A Complete Guide to Memcached Performance Monitoring

Memcached is a popular in-memory key-value store used to speed up dynamic applications. By storing data in memory, Memcached reduces data retrieval time and boosts overall performance. However, as a shared-memory system, it poses unique challenges in terms of troubleshooting and monitoring.

This article will discuss the importance of monitoring Memcached and provide a comprehensive guide to tracking key metrics using native tools.

What is Memcached?

Memcached belongs to the class of software known as in-memory data stores. It predominantly acts as a caching layer sitting in front of a primary database and storing frequently accessed data in memory. This approach allows applications to get data directly from the cache, avoiding the need for time-consuming database queries that would require disk I/O.

Memcached has a distributed architecture in which a virtual memory pool is created and shared among multiple servers in a cluster. This approach enables Memcached to handle high traffic volumes and cater to growing data demands by adding more nodes to the cluster.

As a key-value store that doesn't understand data structures, Memcached expects all uploaded data to be serialized and stores it as key-value pairs where each key uniquely identifies the corresponding value. This efficient storage mechanism allows Memcached to achieve O(1) speed for all commands. On the most performant servers, it can deliver a throughput of millions of keys per second.

Memcached uses an LRU (Least Recently Used) eviction policy to manage memory. It supports different protocols, including HTTP, TCP, and UDP, which makes it easy to integrate Memcached with a wide range of applications.

It can be used for a variety of use cases:

• Caching frequently accessed static web pages
• Caching the result sets of the most frequent database calls
• Caching the most requested API responses
• Storing session data in-memory, enabling faster logins
• Storing real-time analytics data, powering fast BI applications

Memcached vs. Redis, Aerospike, and Elasticsearch

While Redis, Aerospike, and Elasticsearch are compelling alternatives, Memcached provides distinct advantages that make it an ideal choice for specific use cases:

• Simplicity: Memcached is known for its simplicity and lightweight architecture. It is easy to set up and integrate with applications. It also has a smaller memory footprint and minimal overhead compared to Redis, Elasticsearch, and Aerospike.
• Built for caching: Memcached is a purpose-built caching system. Redis, Elasticsearch, and Aerospike offer additional features that may introduce needless complexity when caching is the primary use case.
• Simplified data model: Memcached uses a key-value model that makes data interaction easy. While Redis and Aerospike support multiple data structures for versatility, they may not be necessary for straightforward caching scenarios.

Why is it important to monitor Memcached?

Regular monitoring of a Memcached cluster is essential to ensure bottleneck-free operations. Here are other key reasons why you should actively monitor Memcached:

Because it’s a shared memory system

Memcached has a shared memory architecture, which means that multiple processes can access the same memory block at the same time. This can make it harder to track down performance issues, as a problem may be caused by one or more processes. However, by regularly monitoring key metrics, you can detect issues early on, before they escalate.

For example, if you notice that the cache eviction rate suddenly spikes and coincides with an increase in overall memory usage, you can assume that the cache is running out of memory. This insight can help you to take corrective action in a timely manner, avoiding service disruption.

To ensure high performance

Monitoring Memcached allows you to track key performance metrics, including cache hit ratio, cache miss ratio, and response times. By analyzing trends in these metrics, you can gauge whether a cluster is performing at full potential or requires optimization.

For example, if you are noticing a really high cache miss ratio after every build upgrade, you can surmise that you need a better cache initialization strategy at application startup.

To keep tabs on data integrity

As data stored in Memcached resides solely in memory, it is vital to monitor its integrity. Regularly inspecting cache consistency and validating data accuracy ensures that clients receive reliable and fresh information from the cache.

For example, by analyzing older data records, you may detect a key-value pair that has long been invalidated. After investigating the root cause of the staleness, you can manually update the data to ensure that it is accurate and up to date.

For high availability

Even the most fault-tolerant systems like Memcached require monitoring for high availability. Memcached relies on memory, so tracking memory and resource utilization is essential to ensure that the cluster stays up and running.

For example, a monitoring tool can alert administrators if a node is approaching peak memory utilization. This allows them to investigate the issue and respond accordingly, by, for example, increasing the memory resources of the node.

To optimize configurations

Memcached has several configuration options, and it performs best when it’s tuned according to business needs and the underlying hardware. Proactive monitoring provides insights into the resource usage of the cluster, enabling you to optimize configurations based on the actual workload.

For example, you may tweak the cache size, eviction policy, or connection limits for better memory utilization and improved throughput.

To facilitate faster issue resolution

Quick contextualization of an issue is crucial for its timely resolution. Regular monitoring and alerting enable you to contextualize and diagnose issues as they arise. This helps in decreasing the mean time to resolution (MTTR) and ensuring business continuity.

For example, if you notice a few unexpected connection timeouts or failures, you can analyze logs to establish context and apply a timely fix.

Key metrics to monitor Memcached performance

For holistic monitoring of a Memcached cluster in production, focus on the following key metric categories:

Cache performance metrics

Metrics related to the actual cache performance should be at the top of the list of metrics to monitor. These metrics can help you assess how well Memcached performs as the caching layer in your deployment.

Request metrics

Request metrics offer insights into the command processing layer of Memcached. Let’s look at a few examples:

Memory metrics

Tracking memory metrics is another crucial aspect of monitoring Memcached. Focus on the following important memory metrics:

Network metrics

Network metrics enable you to identify and debug network bottlenecks, latency, and degradations. Focus on the following metrics:

Server health metrics

Keeping an eye on server health metrics allows you to optimize resource utilization and cache efficiency. The following server health metrics are the most important:

Monitoring Memcached using the stats command

Memcached offers a built-in command, stats, which can be used to track its performance in real time. The stats command displays the following key statistics:

Current connections, accepting connections, total connections, flush command counter, cache sizes, evicted elements, total bytes read, CAS hits, CAS misses, increment hits, increment misses, authentication commands, evicted non-zero elements, total pages, and others.

The stats command also offers the following sub commands:

• stats items: Displays information about the data items stored in the cache per different slabs.
• stats slabs: Displays more slab-focused statistics.
• stats sizes: Displays a hypothetical distribution of items in the cache if the slabs were divided into 32-byte buckets instead of the configured number of slabs. This command helps in monitoring memory usage and identifying potential memory inefficiencies.

You can combine different statistics from the output of the stats command to gather even more key insights. For example, you can calculate the global hit rate as get hits / (get hits + get misses). Or you can find the number of free connections using: total connections – current connections.

Monitoring Memcached using the Site24x7 plugin

The Site24x7 Memcached plugin allows you to monitor all aspects of your Memcached cluster from a single pane of glass. You can track several key metrics in real time, including hit ratio, miss ratio, bytes read, bytes written, current connections, number of threads, evictions, latency, and throughput.

The free Python-based plugin can be downloaded directly from GitHub. It seamlessly integrates with the Site24x7 Linux agent, allowing you to view real-time performance metrics on the Site24x7 web client.

Conclusion

Memcached's simplicity and efficiency as an in-memory key-value store make it a great choice for improving the performance of dynamic applications. While it may not offer the extensive feature set of Redis or the interactivity of Aerospike it excels at what it was designed for: lightning-fast caching.

This article aimed to provide you with all the information you need to monitor key Memcached metrics using native tools. By proactively tracking these metrics, you can ensure the seamless operation of your Memcached cluster and deliver optimal performance to your users.