Enabling the Mainframe for IT Operations Analytics and AI OPS

Enabling The Mainframe For IT Operations Analytics And AI OPS

Ed Woods, IBM Corporation Keziah Knopp, IBM Corporation

VISIBILITY Visibility Visualize health and performance of services across your enterprise See your business infrastructure and do it in a more Correlate and services Control predictive manner CORRELATION Automate &CONTROL Correlate information, Manage your complex infrastructure, Manage service risk isolate issues and drive Isolate issues corrective actions when required EVENTS & AUTOMATION zManage - methods, standards, Handle Events and minimize and best practices for IT human error and increase performance and availability productivity through automated Optimize business resolution management for z/OS service delivery

VISIBILITY Visibility Visualize health and performance of services across your enterprise See your business infrastructure and do it in a more Correlate and services Control zManagepredictiveis evolving manner CORRELATION Automate towards&CONTROL IT Operations Correlate information, Manage Analyticsyour & complex AI OPS infrastructure, Manage service risk isolate issues and drive Isolate issues corrective actions when required EVENTS & AUTOMATION zManage - methods, standards, Handle Events and minimize and best practices for IT human error and increase performance and availability productivity through automated Optimize business resolution management for z/OS service delivery

▪ A definition courtesy of Wikipedia “IT operations analytics (ITOA) is an approach or method to retrieve, analyze, and report data for IT operations. ITOA may apply big data analytics to large datasets to produce business insights”

ITOA is “primarily used to discover complex patterns in high volumes of often ‘noisy’ IT system availability and performance data”

Log Analysis Key Functions Indexing & Event Of ITOA Inference Processing Technology

Pattern Search & Discovery Analysis

▪ Another definition courtesy of Wikipedia –“Artificial Intelligence for IT Operations (AIOps) is a term coined by Gartner as an industry category for machine learning analytics technology that enhances IT operations” ▪ AIOps is the acronym of "Algorithmic IT Operations" –Key tasks - automation, performance monitoring and event correlation –“The goal is to receive continuous insights which provide continuous fixes and improvements via automation”

Main Aspects Machine Big Data of AIOps Learning

Performance Automation Security End to End - APM

Events Storage Network Capacity Planning

Analysis

IT Service Management

Performance Automation Security End to End - APM

Events Storage Network Capacity Planning

Analysis

IT Service IT Operations Management Analytics

Performance Automation Security End to End - APM

Events Storage Network Capacity Planning

Analysis

IT Service IT Operations Data, Ingestion, Management Analytics Correlation

Performance Automation Security End to End - APM

Events Storage Network Capacity Planning

Analysis

Dashboards, IT Service IT Operations Data, Ingestion, Visualization, Management Analytics Correlation Searches, Notification

IBM Z Operations Analytics

zAware Splunk/ELK Analysis, Correlation, Visualization

IBM Common Data Provider - CDPz

IBM Z Operations Analytics

zAware Splunk/ELK Analysis, Correlation, Visualization

11 © 2020 IBM Corporation IBM Z IBM Common Data Provider The Pipeline To Feed z/OS Information To ITOA ▪ IBM Common Data Provider enables consistent message/data collection and analysis – Analysis methodology targeted to the user audience – Common collection infrastructure to feed one/multiple solutions

IBM zAware

IBM IZOA Logs Insight packs Dashboards

IBM Common Data Note - IZOA provides SMF Provider for z Splunk Insight packs for Splunk Systems

User Data ELK

Messages

IBM Common Data Provider - CDPz

IBM Z Operations Analytics

zAware Splunk/ELK Analysis, Correlation, Visualization

SMF Messages

IBM Common Data Provider - CDPz

IBM Z Operations Analytics

zAware Splunk/ELK Analysis, Correlation, Visualization

14 © 2020 IBM Corporation IBM Z Common Data Provider Add Feeds From Additional Tools And Components z/OS Network Workload Storage Security ZCEE NetView Automation Other Scheduling SMF tools Capacity Messages Planning Monitoring

