Best practices for optimising your AWS costs

Cloud computing has transformed the way businesses operate, offering scalability, flexibility, and the ability to innovate —and fast. But, with all these benefits, comes challenges —like managing costs effectively.

AWS is the cloud provider of choice for many organisations, but without proper cost management, cloud expenses can quickly spiral out of control.

Let’s explore why cost management is crucial, delve into AWS’s cost management tools, and share some best-practice tips for optimising your costs as an AWS user.

Why the need to manage cloud costs?

Cost management is a critical aspect of cloud computing —in fact, it’s a core pillar of the AWS Well-Architected Framework.

Poor cost management can lead to budget overruns, reduced profitability, and even threaten the viability of a business. Effective cost management ensures that resources are used efficiently, helping organisations maximise their investment in cloud infrastructure.

By keeping cloud expenses under control, businesses can maintain financial health, allocate resources to innovation, and remain competitive in their markets.

AWS and cost management

Luckily, AWS provide a wide range of cost management tools designed to help businesses monitor, manage, and optimise their cloud expenditures. Understanding what tools are available (and how to use them) is essential for any organisation looking to make the most of its AWS solution.

Tools available to help manage costs

AWS Cost Explorer

AWS Cost Explorer is a powerful tool that enables users to visualise, understand, and manage their AWS costs and usage over time. It provides detailed insights into cost drivers, usage patterns, and trends.

With Cost Explorer, you can create custom reports, view historical data, and forecast future costs. This tool is invaluable for highlighting areas where businesses can find cost savings, and for making informed decisions about resource allocation.

AWS Budgets

AWS Budgets lets you set custom cost and usage budgets that alert you when you’re about to exceed your thresholds. This proactive approach to cost management helps prevent unexpected expenses and means that your cloud spending will stay within predefined limits.

AWS Budgets can be tailored to specific needs, such as setting budgets for different projects, teams, or departments, providing granular control over your cloud costings.

AWS Trusted Advisor

AWS Trusted Advisor is a real-time resource optimisation tool that provides recommendations to help you reduce costs, improve performance, and enhance security. Trusted Advisor covers five categories: cost optimisation, performance, security, fault tolerance, and service limits.

By regularly reviewing Trusted Advisor recommendations, you can identify underutilised resources, enhance your configurations, and keep your AWS environment running efficiently and cost-effectively.

Best Practices for using your resources efficiently

Here are the three best practices to get you heading in the right direction:

Right-size your resources

One of the most effective ways to manage AWS costs is by right-sizing your resources. This involves taking a detailed look at your current usage and adjusting the size of your instances, storage, and other resources to match your actual needs.

Implement Auto-Scaling

Auto Scaling helps you automatically adjust the number of instances in response to changing demand. By scaling your resources up during peak times and down during low usage periods, you can optimise your costs with less manual effort. Auto Scaling also helps maintain performance and availability, ensuring that your applications can handle traffic fluctuations efficiently. Tools like AWS S3 Intelligent-Tiering can automatically move data between storage tiers based on changing access patterns, optimising storage costs without manual intervention.

Monitor and review

Regularly review your usage patterns and make adjustments to ensure you are not paying for more than what you actually need. Storage costs can quickly add up, especially if you have large amounts of data. It’s important to continuously keep an eye on your current usage, and project your future needs accurately to ensure you’re not wasting resources before they’re required.

How Bespoke Training can help

At Bespoke Training, we understand that mastering AWS goes beyond just learning how to use development tools. Our courses are designed to equip you with comprehensive skills across various realms of AWS, including cost optimisation.

Whether you’re a beginner looking to understand the basics or an experienced professional aiming to fine-tune your cost management strategies, our expert-led courses provide the knowledge and hands-on experience you need. Learn how to leverage AWS’s cost management tools effectively and implement best practices to ensure your cloud environment is both efficient and cost-effective.

Ready to be your organisation’s cost-optimising hero? Explore our course offerings or get in touch today and take the first step towards a more efficient and cost-effective AWS environment.

Getting Started with Azure: Key Features and Benefits for New Users

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Whether you’re new to cloud computing or a seasoned pro, you’ve probably heard of Microsoft Azure. Azure offers a robust platform packed with powerful tools and services to transform your business operations.

