Author: Dylan Griffiths

Why effective project prioritisation in consultancy is crucial

Posted on: 10 October 2024
Why effective project prioritisation in consultancy is crucial

When it comes to consultancy, project prioritisation is critical so that customers receive urgent or important work first before less vital items. In straightforward projects with one product owner and a finite backlog, you can approach this issue by working through the backlog and asking them to label them using MoSCoW, the prioritisation technique used in project management and business analysis to help stakeholders understand the importance of various requirements, for example. It’s when you move to a project with multiple product owners and an ever– extending backlog that the problems appear, however.  

So, what are the common project prioritisation challenges arising in consultancy nowadays and what solutions are available to consultants to solve them? 

Common challenges in consultancy around project prioritisation

Within each project, each stakeholder (this could be from multiple products, multiple product owners or stakeholders without a product owner) will bring their own backlog, each believing that their demands are the most important and that all your resources are theirs to use. Negotiating between these product owners can be difficult, especially as they may have their own deadlines that they’ve committed to, perhaps only needing your resources for part of their project and a delay could cause their entire project not being delivered on time.  

While earlier and clearer communication would undoubtedly help with these issues in the long run, where do consultants start in the meantime? 

How consultants can improve project prioritisation

Consultants that refer to a categorical prioritisation list for each project (such as the example below) will notice immediate and significant improvements. By scoring each project against a list of categories, with the resulting score used to order the backlog and any incoming items, their respective priority and importance will be illustrated to the wider business.  The category list is:  

Once a project has been scored on each of these points, the total score is calculated. This is then used to rank projects against each other. It’s important to reassess the time rating approximately every three months, as this rating will need to be increased to reflect the real-world situation.  

Benefits of this approach

The advantage of adopting this approach is that it enables you to provide an explanation as to why certain projects are higher priority than others rather than using a more subjective approach. It’s possible to add a higher rating to categories so that the calculation better represents the company’s priorities.  

Potential difficulties of this approach

Some of the issues we’ve noticed so far are that these categories don’t necessarily work as well for enabling items such as a pilot, which won’t deliver any benefit to the system on its own but is required before the new feature can be started. To bolster this, we had to consider the ultimate deliverable being enabled, otherwise, the supporting item would score too low.  

 Technical debt is another type of work that doesn’t quite fit into these categories, which is why we ultimately decided to remove it and prioritise it separately.  

 Despite all the categorisation and discussions, you can end up with a list that doesn’t quite correspond with your gut feeling based on market trends. To mitigate this, a review was organised every few months to monitor scoring accuracy.  

Conclusion  

For projects without a finite backlog where upfront prioritisation isn’t possible, this approach allows you to prioritise against existing work in flight. However, it’s important to account for the amount of time, effort and morale downturn it takes to pause and restart.  

This method of prioritisation is ultimately particularly a useful tool for prioritising the constant stream of incoming projects from multiple product owners. The conversations that come out of the prioritisation are also of substantial value, and to some extent, enable the prediction of what will be delivered in the near future.  

To learn more about project prioritisation in consultancy, speak to one of CACI’s experts today. 

How Mood is guiding organisational transformation

Posted on: 23 September 2024
How Mood is guiding organisational transformation

In today’s rapidly evolving business landscape, organisations nowadays are increasingly tasked with balancing agility with strategic foresight. As digital transformation accelerates, aligning operational processes with overarching business strategies while simultaneously maintaining governance, compliance and scalability is becoming a prevalent challenge. This delicate balancing act requires not only clear visibility, but also an integrated approach that unifies process modelling, digitisation and enterprise architecture.

So, how is Mood enabling businesses to achieve this?

Mood BPMN modelling & process digitisation: bridging the gap between design & execution

At the heart of any successful transformation initiative is a clear understanding of the processes that drive the organisation. Mood offers robust BPMN (Business Process Modelling Notation) 2.0 modelling capabilities that empower business analysts and architects to map, manage, analyse, optimise and communicate business processes. Through interactive models, even the most complex workflows can be broken down into manageable stages and tailored for different stakeholders. This dynamic visualisation ensures that processes are both transparent and adaptable, leading to improved conformance, powerful collaboration, and seamless management across the enterprise.

Where our modelling capabilities ensure no gaps exist between process design and implementation, our drag-and-drop, no-code process digitisation tools take things a step further. Mood enables users across the organisation to digitise complex business processes from end to end, accelerating digital transformation programmes. This approach not only empowers non-technical users to take ownership of their workflows, but also ensures scalability and flexibility, allowing the organisation to remain agile and grow without the overhead of constant change management.

By integrating multiple data sources and enabling rich interaction with real-time insights, Mood reduces the reliance on disparate tools like spreadsheets and manual processes. Instead, data is aggregated in a shared context, enabling it to be interrogated and analysed with precision. The result is streamlined operations, significant efficiency gains, and reduced operational costs,; all while maintaining consistency and governance.

