I worked in presales to present insights into their ITSM operations gathered from Talos back to the client. My involvement was in data cleansing and preparation for injesting into Talos for supervised and unsupervised learning. Once Talos had created the reports, I would then import these to PowerBI to develop the insights. With AI we were able to identify:

• Issue candidates for automation e.g. “password reset”
• Lack of categorisation and service catalogue, poor summaries written in tickets
• 3rd party structured automation information posted into notes fields
• Categorical data located in unstructured notes fields
• Under-utilisation of knowledge
• Change requests logged as tickets leading to high level of tickets with low MTTR
• High level of critical abnormalities requiring problem RCA
• General lack of granularity in categories, impacting management reporting

This was followed up with an offer to the client to deliver the recommendations such as service desk training, restructuring categories, data cleansing, and knowledgebase improvements

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I was technical lead on a project worth $40k to implement the Helix Discovery SaaS solution. Since scanning hybrid infrastructure requires on-prem components there was still substantial Solution Design work required.

At this time the SaaS product was less than 18 months old and there were gaps in features and functionality in how it worked compared to the on-prem version. This led to challenges with unkown behaviour and bugs in the collector/outpost components which had to be resolved whilst maintaining client confidence in the solution they had bought.

An example challenge was in deploying shared outposts (documented as supported) between prod and dev SaaS instances. During deployment, an update was made to prod which delivered a change in key management to the outpost, and caused it to stop communicating with dev. The issue was resolved a week later when dev was updated, however it did mean that future architecture had to be updated to avoid this type of issue. Thankfully it did not impact delivery of the project.

The customer was also given value added data quality reporting allowing them to identify various gaps and misconfiguration across their estate.

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I was the technical lead on a project worth $170k to migrate the on-premise Discovery solution to to Helix Discovery SaaS.

This was a significant project as it was the first migration I had been asked to architect, so I had no templates or documentation to work off. I created the SOW, Solution Design and Project Plans. I decided that the best approach was to conduct a gap analysis and then work out what needed to achieved from there. As I had already worked several project with the SaaS platform, I was not totally in the dark.

The SaaS migration in some was would be technically easy because it was about determining what functionality would be decomissioned as it was not avialable in the cloud. However this needed to be carefully navigated with the stakeholders to reassure them that the functionality was either not needed for the SaaS platform, or there would be an alternative method/workaround for them to achieve the same results they got from the on-premise solution.

One of the interesting things turned up from the gap analysis was that they were under-licensed. As well as my company as a partner company being affected, we had a fiscal duty to report this back to the vendor. This did trigger a discussion with the client which was not initially well-recieved.

After many discussioned had taken place at the c-level I was asked for technical input as to whether there was a way they could be brought back into compliance. Fortunately, I did have an inelligant workaround solution which required a slightly more hands on approach to managing the scanning schedules and data collection. It did however provide satisfaction of the client and vendor, allowing the migration to continue successfully.

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I was technical lead on a project worth $200k to implement the Helix Discovery SaaS solution. Since scanning hybrid infrastructure requires on-prem components there was still substantial Solution Design work required.

At this time the SaaS product was less than 18 months old and there were gaps in features and functionality in how it worked compared to the on-prem version.

This led to challenges with unkown behaviour and bugs in the collector/outpost components which had to be resolved whilst maintaining client confidence in the solution they had bought. All bugs were logged and tracked with the vendor, but thankfully sufficiently minor that they did not delay implementation of the solution.

The customer was also given value added data quality reporting allowing them to identify various gaps and misconfiguration across their estate.

AI Led Operational Improvements

I worked in presales to present insights into their ITSM operations gathered from Talos back to the client. My involvement was in data cleansing and preparation for injesting into Talos for supervised and unsupervised learning. Once Talos had created the reports, I would then import these to PowerBI to develop the insights. With AI we were able to identify:

• Issue candidates for automation e.g. “password reset”
• Categorical data located in unstructured notes fields
• Under-utilisation of knowledge and overuse of top 5 knowledge articles suggesting need to break down into multiple topics
• Poor knowledge tagging to incident correlation, impacting the performance of the chatbot
• High MTTR for self-service leading to higher phone-resolved issues with shorter MTTR
• Discovery of sensitive (GDPR) information in unstructured text fields

This was followed up with an offer to the client to deliver the recommendations such as service desk training, restructuring categories, data cleansing, and knowledgebase improvements.

The post US Steel Manufacturer – ITAM & AIOps appeared first on fitzmoskal.

Over the years I have worked with a leading online betting brand to facilitate various technical and digital transformation requirements including straightforward software configuration to cloud platform migration.

My first engagement was to assist in improving their scanning performance and software license reporting which was accomplished within a three day deadline.

Later, I architected a move of their ITAM discovery solution from on-premise to a new cloud platform. I assisted in a number of areas which needed security clarification, particularly with the storage of credentials and data transfer. This did cause some delay in the migration but the client was grateful for our due diligence and went ahead with the move.

I also delivered corporate training to this customer, and worked on some customisations of their scanning solution with population of the CMDB. As a Principal Consultant at the time I oversaw the technical aspect of managed services solution that was provided to them.

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