But, like most cloud platforms, there are endless configurations, and countless ways to use Azure’s tools —which can make it a little overwhelming if you’re just getting started!

In this beginner’s guide, we’ll explore the fundamentals of Azure: its key features, why you might choose it, and how you can kick-start your cloud computing journey with this powerful tech.

Let’s start with the basics: what is cloud computing?

Cloud computing simplifies how businesses manage and access data, applications, and services over the internet. It provides businesses with scalability in infrastructure, cost-efficiency, and flexibility, making it an ideal choice for startups, enterprises, and everything in between.

Microsoft Azure is a vendor for cloud computing solutions. From Machine Learning, to data storage or compute power supply, Azure helps businesses unlock new ways of operating, and empowers savvy tech teams to hit the ground running.

Benefits of using Azure Cloud

Azure offers companies a number of benefits including:

  • Scalability: Teams can easily scale resources up or down based on demand, avoiding pricey upfront hardware investments and reducing waste.
  • Cost Efficiency: With flexible pricing models, you only pay for what you use.
  • Accessibility: Azure services can be accessed globally from any device connected to the internet —with servers all around the world, you can unlock lower latency, and automatic redundancy to keep your servers always-on and accessible, ensuring minimal downtime.
  • Reliability and security: Top notch security and data recovery processes means your data is safer than ever stored in Azure.
  • Access to analytics: Best of all (for data nerds like us!) teams can see exactly how their system is performing and adjust investment and resources accordingly. From a birds-eye view of your cloud environment’s performance, to nitty-gritty drill downs, you can see what’s working, what’s not and where you might need to invest more resources.
  • Local data centres: Whether for compliance or peace of mind, your organisation may prioritise keeping your data locally – in your country or region. In Australia, Microsoft currently has 3 data centres – Canberra, Melbourne and Sydney. In New Zealand, Microsoft is in the process of building a data centre in Auckland, and there is not currently an ETA on when this will open.

What services Azure has to offer

1. Compute and networking services: Azure Virtual Machines (VMs) offer scalable computing power, while Azure Virtual Network connects your VMs securely. Azure Load Balancer distributes traffic —so you can unlock optimal performance.

2. Storage services: Azure operates through massive global data centres, regions, and availability zones —with the ability to handle large quantities of unstructured data in various storage methods. For instance, File Storage offers managed file shares, and Table Storage manages structured datasets.

3. Identity, access, and security: Microsoft Entra ID manages user identities securely. Role-Based Access Control (RBAC) provides fine-grained access management, and Azure Security Center offers advanced threat protection.

4. Cost Management: Azure offers helpful calculators and tools to help you optimise costs. You can use the Total Cost of Ownership (TCO) and other pricing calculators to estimate your costs and ensure efficient resource allocation.

5. Managing and Deploying Resources: Azure Resource Manager (ARM) simplifies resource management and deployment processes. Azure DevOps facilitates continuous integration and deployment (CI/CD) pipelines.

6. Monitoring Tools: Azure Monitor provides comprehensive insights into your Azure environment, while Application Insights monitors application performance effectively.

Learning the ropes

Diving into Microsoft Azure might seem a bit daunting at first, with all these new terms, tools and services to understand. But, learning these concepts is crucial for anyone looking to harness the full potential of cloud computing.

As cloud computing becomes more integral to business operations, proficiency in Azure is a sought-after skill in the job market. Knowledge of Azure can lead to roles in cloud architecture, development, administration, and more. Understanding Azure allows you to leverage its tools to optimise your processes, reduce costs, and improve service delivery.

Whether you’re an IT professional, developer, or business decision-maker, gaining proficiency in Azure opens up a world of possibilities for innovation, efficiency, and growth.

How Bespoke can help you kick-start your Azure journey

At Bespoke, we’re committed to empowering learners to master Azure. Whether you’re just getting started, or have more experience in cloud, we’ve got structured learning paths and courses designed to supercharge your learning.

  • Explore our Fundamentals Course: Start with our Azure Fundamentals course, designed for beginners to grasp Azure’s basics and core concepts.
  • Take a look at our Learning Paths: Progress through our Azure Learning Paths, tailored to different roles and expertise levels, ensuring a guided approach to mastering Azure services.

No matter your skill level, Bespoke’s resources, labs, and expert guidance will equip you with the skills and knowledge needed to leverage Azure effectively. From foundational concepts to technical execution, there’s a course to help you unlock a new level of cloud understanding.