Enterprise and business architecture modelling: aligning strategy with execution

The foundation of any resilient and scalable organisation lies in its architecture. Mood offers powerful enterprise and business architecture capabilities that allow organisations to strategically align business objectives with operational processes and IT infrastructure. By providing comprehensive tools and blueprints to design and optimise current and future state architectures, Mood ensures that enterprise decisions are not only grounded in clear insights, but are also executed with precision and consistency.

Our platform supports the creation of layered, dynamic models that break down complex organisational structures into navigable and digestible components. These models empower enterprise architects, business strategists and decision-makers to visualise the impact of change initiatives, mitigate risks and maintain alignment with regulatory standards. By integrating architecture with BPMN process models and process digitisation, organisations can bridge the gap between strategic planning and operational success. This end-to-end traceability ensures that there are no gaps from vision to execution, providing a holistic view of enterprise performance that supports continuous improvement.

Businesses can adapt and evolve their architecture in tandem with market changes or organisational growth by leveraging Mood. Our platform’s comprehensive integration options, coupled with robust data management, creates a unified environment that drives optimised decision-making, reduces silos and fosters cross-functional collaboration.

Empowering stakeholders across the business through virtualisation 

In an increasingly complex business environment, organisations need more than just isolated solutions; they need a cohesive, living representation of their operations and strategy. Mood offers exactly that. By combining the strengths of BPMN modelling, process digitisation and enterprise architecture, Mood enables businesses to create a living virtualisation of their organisation, empowering stakeholders across the enterprise to access, update and interrogate data through their unique perspectives while maintaining consistency and robust governance.

Whether it’s a business analyst optimising day-to-day workflows, an enterprise architect planning for future growth or an IT leader driving digital transformation, Mood offers tailored insights and tools for each role. The platform’s integrated approach ensures that everyone, from the C-suite to the front line, is aligned around a single, consistent version of the truth. This not only fosters collaboration, but also drives better decision-making and more agile responses to change.

How Mood can safeguard the future of integrated business and enterprise modelling

As businesses face mounting pressures to stay competitive while maintaining operational excellence, the need for a fully integrated approach to process management and enterprise architecture has never been greater. Mood is uniquely positioned to deliver this by offering a comprehensive, flexible, and scalable platform that aligns strategy with execution, drives efficiency, and supports long-term growth. By enabling organisations to create a living virtualisation of their operations, Mood transforms the way businesses plan, manage, and evolve,; empowering stakeholders at every level to succeed.

To learn more about how we can help you adopt Mood to enhance your business and safeguard it for the future, contact moodenquiries@caci.co.uk  

How building a network automation content library accelerates efforts

Posted on: 19 September 2024
How building a network automation content library accelerates efforts

CACI  has a rich heritage in network engineering, IT infrastructure, delivery assurance and network automation, including NetDevOps practices such as network coding, CI/CD pipeline optimisation, network lifecycle management and more. Our network automation experts engage in a variety of activities for our clients, a few of which include:

Telco (ISP)

  • Build out of a NetBox NSoT (Network Source of Truth) and modelling of an ISP lab environment that allows for seamless network inventory management, such as VLANs, VRFs, IP linknets, cabling, chassis-to-blade mapping and more.

Telco (ISP)

  • Build out of a Python Flask-based application (including frontend, backend and API) “LabDash” to enable management of changing Telco inventory, such as line cards, SFP transceivers, patching – within a lab environment used for Telecommunications (Security) Act 2021 (TSA) testbed and network build-out activities.

Finance

  • Build out of a customised observability solution to complement in-flight NMS, OSS and BSS tooling, with customised metrics around specific values of SNAT count, TCP session count and related for a complex load-balanced application solution.

Defence

  • Build out of IaC blueprints to deploy complex NVA router, NVA firewall, Load Balancer ADC and other centralised infrastructure as part of an Azure landing zone deployment.

In everything we do, we always follow DevOps and software development practices, most notably being “DRY” (Don’t Repeat Yourself). As such, we are building a library of automations and network code that can benefit future clients through a faster delivery of NetDevOps solutions – leading to a flywheel of network affects, meaning the more we do for clients, the more we learn and can apply our shared learnings – and code libraries, modules and approaches – to accelerate network automation efforts for future clients.

Automation library

Giving back to the network automation community

We know that we can’t do this alone, and equally to ensure we  attract and maintain top-quality NetDevOps talent and network automation consultants, we give back to the wider network automation community by building several tools within our public GitHub Repository. These include:

PAC File Performance Comparer 

PAC File Performance Comparer is intended to be run on an ad-hoc basis to allow for a quick comparison using the Pacparser to calculate both the time difference (i.e. performance optimisation gain of the JavaScript PAC code refactor) and conformity against a test set of URL behaviours (i.e. proxy or direct) for a “before” and “after” PAC (Proxy Auto-Configuration File) refactoring exercise.

Azure JSON IP Feed to Juniper SRX Checker

Azure JSON IP Feed to Juniper SRX Checker is intended to be run on a periodic (i.e. daily) basis to check for updates, changes or deletions made by Microsoft to their Azure IP Address Ranges as per the Microsoft-published Azure IP Ranges and Service Tags – Public Cloud JSON feed and convert into Junos SRX-compatible security policy syntax/configuration.

