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MongoDB Monitoring Support

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MongoDB Monitoring Support

MongoDB is pretty widely used, and maintaining great performance means monitoring is really important. Here's a breakdown of key metrics.

· Performance Zone
Free Resource

Evolve your approach to Application Performance Monitoring by adopting five best practices that are outlined and explored in this e-book, brought to you in partnership with BMC.

For many of us in the DevOps field, MongoDB is a critical part of our IT stack. With today’s acquisition of WiredTiger, MongoDB is further establishing itself as the NoSQL DB built to support massive data processing and storage.  It would be an understatement to say that MongoDB does a lot, with many organizations using it as their backend storage framework, analytics backend, and so on.

So your MongoDB cluster really, really needs to be in tip-top shape.  All the time. And if it’s not then you need to know asap — or better yet — prevent problems before they kick in and make your life difficult. That’s where SPM comes in — with MongoDB monitoring, alerting and anomaly detection.  MongoDB exposes a boatload of metrics, but instead of just throwing all of them on endless charts, we’ve taken the time to cherry pick what we think are the top 50 most valuable MongoDB metrics to monitor. We have furthermore made it possible to filter the MongoDB metrics by server, as well as a database and table where possible.

The key metric groups we track are:

  • Database Operations
  • Database Memory
  • Database Storage
  • Documents
  • Locks
  • Network
  • Database Journal
  • Background Flushes


The Overview chart below provides 9 charts with MongoDB key metrics:

  • Row 1 displays CPU, Memory and Disk Metrics
  • Row 2 displays Database Operations, Database Memory and Database Storage Metrics.
  • Row 3 adds Collection/Document Metrics, Locks, and wait times; followed by Network Metrics for MongoDB

MongoDB_Overview

SPM for MongoDB Overview

In case you monitor a MongoDB cluster, the Server Tab provides a quick overview for the Health of each node:

MongoDB_Server_view

SPM Server View

The Reports on the left side of the screen below provide detailed information for each group of metrics. Let’s have a quick look at them.

MongoDB_CPU_details

OS Metrics: CPU Metrics, Memory Usage, Disk Space and I/O

Below is an example of some of the key MongoDB Metrics found in SPM:

  • Database Operations: Counters for Queries, Insert, Update, Delete and other commands for the main database plus replica operations
  • Database Memory: Resident-, Virtual-, Mapped-, and Journal Memory
  • Database Storage: Size of Data Files, Namespace Files, DB Files etc., plus Size of Objects, Number of Collections and Objects

MongoDB_Storage

MongoDB Storage & Collections

The screenshot below shows:

  • Documents: Counters for Documents inserted, updated or returned by queries
  • Locks: Lock counters and lock acquisition wait times for Global, Database, Collection and Journal level. Since MongoDB 3.x Locks are not always global. SPM shows a breakdown for all lock types. These metrics are good candidates for alerting, when anomalies are detected.  Simply add an alert from the menu in the top-left corner in each chart.

MongoDB_Locks

Metrics for all MongoDB Locks

Other key MongoDB metrics that SPM displays are:

  • Network: Number of client connections, Received and transmitted data, Request rate
  • Database Journal: Commits, Early Commits,  Commit times and lock times

MongoDB_Journal_Commits

MongoDB Journal Metrics

In case you like to see MongoDB metrics together with the Top Node.js Metrics, you might like the idea of putting MongoDB and Node.js metrics from SPM for Node.js in a custom dashboard:

MongoDB_Locks-Node.js_Loop

SPM Custom Dashboard with MongoDB Locks and Node.js Event Loop Latency

We hope you like this new addition to SPM. Got ideas how we could make it more useful for you?  Let us know via comments, email or @sematext.

Not using SPM yet? Check out the free 30-day trial by registering here. There’s no commitment and no credit card required. Even better — combine SPM with Logsene to make the integration of performance metrics, logs, events and anomalies more robust for those looking for a single pane of glass.

Evolve your approach to Application Performance Monitoring by adopting five best practices that are outlined and explored in this e-book, brought to you in partnership with BMC.

Topics:
performance ,database ,mongodb

Published at DZone with permission of Mick Emmett, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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