The content of this blog is based on two days spent in company with Atlassian’s Jira Service Management (JSM) product teams in mid December 2022. Attendees included European partners and customers. Throughout this blog there is a shortage of ship dates because Atlassian has committed to publishing a white paper in January 2023 to include targeted ship dates.
This was the first occasion Atlassian held a purely JSM focussed event in Europe and it is a reflection of their very significant investments ($250m) in the product since 2019 to build out JSM as a fully fledged ITSM product. JSM first launched back in 2014 when Atlassian discovered that 38% of its customers were adapting Jira Software (JS) as a simple helpdesk tool.
Atlassian is now starting to look and feel more like an ‘enterprise’ company as they set their sights on a large new opportunity – the IT market as distinct from the Software Development Life Cycle (SDLC) market. Gartner now places JSM in the top right hand quadrant for IT Service Management.
The breadth of the JSM solution driven by acquisitions and organic development now encompasses the following functionality; Deployment Risk Assessments, Major Incident Management and Post Incident Review, Alert Storm ‘noise’ Reduction, Configuration Management Database (CMDB) as well as Slack and Teams Integration into JSM Chat. For existing users of JSM its important to note that older features such as SLA and Queue Management etc. is layered into all of these new modules.
Deployment Risk Assessments
The demo’s we saw were very much based on staged deployment practices where a CAB and IT Operations teams control deployments and have the capability to rollback a deployment from within JSM. Given that software deployment processes cover a broad spectrum from Continuous Integration (CI) (ranging from immediate to monthly) through Continuous Development (CD) Atlassian’s tools support all modes of working but as this event focussed on JSM the demo’s assumed staged deployments with less automation but with the potential to further reduce the manual effort.
The Atlassian Risk Assessment inference engine will assess a number of data points pertinent to any build and provide a ‘score’ to inform CAB decisions. This in turn can be further automated to deploy builds directly to production for features that are deemed low risk by the Risk Assessment engine.It is clear that the product set facilitates ongoing shifts left and further automation in any journey from CI to CD. This approach helps engineering and business teams to gradually build confidence in further automation of their deployment pipelines.
Major Incident Management(MIM) and Post Incident Review(PIR)
Since Atlassian acquired OpsGenie there has been some grumbling that there was duplicate functionality and customers were finding it difficult to know where to implement functionality. There were a couple of reasons behind this -the major one being that customers had built out their own MIM in older versions of JSM and there were also some standard workflows that could be deemed MIM start points.
The product people we spoke with acknowledge there is feature duplication between OpsGenie and JSM. Their dilemma is that OpsGenie only clients expect continuity without JSM. The advice to clients is that if your start point is JSM – you should build all of the MIM and PIR functionality in JSM. The clients who had already built their own MIM workflows bought the promise that Assets and data feeds from CI/CD tools were high value add components to OpsGenie and appreciate it’s better that Atlassian provides this type of functionality out of the box rather than having to maintain their own in house versions.
All data captured during major outages are timestamped and recorded for subsequent PIR.
Alert Storm ‘noise’ Reduction
This functionality will marry alerts from different logging or monitoring tools to clearly identify an incident. If the incident becomes a P1 the agent can assemble a team to swarm on zoom or via a conference bridge to further bear down on relevant data thereby reducing the mean time to diagnose (MTTD) an incident.
Configuration Management Database (CMDB)
Atlassian has rebranded this functionality Assets, a component that is available only in the JSM Premium edition. Use of the term Assets explains that the product can go beyond standard IT components and include anything a business deems an asset including cars, furniture, people, a persons accreditations, facilities etc.
At the heart of Assets is a graph database which is very powerful. Atlassian are currently transitioning away the Assets Discovery component which finds and ingests IT asset meta data to an API centric approach. Early in 2023 they will publish the Assets API together with some of the more popular integrations themselves and they are encouraging third parties to hoover up the balance. They are committed to delivering SCCM, JAMF and Azure. They hope AWS will build an integration and if not they will do so themselves.
Slack and Teams Integration into JSM Chat
Atlassian markets this suite of tools as Unified Help.
Today JSM provides issue capture and resolution from within Slack or Teams and the JSM agent need not leave the JSM application. Users can open tickets and track their progress from within the chat tool of their choice and in ‘background’ mode the Jira ticket is updated and accessible via the standard portal.
Available now and in early release is a virtual agent (bot) described as a tailored AI model including 10 of the most common IT intents (challenges) e.g. password reset. Thereafter client teams must train the model by mapping local utterances e.g. (I forgot my password. I lost my passkey) mapping to intents and building new intents. Atlassian has not yet decided if Machine Learning will be global or local – so if clients ‘opt in’ their data the model gets better but this approach could be impeded by GDPR. The goal is that new intents are discovered over time. The promise is that client teams will not be required to spend hours training the bot – its radio buttons, drag and drop with a simple UI and will not require a highly skilled person.
Its worth knowing that when you implement the non AI element of this technology the volume of calls goes up initially as it’s easier for users to log a call but now you are measuring the all of the issues so real data is collected on the volume and the nature of all issues.
Beyond IT and Engineering Atlassian are now targeting the ‘enterprise’ market where they have acquired and bundled into JSM a low code/no code tool for generic business applications. This set of product features enables business teams to engage their end users as a service. JSM now includes a significant number of oven-ready forms and workflows as templates for HR, Legal, Vendor Onboarding, Facilities Management, Finance etc.
Several clients in IT roles we spoke with at the event have provided low cost service desk solutions to business units that were running their ‘operations’ on spread sheets, email and slack. This recent blog article describes the solution more comprehensively using customer service as an example.
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