Adding to our sandpit

Whenever we develop a module, code, artefact or solution for a client, we always ensure that we contribute any non-sensitive elements of this network code back to our “sandpit”, which is a growing area of internal “scraps” of code and approaches that we use internally to accelerate our development of solutions for clients. This enables our NetDevOps engineers to accelerate their developments into clients’ environment and build on shared learnings within our wider network automation practice.

Below is just a small sample of some of the things we’ve already done and can do faster again – perhaps to help you if your NetDevOps is feeling more like NetDevOops:

  • ajax-code-snippets
  • azure-f5-bigip-ha-cluster-cfe-do
  • azure-natgw-azlb-stress-tester
  • azure-zscaler-ip-lookup-csv
  • caci-ns-employee-profile-tools
  • certificate-automation-python
  • credly-certs-badging
  • cytoscape-network-topology-viewer
  • gartner-market-vendor-scraper
  • hostnames-geoip
  • megaport-api-provisioner
  • network-weathermap-visualiser

Ready to turn your NetDevOops into NetDevOps?

At CACI, we’re well-versed across all areas of IT infrastructure – be that IT, delivery assurance, cloud, network or DevOps and systems administration. Our expert consultants have worked across a large spectrum of clients in varying stages of digital transformation, some with adherence to more agile-led delivery lifecycle, others with adherence to more waterfall-led delivery lifecycle – and have experience across a plethora of industry frameworks, from TOGAF to SAFe to more traditional ITIL deployments.

Get in touch and let us help you assure and stabilise your cloud, IT or network infrastructure to fulfil the four key DORA DevOps metrics in your company (or ask us what they are if you don’t already know) and accelerate your NetDevOps and SRE success!

How to successfully navigate the opinionated NetDevOps stack

Posted on: 17 September 2024
How to successfully navigate the opinionated NetDevOps stack

Getting to NetDevOps and network automation is hard – sure, there may be plenty of free tools and resources available, but knowing which tool to use in certain situations can complicate the process. The often-complicated naming conventions of these tools and resources don’t exactly make matters easier. See for yourself whether you can spot the fake tool or protocol among these:

  • gNMI
  • Batfish
  • Parafidgeon
  • Pandas
  • BaHalmAI
  • Nornir
  • Flask
  • DuncanO
  • Suzieq
  • Pytest
  • Scrapli
  • BookPie
  • pyATS
  • Netmiko
  • AutoM8

(Answer: Keep reading to find out!)

Building with Open Source also has its risks – do you want this to be your network automation stack when it’s in production supporting your mission critical, CNI or other network Infrastructure concern?

Opinions, we’ve got a few

At CACI Network Services, we’ve been doing everything from network infrastructure, telco, delivery assurance, cloud and DevOps infrastructure and more for nearly two decades – just enough time to formulate some opinions on what is good, what actually works, and when to use it in your technology stack. Our mission as a trusted advisor is ultimately to benefit your IT network infrastructure to grow greater than the ever-growing sum of our deep network engineering expertise – where we’re increasingly finding the best way of conveying this to be through articulating which technology to use in which aspect of NetDevOps, depending on a client company’s size, maturity, culture and budget.

Enter the “opinionated stack”, or more concisely, one of the below DevOps mobius loops, with some added context on which tool to use, in which situation and why:

Profiling isn’t always a bad thing

To help direct our clients to the right opinionated stack, we’ve found that profiling our customers across the following three dimensions has helped us gain deeper insight into their network operations behaviours:

Size

  • Small – <100 nodes (routers, switches, NVAs, firewalls, etc.)
  • Medium <1,000 nodes
  • Large >1,000 nodes

Maturity

  • Nascent – mostly ClickOps, box-by-box, limited or no CI/CD or network automation ecosystem
  • Developing – pervasive ClickOps, box-by-box with some or trialling CI/CD or network automation ecosystem
  • Practicing – ClickOps by exception, box-by-box in emergency with strong CI/CD and growing NetDevOps ecosystem

Culture

  • Engineering-led – organisations that value in-house engineering as a primary driver
  • Financial-led – organisations that value minimisation of OpEx as a primary driver
  • Risk-led – organisations that value minimisation and risk mitigation as a primary driver

Want a preview of our work for your organisation? Take a look at our IP Fabric Partnership and forthcoming announcements in this space to see how we can help.

Getting answers

We did promise we’d tell you which were the real tools in network automation, so here goes:

  • Batfish
  • Pandas
  • Nornir
  • Flask
  • Suzieq
  • Pytest
  • Scrapli
  • pyATS
  • Netmiko

How CACI Network Services can help 

If you’d like to know more about these tools, what they can do for your network infrastructure and how we deploy, operate and maintain them for our clients in finance, defence, government, utilities, media and beyond, get in touch to see how we can help demystify them into actionable insights for your IT network infrastructure estate.

Why consultancy is the perfect profession for problem solvers

Posted on: 16 September 2024
Why consultancy is the perfect profession for problem solvers

Puzzle Consultancy

Those who relish the thrill of solving puzzles and the rush of competition are likely to find a perfect match in the world of consultancy. This profession, often associated with high-stakes business decisions and strategic planning, can offer a dynamic environment where one’s passion for learning, problem-solving and helping businesses thrive can come to life. So, how exactly does consultancy work become the ultimate puzzle, providing endless opportunities to learn, solve problems and see tangible benefits unfold? 

The endless puzzle: continuous learning in consultancy 

One of the most exhilarating aspects of consultancy is the constant influx of new challenges. Just like puzzles, each project presents a unique problem to solve, often requiring fresh knowledge and innovative thinking. The variety in consultancy work— ranging from industries like healthcare and finance to technology and retail— ensures that there’s always something new to learn. For puzzle enthusiasts, this is akin to encountering a new, complex puzzle every day. 

Each client and project creates an opportunity to dive into new territories, understand different business models and stay updated with industry trends. This constant learning keeps minds sharp and satisfies curiosity, with every assignment more intricate and rewarding than the last. 

The competitive edge: thriving on problem-solving and strategy  

Consultancy isn’t just about applying standard solutions, it’s about crafting unique strategies that can give clients a competitive edge. This aspect will resonate deeply with those that are naturally competitive. Just as one would approach any challenge with the goal of finding the best and most efficient solution, the aim in consultancy is to devise strategies that not only solve a client’s problem, but also position them favourably in their market. 

The thrill of this competitive element is a significant motivator. It can drive creative thinking, meticulous data analysis and team collaboration to brainstorm the best approaches. The satisfaction that comes from cracking a particularly tough problem or devising a winning strategy can be immensely rewarding, much like completing a particularly challenging puzzle. 

The reward of impact: helping businesses improve 

While the intellectual stimulation and competitive aspects of consultancy can be exciting, the real joy comes from seeing tangible impacts. There’s a unique satisfaction in knowing that recommendations and strategies can significantly improve a business’ operations, profitability or market position, as though seeing the pieces of a puzzle come together to form a clear and complete picture. 

Helping businesses in this way can provide a profound sense of accomplishment, with each success story a testament to the hard work and strategic thinking that goes into project work. This impact-driven aspect of consultancy adds depth to the puzzle-solving experience, making it not just an intellectual exercise, but a meaningful endeavour that positively affects real businesses and people. 

Consultancy as the ultimate puzzle

Consultancy is the ultimate puzzle— one that’s ever-evolving and endlessly rewarding. For those who enjoy puzzles and competition, it offers a perfect blend of continuous learning, problem-solving and the thrill of seeing tangible results. Consultancy is a career that challenges the mind, fosters creativity and provides an unparalleled opportunity to make a real difference to organisations and people. It not only satisfies a love for challenges, but also fuels a passion for helping others succeed.  

Find out how CACI’s expert consultants can support your unique business needs by getting in touch with us here. 

How to determine whether your network is ready for AI

Posted on: 13 September 2024
How to determine whether your network is ready for AI

You’re busy, and so is your network. Or if it’s not, it’s about to be. AI workloads are coming for your network, and to remain competitive in a world where AI-enabled applications and workflows become the norm, it must be embraced. 

Networks are collectively facing their next pivotal moment of transformation and must therefore equip themselves with the necessary network automation and NetDevOps practices to sufficiently operate and enable AI. 

What steps can be taken to prepare a network for AI?

As organisations strive to control the power of AI, it’s crucial to ensure that their network infrastructure is prepared to support these advanced technologies. 

In our experience, AI has two key implications to network environments: 

Changing the operation of the network 

  • AIOps fundamentally changes some monitoring approaches such as the Network Management System (NMS) trap and poll of yesteryear towards observability approaches, leveraging streaming network telemetry 
  • Finding signal in the noise of network alarms shifts from “hard” to “impossible” without the assistance of AI that AIOps brings. 

Changing the deployment of the network 

  • AI workloads are fundamentally different to traditional IT workloads, requiring network topologies that can sustain low flow entropy, high flow burstiness, elephant flows and near-100% bandwidth utilisation 
  • Stock Ethernet isn’t the only player on AI networks, often utilising RDMA-approaches and protocols such as RoCE and InfiniBand, which require differing abilities to design, deploy and operate. 

By taking the following proactive steps, businesses can not only enhance their operational efficiency, but also position themselves as leaders in the AI-driven future. 

Evaluate the current infrastructure for AI compatibility

To ensure your network is ready for the AI era, start by thoroughly understanding and evaluating your current infrastructure for AI compatibility. This includes assessing the following areas: 

  • Link bandwidth utilisation 
  • Average end-to-end latency 
  • Interconnect and Edge capacity 
  • SFP compatibility with known GPU and TPU hardware 
  • Consideration for Smart NIC and DPU offload. 

Just because your current network topology can run an AI workload or cope without AIOps doesn’t mean it will when your business starts deploying AI workloads at increasing pace. 

