DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports Events Over 2 million developers have joined DZone. Join Today! Thanks for visiting DZone today,
Edit Profile Manage Email Subscriptions Moderation Admin Console How to Post to DZone Article Submission Guidelines
View Profile
Sign Out
Refcards
Trend Reports
Events
Zones
Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
  1. DZone
  2. Data Engineering
  3. AI/ML
  4. Are You Being Courted by a Buggy-Whip Vendor?

Are You Being Courted by a Buggy-Whip Vendor?

Don't invest your time and money in monitoring technologies that are becoming obsolete. Let's look at the tech that will shape the future of APM.

David Liff user avatar by
David Liff
·
Aug. 24, 18 · Opinion
Like (1)
Save
Tweet
Share
2.85K Views

Join the DZone community and get the full member experience.

Join For Free

There was a time when buggy-whips were the height of technology. If you wanted your horse and cart to go faster, you invested in a better buggy-whip. And then came the automobile, and all of a sudden buggy-whips were obsolete.

The funny thing though, is that it wasn't instant. The companies who made beautiful buggy-whips carried on making them for quite some time and were stunned that no one was buying them. Buggy whip advertising actually grew, as companies tried harder to convince the consumer to buy more.

And in some ways, the classic application performance monitoring products are finding the same issue.

The classic model of APM relies on monitoring specific technical aspects of computing, such as memory utilization, processor consumption and latency across a network. Using these parameters allows an operator to see if things are approaching a threshold where service level agreements (SLA's) could be impacted. And it works. But it only works in some specific use cases, and things can become very complex where the interaction between many different systems has to be considered.

The classic APM trick is to advise the customer to write libraries of complex scripts to identify actually what applications are doing. This creates an expensive and risky headache for users, who must maintain this massive library of scripts through every update on the infrastructure, platforms, and applications. It's a never-ending complexity headache.

But there is a way for companies to create a level of system monitoring that goes far ahead of the classic APM model, and that is to start to make use of the messages that their middleware solutions are already sending between every component in their application stack. By intelligently using these messages, a business can now monitor exactly what is happening, and even go further and link message records together to see entire technical and even business transactions.

By looking at messages and transactions along with the classic detail of system performance, a business can now do three critical things dramatically better.

  1. Monitor what is happening now (alerts based on business impacts, not just technology including Message Tracking and Transaction Tracking).
  2. Understand in detail what happened in the past (to quickly identify the root cause of any issue)
  3. Predict what will happen in the future (using Artificial Intelligence based on machine learning to identify likely issues well before the happen and identify likely solutions that can stop events ever happening).

These three aspects of operational control, will reduce MTTR (Mean Time to Repair), and increase MTBF (Mean Time Between Failures) and MTTF (Mean Time To Failure) in ways that were previously impossible.

So why aren't classic monitoring and APM solutions providing this level of technology. Well, they make buggy-whips, and surely people still want buggy-whips...

So how can you spot monitoring solutions that are trying to sell you buggy-whips. It's quite easy, companies that invest huge amounts in marketing and sales to sell you things that you are no longer interested in buying, who are focused on being sold to private equity or their competitors.

application Machine learning AI Aspect (computer programming) Monitor (synchronization) IT Library

Published at DZone with permission of David Liff, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Popular on DZone

  • Stream Processing vs. Batch Processing: What to Know
  • PostgreSQL: Bulk Loading Data With Node.js and Sequelize
  • Memory Debugging: A Deep Level of Insight
  • A Real-Time Supply Chain Control Tower Powered by Kafka

Comments

Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 600 Park Offices Drive
  • Suite 300
  • Durham, NC 27709
  • support@dzone.com
  • +1 (919) 678-0300

Let's be friends: