In the era of cloud-native development, as businesses rely on a growing number of software tools to enable agile application delivery, platform engineering has emerged as a crucial discipline for building the technology platforms that drive DevOps efficiency.
In this blog post, we explain the growing importance of platform engineering in high-performance DevOps organizations and how platform teams enable DevOps efficiency, agility, and productivity.
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Platform engineering refers to the practice of designing and building technology platforms that enable modern DevOps teams to efficiently deliver digital services and create better products for their customers. A platform is a collection of software and hardware components that provide a foundation for developers to build and deploy applications.
Platform teams are responsible for developing the architecture, toolchains, and processes that developers will use to ensure the platform is scalable, secure, and reliable. Platform engineers work to understand the needs of developers within the organization and provide an Internal Developer Platform (IDP) that helps drive developer efficiency. IDPs encompass a wide range of technologies, including cloud computing, cloud-native technologies like Kubernetes and Docker, CI/CD pipelines, and more.
A well-engineered IDP helps to increase developer productivity, reduce time to market, improve quality, and drive innovation by providing a solid foundation on which applications can be built.
Platform engineers enable self-service for app development teams by designing, building, and maintaining an IDP. The IDP provides a self-service environment where developers can build, deploy, and manage applications.
The goal of an IDP (and of platform engineers) is to enable developers to focus on building and delivering high-quality applications, rather than spending time on infrastructure setup and maintenance. IDPs have become increasingly popular in organizations that strive to improve the software development lifecycle and accelerate time to market for new releases.
In traditional software development workflows, developers were responsible for writing code, while operations teams were responsible for deploying and maintaining the infrastructure that runs that code. This led to siloed teams, slow release cycles, and a lack of communication and collaboration between developers and operations.
DevOps emerged in 2007-2008 as a response to these challenges, with the goal of breaking down silos and improving collaboration between teams. The big idea behind DevOps was that developers should be able (with the right tools and automation) to deploy and run their applications and services from end to end, including code management, continuous integration and delivery (CI/CD), testing, and monitoring.
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Around the same time, public cloud platforms were emerging in the form of AWS (launched in 2006) and GCP (launched in 2008). Cloud technology provided huge cost savings along with increased scalability and operability for DevOps teams, but it also increased the complexity of the toolchains and workflows used by developers to manage, test, and deliver code.
This increase in complexity made it unrealistic for most developer teams to implement True DevOps (all developers doing all DevOps tasks on their own), so instead they would give some senior developer(s) the tasks of managing environments and infrastructure while the rest of the team focused on delivering code. This creates a situation where the most valuable engineers spend much of their time on infrastructure management and are constantly busy helping junior engineers with DevOps tasks - a real misuse of expensive talent.
Platform engineering provides a real solution for enabling developer productivity in the era of complex cloud-native development. The State of DevOps Report from Puppet found a direct linear correlation between an organization’s level of DevOps evolution and its deployment of an internal platform engineering team building an IDP.
The most mature and successful DevOps organizations depend on internal platform engineers and the IDPs they deliver to enable and enhance developer efficiency.
The success of a platform engineering team depends on how well platform engineers understand the needs of the business and developers they support.
To create successful products, platform engineers must be aware of the tools and frameworks that developers are already using, as well as the challenges they face in their day-to-day work. This means collaborating with development teams to gather insights into their pain points, and then designing and building solutions that address those pain points.
IDPs provide a set of standardized tools and services that developers can use to build, test, and deploy applications. IDPs typically include services for configuration management, deployment, and observability, among others. By creating an internal developer platform, platform engineers can eliminate the need for developers to spend time configuring their own development environments and toolchains, allowing them to focus on writing code and delivering features.
IDPs help organizations maintain consistency across their software development teams, ensuring that all teams use the same tools and follow the same processes. This consistency can improve collaboration and communication between teams and reduce the time required to onboard new developers.
IDPs provide developers with self-service capabilities for managing the entire application life cycle. These capabilities often include:
Cloud Infrastructure orchestration is the process of automating the deployment, configuration, and management of infrastructure resources in cloud environments.
IDPs incorporate APIs and templates to describe infrastructure configurations and automate the creation and management of resources based on these configurations. This automation helps developers spend less time troubleshooting cloud services and infrastructure, and more time coding new releases.
IDPs provide role-based action management capabilities that allow DevOps managers to control which types of actions each user can perform within the system. For example, a developer might be authorized to deploy code to a testing environment, but not to a production environment.
By defining role-based action management policies, organizations can support collaboration between developers while limiting risk by ensuring that devs can perform only the actions necessary for their roles.
Application configuration management is the process of managing the configuration settings and parameters that are used by an application or system. Effective application configuration management involves identifying, documenting, and managing these configuration settings in a consistent and standardized way.
When it comes to streaming application configuration management, IDPs provide centralization, version control, environment-specific configurations, and self-service configuration updates. They also create an audit trail for configuration changes that supports security and compliance use cases.
An IDP helps automate and streamline code deployment by providing a standardized, self-service model for deploying applications. IDPs integrate with other tools and systems like CI/CD pipelines, so developers can move their code through the pipeline and deploy into production without intervention from IT Ops.
Application observability software tools are commonly integrated into the DevOps toolchain by platform engineers. Observability tools allow developers to efficiently monitor the performance of applications in production and testing environments, troubleshoot cloud services, and make informed decisions on how to improve their applications.
The 2023 State of Platform Engineering Report from Puppet identified seven of the top capabilities provided by platform engineers via self-service IDPs.
IDPs provide a standardized set of tools, processes, and best practices for developers to follow when building, testing, and deploying code. As a result, developers can spend time on things other than figuring out how to set up their own environments, which tools to use, or how to deploy their applications. This reduces the time developers spend on administrative tasks and allows them to focus more on writing code and delivering features.
IDPs can also automate many of the repetitive tasks involved in software development, such as building, testing, and deploying code. Automation can save developers a significant amount of time and reduce the risk of errors that can arise from manual processes.
The ChaosSearch Cloud Data Platform is a key component for enabling a best-of-breed approach to DevOps observability so developers can efficiently troubleshoot cloud services and monitor application performance in a self-service model.
Developers using ChaosSearch start by capturing and aggregating application logs in cost-effective Amazon S3 or GCP cloud object storage.
Once those application logs land in S3 or GCP, ChaosSearch indexes the logs to create a representation that's fully searchable with up to 20x file compression.
From there, developers can use our Chaos Refinery® and built-in Kibana Open Distro to analyze log data, create visualizations, and build custom dashboards that reveal insight into application performance - all directly in Amazon S3 or GCP with no data movement or duplication.
By integrating ChaosSearch into their IDP toolchains and software development workflows, platform teams can fulfill their mission of facilitating DevOps excellence within their organizations.
Start a free trial of ChaosSearch and experience exceptional application performance monitoring and observability.