Embark on your Azure journey with confidence. Explore Azure’s capabilities, dive into hands-on labs, and discover how Bespoke can support your learning every step of the way. Ready to get started? Get in touch today to explore your learning journey!

Kick-Start Your AWS Cloud Journey: A Beginner’s Guide

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Amazon Web Services (AWS) has become synonymous with cloud computing, and still holds the largest market share in the cloud infrastructure market. With a wide range of services, AWS is aimed at helping businesses to scale, innovate, and operate more efficiently.

But with such a powerful technology —endlessly configurable and highly adaptable— starting out on your AWS journey can feel a bit daunting.

Let’s dive in to walk through the basics of AWS solutions and how you can get started building your first AWS environment, to help you kick-start your cloud computing education.

What is AWS?

AWS has grown into the leading cloud services provider, offering over 200 fully-featured services from its global data centres. It provides powerful infrastructure that supports a variety of use cases, from start-ups to large enterprises.

With AWS, businesses can easily scale based on demand, benefit from world-class security standards, and harness a global footprint with reduced latency and improved performance when deploying applications. At its core, AWS empowers companies to move faster, be agile and boost innovation.

Key benefits of using AWS

While there are a number of cloud providers in play, AWS firmly sits as a market leader due to a few value propositions that allow teams to get more from their cloud infrastructure:

  • It’s super scalable: AWS makes it easy to scale your solution up or down based on the demands of the business.
  • It’s easy to manage cloud costs: With pay-as-you-go pricing, teams only pay for what they use —which makes cost optimisation super simple.
  • It’s highly secure and great for compliance: AWS features world-class security standards, meaning companies can rest assured they’re meeting compliance requirements.

How to get started — Setting up your AWS account

Before you get started with AWS, you’ll need to set up an account. There are a couple of easy steps involved:

  1. Visit the AWS website and click on “Create an AWS Account.”
  2. Enter your email address and set a password.
  3. Provide your billing information.
  4. Verify your identity, usually via phone.
  5. Select a support plan (basic support is free!)

Once your account is set up, you can log in to the AWS Management Console using your new account credentials and get familiar with the dashboard and navigation options. From there, it’s time to get into the good stuff!

Essential AWS compute services for beginners

AWS offers a variety of core services that are essential for beginners to understand:

  • EC2 (Elastic Compute Cloud): Allows you to launch virtual servers in the cloud.
  • S3 (Simple Storage Service): Enables you to store and manage files in the cloud.
  • RDS (Relational Database Service): Makes it easy to set up, operate, and scale a relational database in the cloud.
  • IAM (Identity and Access Management): Helps you securely control access to AWS services and resources.

A solid understanding of these core principles and services is a strong foundation for your AWS journey. These services not only cover the basic needs of computing, storage, and database management but also ensure that your cloud environment is secure —and well-optimised.

AWS Virtual Private Cloud

One of the key benefits of using AWS is the ability to establish a VPC (Virtual Private Cloud). A VPC allows you to logically isolate your resources in the cloud —from here, you can create and configure subnets, route tables, and gateways to give yourself greater control, and increase the security of the environment.

Network ACLs (Access Control Lists) help to manage inbound and outbound traffic to your VPC instances and help your infrastructure to run more efficiently.

Monitoring and managing your AWS environment

Implementing best practices for security and optimisation is critical. Consider things like multi-factor authentication (MFA) for your AWS account, and regularly review and rotate IAM credentials.

It’s also critical to choose the right instance types and storage options for your needs, to help with cost and resource optimisation. You can also look into tools like auto-scaling to automatically adjust resources based on demand.

Want to supercharge your learning? Training is your best friend!

If this all still sounds a little overwhelming, you’re definitely not alone. The best way to increase your confidence and skill set in the world of AWS is to invest in some quality training.

Our fundamental level one-day courses like AWS Technical Essentials is designed to give you a solid foundation to build your AWS knowledge. It will cover basic terminology, how to navigate the AWS management console, and outline some fundamental use-cases for the compute services like networking, EC2, Lambda and ECS mentioned above.

On top of that, we take you through the basics of best-practice cloud management. From cost optimisation and security to UAM and monitoring services, you’ll have access to top instructors in the sector to help you get a handle on how to best run and manage your AWS solution.

