Spring Boot Actuator module helps you monitor and manage your Spring Boot application by providing production-ready features like health check-up, auditing, metrics gathering, HTTP tracing etc. Actuator also integrates with external application monitoring systems like PrometheusGraphiteDataDogInfluxWavefrontNew Relic and many more. These systems provide you with excellent dashboards, graphs, analytics, and alarms to help you monitor and manage your application from one unified interface.

Actuator uses Micrometeran application metrics facade to integrate with these external application monitoring systems. This makes it super easy to plug-in any application monitoring system with very little configuration. The first part this article teaches you how to configure Actuator in a spring boot application and access its features via HTTP endpoints.

The second part will teach you how to integrate Actuator with an external application monitoring system. Alternatively, you can generate the app from Spring Initializr website.

graphite redis monitoring

You can add spring-boot-actuator module to an existing spring boot application using the following dependency. Actuator creates several so-called endpoints that can be exposed over HTTP or JMX to let you monitor and interact with your application. Note that, every actuator endpoint can be explicitly enabled and disabled. The application will start on port by default.

graphite redis monitoring

The endpoint should display the following. The status will be UP as long as the application is healthy. It will show DOWN if the application gets unhealthy due to any issue like connectivity with the database or lack of disk space etc. Check out the next section to learn more about how Spring Boot determines the health epsxe core stopped android your application and how you can tweak it.

graphite redis monitoring

By default, only the health and info endpoints are exposed over HTTP. Following is a list of some super useful actuator endpoints. You can see the complete list on the official documentation. By default, all the endpoints that I listed in the previous section are enabled except the shutdown endpoint. You can enable or disable an actuator endpoint by setting the property management. For example, to enable the shutdown endpoint, add the following to your application.

The health endpoint checks the health of your application by combining several health indicators. It uses these health indicators as part of the health check-up process.

Redis Server

For example, If your application uses Redisthe RedisHealthIndicator will be used as part of the health check-up. But by default, all these health indicators are enabled and used as part of the health check-up process.

To get the complete details including the status of every health indicator that was checked as part of the health check-up process, add the following property in the application. The health endpoint now includes the details of the DiskSpaceHealthIndicator which is run as part of the health checkup process. If your application has a database say MySQLthe health endpoint will show the status of that as well. You can also create a custom health indicator by implementing the HealthIndicator interface, or extending the AbstractHealthIndicator class.

Once you add the above health indicator in your application, the health endpoint will start showing its details as well. To get the details of an individual metric, you need to pass the metric name in the URL like this.

For example, to get the details of system. This will display the details in JSON format like so. You can also view the details of an individual logger by passing the logger name in the URL like this. The loggers endpoint also allows you to change the log level of a given logger in your application at runtime.We have seen in one of the past articles about Redis clustering and how we can take backup and restore it. In this, we are going to see how we can monitor Redis nodes using Prometheus and Grafana.

We will divide this article into three phases. First, how to expose the metrics, second is where to save the time series data and the last part is how we can plot the data to make sense out of it.

You can build and run it. You can find all the configuration settings on the Github link. Once you run this you will see the metrics on the port specified. Next, we have to tell Prometheus to scrape and metrics and save it. This comes in the second section of our article.

How to monitor Azure Cache for Redis

Now if you are aware of how Prometheus works, what it does it you give config to Prometheus about the location it has to scrape and then it does its job and scrapes and saves the data. Below are the Prometheus config required. For plotting the data we are going to use Grafana. Now you can tell Grafana to use Prometheus as a data store. After that, you can use import this dashboard to plot it.

This was how you can plot your Redis data to Grafana dashboard. If you like the article please share and subscribe. Gaurav is cloud infrastructure engineer and a full stack web developer and blogger. Sportsperson by heart and loves football. Scale is something he loves to work for and always keen to learn new tech. Your email address will not be published. Save my name, email, and website in this browser for the next time I comment.

Notify me of follow-up comments by email. Notify me of new posts by email. This site uses Akismet to reduce spam. Learn how your comment data is processed. Skip to content.This guide will focus on monitoring of Redis application on a Linux server.

Redis is an open source in-memory data structure store, used as a database, cache and message broker. Redis provides a distributed, in-memory key-value database with optional durability. Redis supports different kinds of abstract data structures, such as strings, sets, maps, lists, sorted sets, spatial indexes, and bitmaps. Monitoring Ceph Cluster with Prometheus and Grafana. In addition, for every database there are metrics for total keys, expiring keys and the average TTL for keys in the database.

