I was asked to provide a health check with insights into the clients Discovery operations. I created a custom application called Pithos – a python-based application which collected data from CMDB and Discovery. This data was then imported into Power BI and we were able to present the following back to the client:

• High disk utilisation
• Presence of core dumps
• Segregated architecture, but no network segregation
• Sensitive data such as plaintext usernames and passwords stored in unstructured data fields
• Scan schedules impacting performance

This was followed up with a roadmap of improvements for the client with the option of being delivered by my company.

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I worked with presales to deliver a $55k project with insights into the clients Discovery operations created with Pithos – a custom built python-based application which collected data from CMDB and Discovery. This data was then imported into Power BI and we were able to present the following back to the client:

• Sensitive data filters not capturing plaintext username/password
• Under-specced Outpost sizes causing performance issues
• Active user accounts from departed users not removed
• Various data quality issues
• Configuration discrepencies between prod and dev environments

This was followed up with a roadmap of improvements for the client which included development of a runbook, and 10 consultancy days of remediation.

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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 worked with this German company to enhance their Discovery and CMDB with various storage metadata and data from unsupported storage systems. I wrote extensive TPL code which integrated with APIs for NetApp, Dell Isilon, IBM Spetrum, and Nasuni.

For Nasuni I had to develop the whole model using data extracted from the APIs to model the Management Console, Volumes and Shares.

The outcome of this project was to allow the client to accurately track storage usage and billing.

During this time I also assisted the client in troubleshooting Azure discovery and retrieving additional matadata from VMware.

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As part of a larger digital transformation I was responsible for the architecture of their Discovery, modelling application architecture and data integration pipelines to the CMDB.

The initial deployment was minimal and did not cover the whole estate, which was airgapped. I was challenged to come up with an architecture which would be suitable enough capture data across the airgapped environments. The proposed solution involved manual DB snapshots which would be transferred by ftp, however this was later dropped in favour of deployment of a mutual shared platform, which was desperately needed.

This was a part-time multi-year engagement, during this time I developed and delivered various customatisations to their data collection and pipeline, such as:

• SSL Certificate Discovery
• Netcool edge device intergration
• Service modelling
• Reporting and analytics
• Written maintenance manual

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I was responsible for the improving the managed service architecture of a multi-year service contract already in-flight. There had been significant issues raised over the quality of the service up until my engagemement.

The main complaints were:

• Support resource not seen to be solving any reported issues
• Missing roadmap meetings
• Not feeling the value

An action plan and strategy was put in place, for me to conduct quarterly service reviews where I would present the latest features of the products and recommend strategy for upgrade and utilisation of these features, including any enhancements we could provide to the service.

The support resource issue was identified as being a follow on outcome of the customer not willing to log tickets and instead engaging the named resource directly. In this way the resource was being treated as a contractor and being asked to work on various unspecified tasks and issues. In discussing the issue with the client, I suggested they could either continue with no SLAs and agree to the support resource under 1-day per week effort, or that in order for us to track performance and ensure requests were deailt with, they would need to engage with the service and log tickets.

However, as many of the requests would have been out of the scope of the service and meant engagement with professional services, they did not want to implement this change. They prefered to carry on under the existing arrangement, without further complaint.

During this time I was also able to implement health checks for them and identify a number of security vulnerabilites which were esclated to their CISO. One was the identification of plaintext username/password strings in running processes, and the other was production level software running under a non-service account credential.

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I worked 3 short projects with a US-based energy company over a period of three years to develop customisations to the data pipeline to their CMDB. This was to enable a front-end form for application ownership selection. For this they needed specifically to be able to extract metadata from their IBM DB2, MSSQL, Oracle, MongoDB and MariaDB databases for promotion to the front-end display.

The solution involved custom TPL code applied to BMC Discovery, which used a combination of SQL connections of JDBC and API connectivity with MongoDB. Both Discovery and the CMDB sync connections needed to be modified to make it work.

MongoDB presented the most challenging connection as Discovery was not built for a direct integration, so the solution called for running the API retrieval queries directly on the server as it scanned, with a local encrypted text file which contained the API credentials. The output was then retrieved the normal way.

The solution allowed for the client to be able to correctly identify and assign ownership for their database dependent applications.

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I was contracted to help win a bid for providing a managed service worth $200k to a large US-based vehicle manufacturer. They were intially discussing a multi-year deal for plant inventory discovery, however it was quickly realised by the client that it would make sense to turn this into a managed service.

The service included upgrade of current Discovery solution with right-sizing the architecture, installation of Remedy with CMDB and support services. The scope of Discovery was to scan the plant networks – the challenge being that these were on profinet and were not only sensitive equipment but scanning was only permitted under very strict windows.

We managed to complete the implementation of the solution upgrade and installation, with the implementation of the full managed service coming later due to delays on the client end. As part of value add of the service, the customer was also provided with a custom solution I developed in python that worked with the Discovery API to be able to load IP ranges with updated location information and automatically update the scan data and schedules.

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I was part of a consultancy team to deploy a new ITAM function and I was specifically responsible for discovery and integrations to the CMDB, a project worth $3m over 3 years.

The particular challenges faced were that all of their IT functionalities were outsourced to different partners and vendors and some of these partners insisted on work orders to help us with data gathering. This was a complex challenge which required some level of obtaining buy-in and negotiating with the client to get work orders processed as quickly as possible to meet our tight deadline.

I held multiple workshops with the client and partners – and we deployed a “waterfall” data pipeline for populating the CMDB.

After deployment was completed, an issue arose with the accuracy of the CMDB and the wording of the contract which was “95%” accuracy, with no caveats. The first milestone payment was held back whilst the team resolved this critical issue.

I was not directly involved with the client by this time, but as part of resolution I suggested to the account management team that they needed to ensure the contract wording was updated in future to specific automated data only. I also assisted with identifying the sources of data, and types of data – such as that which would be manually entered and would ultimately be down to the client to ensure it met “95%” quality.

The final approach with the client was to review all CIs and fields within the CMDB to be populated and adopt a MoSCoW approach, determining which data were neccesary and which data they agreed, for example, would be impossible to obtain. This massively improved the baseline results and showed that CMDB population was already very close to “95%”. After some additional work on the data pipeline the customer agreed to release the first payment milestone.

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I was hired as a Delivery Manager and Enterprise Architect for the global rollout of Discovery and CMDB for an international Managment Consulting company. This was a 2 year programme directed at North America and European regions worth €2m.

In the first year I identified and implemented €90k worth of cost savings to the programme by automating level 1 support so that the resources were no longer required. I led a team of 8 offshore engineers in India and Poland and was responsible for their training and managing their progress on the the deployment to individual accounts.

I reported to the Programme Manager and was responsible for not only the software architecture but the security design needed to obtain global CISO sign off and allow the programme to proceed when it hit a major hurdle and was blocked by security compliance. One of the many hurdles was implementing RBAC into the solution which had not been designed for full RBAC control.

I worked with one of my lead engineers to find and document all the group permissions available in the tool, then employed a hack to prevent certain pages from loading without the right permissions. This satisfied the requirements of Global CISO. During the process we even discovered a vulnerability that allowed access without permissions, which was reported back to the vendor. The vendor was so impressed that they asked if they could see our documentation.

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