Modify IT operations practices 

AI comes from a world of software engineering backed by DevOps practices which might be at odds with your current IT service management approaches. Ensure cultural differences of AI workloads and tooling have been considered, such as: 

  • Continuous Integration with Continuous Deployment (CI/CD) pipelines for end-to-end infrastructure operation and deployment 
  • Governance via self-service approaches such as pull request (PR) and merge 
  • Infrastructure as Code (IaC) for self-documenting infrastructure, topologies and design validation 
  • Observability against proactive KPIs to replace reactive capacity management processes 
  • Automated remediation based on categorised risk tolerance levels of network change activity, removing humans from the loop where possible. 

AI isn’t going to wait for an RFC before swamping a poorly-configured uplink with a deluge of elephant flows that exhaust your “deep” packet buffers. Controllerless networks are going to feel more strain, so software-defined networking (SDN) approaches should be considered to remove the need for high-touch human interaction in sustaining network operations. 

Consolidate your current IT operations tooling

In our experience, it is not uncommon for clients to have a multitude of monitoring systems that have collected over the years. No business ever intends to have more than one, but you may have: 

  • Started a proof of concept (PoC) using PRTG for some of your network estate 
  • Implemented SolarWinds for your IT server and virtualisation equipment 
  • Spun up Cisco Prime Infrastructure for your mainly-Cisco network environment 
  • Added Tufin for your firewall and network security appliances 
  • Forgotten the small Juniper Space deployment for your Juniper SRX Firewall data centre edge. 
  • Purchasing yet another monitoring tool that introduces AIOps will not help here.

Now is a good time to reassess each monitoring tool from the perceived benefit against the actual benefit it gives you. 

AIOps in conjunction with a comprehensive review of what you want your monitoring tools to add aligned to Observability pillars such of logs, metrics, and traces – and crucially aligning these to who is going to do what with each outcome – almost certainly will. 

Provide AI-oriented training

Not every team member has to be—or will be—a full-fledged engineer, and that’s okay. There must, however, be at least a basic awareness of some of the nuances of how AI operates and some common pitfalls. For example: 

  • Think in terms of context and having the outcome you want in mind at all times 
  • Work with Large Language Models (LLM) context windows 
  • A PDF export of a NMS device inventory is likely to be bigger (in data storage terms) than a comparable CSV export – therefore use more context window “tokens” when fed into an AI prompt engine.
  • Sanitise sensitive data from network configurations 
  • When using network vendor configurations across device families, the act of find-replacing a SNMP username/password might not be as easy as looking for “snmp-sever username…” due to syntax differences of the same configuration across vendors and even within similar devices from the same network vendor. 
  • Ensure you take extra time in sanitising sensitive data such as IP addresses, hostnames, SNMP username/passwords, PKI (SSH/SSL) certificate fingerprints and the like 
  • Consider AIOps an integral API that is central to your observability stack 
    • How will it process southbound data from network devices and element managers, and what protocol(s) will it utilise? 
  • Define the business logic that will help it understand the context of network deployment in your organisation 
  • Consider common fault scenarios and how these are codified into the AIOps tooling. 

The key to both AIOps and AI workloads is ensuring the upfront work is taken to assess how these will change both technology and culture within your organisation before adding them to the potentially already-full pile of half-used monitoring tools on the organisational shelf. 

How CACI can help 

CACI understands the importance of data and streamlined processing. Our team possesses over 20 years of experience in every network engineering undertaking imaginable, from architecture, design and operations to managed networks and network automation. We are trusted by some of the UK’s most successful companies in finance, telco, utilities, government and public sector to innately understand their systems, culture and industries. 

Talk to our Network Automation experts today and let us get you from network automation to NetDevOps to assure, run and manage the increasing velocity of AI workloads that are coming to network infrastructures on a wider scale. 

 

How to successfully introduce agile thinking in an organisation

Posted on: 12 September 2024
How to successfully introduce agile thinking in an organisation

The transition to agile thinking in an organisation is often a bottom-up process, with development teams buying into the concepts of value-based delivery early on and attempting to share the benefits with the wider business (sometimes with difficulty). For stakeholders, project management officers and reporting lines, tracking a project and asking “when” it will all be delivered instead of focusing on the problems that need resolving (the “why”) is a frequent issue. While the “when” is still important, focusing on this in isolation limits options for the business and often increases the size of deliverables or delays value-adding opportunities. 

From “when” to “what” and “why”: dissecting the agile approach

In agile communities, you’ll hear and read plenty about pushing the focus to the issue and getting a better understanding of “why” a change is useful, which is a valid approach. From the stakeholder’s world view, though, it is a big leap away from their current measure of success. Therefore, an easier step in mindset to make from the “when” is to the “what” before then going to the “why”. 

When you have a stakeholder with many features they want to deliver, their focus will usually be on “When can I get it?”. Instead of jumping straight to “Why does this change matter to you?”, which may receive a defensive response (for many different, and valid, reasons), asking “What aspect is important?” or “What do you want next?” followed by “Because perhaps we can give you this bit sooner?” can show the value of an iterative approach. Once this cadence of talking about the “what next” becomes the norm, alongside the confidence established by consistently delivering tangible value, the discussion about “Why this is important” becomes a much smaller and easier step. The “why” aspect gives more context, and in turn, more options on how to proceed. Things could be delivered sooner, there could be a dependency or lead times that need tracking. 

