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The Australian Defence Reserves Support Council Awards JDS

April 28, 2017 NewsJDS

Lt. Samuel Abdelsayed receives the 'Employer Support Award - Medium Business' on behalf of JDS. — Lt. Samuel Abdelsayed receives the ‘Employer Support Award – Medium Business’ on behalf of JDS.

JDS has again been awarded by the Australian Defence Reserves Support Council, an organisation which assists Reservists both within Australia and overseas.

This is the second time JDS has received an ‘Employer Support Award’. Staff member, Lieutenant Samuel Abdelsayed, nominated JDS for being supportive of his Reserve activities and enabling him to attend all training activities and courses.

JDS Managing Director John Bearsley says that Sam’s service in the defence forces is to be highly commended, highlighting the role of service in developing professionalism and problem-solving skills.

Thanks go to both the Defence Reserves Support Council, and to Sam for his demonstration of leadership and commitment.

Read more:

JDS Receives Award from ADRSC

JDS is now a CAUDIT Splunk Provider

April 26, 2017 Higher Education, News, SplunkJDS

Splunk Enterprise provides universities with a fast, easy and resilient way to collect, analyse and secure the streams of machine data generated by their IT systems and infrastructure. JDS, as one of Australia’s leading Splunk experts, has a tradition of excellence in ensuring higher education institutions have solutions that maximise the performance and availability of campus-critical IT systems and infrastructure.

The CAUDIT Splunk offering provides Council of Australian University Directors of Information Technology (CAUDIT) Member Universities with the opportunity to buy on-premise Splunk Enterprise on a discounted, 3-year basis. In acknowledgement of JDS’ expertise and dedication to client solutions, Splunk Inc. has elevated JDS to a provider of this sector-specific offering, meaning we are now better placed than ever to help the higher education sector reach their data collection and analysis goals.

What does this mean for organisations?

Not-for-profit higher education institutions that are members of CAUDIT can now use JDS to access discounted prices for on-premises deployments of Splunk Enterprise. JDS are able to leverage their expertise in Splunk and customised solutions built on the platform, in combination with their insight into the higher education sector, to ensure that organisations have the Splunk solution that meet their specific needs.

Secure organisational applications and data, gain visibility over service performance, and ensure your organisation has the information to inform better decision-making. JDS and Splunk are here to help.

You can learn more about JDS’ custom Splunk solutions here: JDS Splunkbase Apps

JDS wins AppDynamics Partner Award

November 15, 2016 AppDynamics, NewsJDS

JDS Win AppDynamics 2016 Emerging Markets Partner of the Year Award

We are delighted to announce JDS have received the AppDynamics 2016 Emerging Markets Partner of the Year Award at AppSphere 2016 in Las Vegas on the 15th Of November. As a team, we are very proud of this award as it is the result of a lot of hard work from a lot of talented people at JDS.

John Bearsley, Managing Director of JDS said, “AppDynamics has stormed the market in the past few years as one of the leading next generation Application Performance Management Tools. We have seen first hand how it can transform the monitoring landscape for our customers providing them great visibility into the end user experience and the performance and availability of their business critical applications. AppDynamics is a vendor we are proud to support and we look forward to helping many more customers derive its significant benefits in the years to come”.

To see how JDS can help ensure it works with AppDynamics check out our AppDynamics Page.

Machine Learning with Splunk

July 16, 2016 News, SplunkJDS

Learn about how to optimise machine learning using Splunk, with this video from JDS Consultant Danesen Narayanen.

Filtered Reference Fields in ServiceNow

June 6, 2016 ServiceNow, Tech TipsJDS

One common requirement JDS sees when working with ServiceNow customers is the need to dynamically filter the available choices in reference fields. This can be useful in both general form development and record producers.

Consider the following business requirement:
A national charity wants to implement a feedback form for its staff.
As staff work across a variety of areas, it’s important to match staff with the correct department, so the correct department manager can be notified about the feedback.

The charity has provided us with some sample data for testing:

Departments

Department Staff

As this feedback form is available to anyone working within the charity, JDS has built a record producer to capture feedback using the Service Catalog within ServiceNow.

To limit the available choices to only staff within a particular department, we’ll need to use a script that is triggered whenever anyone starts typing in the field or accesses a value lookup for the variable “Who would you recommend?”
Although there are numerous ways to approach this, always look for the simplest option. Rather than calling a custom script, use the Reference qualifier field in ServiceNow to set up the relationship.

Normally, fields on a form can be referenced using current.fieldname but record producers within a service catalog are slightly different, and need a slightly more qualified reference of current.variables.fieldname.

Let’s look at the results…

If we select “Community Outreach” the list of staff available under “Who would you recommend?” is limited to Jane Brown and Sarah Smith.

