Since DevOps principles began reshaping the way companies approach software delivery more than 10 years ago, many DevOps practices have matured and become standard. Continuous delivery is part and parcel of many enterprise software delivery workflows today, for example. So are concepts like continuous improvement and shift-left testing.
Yet despite all of the innovation that DevOps has ushered in over the past decade, there remains a core tension that hampers the ability of many teams to make the very most of continuous delivery. That tension results from the tendency of DevOps teams to prioritize delivery speed over visibility into the software delivery process.
To put this another way: The ability to deliver new application releases early and often has traditionally been seen as the ultimate measure of DevOps success. Understanding what actually happens during the delivery process and getting ahead of delivery chain issues that could snowball into major problems are not typically priorities.
To close this gap in the DevOps process, teams must invest as much effort into analyzing and measuring the software development life cycle across all its stages as they do into monitoring and managing the code that flows through that cycle. In other words, they must achieve full breadth of visibility into what happens as their code moves from development, through staging and testing, and finally into the cloud where it’s deployed. Depth of visibility into applications themselves is not enough to guarantee a positive end-user experience.
It’s only by understanding and optimizing their software delivery pipelines that developers can fully perfect the applications they deliver.
This article explains how to take a data-driven approach to analyzing and measuring the software development life cycle in order to achieve code-to-cloud visibility. In it, we’ll discuss why this oft-overlooked task is so critical for DevOps success by ensuring that delivering software quickly doesn’t mean sacrificing visibility into the delivery process. We’ll also identify the methodology and types of data that teams need to gain visibility into the software development life cycle, and explain which tools are available to address these needs.
The DevOps visibility gap
Again, DevOps has traditionally tended to prioritize software delivery velocity above all else. Almost in Machiavellian fashion, DevOps teams have assumed that as long as they deliver new releases quickly, they’re succeeding at DevOps. After all, increasing delivery velocity by improving communication between developers and IT operations is one of the foundational goals of DevOps.
This doesn’t mean DevOps teams only think about delivery velocity, of course. Most also test new releases to reduce the risk of performance problems in production. They think about which feature enhancements and bug fixes are most important for achieving continuous improvement, too.
Still, delivery velocity has tended to remain the core goal. If you’re not delivering fast, you’re not in a position to help your business keep up with the competition (or so DevOps engineers are told).
It’s true that delivery velocity is one important pillar of DevOps. The point of this article is absolutely not to tell DevOps teams to slow down. On the contrary, we want DevOps teams to deliver as quickly as possible.
In order to do that, however, teams need visibility into their complete software development life cycle. If they don’t understand the delivery process and lack visibility into its risks and shortcomings, they are unlikely to be able to sustain a continuous delivery operation for long. Velocity has a shelf life, and it expires quickly if the delivery pipeline bottlenecks in areas like the handoff of a new release from developers to the testing team, or from the DevOps team to the IT or SRE team.
Beyond just velocity, lack of visibility into the software development life cycle undercuts other DevOps principles, too. For example, it’s hard to “fail fast” and improve continuously when you lack the data about the software delivery process to pinpoint where you failed. No visibility means no learning, and hence no improvement.
To put this another way, DevOps suffers from a visibility gap. To date, teams have not tended to invest the same resources in software development life cycle visibility as they have into most other DevOps processes. And that creates a critical risk, because a team’s ability to sustain high velocity over the long term hinges on its ability to understand the life cycle that powers its speed.
Why DevOps needs code-to-cloud visibility
Code-to-cloud visibility means collecting and analyzing data from all stages of the software development life cycle — from development, staging and testing to deployment and production management — to gain visibility into what happens as code flows through the DevOps delivery pipeline.
This may seem obvious. DevOps teams certainly understand the importance of visibility in principle. They are also not lacking in the tools they need to collect data from different stages of the delivery chain.
Yet the challenge in achieving code-to-cloud visibility arises from the difficulty of actually integrating and sharing data that originates from different stages of the delivery chain, and that matters more to some stakeholders than others. It may be easy enough for developers to collect and analyze data about development operations, for example, and for IT engineers to study data about deployment operations. What’s much harder is integrating and correlating this data in a way that provides end-to-end visibility into the complete software development life cycle, exposing its strengths and weaknesses so that teams can maintain velocity and improve continuously over time.
Code-to-cloud visibility can also be difficult to implement in practice because it requires not just understanding the trends and patterns that define the software development life cycle, but also aligning them with business outcomes. How does a slow build process or a problematic handoff between development and testing impact revenue or customer churn rate, for example? That’s the type of question that DevOps teams need to answer to achieve total code-to-cloud visibility. It can be difficult for technical teams to devise a process that aligns technical data with business data in the way necessary to answer this type of question.
The three components of code-to-cloud visibility
Overcoming these challenges and achieving code-to-cloud visibility requires implementing three key domains of functionality across your software development life cycle. When combined, these types of functionality provide both the depth of insight and the breadth of visibility that teams need to understand what’s working and what’s not at all stages of the delivery chain.
Pipeline analytics provide broad visibility into the software delivery cycle by allowing DevOps teams to understand software delivery operations at all stages — from first code commits to deployment into the cloud (or wherever your application runs). They make it possible to track the flow of releases, understand where handoffs occur and where bottlenecks may develop, pinpoint the source of delays and so on.
In other words, pipeline analytics provides visibility into all aspects of CI/CD operations, establishing the foundation for correlating software delivery problems with other types of issues that may be exposed by code-to-cloud analysis.
Once code is deployed, teams need to understand what is happening within their applications as each release flows down the delivery pipeline. You can’t understand your pipeline, or correlate pipeline events with application performance and end-user experience, if you don’t understand what is happening inside your application.
This is where application testing and performance management come in. Through synthetic monitoring, analysis of real-user transactions, log analytics and metrics tracking, teams can understand the state of their code from development through deployment. This understanding offers the depth that teams need to gain visibility into the state of each release across the development life cycle.
Security, too, is a crucial component of code-to-cloud visibility. Teams must be able to secure code at all stages of the development life cycle. They must audit it during development, perform security tests and vulnerability scans during testing and deploy runtime security and security compliance enforcement to secure production applications.
Putting it all together with Splunk
The above are the three pillars of code-to-cloud visibility. They undergird a DevOps strategy that doesn’t sacrifice visibility in the name of velocity, and that avoids professing a commitment to continuous improvement without giving teams the data they actually need to improve continuously.
On their own, however, these individual pillars don’t deliver full visibility into the software development life cycle. To achieve that, teams must integrate the data they collect through these various sources, then analyze and measure it collectively in order to gain full context into software delivery issues, as well as align technical challenges with business challenges.
Splunk is your trusted partner for creating visibility across the entire software delivery chain. Splunk Cloud provides breadth of visibility with pipeline analytics, while Splunk’s Security Cloud helps teams secure the tool chain and applications in production. And the Splunk Observability Cloud gives operations teams the depth they need to support modern cloud applications. With Splunk, DevOps engineers, quality engineers, developers and SREs gain the visibility they need to understand what is happening inside applications as they move through the software development life cycle. At the same time, it provides security and operations teams the visibility necessary to analyze how observability data fits within the larger code-to-cloud picture by conveying all aspects of the infrastructure and software environments that power the delivery chain.
To learn more about how Splunk can help your team close the DevOps visibility gap and optimize your operations from the code through the cloud, check out this demo. Ready to achieve end-to-end visibility? Watch this demo and start your free trial of Splunk Observability Cloud today.