Considerations for high-level stakeholders & project management to adopt an agile mindset

High-level stakeholders that use dates to track a department as part of their KPIs can obfuscate helping different levels or types of stakeholders when it comes to transitioning to an agile mindset. Although it can follow the same principles, understanding what value they want followed by why they want it and whether the problem can be resolved instead of giving something of low value that has a higher risk of losing stakeholder trust is critical. There are several KPIs that can be tracked to gain confidence in the team’s performance, and the end goal should be a backlog of problems, with the top section being small enough to resolve iteratively. This can also be displayed left to right over a timeline, with higher confidence in the ability to deliver to forecasted timelines for those on the left. 

How CACI can help

When it comes to agility, seeing is believing. If you increase your release frequency and deliver smaller chunks of tangible value more often, conversations will start to shift from “when” to “what next”, which is a much smaller mindset step towards the goal of “why”. Of course, this is not a one-size-fits-all approach, but more coaching what’s available in your coaching toolkit. 

Practical steps for transition 

  1. Clarify the transition process: Development teams should share agile benefits with the wider business through workshops and regular updates. 
  2. Address common challenges: Identify and discuss common challenges such as resistance to change and offer practical solutions like training sessions and pilot projects. 
  3. Include case studies: Share real-life case studies or success stories to make the transition more relatable and convincing. 
  4. Visual aids: Use diagrams or flowcharts to visually represent the shift from “when” to “what” and “why”. 
  5. Engage the reader: Pose questions or scenarios to engage the reader and encourage them to reflect on their own organisation’s practices. 

If you have any scenarios within your own organisation that you’d like to discuss with one of our experts or to find out how something like this can be applied, please get in touch with us. 

How NetDevOps transforms network management for AI applications

Posted on: 11 September 2024
How NetDevOps transforms network management for AI applications

AI – more specifically, GenAI (Generative AI) – is continuously making its presence known through embedded integration into various network applications and workloads. First, there was DevOps – a grassroots initiative to unite the fractured worlds of development and operations. Then there was NetDevOps, where network engineers joined in to complete the trifecta:

NetDevOps transformation

AI workloads with disparate and sprawling protocol interdependencies mandate something new: AIOps. Humans could previously keep pace with FCAPS processes such as SNMP Traps, Syslog Alerts, NMS Alarms and more. Now, however, the network is evolving in such a pace that manual processes won’t cut it. 

The future of network engineering is clear: network automation through NetDevOps is the only viable way to achieve a semblance of sanity in obtaining signal to noise (SNR) in the demanding, high throughput, zero-loss network utilisation that AI workloads demand. 

What roles do NetDevOps and network automation play in business operations? 

High-performing networks are now vital for business operations, as digital transformation becomes a reality for most enterprises – enabled perhaps most notably by the pandemic and compounded by technological innovations such as GenAI and the “GPT” conversational interface to the Large Language Model (LLM). In a climate of recessions, tightening budgets, decreased human workers and increased AI agents, the network simply can’t continue to look like: 

  • Ticket-led troubleshooting slowly finding the Resolver Group in Servicenow 
  • Ad-hoc configuration changes driven via vendor syntax in notepad.exe 
  • Failed firmware upgrades caused by inaccurate human knowledge of HA architectures 
  • Fragile underlays, circuits and protocols with high provisioning times driven through paper request processes and Word documents 
  • Static network architectures focused more on artificial tiers that only help network vendors sell their quota for the month. 

Where network automation focuses on the changes required to the network engineering discipline itself, NetDevOps builds on this by uniting the teams required to achieve this, turning network engineering from mastering the dark arts to coding against the well-trodden software engineering path. 

NetDevOps is essentially the enabler that speeds up automation within a network engineering department through cultural reinforcement and moving the network towards an “as a service” offering. It also aligns deployment, change and provision of the network towards platform engineering and self-service approaches as seen elsewhere in IT Service Management (ITSM) and software development. Through NetDevOps, you can achieve: 

  • Version control for network state through mature configuration management that escapes the bureaucracy of the CMDB 
  • Abstracted intent-based network configuration to achieve network vendor independence, deduplication of network coding and cross-team collaboration on previously opaque network vendor settings 
  • Operational state verification through testing approaches to bring the rigour of software development practices to the previous discipline of network engineering 
  • Expedited mass deployment using sequential means of network configuration via API rather than CLI 
  • Self-documenting infrastructure provision using Infrastructure as Code (IaC) to consistently, efficiently and universally bring complex multi-vendor NVA routing, firewall and security solutions into reality. 

What will the impact of AI be on traditional network engineering?

NetDevOps supplies one key component that traditional network engineering has fallen short on: reliable infrastructure velocity. AIOps gives operations one key component that network management has fallen short on: expedited network remediation. Finally, AI workloads give the network one key problem that previous IT workloads have not: high-throughput, lossless utilisation. 

