opted for. As is with everything else required for software development, the upfront cost of setting up observability tools for on-premise setups is more expensive than SaaS solutions. SaaS offers pay-as-you-use and flexible subscription-based payment models making it less expensive for the observability vertical as well.

2) Software Ecosystem: The application which becomes the final product is developed in an environment that includes several interconnected software applications that aid in development. This cumulatively makes up the software ecosystem and could either be closed or open based on the rights of access. Closed ecosystems consist of a gatekeeping entity that controls the level of access to software, on-premise hardware, and other services. When it comes to closed ecosystems, the software vendor may levy a penalty every time a new data source needs to be brought into the system for enhanced observability.

3) Pricing Models: Pricing models, which subsequently help in the definition of buying models, are units of measurement for vendors that they can then use to gauge the volume of resources utilized. This categorizes pricing models into the following:

  • Infrastructure-based pricing gauges the number of units in terms of hosts, agents, and nodes being utilized for observability
  • Service-based pricing measures the quantity terms of the service being monitored
  • User-based pricing counts the number of provisioned users who are engaged with the monitoring tools or observability platform
  • Telemetry-based pricing is also usage-based but measures data ingestion, storage utilized, as well as the queries executed for data extraction

DevOps Observability Dashboard-cloudzero

Image: DevOps Observability Costs Dashboard

Source: cloudzero.com

How to Manage Observability to Maximize ROI

For greater innovation and more next-generation technology pioneering, software development strategies must be designed around observability. As newer technologies like 5G, blockchain, deep learning, AGI, and Web3 are increasingly being integrated with the latest applications, the need for cost-effective observability has become even more relevant.

So how do DevOps teams ensure that their observability initiatives are not draining their development budgets? Companies striving to stay in front of the competition need to leverage observability for identifying the most viable and latest technology stacks to produce high-quality software. The following are some ways they can do so cost-effectively:

1) Deriving Value from Pricing Structure 

The thumb rule for selecting a price structure is to make sure that it delivers a good ROI while delivering all the required observability tools. Transparent pricing and accurate prediction of future spending help facilitate this. Other requirements include the ability for automated scaling without having to purchase laddered subscriptions as well provisions for switching easily to a pay-as-you-go pricing model. Software development teams are fully prepared to spend immensely on a robust DevOps Observability toolchain but need predictable pricing graphs. They require a pricing structure that accounts for quick changes in the observability metrics and switching among the types of telemetry data being monitored.

2) Gauging Total Cost of Ownership

The observability stack tends to have a Total Cost of Ownership (TCO) attached to it that helps determine the long-term expenditures beyond the upfront payments. These costs may include but are not limited to:

  • Training of DevOps teams for operating cutting-edge observability tools
  • Ensuring no interruptions during the scaling of observability strategies
  • Enabling easy integration of new tools into the existing tech stack
  • Changes in pricing structures when switching from open source to proprietary tools

3) Extensive Preparation

Any tech organization needs to implement the fundamentals if they need great returns from their software delivery initiative. The fundamentals include the distribution of the best tools to the ablest among the team members while training them extensively in the use of these tools. The organization needs a bird's eye view of its DevOps pipeline if it wants to derive the most of its observability stack. Moreover, to drive rapid scaling in the future, they need to prepare the existing observability stack to brace for system outages and any breaches that could lead to downtime.

4) Sustainable Maturity

There is always scope for improved maturity in an organization's observability stack. To achieve sustainable maturity in DevOps observability, an organization should have a well-defined strategy and approach for implementing and maintaining observability practices. This includes establishing clear goals and objectives, selecting appropriate tools and technologies, defining processes and workflows, and establishing metrics and KPIs to measure the effectiveness of observability practices. It also requires a culture of collaboration and continuous improvement, where teams work together to identify and resolve issues, share knowledge and best practices, and continuously optimize observability practices.

ALSO READ: Benefits of Using Cloud with DevOps Services

Manage your Observability Costs to Ensure Continued ROI 

Controlling DevOps observability costs requires a combination of strategic planning, smart tooling, and consistent monitoring. By taking a proactive approach to optimizing your observability stack, you can gain valuable insights into your system's performance and identify potential issues before they become costly problems. 

It's essential to strike a balance between cost and effectiveness, but by following the tips and best practices outlined in this blog, you can ensure that your observability initiatives remain on track without breaking the bank. You can achieve this and more by leveraging the DevOps Services expertise offered by Daffodil Software.

 

Topics: DevOps CloudOps

Allen Victor

Written by Allen Victor

Writes content around viral technologies and strives to make them accessible for the layman. Follow his simplistic thought pieces that focus on software solutions for industry-specific pressure points.

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