If we select “Youth Action” the list of staff available under “Who would you recommend?” is limited to Matthew Jones and Sarah Smith.

ServiceNow is a powerful platform that allows for advanced customisations to ensure a good fit with business requirements.

Completing the APM picture with AppDynamics EUM

May 20, 2016 AppDynamics, NewsJDS

How are your customers really experiencing your apps right now? How is your business reputation, loyalty and revenue being affected by the world between your application servers and your customer? AppDynamics End User Monitoring (EUM) completes the APM picture by letting you See, Act on, and Know about your customers' real experiences in real time.

With EUM, AppDynamics extends the valuable insights it provides by tracing all the way out to the browser or mobile app giving complete end-to-end visibility for every customer experience.

Watch this session to learn:

Why you need to understand the full customer experience on top of what is happening in your data centre.
The customer experience metrics that matter most.
How AppDynamics EUM gives visibility of the complete picture from your customer's devices to and through your backend APIs and applications.
How EUM Synthetics further helps you to Know at all times that your apps are working at their best.

Discover exactly how your end users experience and engage with your applications.

Straight-Through Processing with ServiceNow

May 10, 2016 ServiceNow, Tech TipsJDS

How much time is your organisation wasting on manual processes?

What is the true cost of lost productivity?

Straight-through processing (STP) has long been recognised as the Holy Grail of business processes, as it promises to eliminate manual paper forms along with human intervention at the back end. By avoiding the duplication of effort, straight-through processing promises to drastically improve the speed and accuracy of business processes.

Although straight-through processing has been attempted by numerous enterprise applications, such as SAP, IBM and Oracle, the problem has been that no single system handles data collection in a consistent, comprehensive manner.

Single System of Record
ServiceNow is unique among enterprise applications in that it uses a single system of record with common/shared supporting processes, such as workflows and notifications. Although there are hundreds of tables in the ServiceNow database, they are all closely related, and are often based on the two core tables — CI (Configuration Item in a CMDB) and Task. In ordinary business terms, CI and Task translate into objects and actions—and ultimately, all business processes revolve around things/people, and actions applied to them.

Source: https://thisiswhatgoodlookslike.files.wordpress.com/2014/05/platform.png

By using a common architecture for all applications, ServiceNow avoids the problem of integrating with conflicting data structures/applications. In essence, everything speaks the same language.

Straight-through processing
ServiceNow has a single system of record, making it ideally suited to straight-through processing. ServiceNow has the flexibility to adapt to multiple different application requirements whilst leveraging common structures and components. For example, fleet car management, purchase orders, and timesheet entries are entirely different business processes, but in essence they deal with objects (cars/orders/people) and activities (driving/tracking expenditure/working hours), and have similar requirements (approvals, workflow, records management, notifications, common master data, etc).

Essentially, the ServiceNow Automation Platform allows different business processes to be captured without changing the underlying system.

JDS recommends deploying straight-through processing in an iterative manner, using an agile approach.

Validate user input with the target system
Digitise paper forms
Straight-through processing
Automation

By adopting an agile approach with implementation in phases, organisations can see incremental benefits throughout the project.

Phase One: Validate user input with the target system
For straight-through processing to be successful, ServiceNow needs to validate incoming information to ensure it’s compatible with the target system. To do this, ServiceNow forms need to be pre-populated with values taken from the core system.

For example, organisational data such as cost centres and approvers would be integrated with ServiceNow overnight to provide defaults/selection values within ServiceNow form fields. This approach provides the best performance, as access to up-to-the-minute data is not typically required, and the data integration ultimately ensures the consistency and accuracy of straight-through processing.

Phase Two: Digitise paper forms
Once ServiceNow has default values to validate end user input at the point of entry, existing paper forms can be digitized.
In the first phase, the front-end will be transformed with forms which are pre-filled and built upon a responsive UI, whilst the back-end process is unchanged.

Although it is possible to automate the entire business process at once, in practice, most organisations prefer a phased approach so they can manage change and reduce the risk of any inadvertent impact on their core system during this time of transition.
Note that this approach immediately has a positive impact on end users, as the old paper forms have been transformed and are now made available through a searchable and user-friendly service catalog, while back-end processes stay largely the same, avoiding any disruption to existing services. The organisation has the opportunity to introduce streamlined processing without causing upheaval in the back office.

Phase Three: Straight-through processing
Once the digitization of paper forms has been established, it is time to automate the process to introduce efficiency to the back office.

As straight-through processing is often interacting with core systems associated with Finance and HR, JDS recommends establishing an approval workflow process. Instead of manually entering all the request information, back office staff now provide oversight and approval of straight-through processing.

