A guide to ClickHouse® upgrades and best practices

If you are using ClickHouse in a production environment, you have likely encountered a familiar dilemma: How do you stay current with new features and improvements without compromising stability?

In our first upgrade blog, we explored why regular ClickHouse upgrades are a non-negotiable part of a healthy data platform. We covered how the release model works, what the versioning tells us, and why staying up to date is critical for performance, security, and long-term support.

Now, in this second blog, we shift from the “why” to the “how.” We’ll provide a strategic framework to help you determine the ideal upgrade frequency based on your workload and operational priorities. Then, we’ll walk through a set of proven best practices to ensure your upgrade process is smooth, low-risk, and scalable.

In this blog, we’ll break down:

• When and how often to upgrade: Optimal frequency for upgrading the ClickHouse cluster
• Best practices for upgrades: Proven strategies for a seamless, low-risk upgrade process

When and how often to upgrade

Deciding when and how often to upgrade your ClickHouse cluster is crucial for maintaining optimal performance and stability. The right upgrade frequency depends not only on how your cluster is used, but also on your risk tolerance, the criticality of the workloads, and how fast your team wants to innovate.

To understand the timing of upgrades, it’s essential to first recognize that different workloads have fundamentally different upgrade needs. ClickHouse powers a wide range of environments: mission-critical business dashboards, event ingestion pipelines, real-time analytics applications, data warehousing solutions, and development sandboxes. Each of these carries different priorities—some need absolute stability, while others thrive on rapid iteration.

Let’s break down the ideal upgrade strategy for each type of environment.

When to use LTS (Long-Term Support) releases

ClickHouse’s Long-Term Support (LTS) releases are designed for environments where stability is paramount. These versions are curated for stability, with the team focusing on backporting only critical bug fixes and security patches.

They prioritize minimizing operational risk and provide a dependable foundation for long-term deployments. That’s why we offer every LTS release on Instaclustr for ClickHouse—our fully managed platform that ensures compatibility, reliability, and seamless upgrade paths.

If your primary concern is maintaining a stable and predictable production environment, LTS is the safest path forward—and Instaclustr for ClickHouse makes it even easier to adopt.

LTS releases are best suited for

• For critical production workloads: This category includes business intelligence dashboards, financial reporting systems, customer-facing analytics portals, and any environment with strict SLAs. These systems prioritize uptime, predictable behavior, and long-term consistency. Teams running such systems should plan an upgrade every six to twelve months. This approach balances the need for stability with a reasonable cadence that prevents you from falling too far behind. Upgrades should be thoroughly tested in a staging environment and rolled out incrementally to reduce risk. The goal is to maintain a predictable, low-risk lifecycle for your most important systems.
• For cold storage/data warehouse environment: Cold storage clusters, used for long-term retention or compliance, are another suitable workload. They ingest data infrequently and are queried only occasionally. For these systems, stability is everything, and the benefit of new features is minimal. These clusters can safely remain on a well-tested LTS version and may only need an upgrade every 12 months. The primary reason to upgrade here is to maintain compatibility with newer client tools or avoid being locked out of future migration paths.

When to use stable releases

Stable releases are published monthly and include the latest features, performance enhancements, and optimizations. They’re ideal for environments that prioritize rapid iteration, early access to new capabilities, and continuous improvement. These releases allow teams to experiment with cutting-edge functionality and respond quickly to evolving business needs.

However, because stable releases may introduce changes more frequently, they’re best suited for workloads with flexible SLAs and robust testing pipelines that can accommodate faster upgrade cycles.

Stable releases are a great fit for:

• Data science and machine learning: Data science and machine learning clusters are often used for generating training datasets or running exploratory queries. While they don’t have the same uptime demands as production dashboards, they greatly benefit from expressiveness and performance.The ClickHouse project frequently adds new SQL functions, improves joins, and enhances array and map handling. Staying reasonably current—within one or two months of the latest release—gives data scientists and ML engineers access to a richer query language and reduces the need for heavy data wrangling outside the database.
• For real-time ingestion pipelines: Workloads like high-frequency event ingestion or real-time analytics benefit immensely from ClickHouse’s frequent engine-level improvements. With each new stable version, ClickHouse introduces engine-level optimizations that improve merge performance, background task scheduling, disk I/O efficiency, and query execution paths. Updates to how parts are compacted, how joins are planned, or how mutations are processed can result in immediate, measurable performance gains—often without any changes to schema or queries.For such use cases, a more aggressive upgrade cadence of every 1–3 months is both practical and beneficial. It ensures you stay close to the latest improvements while keeping the testing and validation window manageable.

Best practices for upgrades

Upgrading ClickHouse is a bit like renovating a house while still living in it—you want to improve the structure without disrupting daily life. When executed properly, the upgrade process can be seamless, resulting in minimal or no downtime. However, if mishandled, it may lead to query failures, replication delays, or even data inconsistencies.

At NetApp, we have established a set of best practices that reduce risk and build confidence. These practices turn upgrades from a stressful and error-prone process into a routine operational task. These upgrades best practices can be broken down into three phases: Pre-upgrade, during-upgrade, and post-upgrade.