The exporter will also export the size or, depending on the data type, the length of the key. This can be used to export the number of elements in sorted sets, hashes, lists, etc. The last step is to add a job to the Prometheus server for scraping metrics.

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So far we have covered the following monitoring with Prometheus:. This Prometheus exporter for Redis metrics supports Redis 2. NOTE: mutually exclusive with redis. Connected to Add Prometheus data source to Grafana and import or create a grafana dashboard for Redis. Wait for data to start appearing on your Grafana Dashboard, below is a sample view. How to Install Redis on Ubuntu Josphat Mutai - Modified date: January 10, 0. Introduction Maybe you are a security practitioner, manager or executive and you feel the need to prove your skills Best Kubernetes Study books Modified date: January 10, Best Books for Learning Node.

Modified date: November 2, Install MariaDB Modified date: October 20, How to install PHP 7. Modified date: January 21, Install and Configure DBeaver on Ubuntu Azure Cache for Redis uses Azure Monitor to provide several options for monitoring your cache instances.

You can view metrics, pin metrics charts to the Startboard, customize the date and time range of monitoring charts, add and remove metrics from the charts, and set alerts when certain conditions are met. These tools enable you to monitor the health of your Azure Cache for Redis instances and help you manage your caching applications. Metrics for Azure Cache for Redis instances are collected using the Redis INFO command approximately twice per minute and automatically stored for 30 days see Export cache metrics to configure a different retention policy so they can be displayed in the metrics charts and evaluated by alert rules.

Redis Monitoring

For more information about the different INFO values used for each cache metric, see Available metrics and reporting intervals. To view cache metrics, browse to your cache instance in the Azure portal. Azure Cache for Redis provides some built-in charts on the Overview blade and the Redis metrics blade. Each chart can be customized by adding or removing metrics and changing the reporting interval. The Pricing tier displays the cache pricing tier, and can be used to scale the cache to a different pricing tier.

To view Redis metrics and create custom charts using Azure Monitor, click Metrics from the Resource menuand customize your chart using the desired metrics, reporting interval, chart type, and more. For more information on working with metrics using Azure Monitor, see Overview of metrics in Microsoft Azure. By default, cache metrics in Azure Monitor are stored for 30 days and then deleted.

To persist your cache metrics for longer than 30 days, you can designate a storage account and specify a Retention days policy for your cache metrics. In addition to archiving your cache metrics to storage, you can also stream them to an Event hub or send them to Azure Monitor logs. If you change storage accounts, the data in the previously configured storage account remains available for download, but it is not displayed in the Azure portal.

Cache metrics are reported using several reporting intervals, including Past hourTodayPast weekand Custom. The Metric blade for each metrics chart displays the average, minimum, and maximum values for each metric in the chart, and some metrics display a total for the reporting interval. Each metric includes two versions. One metric measures performance for the entire cache, and for caches that use clusteringa second version of the metric that includes Shard in the name measures performance for a single shard in a cache.

For example if a cache has four shards, Cache Hits is the total number of hits for the entire cache, and Cache Hits Shard 3 is just the hits for that shard of the cache. Even when the cache is idle with no connected active client applications, you may see some cache activity, such as connected clients, memory usage, and operations being performed. This activity is normal during the operation of an Azure Cache for Redis instance. You can configure to receive alerts based on metrics and activity logs.

Azure Monitor allows you to configure an alert to do the following when it triggers:. To configure Alert rules for your cache, click Alert rules from the Resource menu.

It's not in Production Unless it's Monitored by Joseph Ruscio

For more information about configuring and using Alerts, see Overview of Alerts. Activity logs provide insight into the operations that were performed on your Azure Cache for Redis instances. It was previously known as "audit logs" or "operational logs".

To view activity logs for your cache, click Activity logs from the Resource menu. You may also leave feedback directly on GitHub. Skip to main content. Exit focus mode. Learn at your own pace. See training modules. Dismiss alert. View pre-configured metrics charts The Overview blade has the following pre-configured monitoring charts. View metrics with Azure monitor To view Redis metrics and create custom charts using Azure Monitor, click Metrics from the Resource menuand customize your chart using the desired metrics, reporting interval, chart type, and more.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again.

graphite redis monitoring

If nothing happens, download the GitHub extension for Visual Studio and try again. There are no dependencies except an external time series data store. Head to grafana. If you have any problems please read the troubleshooting guide. Be sure to read the getting started guide and the other feature guides. If you want to build a package yourself, or contribute. Here is a guide for how to do that. You can always find the latest master builds here. Since imports of dependencies use the absolute path github.

