Submit to Speak at IMPACT 2022
S. Easily the best part of IMPACT is our community as they share their expertise with others. Our call for sessions is CLOSED, except for limited sponsored or keynote sessions remaining and please email [email protected] for info.
We want to feature sessions that cover key topics in enterprise IT including:
Cloud Computing | Mainframe | System Engineering | Machine Learning/AI/Deep Learning | Scalability and Resilience
Infrastructure Design | Performance and Capacity Planning | Strategic Vision | DevOps | On-Call Strategies | Managing IT Teams | Continuous Delivery | Security | Monitoring and Instrumentation | Performance and Debugging | Backup and Recovery | Solving the Customer Experience
Submission system below is closed.
About Speaking at IMPACT 2022
CMG will be accepting speaker submissions on a rolling basis.
2022 speakers will receive free conference admission
Speakers will be required to participate in a practice session and pre-record their session for broadcast and archiving.
Sessions are 40 minutes with a 15 minute Q&A session immediately following.
Speakers are asked to engage in live video Q&A sessions immediately after their scheduled broadcast.
Questions? Contact [email protected]
See our Terms and Conditions for speakers
We will be accepting sessions on a rolling basis with these 3 selection deadlines. If you are interested in speaking, you are highly encouraged to submit early!
– September 17: First Round Deadline
– October 22: Second Round Deadline
– November 19: Third and Final Round Deadline
Past Sessions

Digital Twins in a Pandemic: Use Simulation Data for Quadcopter Mission Planning
Learn how drones aid in COVID-19 medical deliveries. In this hands-on workshop, you will use a digital twin of a quadcopter to collect simulation data, analyze collision avoidance controls and test...

The Golden Era of AI and Machine Learning: The case for on-premise AI resources
We truly are experiencing AI’s golden era. The confluence of AI algorithms coming to reality, performance and economics of computational infrastructure, and explosion of IoT-fueled Big Data has...

Fireside Chat with Harry Moseley, CIO of Zoom Video Communications
Speaker Harry D. Moseley Global Chief Information Officer, Zoom Track Modern Enterprise IT / What's New

Technical methods to solve performance issues
Based on a case study that involves reporting and automation with zWR and zGuard, this session will explore how to avoid MSU MLC costs overrun and deploy tuning in a mainframe environment. ...

Surfacing Mainframe Hidden Costs and Operational Gaps
“Help! My management wants yet another opex report”. With all of the data that’s available in your mainframe environment, it’s challenging to figure out what you should focus on. Being able to...

Enable Your DevOps Transformation
Rapid delivery of core business systems needs to be enterprise-wide, and DevOps is now mainstream, even on the mainframe. Your mainframe DevOps tool chain needs to integrate and communicate all...

Locating CICS Abnormal Reponse Times
Most of z/OS sites run CICS to serve transactional applications. These CICS environments are often very complex with thousands of different transaction codes running in hundreds of CICS regions...

Java performance in 2021: How AI optimization will debunk 4 long-standing Java tuning myths
Java is ubiquitous in online services, yet ensuring Java applications’ availability and performance remains a challenging task. In this talk, we show how established industry approaches and...

Everything I Need To Know About AIOps I Learned From My Rice Cooker
It seems you can’t throw a rock these days without it glancing off a shiny new application of ‘artificial intelligence’ or ‘machine learning’. Indeed, the promise of ‘AIOps’ proposes a...

Practical Ways to Leverage AI in your IT Operations
Join this session for a technical deep dive on practical ways to leverage AI in your IT operations, including discussions on topology, Cassandra, Kafka bus, graph database and more. Speaker Dave...

Capacity Management in a Changing World or Turning the Lights on in Capacity Management
Capacity Management process maturity includes aligning capacity, performance and cost. This process alignment are critical goals in determining business service levels constrained by capacity, and...

Anomalies Detection and Cloud Platform Selection During DevOps
In this session, the presenters will review the challenges of anomaly detection during DevOps and discuss the methodology and use case of cloud platform selection for the application. There will be...

Mainframe Modernization, a trusted comprehensive approach
The Mainframe applications that are critical to many of the businesses and governmental functions that support everyday lives require significant enhancement to meet the need for flexible and cost...

Mainframe Modernization Success Use Cases
Every journey is different, and theoretically ongoing. Smart Digital Transformation is strategic, avoids the sharp turns that threaten business continuity, and is programmed to address the three...

Failing over without falling over – Adrian Cockcroft
In this keynote presentation, Adrian Cockroft will talk about failing over without falling over; using chaos engineering and cloud to build resilient systems. Currently serving as VP Cloud...

Capacity Analysis Techniques for VMware VM I/O
The methodology previously presented for VMware capacity/performance analysis is extended to I/O analysis (memory analysis, 2013, and CPU analysis, 2019). The methodology demonstrates a holistic...

Performance Engineering – FinOps
This session will talk about how performance engineering is related to Fin Ops and especially in the cloud world; where every one is either moving or already in cloud. Fin Ops will be the key major...

