Revamp root cause analysis in four steps
During significant systems downtime or performance challenges, IT teams respond promptly to restore services. Certain IT organizations adhere to IT service management (ITSM) incident management practices for service restoration, followed by problem management procedures for conducting root cause analysis (RCA). Advanced organizations may integrate site reliability engineers (SREs) into incident and problem management, prioritizing proactive measures to reduce error rates and enhance service level objectives.
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Although much attention within IT operations centers on major incidents such as outages, disruptive performance issues, and security breaches, identifying the root cause of sporadic, elusive issues presents a notable challenge. These issues occur infrequently, affecting a limited user subset or enduring for brief periods. Nevertheless, they can severely impact business operations if they arise during critical tasks performed by key end users. Identifying the underlying reason for intermittent performance problems.
Having worked as a developer earlier in my career and later transitioning to the role of a CIO, I've encountered numerous elusive issues, making pinpointing the root cause both time-consuming and prone to errors.
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Occasionally, the difficulty lies in sifting through excessive data to identify the root cause, a challenge that AIops platforms can assist in resolving. Alternatively, there are instances where essential data is missing, data quality is compromised, or datasets require integration. According to Geoff Hixon, VP of solutions engineering at Lakeside Software, "Resolving application performance issues isn't always straightforward, particularly when there are gaps in data that can obscure the true root cause.
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Instructions on conducting root cause analysis (RCA).
A process is required that SREs, developers, and IT operational engineers can utilize to conduct RCA for challenging issues. I suggest four steps:
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1. Organize observability as a product.
2. Implement both top-down and bottom-up analysis.
3. Evaluate if the issue pertains to the network.
4. Foster collaboration and triangulation in identifying root causes.
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STEP 1:- Organize observability as a product.
In my book, "Digital Trailblazer," I share various anecdotes about addressing performance issues through observability. "It's common for individuals to pursue the wrong leads, and observability data should serve as a guide for teams to focus on the most critical areas."
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An established DevOps practice involves enhancing the observability of microservices, data pipelines, applications, and other internally developed software. Many organizations struggle with establishing and enhancing data standards to ensure consistency, thereby facilitating ease of use during root cause analysis (RCA).
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Nick Heudecker, senior director of market strategy and competitive intelligence at Cribl, suggests taking standardization a step further by treating application logs as a consumable data product for IT operations. "The key to identifying application performance issues lies in ensuring that telemetry from applications is usable by downstream systems. This entails structuring logs, enriching them with relevant context, and delivering them to appropriate platforms. While it may seem straightforward, developers who generate the logs often differ from those who utilize them in operations."
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Standardizing observability data streamlines its utilization for operational requirements, serving as a means to simplify observability. Additional DevOps best practices for observability include collaborating with risk management on sensitive data and data retention policies. DevOps teams should also educate Site Reliability Engineers (SREs) and personnel in Network and Security Operations Centers (NOCs and SOCs) to bridge the gap between software functionality and the representation of observability data in log files and other repositories.
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For large organizations developing numerous applications and microservices, observability standards should be complemented with automation, analytics tools, and models to facilitate root cause analysis.
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"Asaf Yigal, co-founder and CTO of Logz.io, emphasizes the importance of transitioning towards a targeted, real-time data analysis approach in observability practices within companies. This empowers engineers to proactively interrogate data and gain insights necessary to resolve complex application performance issues. To address critical performance issues in modern microservice-heavy systems, a more efficient solution is required, one that utilizes automation for data analysis, enabling proactive responses rather than reactive ones."
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Maintaining a continuous improvement mindset and adopting an incremental release strategy for observability standards is crucial. As NOCs, SOCs, and SREs encounter new challenges, DevOps teams should leverage feedback to refine data collection methodologies.
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STEP2:- Implement both top-down and bottom-up analysis.
Identifying a slow query using basic database logfiles is relatively straightforward. However, pinpointing root causes becomes more intricate when query performance deteriorates only under database load and when multiple queries vie for the same system resources.
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Grant Fritchey, a devops advocate at Redgate Software, illustrates this with an example of a query that initially appeared fast, averaging about 6ms. "While it may seem insignificant from a performance measurement perspective, upon examining the execution counts, it became evident that the query was being called thousands of times per minute. Even with a 6ms execution time, it wasn't sufficiently fast. This emphasizes the importance of integrating observability and database monitoring tools to gain a comprehensive and nuanced understanding of system performance."
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Effective root cause analysis (RCA) necessitates monitoring tools that extend beyond basic alerting for outages or major performance issues. Operations teams and Site Reliability Engineers (SREs) require indicators for performance deviations from the norm and tools for conducting top-down analytics to delve into suspicious transactions and activities. These tools should also aid in identifying performance outliers, particularly for high-volume and underperforming activities. Advanced tools further facilitate the isolation of end-user experiences, enabling operations teams to conduct RCA for specific user-reported issues, such as those initiated by customer support calls.
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STEP 3:- Evaluate if the issue pertains to the network.
DevOps teams often default to attributing performance issues to network and infrastructure problems, especially if these areas fall under the jurisdiction of a vendor or another department. This knee-jerk reaction posed a significant challenge until organizations embraced DevOps culture and acknowledged that agility and operational resilience are collective responsibilities.
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Nicolas Vibert of Isovalent notes, "The network is frequently blamed for application performance issues, yet proving its culpability is exceedingly difficult. The advent of cloud-native technologies and the intricate layers of network virtualization resulting from containerization further complicate efforts to establish the network as the root cause."
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The task of identifying and resolving complex network issues becomes even more daunting when constructing microservices, applications interfacing with third-party systems, IoT data streams, and other real-time distributed systems. This complexity underscores the necessity for IT operations to effectively monitor networks, correlate them with application performance issues, and streamline network root cause analyses.
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Eileen Haggerty, AVP of Product and Solutions Marketing at NETSCOUT, emphasizes the importance of integrated packet monitoring across virtualized environments for both north-south and east-west traffic paths. "Consistent, real-time insights into traffic and application performance are provided through such integration. Regardless of the hosting environment, every domain and location must have uniform analytics, intelligence, and visibility levels. A standardized measurement approach across all hosting environments facilitates swifter determination of the root cause and location of performance issues for applications across any network infrastructure.
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STEP 4:- Foster collaboration and triangulation in identifying root causes.
Two additional recommendations revolve around team collaboration in resolving incidents and conducting root cause analysis (RCA). I've overseen numerous bridge calls and coordination efforts aimed at identifying and rectifying issues, which are often unavoidable during significant outages. However, these methods prove less effective when addressing sporadic performance issues requiring the correlation of data from various tools and observability sources. Such challenges often necessitate the collaboration of multidisciplinary teams to efficiently share knowledge and work together when conducting RCA.
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Chris Hendrich, Associate CTO at SADA, observes, "In many larger and well-established organizations, I've noticed a significant lack of application documentation and limited inter-team communication. Breaking down these fragmented silos can enhance companies' ability to conduct root cause analysis."
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The second recommendation pertains to the approach teams take in searching for root causes. According to Fong-Jones of Honeycomb, "Rather than directly diving into the needle in the haystack, it's essential to methodically narrow down segments of the haystack where the needle may or may not be present until it's located. Tools can aid in generating inquiries that assist in filtering the haystack."
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Every IT organization encounters performance issues that prove challenging to resolve. Teams that foster collaboration, exchange information, establish observability standards, and cultivate expertise in utilizing monitoring tools can alleviate stress, reduce time requirements, and enhance the accuracy of their RCA processes.
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Conclusion
In conclusion, effective incident resolution and root cause analysis are essential components of modern IT operations. By fostering collaboration among diverse teams and refining approaches to identifying root causes, organizations can improve their ability to address both major outages and sporadic performance issues. Breaking down silos and promoting open communication facilitate the sharing of knowledge and expertise, leading to more thorough and efficient RCAs. Additionally, adopting strategic methods for root cause identification, supported by advanced tools and techniques, enables organizations to streamline problem-solving processes and enhance overall operational resilience. Ultimately, prioritizing collaboration, communication, and methodical analysis empowers organizations to mitigate downtime, optimize performance, and drive continuous improvement in their IT environments.