Phase 1: Pre-upgrade (planning and preparation)

The success of any upgrade is determined during the planning phase. This planning phase is where you identify risks, prepare backups, and ensure your team is ready for anything unexpected.

• Read the release notes: This step is critical and should never be skipped. ClickHouse evolves rapidly and typically maintains a one-year compatibility window, which includes support for two Long-Term Support (LTS) versions. However, some updates may introduce changes that affect query behavior, performance, or deprecate existing configuration parameters. It is therefore essential to carefully review the release notes for the target version, especially the section on backward incompatible changes, to proactively identify any potential issues such changes might cause with your current configuration.
• Complete testing in a staging environment: Never upgrade your production environment directly. Always test the upgrade in a staging environment first. Your staging environment should closely mirror production, replicating the same schema, data distribution, and representative query patterns. This setup allows you to run essential queries and ETL jobs against the new version to detect any regressions. It’s also an ideal place to test how your cluster will behave with mixed-version replicas during a rolling upgrade.
• Determine upgrade sequence: Identify the cluster topology and determine the upgrade sequence by examining the system tables for leader and non-leader replicas. Start the upgrade with non-leader replicas and upgrade the leader replica last to ensure minimal disruption. Document the sequence to coordinate the upgrade process effectively.
• Backup everything: Backups are your ultimate safety net. Before upgrading any node, take a complete and tested backup of both your data and metadata. Please note that testing the backup restore process beforehand is equally important to confirm its reliability.
• Rollback plan: Have a clear, documented rollback procedure in place to revert to the previous version if needed. This should include steps for restoring backups, reconfiguring services, and validating system integrity post-rollback. A well-prepared rollback plan helps minimise downtime and ensures business continuity in case of unexpected issues.

Phase 2: During upgrade (execution with care)

Once you’re confident in your preparation, it’s time to execute the upgrade. The guiding principles during this phase are isolation and observation which can be achieved by upgrading one node at a time and monitoring its behavior closely before starting an upgrade on the next.

• Use rolling upgrade method: In a replicated environment, always perform a rolling upgrade. Begin with a replica that is not actively serving production traffic (non-leader). Before initiating the upgrade, pause merges and fetches on that node to prevent it from processing new data while offline. This helps maintain cluster stability and avoids introducing inconsistencies during the upgrade process.
• Upgrade and monitor: Perform the upgrade cleanly. After restarting the node, monitor the logs closely for any startup errors. A successful restart doesn’t always mean the node is healthy; also pay attention to replication lag and queued fetches and merge activities.
• Repeat incrementally: Repeat this process for each node (replica by replica), one at a time, verifying its health before moving on. Avoid upgrading all nodes simultaneously. During the entire process, keep a real-time eye on your monitoring dashboards for any spikes in query error rates, replication lag, or resource utilization. Any unusual activity is a signal to pause the rollout and investigate.

Phase 3: Post-upgrade (validation and stabilization)

Once all nodes are running the new version, the upgrade process isn’t complete until the cluster is fully validated and stabilized. This phase ensures that the system is healthy, data is consistent, and performance aligns with expectations.

• Verify background merges and fetches: After the upgrade, resume and validate background merges and fetches that were paused prior to the upgrade. Depending on the duration of the upgrade, you may observe a temporary spike in merge activity, which is expected. However, it’s important to monitor system load closely to ensure that the increased activity does not negatively impact query latency or overall performance.
• Smoke test: Run your smoke tests—a set of quick targeted validation queries that cover the most critical parts of your workload. Successful execution provides baseline confidence that the system is functioning correctly.
• Review key system tables: Inspect system tables such as system.parts,system.replication_queue, and system.errors. Look for orphaned parts, stuck replication entries, or recurring errors that may have emerged post-upgrade.
• Apply configuration changes: If the new version introduces updated or additional configuration options, now is the time to apply them. Sometimes defaults change between versions, introducing opportunities for better performance or stability. Review your config.xml and users.xml against the new version’s defaults to identify and apply beneficial changes.
• Documentation: Finally, document what changed, any anomalies you observed, and the benefits of the upgrade for future reference. This documentation will be invaluable for future upgrades, helping make the process more predictable and less stressful.

How we help

At NetApp, through our managed offering Instaclustr for ClickHouse, we handle critical tasks across all phases of the upgrade process to ensure a smooth and successful experience:

Conclusion

The most effective approach is a planned, proactive upgrade strategy. Align your upgrade cadence with your workload’s needs, prepare thoroughly, execute methodically, and validate rigorously. Over time, upgrades will shift from being high-stakes events to becoming routine operational tasks to just another part of maintaining a healthy ClickHouse environment.

With Instaclustr for ClickHouse, we take care of the heavy lifting—striving to provide zero-downtime upgrades, proactive release analysis, and expert guidance tailored to your environment. Our platform is designed to ensure your upgrades are seamless, safe, and aligned with ClickHouse standards.