AI Data Acquisition and Governance: Considerations for Success
Data is the new IP - AI can’t exist without a strong data acquisition and curation strategy. Planning the data pipeline, governance, and for growth and updating models regularly need to be part of...

Cost-to-Serve: Computing Transaction Efficiency
In a cloud operating environment, it is of utmost importance to understand performance, capacity and scale needs. It is also equally critical to identify areas of optimization and improvement before...

DevOps: Delivering Relationships and Solutions
In this talk, I will discuss novel deliverables from a DevOps perspective; delivering people skills, relationships and community through a DevOps lens. It is particularly important, especially now,...

Using an Open Architecture to Accelerate AIOps Value
Use of AIOps to augment IT functions such as event correlation and analysis, anomaly detection and root cause analysis is growing rapidly. However, limited access to data, lack of skills and...

Determining the Best Use of AI to Meet Your IT Ops Needs
There is a misconception that AI is about replacing people, but it’s more about using technology to assist us in accomplishing objectives more efficiently. When it comes to applying AI to IT...

Introduction to Precision Time Protocol (PTP) on IBM Z
To help IBM Z clients in the financial industry better comply with increasingly stringent time synchronization accuracy regulations, IBM Z introduced support for Precision Time Protocol on the z15...

Using Machine Learning for Software Capacity Planning
In this session, I would be sharing some insight into how machine learning is impacting the areas of Software Capacity Planning. I will share my insight into using Machine Learning Algorithms to...

Proactive Capacity Management is dead; long live Capacity Management!
The long held notion that a proactive Capacity Management strategy is IT's nirvana is no longer relevant. Business and Technology are moving too fast and it is seen as a blocker. However, all is not...

Providing Business Value Through Observability
When we look at business value, we often assume that the product we are building, that app which is going to revolutionize the world, that change in the infrastructure of a complex process, will...

Observability for Microservices
For the last few years, the buzzword of 'observability' has stood in for heavy, expensive Service solutions really only workable for enterprises. With the rise of microservices has come a new breed...

How Deep Learning Model Architecture Impacts Optimal Training Configuration in the Cloud
This session is part of a long research program aimed at scrutinizing how different components of server hardware and software stack affect deep learning model's training time and cost. Even a very...

Life Cycle of a Query in SQL Server
Many Developers work with SQL Server but don’t fully understand how it really works behind the scenes. Join Deepthi on her dive into the internals of SQL Server to explain why knowing what goes on...

Performance Engineering Maturity Model: The Four Stages of Performance Culture
As organizations shift towards agile and CI/CD approaches, performance engineering must change. Success cannot be achieved without a shift in the organization’s culture, where all teams participate...

Transforming humanity with Lean, Agile and DevOps methodologies during a global pandemic
COVID19 has become a compelling event for many organizations to rapidly transform their businesses, but that has put a lot of stress on the workforce. In this session, I explore how this impacts us...

Dynamic Capacity Management for Hybrid Multi-Cloud Environment
IT Managers, Architects, DBAs and Systems Analysts involved in Cloud Selection often perform POC projects to compare clouds performance, scalability, security and other criteria. After finishing POC...

Capacity and performance before and after a major infrastructure transition
Major infrastructure transitions like moving to a new data center, outsourcing or changing outsourcers, or simply upgrading your mainframe often involve a lot of educated guesses about capacity and...

Improving Forecasting for Capacity Management Using Segmented Regression
One problem with the use of linear regression for capacity planning forecasting is that step changes in the data can lead to false predictions. This session demonstrates how delegates can apply...

z14 and z15 Pipelines
The z13 can execute about 12% more [1.695/1.514] Instructions than the zEC12, although its Cycle Time is about 9% higher [5/5,5 GHz], but its Execution Units have almost 2x of Circuits, compared to...

Overcoming Automation Fear in Infrastructure as Code
Following the same research line (IaC), this year I would like to address how to deal with the main challenges in the adoption of dynamic infrastructure and the use of automated configuration tools....

Three Tricky Performance Problems Solved with Oracle Trace Data
The Oracle Database kernel has a rich tracing feature built into it, but many analysts choose tracing as only a last resort. This session tells three stories of how we helped solve a tricky...

Python Performance And Other Non-Functional Testing Techniques
We'll look at the extremely popular Python language and a specific misconception -- Python is slow. This session will cover how to make Python efficient and how to monitor that performance and how...

Mainframe Modernization Challenges and Strategy
The Mainframe is still strategic and will exist for a long time to come ... The projection of the Mainframe in the IS evolution roadmaps requires the implementation of a modernization and...

Finetune your mainframe performance through the analysis of WLM and HIS
Mainframe performance is not only limited to the amount of available resources but strongly depends on how well you organize the work running on your machine. The Workload Manager helps you organize...

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...

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...

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...

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...

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...

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...

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,...

Controversial z/os performance topics debated
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,...

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...

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...