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Azure Monitor vs Apache Spark MLlib

Azure Monitor logo

Azure Monitor

Logging

Azure's Monitoring and Diagnostics Service

From
Free
Rated
-
Full reviewWebsite
Apache Spark MLlib logo

Apache Spark MLlib

Machine Learning

Scalable machine learning on Apache Spark

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Azure Monitor billed per GB ingested across three separate log plans, Auxiliary, Basic and Analytics, so the plan chosen changes the rate as much as the volume does; Apache Spark MLlib apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.
  • They diverge on capability: Azure Monitor covers Log collection, Apache Spark MLlib covers Classification.

Where they differ

Only the attributes on which Azure Monitor and Apache Spark MLlib actually diverge.

Attributes where Azure Monitor and Apache Spark MLlib differ
AttributeAzure MonitorApache Spark MLlib
Pricing modelusage-basedopen-source
PlatformsWeb, ApiLinux, macOS, Windows
CategoryLoggingMachine Learning
Founded20101999

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Azure Monitor

  • Log collection
  • Metrics collection
  • Alerts and notifications
  • Custom dashboards
  • API
  • Webhooks
  • REST
  • Web support

Only in Apache Spark MLlib

  • Classification
  • Regression
  • Clustering
  • Collaborative filtering
  • Feature engineering
  • Apache Spark
  • Hadoop
  • Kafka

What people use each for

The jobs each tool is most often brought in to do.

Azure Monitor

  • Collecting logs and metrics from Azure resourcesnot Apache Spark MLlib
  • Alerting on metric thresholds and log queriesnot Apache Spark MLlib
  • Application performance monitoring through Application Insightsnot Apache Spark MLlib
  • Long-term log retention for compliancenot Apache Spark MLlib
  • Querying operational data with KQLnot Apache Spark MLlib

Apache Spark MLlib

  • Machine learningnot Azure Monitor
  • Data sciencenot Azure Monitor
  • Distributed computingnot Azure Monitor

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Azure Monitor

  • Billed per GB ingested across three separate log plans, Auxiliary, Basic and Analytics, so the plan chosen changes the rate as much as the volume does
  • Only the first 5 GB a month of Analytics logs is free per billing account
  • Retention beyond the base period is charged per GB per month, up to 2 years interactive and 12 years long term
  • Log queries and search jobs are billed per GB scanned, so investigating an incident costs money
  • Alert rules are billed per time series for metrics and by execution frequency for logs
  • The pricing page shows placeholders rather than rates until a region and currency are chosen

Apache Spark MLlib

  • Apache Spark MLlib is Apache 2.0 licensed and free with no paid tier from the Apache project itself; SLA-backed support has to be sourced from a third party such as a managed Spark vendor rather than from Apache.

Pricing, plan by plan

Azure Monitor

Free
  • FreeFree
    • Log collection
    • Metrics collection
    • Alerts and notifications

Apache Spark MLlib

Free

No published plan breakdown. See the Apache Spark MLlib review.

Which should you pick?

Choose Azure Monitor if

  • You need log collection.
  • You want to start without paying.
  • You work on Web, Api.
  • You also want metrics collection.
Azure Monitor review

Choose Apache Spark MLlib if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want regression.
Apache Spark MLlib review

Questions people ask

Is Azure Monitor or Apache Spark MLlib better?
Neither clearly leads. Azure Monitor starts at Free and Apache Spark MLlib at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Azure Monitor or Apache Spark MLlib?
Azure Monitor starts at Free and Apache Spark MLlib at Free.
Does Azure Monitor or Apache Spark MLlib run on more platforms?
Azure Monitor runs on Web, Api. Apache Spark MLlib runs on Linux, macOS, Windows.
Can I use Azure Monitor for free?
Both have a free tier, so you can try either at no cost before committing.
What is Azure Monitor best used for?
Azure Monitor is most often used for collecting logs and metrics from azure resources, alerting on metric thresholds and log queries, application performance monitoring through application insights, long-term log retention for compliance. Of those, collecting logs and metrics from azure resources and alerting on metric thresholds and log queries are not what Apache Spark MLlib is typically brought in for.
What can Azure Monitor do that Apache Spark MLlib cannot?
Azure Monitor covers Log collection, Metrics collection, Alerts and notifications, Custom dashboards. Apache Spark MLlib covers Classification, Regression, Clustering, Collaborative filtering.

Answered from the vendors’ own pages

Azure Monitor: How does Azure Monitor billing work?

Billing is based on data volume ingested into Azure Monitor. Additional charges apply separately for alerts, notifications, web tests, and data export. Activity log and platform metrics are automatically collected with an Azure subscription.

Source
Apache Spark MLlib: How much does Apache Spark MLlib cost?

MLlib is completely free and open source, licensed under the Apache License Version 2.0. There are no subscription, licensing, or usage fees.

Source
Azure Monitor: What savings are available with Azure Monitor?

Capacity reservations offer up to 36% savings compared to standard pay-as-you-go pricing when you commit to reserved capacity upfront.

Source
Apache Spark MLlib: What licensing does MLlib use?

MLlib is licensed under Apache License Version 2.0, making it freely available for all users regardless of organization size or use case.

Source
Azure Monitor: Is there a free tier for Azure Monitor?

No dedicated free tier exists. Activity log and platform metrics are automatically collected with an Azure subscription, but detailed monitoring requires additional configuration and associated costs.

Source
Apache Spark MLlib: How do I use MLlib?

MLlib is built into Apache Spark. Download Spark, which includes MLlib as a module, and deploy on your choice of infrastructure including Hadoop, Mesos, Kubernetes, standalone, or cloud.

Source
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