Whether your organization is moving more IT operations to the cloud or enhancing its deployments on-premises, it’s critical to understand the impact of excluding essential data points from legacy systems has on your bottom line. That said, optimizing your cloud deployment isn’t just about cost reduction — it can also positively enhance how you deliver services to your business.
Whether you are just getting started on your cloud journey or are looking to make more data available for your IT operations, Precisely Ironstream can help. In this on-demand webinar, learn how Precisely Ironstream helps customers make IBM Z platform and IBM i operational intelligence available in top cloud IT operational platforms like Splunk, Elastic, and Kafka.
Join this webinar to learn:
- Best practices for easily integrating IBM Z platform (mainframe) and IBM i operational metrics integrated into Splunk, Elastic, and Kafka
- The operational and financial ROI of using Ironstream to integrate legacy systems into modern IT platforms
- How Ironstream customers have benefited from bringing in IBM Z platform (mainframe) and IBM i machine/log data into Splunk, Elastic, and Kafka
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Integrating IBM Z and IBM i Operational Intelligence Into Splunk, Elastic, and Kafka
1. Integrating IBM Z and
IBM i data into Splunk,
Elastic, and Kafka
Making a case for heritage tech
in modern IT analytics operational platforms
Ian Hartley | Product Management Director
2. Housekeeping
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Recording and slides
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3. Why IT analytics
operational platforms?
Unites and integrates
data from across the
enterprise, making data
available for a variety
of projects and business
needs in one place
4. Examples of IT analytics operational platforms
Elasticsearch is a trademark of Elasticsearch B.V., registered in the U.S. and in other countries.
KAFKA is a registered trademark of The Apache Software Foundation
Splunk is a trademark or registered trademark of Splunk Inc. in the United States and other countries.
5. What can you do with these platforms?
Search and
investigation
Proactive
monitoring
Operational
visibility
Real-time
insights
6. What are the
benefits of an
IT analytics
operational
platform?
Visibility into
usage, trends,
projections
Better
operational
& business
insights
Identify
issues &
anomalies
(sooner!)
Enhance
security &
compliance
7. Reality check: you have a blind spot!
BLIND SPOT!
IT Workflows
Employee
Workflows
Customer
Workflows
Building Apps
IT Operations
Management
IT Service
Management
IT Business Management
IT Asset
Management
Service Management Governance/Risk
Compliance
8. Value that IBM Z and
IBM i brings
• Better insight into applications
running on core systems
• Clearer security information on
systems with sensitive data
• Enhanced event correlation
across systems
Remove the “blind-spot”
®
9. What happens when IBM Z
and IBM i are included?
Real-time
• Insights
• Monitoring
• Trends
• Alerts!
Improved
• Identification
(MTTI)
• Resolution
(MTTR)
Eliminate
• Blind spot
• SME Dependencies
• Homegrown
solutions
• Complexities
11. Financial services company needed real-time
alerts for monitoring and faster insights
Top level mandate to:
1. Improve visibility into potential issues on core banking applications running
on its mainframe platform
2. Limit the number of outages that could shut down online banking
3. Consolidating the delivery of real-time monitoring and alerts using Splunk
Challenge: Mainframe could not natively integrate into Kafka for security monitoring
12. Precisely Ironstream makes mainframe
available in real-time to Kafka
Solution
• Precisely Ironstream
• Kafka
Results
• Decrease in the number of system
outages from mainframe
• Improved customer experiences due to
limited disruptions to services
• Proactive security monitoring of all
systems
• No more mainframe blind spots!
14. Bank looks to improve their IT operations
Top level mandate to:
1. Drive continuous improvement of IT operations by reducing MTTR
2. Get mainframe log data into Splunk to follow compliance requirements of
the industry
3. Improve the visibility and management of critical IT assets and systems
Challenge: The mainframe was not visible in the company’s enterprise platform
of choice, Splunk
15. Solution
• Precisely Ironstream
• Splunk
Precisely delivers agile solution for Splunk
and mainframe
Results
• Reduced MTTR
• Machine data from mainframe is made
available to critical stakeholders
• Processes are now in compliance and
delivered in a timely manner
• Better insights and “heads up” on system
issues
17. Retail bank seeks reduce resource consumption
and improve customer experience
Top level mandate to:
1. Improve the performance of systems for customers using online
banking portal
2. Visualization of systems being monitoring to determine resource
consumption quickly and efficiently
3. Real-time data delivery to improve response time without increasing
CPU consumption
Challenge: Homegrown tools and skills gaps prevented the mainframe from being
integrated into Elastic
18. Real-time delivery and visibility of the
mainframe in Elastic
Solution
• Precisely Ironstream
• Elastic
Results
• Improved transaction response time for
current customers
• Increased the number of new customers
in banking system without a delay in
transaction response time
• Visualization of all systems using Grafana
to quickly diagnose problems
• Integrated the mainframe to Elastic
without impacting CPU consumption
19. Lessons learned, putting into practice
• Clearly define the goals of your efforts both technical and business facing
• Are you trying to save costs, improve a business result, or something else?
• Chose data integration solutions that allow you to enable complete visibility in your IT analytics
operational platforms
• New requirements for IT analytics operational platforms will require you to rethink how “it was
always done” and may break current processes
Visibility - See the whole picture, track performance and make better decisions. Visualize usage trends to better plan for capacity; spot SLA infractions, track how they are being measured by the business.
Insights - Make better-informed business decisions by understanding trends, patterns and gaining Operational Intelligence from your machine data. See the success of new online services by channel or demographic, reconcile 3rd 3rd-party service provider fees against actual use, find the heaviest users and heaviest abusers, and more.
Identify – Get answers and gain new business insights and intelligence from machine data significantly faster than traditional approaches.
Compliance – Helps to identify irregularities in systems and is important for monitoring security of those systems
When it comes to implementing IT analytics platforms there is a level of complexity that exists across an enterprise
Need to bring together systems from a variety of sources from the cloud to on-prem systems.
However, even after going through and setting up your platform for use, you can still have blind spots with IBM Z and IBM i platforms that don’t natively fit into these IT analytics platforms [CLICK FOR ANIMATION}
From speaking with Precisely customers and prospects, we have found these 3 things happen when it comes to integrating IBM Z and IBM i systems into their solutions
This company wants to vastly improve its tracking and package visibility. They feel that they need to offer customers more visibility into the movement of goods. Pushing the status of goods to customer dashboards will give them the ability to provide more real-time location and updates to transit time and delivery.
This concept is familiar to consumer shipping, we know when and where our package is in real-time, not so much when it comes to freight. To accomplish this, they needed data from disparate data sources, including DB2/z and SQL Server. They connect their legacy sources and their target Snowflake.
This company wants to vastly improve its tracking and package visibility. They feel that they need to offer customers more visibility into the movement of goods. Pushing the status of goods to customer dashboards will give them the ability to provide more real-time location and updates to transit time and delivery.
This concept is familiar to consumer shipping, we know when and where our package is in real-time, not so much when it comes to freight. To accomplish this, they needed data from disparate data sources, including DB2/z and SQL Server. They connect their legacy sources and their target Snowflake.