Jira Service Desk and Insight for Ticketing and Signal Monitoring

anarcon deployed Insight for MX1 – a global media provider – where their Service Catalog and Technical Documentation is fully integrated with Jira Service Desk. As a result, MX1 is now able to monitor the SLAs and impact on any service in their catalogue, at a glance and instantly. Their next goal is to expand to 100,000 assets and remove other legacy systems.


MX1 is a global media service provider that has satellites in place to manage distribution of media to TV channels.


The internationally successful company distributes more than 3,000 TV channels, oversees the delivery of over 500 channels and provides content on video-on-demand platforms and streaming services for more than 8,400 hours. The services are offered from Munich, New York, Tel Aviv and Bucharest to provide optimal connections to the various satellites.


MX1 was looking for a service desk solution for signal monitoring, where they could also manage their entire service documentation.


With Jira Service Desk and Insight for asset management, we built a solution where they can track all tickets in Jira Service Desk, and link them to the technical service documentation (or their service catalog) that is managed in Insight asset management for Jira. The solution is running on Data Center with 250 agents on their own cloud infrastructure.


Insight as a Service Catalog


All services that MX1 services, including technical documentation such as satellite frequencies or the network of video signals – are mapped using Insight, which is integrated directly into the Jira Service Desk.


One of the information that are stored in Insight are the SLA levels. Because of strict SLA conditions in MX1’s service contracts, it is very important for the operations team to have the technical documentation in the ticketing system for the agents to have a direct and quick access to the information needed to shorten the resolution time for all incoming incidents.


With the new solution of Jira Service Desk and Insight, the team can now see immediately the effects each incident is having on the services they provide. For example, if a fiber channel breaks, it might affect 50 services. Because of how the data is modelled in Insight, the operations team will see this relationship, so they can immediately assess the urgency and scope of the incident.


Customization: SLA reports and displaying graphs in Confluence


SLAs are important to MX1 and all service contracts are conditioned by SLA. In Jira, the SLA calculations are based on issues, but we needed to measure it based on services which are stored in Insight. For each service, we calculate how much downtime there is for each service for a given time. To actively monitor SLAs in real-time, we customized a reporting module using data from Insight. The reports can be complicated, as the services have different calendars and the channels have different broadcasting times. For example , the Disney Channel is not broadcasting during the night, so that needs to be considered in the calculations.


The key to a successful implementation


When working with a customer on a solution, we recommend to setup a sandbox instance early in the process to try out different approaches. Don’t spend too much time on discussions and drawing possible solutions on whiteboards. It’s easier to get people involved by setting up a sandbox and allow them to play around and relate to the system. By doing that, people will see and feel what is possible and what is not. And this is were Jira and Insight are strong candidates, due to the fact how relatively easy it is to set up.


Written by Sandra Axelsdottir from Insight. Read full article here.