IMPACT 2021 – IMPACT Conference

January 19-21 & 26-28 | Virtual Conference

Join us for 6 virtual conference days with networking sessions, vendors, and speakers from all over the globe.

Presented by

The 46th IMPACT Conference

For more than 40 years, CMG’s international conference has been the source for education and peer-to-peer exchange for all things enterprise IT and infrastructure. It is the only conference of its kind where attendees can obtain real-world knowledge and training that is not vendor-run.

IMPACT features sessions on the full scope of digital transformation technologies including Artificial Intelligence and Machine Learning, Observability, DevOps, Performance Engineering, Digital Process, Cloud Native Applications, and the IT infrastructures that support them.

Sessions and Speakers

Each year, CMG brings together leading technology practitioners and vendors for a conference like no other. With an emphasis on peer-to-peer education, the conference facilitates open communication and problem solving for its attendees.

See our 2021 Sessions

When your Site Fails it can be Great for Business

The site crash was and still is their best sales day, ever. The platform failing over caused people to keep trying and trying to get through. The site failing over made them more desirable. They didn’t just keep trying for 5-10 mins and give up. They were trying all day. People had a fear of missing out…

Speaker
Thomas Ballard
Chief Commercial Officer
Market Hill
London, England United Kingdom

Track
What’s New / Modern Enterprise IT

Schedule
TBA

Concurrent Users – An analytical approach to proper workload simulation

Concurrent User is one of the key performance metrics in a system. Many performance issues that can only be exposed under load are related to the increased number of concurrent users. In the context of load test, we often hear phrases such as “test the system under x concurrent users”. This is a common misunderstanding of the term. In most cases, Concurrent User is a Random Variable. We propose an analytical alternative to the classic queuing theory for estimating Concurrent User. This model helps us determine whether the simulated workload is a proper representation of the expected production scenario.

Speaker
Xiaosong Lou
Senior Performance Engineer
Blackline Inc
Woodland Hills, CA

Track
Performance Engineering and DevOps

Schedule
TBA

Cloud Resources Workload Profiling

How to be sure a cloud object’s (e.g, AWS EC2, RDS or EBS) workload fits the rightsized resources (Compute, RAM, IO/s and Network traffic)? It is very difficult to do using raw system performance data from monitoring tools. The best way to do that is using a weekly workload profile, which is a graphical visualization in form of MASF IT-Control chart. This chart shows the stability of the workload, reveals the anomalies happened recently, such as run-away, memory leaks or specifically important for cloud objects, the unusual number of hours the object is down all compared with the usual weekly pattern.

This presentation will describe how to build, read, and use workload profiles using real data examples and demonstrates how cloud capacity scaling could be verified.

Speaker
Igor Trubin
IT Manager
Capital One
Alexandria, Virginia United States

Track
Data Centers and Cloud Infrastructure

Schedule
TBA

Recruiting and retaining the new generation of Z System specialists

As many Z Systems specialists approach retirement, the issue of their successors arises. While younger analysts may find working with other platforms more appealing, several facets of Z Systems may be shown to convince them of their stability, reliability, and career security.

Speaker
Greg Caliri
Senior Systems Consultant (mainframe)
SVA Software
Bradford, Massachusetts

Track
Mainframe Modernized

Schedule
TBA

Sogei’s experience with IBM Db2 Analytics Accelerator

Overview of Sogei’s main software application running on acceletator. Challanges and benefits. Migration to v7. Monitoring of the accelelrator. Outcome of taking part in the InSync Early Support Program.

Speaker
Chiara Baldan
Data Engineer
Sogei
Rome, Italy

Track
Mainframe Modernized

Schedule
TBA

A Mainframe Security Rosetta

What’s an ESM on z/OS? Why are there three of them? Why does each have such a different personality from the other two? And if I know how to use one of them, is there a way for me to understand the other two more easily? Come to this session, and get ready for a Rosetta stone’s worth of insight into the ways and meanings of RACF, ACF2, and Top Secret Security.

Speaker
Reg Harbeck
Chief Strategist
Langley, BC Canada

Track
Mainframe Modernized

Schedule
TBA

Natural Language Generation: Creating human readable text with machines

Not all performance topics and recommendations simply cut and dry. Many are controversial. These are the recommendations that tend to generate discussion amongst peers, need careful consideration, or may depend on which ‘performance camp’ you belong to. During this presentation, we will explore some of these topics.

Speaker
Mohammed Jalil
Co-founder
Metapair
Kuala Lumpur, Selangor Malaysia

Track
What’s New / Modern Enterprise IT

Schedule
TBA

Controversial z/os performance topics debated

Speaker
Scott Chapman
CIO
Enterprise Performance Strategies, Inc.
Galena, Ohio United States

Peter Enrico
President
Enterprise Performance Strategies, Inc.
Bradenton, Florida, United States

Track
Mainframe Modernized

Schedule
TBA

Detection of Performance Anomaly using DESOM

Deep Embedded Self Organizing Map (DESOM), a hybrid Deep Neural Network based Autoencoder-Decoder (AE-DE) with an embedded Self Organizing Map (SOM), is applied successfully for the first time to detect anomaly in the performance metrics of mobile network entities with over 94% accuracy. SOM has been widely used in many areas for anomaly detection such as fraud detection, intrusion detection, etc. DESOM is a recent enhancement of SOM but not evaluated as practical solution for real problems prior to this work. Several novel methods to detect concept drift using the intrinsic features of DESOM have been incorporated in the complete solution pipeline.

Speaker
Jayanta Choudhury
Senior Data Scientist
Ericsson Inc.
Santa Clara, California United States

Anila Joshi
Sr. Data Science Manager
Ericsson Inc.
Santa Clara, California United States

Track
Performance Engineering and DevOps

Schedule
TBA

Bringing AI Out of the Lab: Realizing Real-World Deployments of Deep Learning on Edge Devices, at Scale

As far as research is concerned, deep learning works seamlessly in the lab today. However, businesses are running into trouble when trying to commercialize deep learning into a product or real-world application. Deep learning deployment today is limited mostly to cloud, and even there, involves huge costs for expensive processors, large amounts of memory, and especially high electricity costs, due to intensive computing requirements. On edge devices too (mobile devices, drones, etc.), deep learning deployment remains very limited due to these heavy processing, memory, and battery requirements. Dr. David will elaborate on the specific pain points and questions CIOs are looking to address as they seek to gain more business value from AI technology, and discuss how deep learning technology must shift to become applicable beyond the lab and truly enable real-world deployment.

Speaker
Dr. Eli David
Co-founder, DeepCube
Tel Aviv, Israel

Track
What’s New / Modern Enterprise IT

Schedule
TBA