The last options makes it possible to change easily the grafana repository you want to build. Run the following:. Create a custom. You only need to add the options you want to override. Config files are applied in the order of:. Before or after you create a pull request, sign the contributor license agreement. If you have any idea for an improvement or found a bug do not hesitate to open an issue.

Grafana is distributed under Apache 2. Work in progress Grafana 2. Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Sign up.This article will outline what Redis database monitoring is and how to set up a Redis database monitoring system with MetricFire.

A Redis Database is an in-memory Data Structure Store which organizes data into key-value pairs which can be used as a database, cache, or message broker. Redis DB is open-source, and there are various hosted services offered. A Redis data structure is efficient both in terms of performance and ease of use. Redis DBs are usually used for data that needs to be retrieved quickly, such as a password that is connected to a single username, or for data that is transient and can be deleted shortly afterwards.

The simple command-line interface reduces developmental effort and the in-memory component reduces latency and increases throughput. A Redis cluster is an implementation of Redis DB that allows data to be automatically sharded across multiple Redis nodes. Monitoring Redis metrics with Prometheus causes little to no load to the database.

Redis will push the required metrics to the Prometheus endpoint where users can scrape Prometheus for the available Redis metrics, avoiding scraping Redis each time a metric is queried. You can monitor the total number of keys in a Redis cluster, the current number of commands processed, memory usage, and total Redis connections. In addition, you can monitor cluster-wide data, individual node data, or single database data.

If you are using hosted Prometheus by MetricFire, it works in exactly the same way. MetricFire scrapes the Redis DB endpoint for metrics information, and displays it automatically in the Grafana dashboard. According to docs. The cluster name can be either the fully-qualified domain name or the IP address.

As seen below. As seen below, you can see the Prometheus data source settings menu. For Access, select Browser. This is an example of a row within a Grafana Dashboard. This row is made up of four panels. Grafana has the ability to group graphs, text, and tables into relevant categories so you can easily sort through different metrics within one dashboard. Organizing your panels helps with correlation and being able to quickly troubleshoot the issue.

This graph shows the total memory usage for different aggregation machines. These machines are responsible for gathering data that is ingested and aggregating the data into more manageable formats. We want to monitor how much memory each resource is using.

When a resource is getting close to max memory consumption, performance will start to decrease. A spike in memory usage can act as an identifier for important changes in your application and processes. This makes it easier to see the different metrics being sent when their values are all similar. This graph also has a floating legend, which helps with easy reading. It shows the different groups of machines running a Redis DB instance and their associated number of commands processed.

This shows us the traffic and potential stress placed on the resource. This is the zoomed in Key View graph from the dashboard row above. This is showing the total number of keys in each Redis DB instance. Similar to the other graphs, knowing the total number of keys within an instance gives administrators greater insight into each Redis DB.With OpsDash, you can quickly start monitoring Redis, and get instant insight into key performance and health metrics.

OpsDash dashboards come pre-configured, setup to monitor the most important Redis metrics. No messing around with individual metrics, figuring out which of them are important, no editing graph templates. OpsDash strives to save you the tedious work of setting up a useful dashboard. The metrics you see here were carefully chosen to ensure effective Redis monitoring.

Memory Usage : The memory used by all the items that are currently resident in memory. Open Connections : The total number of connections that are currently open.

Cache Hit Rate : The count of hits and misses that happen each second. Operations per Second : The number of operations that are being performed each second.

Evictions per Second : The number of items that are evicted each second. Expirations per Second : The number of items that expire each second. Latency : The time taken by the Redis instance to start responding to a command.

Each OpsDash Smart Agent includes the industry-standard statsd interface and even a graphite interface to easily report custom metrics. With OpsDash, Redis monitoring is fast and easy. Try it! OpsDash is a comprehensive solution for server monitoring, service monitoring, database monitoring and application metrics monitoring.

Send in your custom metrics with StatsD and Graphite interfaces built into each agent. Try OpsDash Today! Sign up here. All Rights Reserved. Toggle navigation OpsDash by RapidLoop.

Redis Monitoring.