How Developers Use Observability Pipelines
In data management, numerous roles rely on and regularly use telemetry data.
The developer is one of these roles.
Developers are the creative masterminds behind the software applications and systems we use and enjoy today. From conception to finished product, they map out, build, test, and maintain software.
With the number of use cases around telemetry data (logs, metrics, traces) increasing, organizations need to understand how developers utilize it and what challenges they face while accessing it. It’s why Mezmo recently conducted research with The Harris Poll to better understand how they interact with observability data, the challenges they face when managing it at scale, and what their ideal solution might look like.
Meet your typical developer.
They love their job and, for the most part, have always been a developer and want to continue in this line of work. They prioritize advancing their skill and experience in terms of career goals and, above all else, have an innate desire and curiosity for solving complex problems, finding out how things work, and improving upon already existing practices, processes, and systems.
At a company, the developer is likely to be responsible for:
- Data Engineering: Developers design and build systems for collecting, managing, storing, and analyzing data at scale.
- Front-End Development: Developers design and create the graphical interfaces of client-side applications and websites.
- Back-End Development: Developers write and maintain code that communicates between an application or website’s database and the browser of the user interacting with it.
Developers regularly use observability data for numerous tasks, such as troubleshooting, debugging, and testing. However, that data comes from various applications and environments, on an average of 4 different sources. In addition, they are often shuffling between 3-4 different platforms to manage, access, and take action on that data.
Low Volume, High Value: The Developer’s Dream
For developers, the biggest issue they often encounter is the sheer volume of observability data they manage and paying the associated storage cost. This is mostly due to the fact that data sources are growing and they are heterogeneous in nature (such as containerized environments, for example). Not only does this data take time to gather and process, but you also have to remember that developers are dealing with roughly 3-4 application components at a given time, whether it's taking in data, pushing out data, or acting on any insights they may gain from the data.
Additionally, even though developers can generally predict how much they'll have to spend to manage, move, and store observability data, thinking about the cost of aggregating these large amounts of data in one place can be agonizing. Even if the cost is predictable, the reality is that their allocated budget simply can’t keep up with rising data volumes.
Fortunately for developers in today's digital landscape, observability pipelines exist.
The Ideal Observability Pipeline for the Developer
Observability pipelines can reduce the amount of management developers have to do with their data at the application level, ultimately enabling them to better control and derive value from it. By enabling developers to collect, transform, and route data to the right destination with the right context, developers can reduce spending on data, get more value from it and pay only for the data that they plan to use.
That said, the ideal observability pipeline for the developer would support these key things.
Collection of Data from Multiple Sources
The developer, in most cases, utilizes numerous products and software to help manage data for their organization, depending on what they're doing. An observability pipeline that can aggregate data from these various sources (for example, cloud services and applications) would reduce a lot of toil associated with collecting and managing it manually.
Additionally, the observability pipeline would support standard network protocols and popular formats in order to make the process of ingesting data as effortless as possible, allowing developers to point existing clients to new ingestion points by a simple config change as opposed to having to replace or rearchitect an entire agent deployment.
Data Transformation and Routing
One seldom mentioned aspect of data management, especially with respect to observability, is the ability to not only route the data, but to transform it as well. With traditional data management, it's often difficult for developers to make data consistent, especially with difference sources and formats. Having the ability to transform data into a more consistent and useful format is an incredibly helpful foundation for deriving cross-team data-driven insights.
Easy Integration Functionality
Developers and their teams often invest many resources in integrating their data with a provider. Having to go through that again because a pipeline solution doesn't support integration with the technology their team currently uses would require a lot of time, resources, and (more) manual management.
Mezmo Empowers the Developer
By helping collect, transform, and route observability data, Mezmo’s Observability Pipeline solution enables the developer to have the ability to manage high volumes of data and get insights in their platform of choice. With Mezmo, developers avoid spending time on complex integrations and hunting for the right data so they can spend more time creating solutions to high impact problems and less time looking for the information they need to do it.
Additionally, because you only pay for the data most valuable and have the option to store or process data in the right platforms, companies don’t have to worry about breaking the bank to enable their developers to do their job.
Tip: To learn more about the developer’s needs, priorities, and how they interact with other roles in an organization, like the security engineer and site reliability engineer (SRE), check out our latest white paper, The Impact of Observability: A Cross-Organizational Study.
With Observability Pipeline, you can:
- Access and control data to improve efficiency and reduce costs
- Aggregate and reduce observability data so that developers can leverage and see the information they need from one central location
- Transform your organization by empowering every team with the data they need