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 Video Library
Refcards
Trend Reports

Events

View Events Video Library

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

Curious about the future of data-driven systems? Join our Data Engineering roundtable and learn how to build scalable data platforms.

Data Engineering: The industry has come a long way from organizing unstructured data to adopting today's modern data pipelines. See how.

Threat Detection: Learn core practices for managing security risks and vulnerabilities in your organization — don't regret those threats!

Managing API integrations: Assess your use case and needs — plus learn patterns for the design, build, and maintenance of your integrations.

Related

  • Integrating Pub/Sub With MuleSoft
  • The SOC Technology Stack: XDR, SIEM, WAF, and More
  • Digging Into Sockets With Java Flight Recorder
  • Spring Application Listeners

Trending

  • Faster Startup With Spring Boot 3.2 and CRaC, Part 2
  • The Data (Pipeline) Movement: A Guide to Real-Time Data Streaming and Future Proofing Through AI Automation and Vector Databases
  • Digitalization of Airport and Airlines With IoT and Data Streaming Using Kafka and Flink
  • Navigating API Challenges in Kubernetes

Five Reasons Why BAM and CEP Have Failed You

By 
Maneesh Joshi user avatar
Maneesh Joshi
·
Jun. 23, 15 · Interview
Likes (0)
Comment
Save
Tweet
Share
1.1K Views

Join the DZone community and get the full member experience.

Join For Free

[This article was written by Maneesh Joshi]

Back in 2005, the concept Business Activity Monitoring (BAM) was coined by Gartner to capture the requirement of visibility into business operations. BAM delivered this visibility through aggregation and summarization of information around business activities. The BAM solution would capture event data, aggregate them into a single store, apply some context on top of the data, and then deliver dashboard-based visibility to business operations managers and sometimes executives.

A few questions that a typical BAM solution would answer for the business operations manager at a mortgage lender were:

  1. How long does the typical loan application take from submission to approval?
  2. Where is the most time spent in the loan application workflow?
  3. How many calls does the average call center rep answer per day?

Unfortunately, BAM never delivered on it’s promise. I can think of four challenges that made the BAM solution fall short.

1. Vendor-Focused Solutions

The first challenge with this approach to BAM was that the solutions were typically built by the large enterprise software vendors that offered it as a complement to their own big and wide technology stacks. This approach made the offerings very vendor-centric and often didn’t cover the heterogeneous set of technologies that most businesses owned. The visibility hence was rather restricted to the large vendor stacks and created information silos and narrow visibility.

2. Too Much Customization

The second challenge arose as a result of the fact that no two business processes are alike. There were very few commonalities between business processes for the vendors to build repeatable and scalable pre-packaged dashboards around. In order to build a solution that worked for these processes, heavy customization and services were necessary. For the solution to be meaningful and provide the right kind of visibility, the customization often included intrusive code changes to the application in order to raise business events, whether it was Java code in the Java tier, or the SQL packages in the database tier.

3. No Real-Time Visibility

The third challenge was from the lack of real-time nature of the visibility that the BAM technology delivered. By the time the operational data was collected from the sources, aggregated into a database, applied context on, analyzed, and presented into a dashboard, the visibility provided was already stale. In order to address this staleness problem, the notion of complex event processing (CEP) came into being. CEP technologies were purpose built to correlate events and detect patterns across event streams in real-time.

4. Lack of Business Context

Despite CEP attempting to solve the staleness problem, it introduced a problem of its own. The events processed by CEP are typically lightweight events and low on context richness. When CEP would attempt to correlate events to detect patterns across disparate streams, it lacked the business context. This lack of context made the solution less effective as no meaningful pattern matching or correlation could be done without the context. The business context needs to be captured at the source when the events are being captured in order to make the correlation relevant.

5. Premature Technology Stack

The last and main blocker was that the underlying technology stacks and the surrounding applications were not mature enough to support the vision. For instance, the relational databases that couldn’t capture unstructured events, or the inability to crunch massive volumes of data in real-time at low latencies while applying the context severely restricted the vendors from delivering on the promise. The packaged applications were very monolithic with very little extensibility, which resulted into implementing intrusive code changes to raise business events.

To be fair, the vision for BAM and CEP was spot on then and is spot on today. The vision was clearly ahead of its time and the problems it promised to solve very real. Who doesn’t want visibility into their business operations?! In fact BAM and CEP become all the more important is today’s day and age of software-defined businesses.

In my next blog post, I will discuss a new approach to BAM. I will also review as to how the technology and application stacks have evolved, and why you should consider revisiting your opinions about BAM and CEP use cases.

Event Visibility (geometry) application IT

Published at DZone with permission of Maneesh Joshi, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Integrating Pub/Sub With MuleSoft
  • The SOC Technology Stack: XDR, SIEM, WAF, and More
  • Digging Into Sockets With Java Flight Recorder
  • Spring Application Listeners

Partner Resources


Comments

The likes didn't load as expected. Please refresh the page and try again.

ABOUT US

  • About DZone
  • Support and feedback
  • Community research
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

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

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 100
  • Nashville, TN 37211
  • support@dzone.com

Let's be friends: