Multi-Cluster Observability Part 3: Practical Tips for Operational Success

Andreas PrinsCEO
7 min read

This is the final article of a three-part series. To start at the beginning, read Part 1: Benefiting from multi-cluster setups requires familiarity with common variations and Part 2: Exploring the facets of a multi-cluster observability strategy.

As companies scale software production, they lean on Kubernetes as a crucial container orchestration platform for managing, deploying and ensuring software availability. But Kubernetes can get tricky and hard-to-detect issues can cause overarching problems like service disruptions. full-blown outages and unexpected costs - especially if you're working with more than one cluster. That's why there's a real need for better observability in managing multi-cluster systems.

Seven steps to a better multi-cluster observability approach

Executing a multi-cluster observability strategy demands meticulous planning and execution, from defining your needs to continuous improvement. Throughout the process, it's important to maintain clear communication, align with business goals and focus on creating value through enhanced visibility and insights into your multi-cluster environment. 

Follow the best practices in this guide for a smooth rollout, to turn your observability vision into a successful operational reality.

STEP 1: Definition of Need

Assess the current and future requirements of your systems. This involves understanding the scale, complexity and specific needs of your applications and infrastructure. Remember to determine why multi-cluster observability is necessary – for instance, for scalability, reliability or compliance reasons. This step should conclude with a clear understanding of what you need from an observability solution.

STEP 2: Determine Stakeholders, Take Developer Experience into Account

Identify all stakeholders involved in the observability process, including IT operations, developers, security teams and business leadership. Understand their needs and pain points. Developer experience is critical, so you’ll want to be certain that the solution you decide on eases their workflow, integrates into their development lifecycle and provides them with actionable insights. This step aims to create a solution that balances technical and business requirements and is user-friendly for all involved parties.

STEP 3: Tool Selection

Based on the defined needs and stakeholder input, choose the right set of tools for monitoring, logging, tracing and analytics. Consider factors like scalability, ease of integration, support for multi-cluster environments and the ability to handle the complexity of your setup. This might involve comparing different products, conducting proof-of-concept tests and negotiating with vendors.

STEP 4: Implementation and Configuration

Once tools are selected, proceed with implementation. This includes setting up the infrastructure, installing software and configuring the tools across your clusters. It should be done in a way that results in minimal disruption to existing workflows. The configuration should reflect the unique aspects of each cluster while maintaining a standardized approach across the environment.

STEP 5: Onboarding Teams

Start with a pilot program involving one or two teams and provide comprehensive training and support throughout. Then, gather feedback to understand the user experience and any issues that might have been encountered. The goal here is to validate the setup in a controlled environment before a full-scale rollout.

STEP 6: Roll Out

Gradually expand the observability solution across the organization. This should be done in phases — each involving more teams and clusters — to manage the change effectively. Continue providing training and support during this process and monitor the rollout closely to address any issues as soon as they arise.

STEP 7: Continuous Improvement

Observability is not a set-it-and-forget-it solution. You’ll want to regularly review and update your strategy based on new technological advancements, the organization’s evolving needs and user input. This involves encouraging a culture of feedback, refining your toolset, updating configurations and continuously adjusting the user experience.

Top capabilities needed to deliver optimal multi-cluster observability

In this final section of our 3-part blog series, we spotlight StackState's capabilities in delivering high-quality, easy-to-use, out-of-the-box multi-cluster observability. As you read on, you’ll see how each StackState feature — our expansive topology map, centralized metrics store, continuous health monitors and more — aligns with the core challenges and strategies of multi-cluster observability and ensures that your organization is equipped with the tools needed for effective and efficient system monitoring and management.

Here are the StackState features that will revolutionize your approach to observability.

Extensive Topology Mapping: StackState’s topology map visualizes dependencies between components across clusters, aiding in understanding system-wide interactions and aligning with the need for a unified view. Crucial during the implementation and configuration phases, topology mapping allows teams to see how components interconnect without additional code instrumentation. It addresses the challenge of complexity in integration and management by providing a clear, comprehensive visual of your system's architecture.

Metrics Store: Consistent monitoring and logging is crucial, and a centralized metrics store plays a vital role in achieving this. StackState addresses this need by consolidating metrics from all clusters into a single repository. This not only maintains a uniform data format and accessibility but also supports the roll-out phase by providing a unified data source for all teams. In addition, it expertly handles challenges related to data volume and overload and results in effective storage and management of large amounts of data.

Set of Monitors: To maintain system integrity, continuous health checks of components and applications are essential. StackState's monitors play a key role in this by facilitating ongoing health assessment, aligning seamlessly with the continuous improvement step. This feature not only ensures the scalability of observability tools but also provides scalable monitoring capabilities across all clusters.

Remediation Guides: Remediation guides infused with expert knowledge prove invaluable during the onboarding of initial teams and the continuous improvement phase alike. These guides equip teams with essential information to effectively address issues and promote general adherence to best practices. In doing so, they successfully tackle the skillset and training challenges by providing teams with expert guidance.

Alerting Possibilities: Integrating tools such as Teams, Slack, OpsGenie and PagerDuty for alerting is crucial for timely communication. Especially in the roll-out phase, this guarantees prompt notification of issues to all teams. This integration effectively addresses the challenge of alerting and anomaly detection, making sure alerts are both meaningful and actionable.

End-to-End Chain Visualization: Understanding the full scope of what is running where, especially during complex outages, is beyond important. This contributes to a unified view, offering detailed visibility during both implementation and incident management. By providing clear visibility into the interactions of components across clusters, it addresses network complexity and latency challenges effectively and efficiently.

Extensive Filtering: The ability to slice and dice information as needed is a key feature for managing large volumes of data. StackState’s extensive filtering capabilities align with the granularity and data sifting needs of a modern observability strategy, which is really important during onboarding as well as during the continuous improvement phase. Filtering directly addresses the challenge of handling data volume and making certain that meaningful insights can be drawn from the data.

Fine-Grained RBAC (Role-Based Access Control): Having a robust RBAC is essential for maintaining data security and compliance. It ensures that different teams access only permitted data, a necessity during the roll-out and continuous improvement phases in a multi-cluster environment — and especially important in regard to the distinctions in security and compliance regulations across industries and geographical regions.

Take a test drive with better observability

If your development and deployment rely on multiple clusters, StackState observability is your key to enhancing organizational value. With StackState, you can optimize expenses and drastically cut down developer time by consolidating and correlating all monitored data into a single, user-friendly solution—a comprehensive observability platform providing expertly guided cross-team clarity.

To get the most out of StackState, take us for a test drive. Or use your own data (or ours) when you try us out in our playground!