ITOAVision

Similar to integration Q., by collecting data from ALL relevant IT tools available in the organization, ITOA allows us to finally see the whole picture.

I'm sure reducing the blame game with clear answers helps improve morale

one way is it is bridging the gap between IT Ops and ITSM with deeper insights into incident, problem, and other ticket data.

It brings together data from tooling that has traditionally been quite siloed, and combines it in useful ways

broad range data/insight for development, operations and line of business owners

analytics is silo agnostic, and allows an IT organization to become data driven rather than silo driven.

When correlated and analyzed together, ITOA is capable of delivering cross silo insights. e.g., being able to detect unauthorized changes (changes authorized or unauthorized tend to be true root causes of performance & availability issues.

Mobile Apps are supported by middleware infrastructures supporting virtual cloud environments. Operations Analytics provides the views of system messages, middleware and any solution with logs. A view across solution silos.

Facilitates both historical (retrospective) analysis and current online operation analysis using same technologies and approaches

Simple example .. Combine Performance data with log data to see how performance was affected by configuration changes

And Mobile Devices are paperweights without the supporting IT Infrastructure

Analytics also provides a quick view of infrastructure issues so an operations team can approach the web, database, solution stack and systems teams with gained insights on actions needed to address issues. The data key, facts in the pocket

@AmandaTene Removes subjectivity .... take us where the data leads!

No more 'my data' - teams must share data across those former silos to get maximum value - sum/parts stuff!

thru early warning detection. With self-learning analytics capabilities, you can baseline on what you know is normal, and then warn when you are outside of the learned normal range.

One of the pillars of ITOA is its predictive analytics. Predictive analytics allows IT ops organizations to detect risks early or before they turn into high impact incidents and act on them.

identification of emerging issues before they become service impacting. Move from firefighting to playing chess.

Some of the ITOA tools today can detect unauthorized changes which allows IT to investigate this before performance or security is impacted.

collecting and correlating operational data from a wide range of sources enables quicker, more accurate problem identification and root-cause analysis

Undertstand trends in the environment, and when those trends are likely to become problematic

From the banking industry, finding out that I am about ready to run out of space or issues with a transaction table on a key transfer transaction database is huge to prevent outages and large financial losses that occur in seconds.

Optimize resource allocation based upon trends and analysis of historical problems

putting the right data in front of you at the right time is critical. I agree with @ItoaLandscape the connection with changes and change management is a key.

Facilitate what-if scenario planning, close to real-time to explore impacts of proposed configuration changes

In the increasing mobile sensitive environment, the moment of IT Operations teams pain is instant and viral if an outage occurs. Analytics catch it before they realize there is an issue.

the bottom line is, you need to introduce self-learning, dynamic baselining, and anomaly detection capabilities into the workflow.

Eventually ITOA tools will help IT sift through data real-time for continuously improving and providing effective descriptive, predictive, and, eventually, prescriptive IT operations analytics.

Look for patterns or signatures of historically problematic behavior and alert operators

Extension-able, like in Log Analysis add additional Insight Pack for further environment coverage or can derive specific coverage packages.

the range of operational data that can be collected and analyzed - logs, performance, events, trouble tickets, change info even System z data

the breadth of data and analysis. IBM focuses on multiple use cases: "Predict, Search, and Optimize". And within those use cases, analysis on multiple data types: logs, events, performance metrics, z data, tickets...

Designed to integrate and share data and insights seamlessly to eliminate silos

You can predict, search and optimize across all the IT data

Taken together with the extensions into Performance Monitoring (APM) solutions and Service Desks, operations staff have the ability to get a broader picture of their environment.

predictive analytics that don't require a data scientist to configure.

integration with other IBM Service Mgmt solutions

IBM Operations Analytics provides more insight into IBM Middleware data (WebSphere, MQ, OMNIbus, APM), System Z etc.

Integration with help desk beyond those offered by IBM.

IBM's deep knowledge about what data and what perspectives provide maximum insight are conveniently packaged in these solutions

@janeclabby I think the integration point is an important one. Enables the user to have a complete IT Ops workflow.

easily attaches to any vendor's IT Service Management solutions to provide additional insight across operations, performance, and automation data

another unique point is that IBM's ITOA solutions are built with Watson capabilities inside.

Take a look at the Predictive Insights Integration with Performance Management: https://developer.ib...

Maybe I'm biased but Watson's intelligent algorithms for understanding normal and anomalous behavior are pretty superior

and the out-of-the-box entitlement and integration with Big Insights Hadoop is also unique from other vendors.

our teams work very directly with the Watson research teams on the latest and greatest algorithms and how they could be applied to ITOA

Works with any Data, i.e. Trouble tickets from ServiceNow and appl metrics from AppDynamics

We see ITOA as the “glue” that connects silos of data together. ITOA enables both proactive and reactive work.

ITOA correlates and analyzes data providing a robust view of the broader landscape

it can help an transform the operations workflow from reactive problem management to proactive problem management.

@ItoaLandscape Proactivity is key. We all want to fix problems before they occur!

@ facilitates DevOps collaboration

Combine (traditionally) siloed perspectives on system behavior into overall views and understanding

it can help reduce the "event noise" within your manager of managers through early warning. And it better isolates issues detected in your APM stack.

@rmckeown Agree Robert, combination of methods to draw intelligent correlations and extract useful insights from IT operations data.

issues identified before applications are released

Rapidly identify true problem areas and avoid the traditional multi-day email threads when chasing down issues

@janeclabby yes! and the DevOps persona is one of the biggest disruptions to the industry today. A key in this space is resolving their problems.

Exactly! . Essentially, analyzing the blend of data sources together (Performance, Logs, Automation and Change Data), it’s much easier to identify behavioral patterns, unusual event occurrences and anomalies. Proactivity.

ITOA can help you identify the right data to look at, at the right time so you can focus your resources appropriately.

@ItoaLandscape Yes! Aggregated views combining different perspectives

From a day to day operations perspective, an operations team can use the dashboards to get a quick periodic view of trending items. This gives them a chance to notice and drill down to determine if messages of concern.