With DevOps gaining traction, development and operations teams have started collaborating more regularly. Observability, or the ability to monitor and understand a system's behavior, is a new approach to manage data and application code.
From infrastructure as code to observability as code
The recent surge in infrastructure as code (IaC) adoption has revolutionized how organizations manage and operate infrastructure. IaC manages and provisions infrastructure -- VMs, networks and load balancers -- with code instead of manually, which simplifies the configuration process.
By codifying infrastructure in a version control system, development teams can collaborate and communicate more effectively. However, infrastructure will not operate as intended with IaC alone. Enter observability as code.
With observability as code, IT ops teams can codify their observability workflows in the same manner they codify their infrastructure. Doing so enables IT ops teams to monitor, troubleshoot, detect and respond to problems.
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What is observability as code?
Observability as code is the practice of using code to automate the creation and management of observability infrastructure. This includes everything from setting up alerts to creating dashboards and visualizations.
Observability as code is an approach to managing observability data and configuration with the same tools and processes used for development and testing. It is a new approach that treats observability configuration and data collection as code, which can be checked in to version control.
Why observability as code?
This approach has several benefits:
- Enabling IT ops teams to manage observability data and configuration the same way they manage code. This makes tracking changes easier and ensures observability data is up to date.
- Making it easier to share observability data and configuration between teams. This helps to ensure everyone is using the same data and configuration, and makes it easier to debug problems.
- Helping to automate the process to set up and maintain observability data and configuration. This can save time and reduce the chance of errors.
- Helping IT ops teams use the application to generate telemetry data to determine how an application has been performing in real time through logging, monitoring and tracing.
The need for enhanced observability in the enterprise
In today's fast-paced business world, enterprises must respond rapidly to changes in their environment to maintain a competitive advantage. Organizations need access to timely and accurate information about what is happening within their systems.
While traditional monitoring tools provide some level of observability, they often fail to provide the detail necessary to troubleshoot complex issues. Many enterprises are turning to observability as code because it enables them to instrument their systems more effectively and gain greater visibility into their operations.
Code-based observability software and platforms offer many benefits over traditional monitoring tools, such as the ability to do the following:
- Monitor systems more effectively. Code-based observability provides granular visibility into every aspect of the system, enabling effective monitoring and problem diagnosis.
- Scale quickly and easily. Code-based observability tools deploy quickly and scale to meet the enterprise's needs.
- Reduce costs. Code-based observability reduces the need to monitor hardware and software, saving the enterprise money.
Observability in the cloud operating model
The cloud operating model automates cloud-based resource provisioning, monitoring and management. Observability must be built into the fabric of the cloud operating model to detect and remediate issues promptly.
By codifying observability into the cloud operating model, organizations access the many benefits of DevOps practices, such as increased agility and faster market time.
Use an infrastructure as code management tool, such as Terraform, Pulumi or CloudFormation, to manage observability infrastructure provisioning. An IaC tool automates the entire process and enables IT pros to track changes over time. Configuration management tools, such as Puppet or Ansible, provide better control over the individual components that make up the observability infrastructure.
In addition, codify the observability infrastructure for easy management and maintenance. This helps IT ops teams take full advantage of a cloud operating model's benefits.
Requirements for a modern observability platform
With an observability platform in place, IT ops teams can detect and diagnose issues in real time, identify trends and potential problems before they become critical, and make informed decisions.
However, organizations must consider several factors when building an observability platform, such as these five essential requirements:
- Scalability. As a system grows, so must the observability platform. It should handle the increased load without sacrificing performance or accuracy.
- Flexibility. The platform should adapt as needs change. Whether IT ops teams want to add new data sources or change how data is processed, the platform should accommodate any necessary changes.
- Visibility. An observability platform must provide visibility into all aspects of an IT ecosystem to be truly effective. This means everything from code changes to application and infrastructure performance.
- Alert mechanisms. These should include alerting mechanisms for memory faults or CPU consumption, such as configuration errors and networking issues, as well as configure data retention periods.
- Integration. Integration with popular tools for debugging and analysis, such as Node.js, Docker and Prometheus, is essential. An observability platform should provide built-in compatibility with these tools.
The current observability landscape
The rise of microservices and distributed systems has made it critical to monitor and debug complex systems. Observability as code enables IT ops teams to use the development and testing tools and processes already in use to manage observability data and configuration. This is a massive shift from the traditional observability approach, which has been a primarily manual process. In addition, the current ecosystem of Kubernetes observability tools is growing, with numerous competing projects.
Observability as code is a new approach to monitor and log modern distributed systems. By treating monitoring and logging configuration as code, IT ops teams can manage it the same way they manage application code. This also enables organizations to use the same tools, processes and practices to manage the observability configuration that they already use for application code.