IBM Common Data Provider - CDPz

IBM Z Operations Analytics

zAware Splunk/ELK Machine Learning Analysis, Correlation, Visualization

SMF Data

Log Data

CDP Streaming API IBM Z Common

IBM Z Performance Data and Capacity Analytics Provider z/OS Connect IMS Connect Extension

NetView

Workload Scheduler Common Data Provider Enabling IBM Z ITOA And AI OPS

SMF Data

Log Data

CDP Streaming API IBM Z Common

IBM Z Performance Data and Capacity Analytics Provider z/OS Connect IBM Machine IMS Connect Learning Extension z Performance NetView Capacity Analytics Workload Scheduler Common Data Provider – Feed To ITOA And AI OPS

CDPz Configuration Common Data Provider – Feed To ITOA And AI OPS Subscriber CDPz Configuration Common Data Provider – Feed To ITOA And AI OPS Subscriber CDPz Configuration

Splunk Example z/OS SYSLOG Data Rendered In Splunk Dashboards & Searches – Insight into Operational Data Available on IBM, Splunk, and Elastic Stack

Subsystem Dashboards Domain-specific ‘Quick Searches’ available out-of-the-box z/OS, WebSphere, DB2, CICS, IMS, MQ, Network, and Security • Based on the combined experience of subject matter experts, support teams and customers. • Immediate value out of the box. Anomaly Detection An IBM AI Operations Journey

Autonomous Operations

Early Detection of Deliver Guidance Departure from “Normal” Preemptive action on problems Use Machine Learn ”Normal” through proven Learning on tribal automation from history knowledge together Use Machine with prescriptive Goal: allow the Learning to detect analytics to system to manage changes in system provide guidance its “normal” health behavior together on actions to take with predictive analytics to Goal: provide Use Machine determine likely insight and Learning to leverage outcomes to alert recommend historical normal operations for early remediation system data to intervention establish a baseline Goal: Eliminate / Reduce Impact from service disruptions

23 Problem Insights Automatically surface important messages and anomalies

Provides easy to read problem summary and suggested actions for problem resolution.

Link to search for this Count of this message Total number of Problem message in this time over the timeframe Insights found per Sysplex period

Click to show the suggested actions for this message Machine Learning Data and Analytic Flow Training, Scoring, and Anomaly Detection

3. Visualize Anomaly Scores

Visualize anomaly scores for each KPI in the subsystem to help diagnose potential issues

2.Trained Training Model 2. Scoring

Data represents Watson Machine Learning for z/OS Scoring runs unattended to normal system generate live anomaly scores behavior createstrained modela model of 1. Collect Data expected behavior Normal Watson Machine metrics Learning for z/OS Model CDP batch ………… compares model load for …… with live metrics training

SMF IZOA ML CDP Db2 DB Live streaming metrics for …………… scoring … …………… … 26

Problem Insights Subsystem Scorecards

SYSA

SYSD CICS020AT

SYSD CICSA17

SYSA

SYSD CICST4

SYSD CICSIL3

IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z / DOC ID / July 17, 2017 / © 2017 IBM Corporation IBM Z Operations Insight Suite V1.1 - Client Presentation / January 2020 / © 2020 IBM Corporation Empower Capacity Planning Through Advanced Forecasting

Capacity Forecasting

Accurately forecast future needs to: • Determine the right application & environment capacity • Determine the best strategy for upgrades • Avoid unnecessary costs • Optimize application performance & availability • Communicate capacity needs Support Capacity Planners with: • Multiple forecasting algorithms • Low overhead with IBM z Systems Integrated Information Processor (zIIP)-eligible forecaster module *zIIP - z Systems Integrated Information Processor Forecasting is critical to avoid surprises…

The forecast report indicates when we believe MSU consumption will exceed the baseline for the current year

It is for the business to decide if this is a good or bad thing! The key is that you have the visibility to make an informed decision And Now A Demo!