supabase High CPU Usage

The CPU usage has exceeded the defined threshold, indicating potential over-utilization of server resources.

Understanding Supabase and Its Purpose

Supabase is an open-source backend-as-a-service (BaaS) platform that provides developers with a suite of tools to build and scale applications quickly. It offers features like a real-time database, authentication, storage, and auto-generated APIs, all built on top of PostgreSQL. Supabase aims to simplify the development process by providing a seamless integration of these services, allowing developers to focus on building their applications without worrying about the backend infrastructure.

Symptom: High CPU Usage Alert

In a Supabase environment, you might encounter a Prometheus alert indicating High CPU Usage. This alert is triggered when the CPU usage of your server exceeds a predefined threshold, suggesting that the server is under heavy load and may not be able to handle additional requests efficiently.

Details About the High CPU Usage Alert

The High CPU Usage alert is a critical indicator that your server resources are being over-utilized. This can lead to slower response times, increased latency, and even downtime if not addressed promptly. The alert is typically configured in Prometheus to monitor CPU metrics and trigger when usage surpasses a certain percentage over a specified period. This ensures that you are notified before the situation becomes critical.

Potential Causes of High CPU Usage

Intensive queries or operations running on the database.
Suboptimal indexing or missing indexes in the database.
High traffic or unexpected spikes in user activity.
Background processes consuming excessive resources.

Steps to Fix the High CPU Usage Alert

1. Investigate Running Processes

Start by identifying the processes consuming the most CPU resources. You can use tools like htop or top on your server to get a real-time view of CPU usage. Look for any processes that are using an unusually high amount of CPU and investigate further.

2. Optimize Database Queries

Review the queries running on your database. Use the PostgreSQL EXPLAIN command to analyze query execution plans and identify any inefficiencies. Consider adding indexes to speed up query execution. For more information on optimizing PostgreSQL queries, refer to the PostgreSQL Performance Tips.

3. Scale Up Server Resources

If the CPU usage remains high despite optimization efforts, it may be necessary to scale up your server resources. Consider upgrading your server to a higher tier with more CPU capacity. Supabase provides options for scaling resources based on your needs. Check the Supabase Scaling Guide for detailed instructions.

4. Monitor and Adjust Alert Thresholds

Ensure that your Prometheus alert thresholds are set appropriately. If your application experiences regular spikes in CPU usage, you may need to adjust the thresholds to reduce false positives. Refer to the Prometheus Alertmanager Documentation for guidance on configuring alerts.

Conclusion

Addressing high CPU usage in a Supabase environment requires a combination of monitoring, optimization, and scaling. By following the steps outlined above, you can effectively diagnose and resolve high CPU usage alerts, ensuring that your application remains responsive and performant.

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supabase High Load Average

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supabase High Network Traffic

Unusually high network traffic, which may indicate a DDoS attack or misconfigured services.

supabase Backup Failure

Scheduled backups have failed, risking data loss in case of system failures.

supabase High Latency

Increased response times for requests, which may impact user experience.

supabase Unauthorized Access Attempts

Multiple failed login attempts detected, indicating potential security threats.

supabase Pod CrashLoopBackOff

A pod is repeatedly crashing and restarting, indicating issues with the application or configuration.

supabase Certificate Expiry

SSL/TLS certificates are nearing expiration, risking secure communication failures.

supabase Node Not Ready

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The memory consumption has surpassed the set limit, which may lead to performance degradation.

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The available disk space is below the acceptable threshold, risking data write failures.

supabase High CPU Usage

The CPU usage has exceeded the defined threshold, indicating potential over-utilization of server resources.

supabase Database Connection Errors

Frequent connection errors to the database, possibly due to network issues or misconfigurations.

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supabase Slow Query Response

Queries are taking longer than expected to execute, affecting application performance.

OpenSearch Index Recovery Failure

An index recovery operation has failed, potentially due to resource constraints or configuration issues.

OpenSearch Cluster Node Joined

A new node has joined the cluster, potentially affecting cluster balance.

OpenSearch Index Read-Only Mode

An index has been set to read-only mode due to disk space issues.

OpenSearch Node Heap Dump Generated

A heap dump has been generated, indicating potential memory issues.

OpenSearch Cluster Node Left

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Network latency between nodes is higher than expected, impacting cluster performance.

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OpenSearch Cluster State Update Failure

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OpenSearch Node Disk I/O High

Disk I/O operations on a node are consistently high, impacting performance.

OpenSearch Indexing Throughput Low

The rate of indexing operations is lower than expected.

OpenSearch Search Throughput Low

The rate of search operations is lower than expected.

OpenSearch Node JVM Heap Pressure High

The JVM heap pressure on a node is consistently high, indicating potential memory issues.

OpenSearch Cluster Node Count Low

The number of nodes in the cluster is below the expected count.

OpenSearch Snapshot Failure

A snapshot operation has failed, potentially due to storage issues or configuration errors.

OpenSearch Node Disk Watermark Exceeded

Disk usage on a node has exceeded the high watermark threshold.

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One or more index shards have grown larger than the recommended size.

OpenSearch Snapshot Duration High

Snapshot operations are taking longer than expected to complete.

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OpenSearch Pending Tasks High

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OpenSearch Cluster Shard Allocation Failure

The cluster is unable to allocate shards due to resource constraints or configuration issues.

OpenSearch Search Latency High

Search queries are taking longer than expected to complete.

OpenSearch Indexing Latency High

Indexing operations are taking longer than expected.

OpenSearch Frequent Garbage Collection

Frequent garbage collection events are occurring, impacting performance.

OpenSearch High JVM Heap Usage

The JVM heap usage is consistently high, leading to potential garbage collection issues.

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An OpenSearch node is not reachable or has been removed from the cluster.

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ClickHouse ClickHouseHighZooKeeperNodeCount

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ClickHouse ClickHouseHighZooKeeperSessionCount

The number of ZooKeeper sessions is too high, potentially overloading the ZooKeeper cluster.

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A high number of errors are occurring in requests to ZooKeeper, disrupting coordination.

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ClickHouse ClickHouseHighNetworkErrors

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ClickHouse ClickHouseInsertFailureRateHigh

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Background merge operations are failing, which can lead to performance issues.

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ClickHouse ClickHouseZooKeeperSessionExpired

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Write operations are experiencing high latency, which can delay data ingestion.

ClickHouse ClickHouseHighReadLatency

Read operations are experiencing high latency, affecting query performance.

ClickHouse ClickHouseReplicaDown

One or more replicas are not reachable, which can affect data redundancy and availability.

ClickHouse ClickHouseZooKeeperConnectionLoss

The ClickHouse server has lost connection to ZooKeeper, affecting distributed coordination.

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The ClickHouse server is using an unusually high amount of memory, which could lead to performance degradation or crashes.

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The CPU usage on the ClickHouse server is consistently high, indicating potential performance issues.

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The number of connections to the ClickHouse server has exceeded the configured limit.

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Queries are taking too long to execute and are timing out.

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One or more replicas are lagging behind the primary server, which can lead to stale reads.

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