Phase 4: Automation
There may be some business processes which involve multiple parties and integrate with multiple systems end-to-end that could be automated in their entirety, such as ordering of software or employee on-boarding. In this case, ServiceNow can streamline straight-through processing with the use of ServiceNow Orchestration.

Orchestration is implemented by workflows in ServiceNow, allowing JDS to configure complex processes that span multiple systems. These may include activities such as approval and follow-on tasks which utilise data outputs from a system called inside the workflow to determine the next action.

How much is manual processes costing your organisation at the moment?

Think of how much productivity is lost because users are forced to fill out paper forms, or back office staff are required to enter information into multiple systems. By implementing straight-through processing with ServiceNow, JDS can help you streamline your business processes, saving time and money, while radically improving your customer satisfaction.

How operational health builds business revenue

February 10, 2016 News, SplunkJDS

Splunk IT Service Intelligence (ITSI) is a next-generation monitoring and analytics solution that provides new levels of visibility into the health and key performance indicators of IT services. Use powerful visualizations and advanced analytics to highlight anomalies, accelerate investigations and pinpoint the root causes that impact service levels critical to the business.Join this session to learn how to:

Translate operational data into business impact.
Provide cross-silo visibility into the health of services by integrating data across the enterprise.
Visually map services and KPIs to discover new insights.
Transform machine data into actionable intelligence.

What is Service Intelligence?
IT operations is responsible for running and managing the services that businesses depend on. Service intelligence improves service quality, helps IT make well-informed decisions and supports business priorities.

Why Splunk IT Service Intelligence?
Splunk ITSI transforms machine data into actionable intelligence. It provides cross-silo visibility into the health of services by integrating data across the enterprise, visually mapping services and KPIs to discover new insights, and translating operational data into business impact. With timely, correlated information on services that impact the business, Splunk ITSI unifies data silos, reduces time to resolution, improves service operations and enables service intelligence.

ensure IT works with

Splunk: Using Regex to Simplify Your Data

January 13, 2016 Splunk, Tech TipsJDS

Splunk is an extremely powerful tool for extracting information from machine data, but machine data is often structured in a way that makes sense to a particular application or process while appearing as a garbled mess to the rest of us. Splunk allows you to cater for this and retrieve meaningful information using regular expressions (regex).

You can write your own regex to retrieve information from machine data, but it’s important to understand that Splunk does this behind the scenes anyway, so rather than writing your own regex, let Splunk do the heavy lifting for you.

The Splunk field extractor is a WYSIWYG regex editor.

When working with something like Netscaler log files, it’s not uncommon to see the same information represented in different ways within the same log file. For example, userIDs and source IP addresses appear in two different locations on different lines.

Source 192.168.001.001:10426 – Destination 10.75.001.001:2598 – username:domainname x987654:int – applicationName Standard Desktop – IE10
Context [email protected] – SessionId: 123456- desktop.biz User x987654: Group ABCDEFG

As you can see, the log file contains the following userID and IP address, but in different formats.

userID = x987654
IP address = 192.168.001.001

The question then arises, how can we combine these into a single field within Splunk?
The answer is: regex.

You could write these regex expressions yourself, but be warned, although Splunk adheres to the pcre (php) implementation of regex, in practice there are subtle differences (such as no formal use of look forward or look back).

So how can you combine two different regex strings to build a single field in Splunk? The easiest way to let Splunk build the regex for you in the field extractor.

If you work through the wizard using the Regular Expression option and select the user value in your log file (from in front of “undername:domainname”) you’ll reach the save screen.
(Be sure to use the validate step in the wizard as this will allow you to eliminate any false positives and automatically refines your regex to ensure it works accurately)
Stop when you get to the save screen.
Don’t click Finish.

Copy the regular expression from this screen and save it in Notepad.
Then use the small back arrow (highlighted in red) to move back through the wizard to the Select Sample screen again.
Now go through the same process, but selecting the userID from in front of “User.”
When you get back to the save screen, you’ll notice Splunk has built another regex for this use case.

Take a copy of this regex and put it in Notepad.
Those with an eagle eye will notice Splunk has inadvertently included a trailing space with this capture (underlined above). We’ll get rid of this when we merge these into a single regex using the following logic.
[First regex]|[Second regex](?PCapture regex)

Essentially, all we’ve done is to join two Splunk created regex strings together using the pipe ‘|’
Copy the new joined regex expression and again click the back arrow to return to the first screen

But this time, click on I prefer to write the regular expression myself.

Then paste your regex and be sure to click on the Preview button to confirm the results are what you’re after.

And you’re done… click Save and then Finish and you can now search on a field that combines multiple regex to ensure your field is correctly populated.

Author: JDS

What does this mean for organisations?

JDS Win AppDynamics 2016 Emerging Markets Partner of the Year Award