Essentially, the impact of AI on network engineering will be twofold, becoming the cure to the problem it creates: 

  • The problem: Super-high utilisation of network capacity through continuously-bursty elephant flows, requiring near-lossless network throughput. 
  • The solution: Instantly intuitive insight, observability and remediation of network faults and capacity exhaustion through AIOps. 

AI is not just a passing trend, it is a transformative force that will reshape the way networks operate and evolve. As AI-driven applications and workloads become more complex, your network will need to handle unprecedented levels of data traffic while maintaining optimal performance and security. 

How CACI can help

We understand that every network is unique and have worked on some of the most unique and well-known network architectures deployed from Critical National Infrastructure (CNI), through to telecommunications, data centres, hybrid cloud and service provider. 

Whether you are looking to integrate AI into your existing ITSM tooling, CI/CD pipelines or overhaul your network deployment scripts, we have over 20 years’ experience across a breadth of network technologies to support you. 

Benefits of our NetDevOps services include: 

  • Eliminating manual network provisioning and troubleshooting tasks 
  • Codifying understanding of network topology in a structured data format 
  • Integrating network provisioning workflows into IT Service Management (ITSM) tooling 
  • Expediting network troubleshooting through assisted alarm and event correlation 
  • Reducing the risk of network deployment mistakes and rework 
  • Minimising costs through modularisation of network configuration approach 
  • Increasing ROI through reuse of codified Network Functions as Code. 

We understand that the network is a piece of the wider infrastructure that underpins your business. CACI manages and delivers entire technology transformation programmes – from programme management, business analysis, service design, managed services and more, we offer the full stack of IT network expertise for your business. 

Contact CACI Network Services today to find out more about how our team of experts can guide you through the disruptive AI network wave.

Unlocking the Power of Government Data: Moving from Siloed Information to Smart Public Services

Posted on: 10 September 2024
Unlocking the Power of Government Data: Moving from Siloed Information to Smart Public Services

Government agencies are collecting unprecedented volumes of data, yet much of it remains untapped, trapped in silos that prevent effective decision-making and service improvements. This data holds immense potential to transform public services by enabling more accurate, timely insights into service delivery, effectiveness, and efficiency. However, the way data is currently collected, stored, and structured often renders it under-utilised or completely unused.

In this blog, co-authored by Ali Nicholl and Nick Turner from CACI, we explore the critical user requirements for a data-driven smarter state and propose a scalable, federated approach to data discovery, access, and sharing. By enabling real-time data access at the point of need, this approach not only empowers better public services but also provides a coherent AI-ready workflow that leverages existing legacy systems without disruptive centralisation, duplication, or increased complexity.

The Challenge: Making Data Work for Everyone

In today’s environment, where both government and industry are under pressure to do more with less, reduce complexity, and comply with stringent regulations, several pain points persist:

  • Breaking down data silos: Data is often trapped within departmental or organisational boundaries.
  • Improving data quality: Data accuracy and consistency are compromised without a coordinated approach.
  • Addressing data custodianship concerns: Worries around GDPR, security, and data misinterpretation hinder sharing.
  • Ensuring controlled access: Striking the right balance between open access and secure controls.
  • Managing costs: High expenses related to data transit, hosting, and maintenance.
  • Overcoming budget constraints: Investment in new systems while maximising returns on legacy assets.
  • Becoming AI-ready: Adopting new technologies without costly overhauls.

For any system to be truly data-driven, it needs a minimum standard for quality, availability, consistency, and interoperability—without sacrificing security and appropriate access control. It’s the organisations closest to the data sources that have the best insights into managing quality and availability. However, leaving consistency and interoperability solely in the hands of data owners can lead to fragmentation, while expecting any single organisation to manage all data ownership is unrealistic.

The Evolving Solution Space: Technology, Policy, and Attitude Shifts

Recent advances in technology and shifts in policy have begun to address these challenges. Nearly two decades ago, the Reuse of Public Sector Information Regulations (2005) and the Transparency Agenda (2010) laid the foundation for more open attitudes towards data sharing in the UK. The evolution of cloud technology and API-driven architectures has further improved data accessibility by reducing latency and enhancing interoperability.

For example, the UK Transport Sector has effectively used open data APIs to share real-time transport information with developers and service providers, resulting in over 600 apps that benefit millions of Londoners every day. However, while these methodologies improve access, they do not fully solve the “data silo problem”—where data remains fragmented and lacks context, limiting its utility for broader insights.

A Federated Approach: Keeping Data in Place While Maximising Its Value

Our combined experience at CACI has only reinforced how unsustainable current approaches are. A smarter state needs a smarter approach. A federated approach. A federated approach allows data to stay in situ within its existing silos, accessible through a controlled, consistent, and extensible framework. This approach eliminates the need for costly mass data migrations while still unlocking insights at the point of need. Creating a more equitable democratisation of decision-making by ensuring that the right data is available at the right time.

This methodology aligns with how Health Services in the UK have approached data integration in recent initiatives. Within Social Care Networks, for example, connecting existing systems rather than centralising all data has ensured the Healthcare sector maintains flexibility to access relevant information while adhering to security and privacy requirements.

