Transform Your DevOps with Log Management and Observability Development
Log management and observability can change how you think about DevOps challenges.
Colin Fallwell of Sumo Logic highlights how tasks like log analysis have become more complicated, making log aggregation almost mandatory. Disparate systems and data must be accurately correlated, and gaining uniformity across the CI/CD process and toolchains is critical.
For DevOps professionals, the speed and complexity of change can be overwhelming. Systems are deeper than ever, yet business leaders demand faster time to market and foolproof security from their applications. Sumo Logic’s site reliability engineering (SRE) pulse survey helps articulate these concerns.
According to the survey, DevOps professionals are focused on reliability and security, including reducing the risk of service failure and unplanned downtime (68%), improving competitive readiness with reliable services and offerings (65%), and ensuring business partner satisfaction by reducing the frequency and severity of incidents (59%).
While rapidly evolving technologies and skills gaps can keep developers from achieving these goals, another issue — a lack of process and rigor in the CI/CD process — may be equally to blame.
Measuring Performance with Capability of Process
Luckily there’s a way to evaluate how well your process is performing. With roots in early 20th-century automation, capability of process (CP) measures how a process performs in terms of accuracy, precision, and stability. CP users establish high and low-performance thresholds for their process, in effect creating a ‘performance corridor.’ The aim is to keep the process functioning reliably within that corridor.
For developers, that means establishing multiple criteria and collecting the data necessary to measure performance over time. CP requires good data quality and a high data sampling rate to gain statistical deviations by normalizing data to see where deviations are occurring.
This approach may sound familiar. Modern service level management, with SLOs, burn downs, managing to the nines, etc., is built on similar concepts. With CP, developers can evaluate code performance and use performance deviations to isolate and address issues quickly.
Characteristics of Organizations with High-quality Processes
Competitive, best-in-class organizations use CP to respond quickly to changes and new opportunities. From a DevOps perspective, they are often ‘chaos engineers,’ intentionally breaking things to learn how to respond to and recover from failures with agility.
Organizations with high-capability processes in DevOps have common characteristics and share several best practices. These include:
- DevSecOps and business analysis are intelligent, continuous, immutable, and real-time.
- Common instrumentation libraries are used across the organization – metadata is consistent and declarative.
- CI, telemetry, and communication pipelines are autonomous, consistent, and declarative.
- Observability is cleanly annotated, and instrumentation is done with domain/aspect-oriented programming.
- Metrics for monitoring health and performance are declarative.
- Dashboards, alerts, and alert thresholds are declarative and deployed with each merge.
The Benefits of Observability-driven Development
The ultimate goal as a developer is to be able to go straight from laptop to production and leverage the production environment for testing. This ability to move fast and innovate separates elite industry performers from the rest of the pack. One approach that industry leaders commonly use is Observability-Driven Development (ODD).
ODD emphasizes building systems with high observability. In the context of software development, ODD focuses on designing and building systems that are easily monitored, debugged, and diagnosed. It involves instrumenting code and infrastructure to generate meaningful and actionable telemetry data used to gain insights into system behavior, identify issues, and drive improvements. ODD offers many benefits, including:
- Rapid Troubleshooting: High observability enables developers to identify and diagnose production system issues quickly. By analyzing real-time telemetry, developers can gain deep visibility into the system’s behavior and pinpoint the root causes of the problems.
- Performance Optimization: ODD helps DevOps teams identify performance bottlenecks and optimize system behavior by fine-tuning code, optimizing algorithms, and improving overall system efficiency.
- Continuous Improvement: Monitoring and analyzing system behavior facilitates rapid experimentation, hypothesis testing, and the incorporation of user feedback — all in aid of driving ongoing refinements and system evolution.
The Importance of Log Management
Another valuable tool for DevOps teams is log management. Logging tracks every action or event that takes place within the software, applications, and IT infrastructures. An effective log management system provides analysts with a single place to compile and store all logs from across the entire environment.
Log management helps stakeholders troubleshoot issues, capture useful insights, and offers many other benefits, including:
- Expediting applications and infrastructure health checks: A centralized log management system reduces the time and effort required to sort logs and identify potential errors. Log management best practices can also allow analysts to proactively monitor for potential problems before they arise.
- Ensuring an exceptional customer digital experience: Reviewing data on the reliability and performance of your applications provides insights into user experience and helps resolve issues before they impact users.
- Providing insights into a security breach: By compiling all logs in a central location, log management makes it easier to monitor for security breaches and can help speed remediation.
- Maintaining policy compliance: Organizations with cybersecurity, privacy, financial recording, or reporting guidelines can use log management to document and demonstrate compliance.
The Value of Failure (Why It’s Good To Break Things)
Ask a group of developers how often they (intentionally) break their environments, and you might get some strange looks. However, there’s tremendous value in pushing your applications and environments to failure.
NASA engineers know this well. Every rocket component is tested repeatedly until it breaks, allowing NASA engineers to recognize failure and affect necessary improvements. Then they break things again, repeating the cycle.
Savvy developers take the same approach to determine the limits of their solutions. How much can it handle? When should you scale out, and what are the downstream dependencies?
Pushing to failure is a reliable means of establishing performance limits. While it’s safer for developers than test pilots, the idea is the same.
Driving Elite DevOps Performance
Building a high-performance DevOps team often means breaking away from established norms. Taking a radical approach to a new project or line of business is challenging and requires executive sponsorship. Developers must educate C-level sponsors on how ‘moving fast and breaking things’ can reduce risk rather than increase it. And ultimately, they must also demonstrate how this new paradigm will benefit the business’s bottom line.
To succeed, stakeholders need to establish firm ground rules upfront. These will help inform decision-making and keep everyone on the same page. Examples may include:
- Standardize project types and have only one way to test and ship come for each type.
- Automate all steps in the PR and merge processes.
- Test on every commit.
- Build artifacts often. Code should be built as often as it’s tested and deployable at any time.
- Maximize portability and be environment-agnostic.
- Gather consistent feedback and shorten feedback loops.
- Use well-tested code that is stored in version control and can be easily changed or developed at any time.
Count on Even More Change
From the widespread adoption of AI to the low code/no code movement and advanced security threats, the pace and complexity of change are only increasing. To improve performance and avoid burnout, developers should focus on performance measurement, employ proven, high-quality processes across all initiatives, and embrace a ‘break it to make it better’ approach.
What DevOps challenges can smarter log management and observability help address for your business? Share with us on Facebook, X, and LinkedIn. We’d love to hear from you!
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