Data visualisation

Understanding Stakeholder Needs: Tailoring Solutions for Maximum Impact

Different stakeholders have different goals and challenges when it comes to leveraging data. Here’s how a federated approach such as ours addresses their specific pain points:

  • CIOs need timely, reliable data for informed decision-making. Our solution ensures up-to-date insights without the need for complex data migration, helping CIOs set policies and make strategic decisions with confidence.
  • Heads of Data and CDOs seek to maximise ROI from data assets. We provide enhanced data discoverability and governance, ensuring that those who need access can find and use data efficiently.
  • Service Owners focus on delivering policy or strategic outcomes. Our approach reduces the under-utilisation of data, enabling service improvements without significant operational disruption.
  • Data Analysts require consistent and high-quality data for accurate analysis. By maintaining data integrity and enabling seamless integration across sources, we empower analysts to deliver actionable insights.
  • End Users demand real-time access to relevant data without navigating multiple platforms. Our solution brings data closer to its source, maximising relevance and minimising inconsistency.

Building a Data-Driven Smarter State: The Path Forward

Creating a data-driven smarter state requires lowering the barriers for departments, organisations, and individuals to surface their data and enrich it with context, turning it into actionable insights. A federated approach represents a scalable, flexible, and low-risk path towards unlocking the full potential of government data. The journey from siloed information to integrated insight is not just about technology; it’s about creating an ecosystem where data flows seamlessly, fostering collaboration, innovation, and smarter decision-making across the public sector.

To build this future, we must prioritise accessible, context-rich data and scalable collaboration across stakeholders. The smarter state of tomorrow is within reach if we embrace these principles today.

This blog was submitted to TechUK as part of their “Building the Smarter State Week” and can be found on their website here.

How AI is rewriting the rules of network engineering

Posted on: 4 September 2024
How AI is rewriting the rules of network engineering

AI is coming for your network… but not as you expect

Seasoned IT professionals are no strangers to technology transformations and weathering the storms associated with them. Artificial Intelligence (AI), however, presents different, unique challenges to your network. Everyone is talking about the changes that AI will bring to your work, but few are talking about the changes AI application workloads bring to the design, architecture and operations of your network.

What changes are coming to network engineering and automation due to AI?

The advent of AI means that now more now than ever before, the architecture, design and operational excellence of your network matters. Network automation is coming to the fore to deal with the changes AI requires of networks, including: 

  • High throughput transactions facilitated via features such as RoCE Adaptive Routing (AR) 
  • Parallelised datagram transmission through AI network protocols such as RoCE, InfiniBand and other RDMA-based approaches 
  • Dense port connectivity to interconnect numerous distributed GPU and TPU processors required for generative AI (GenAI) training and model processing 
  • Lossless packet transmission to optimise LLM training runs and prevent the need for costly retransmission that can lead to AI training data corruption 
  • Extreme bandwidth utilisation from bursty elephant flows which can flow up to the line-rate of the connected NICs. 

AI workloads such as GPT, LLM and ML have different requirements of your network to traditional IT workloads. Legacy ITSM approaches also won’t cut it for AI-enabled business applications. It isn’t just routers, switches, firewalls and cables – it’s the 24/7 backbone of your organisation’s competitive advantage. 

This is FCoE (Fibre Channel over Ethernet) all over again; only this time it’s not going away – AI is here to stay. Humans driven through ITIL don’t work 24/7 at 100% capacity like AI does, which is where automation comes in. Specifically, network automation facilitated through expert NetDevOps practices and tooling. 

How CACI can help

Embracing the power of automation will lead to a robust and agile network infrastructure for your organisation. With over 20 years of experience with all aspects of network engineering – data centre, service provider, hybrid cloud and beyond – including complimentary offerings in delivery assurance and DevOps, CACI has networked, designed automated some of the UK’s most successful companies in financial services, telecommunications, utilities, government and public sector. 

Our renowned network automation and NetDevOps services revolutionise your network infrastructure by leveraging advance technologies required for AI workloads. From configuration management to network monitoring and troubleshooting through observability, we streamline your operations, improve efficiency and maximise your network performance. 

A few of the many benefits of CACI’s network automation services include:

  • Automating network provisioning and troubleshooting: Eliminating manual network provisioning and expediting network troubleshooting through assisted alarm and event correlation 
  • Enhancing network understanding and management: Codifying an understanding of the network topology in a structured data format and integrating network provisioning workflows into IT Service Management (ITSM) tooling 
  • Improving efficiency and cost-effectiveness: Reducing the risk of network deployment mistakes and rework and minimising costs through a modularisation of network configuration approach 
  • Optimising resource utilisation and talent management: Increasing ROI through reuse of codified “Network Functions as Code” and retaining in-demand network engineering talent through use of modern network deployment working practices. 

Don’t let your network get left behind by the AI network revolution. – Contact CACI today to navigate AI and bolster your network ready for the AI-enabled, LLM-led, ML-fed future.