Choose your AWS Learning Path

If you’re wanting a little more structure to help you find your feet, we’ve got learning paths that can take you from novice to pro. If you’re just starting out, take a look at the Cloud Practitioner learning path. Once you’ve got the basics covered, you can dive deeper into our Migrating, Security or Technical Essentials learning paths to take your learning journey further.

If you’re just starting to dip your toe in the water of cloud computing, download this free guide to AWS training at Bespoke or explore our learning paths in more detail.

Bespoke is here to help

Bespoke can help you find the right learning path for you, based on your current knowledge and your career goals. From fundamentals to specialities and training for certifications, we’ve got courses to support your learning with expert-led virtual training.

With world-class AWS certified instructors and hands-on labs, this training is built to enhance your understanding of AWS services.

Ready to take your AWS skills to the next level? Bespoke offers comprehensive AWS training programs designed to empower you with the knowledge and skills needed to excel. Get in touch with our team, or browse our training directory to kick-start your AWS learning journey today!

Leveraging Data-Driven Innovation Using The Cloud

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Access to good data is no longer a business luxury; it’s a necessity. Organisations across industries are increasingly leveraging data to speed up decision-making, streamline operations, and drive innovation.

Data-driven innovation means using data to inform and inspire growth — in ideas, products, services, and processes. This approach is transforming industries, from healthcare to finance to retail. By analysing vast amounts of data, companies can uncover trends, predict future behaviours, and make informed decisions that drive progress.

There are many benefits to a data-driven approach: enhanced decision-making, improved efficiency —and ultimately, a significant competitive edge. But, it’s not quite as simple as hitting ‘go’ on data: good data is underpinned by good tech.

Cloud empowers data-driven innovation

To that end, it’s easy to see why cloud computing is key to data-driven innovation. It provides the infrastructure for storing, processing, and analysing vast amounts of data efficiently —and cost-effectively. Cloud platforms offer scalability, flexibility, and accessibility, making it ideal for data-driven initiatives.

How to get started with a data-driven approach

Transition to a data-driven approach in a few key steps:

1. Build a data-centric culture

Organisations need to build a data-centric culture where data-driven decision-making is the norm, and employees at all levels to value and utilise data in their daily tasks. Leaders should promote transparency and data sharing, ensuring that everyone understands the importance of data in driving business success.

2. Assess your current data capabilities

It’s a good idea to conduct a comprehensive audit to identify gaps and areas for improvement in your company’s current data capabilities. This helps in developing a roadmap, seeing where you could increase focus, and ensures that the organisation is prepared to leverage data effectively.

3. Develop a data strategy

A well-defined data strategy is crucial. This strategy should outline clear objectives and limitations for data usage that align with the organisation’s overall goals. It should address key areas such as data collection, storage, analysis, and governance.

4. Invest in the right tools and technologies

Choosing the appropriate cloud platforms, analytics tools, and machine learning frameworks is essential for effective data utilisation. Organisations should prioritise investment in cloud solutions that are scalable, flexible, and capable of integrating with existing systems. The right tools enable seamless data processing, analysis, and collaboration, driving innovation across the business.

5. Prioritise data governance

Establishing policies and practices for data management, privacy, and security is critical for maintaining data integrity and compliance with regulations. This involves defining roles and responsibilities, setting data standards, and implementing security measures to protect sensitive information.

6. The most important step? Train your team

As a cloud training provider, we understand the importance of cloud training in empowering data-driven strategies. By equipping professionals with the skills to use cloud technologies, we enable organisations to maximise their data’s potential. Cloud training encompasses a range of skills, from data management to analytics to machine learning, all of which are crucial for data-driven innovation.

Encouraging employees to participate in ongoing training and certification programs can keep the workforce up-to-date with the latest cloud advancements, fostering a culture of continuous improvement —and innovation.

Ready to put your data to work? Start with training your team.

Data-driven innovation is transforming industries —and cloud training plays a key role in this journey. By fostering a data-centric culture, investing in the right tools, and equipping professionals with cloud skills, organisations can accelerate their innovation efforts.

The future belongs to those who can effectively put data to work, and cloud training is the key to unlocking this potential.

AWS and Microsoft Azure Data courses

Both major cloud providers have excellent courses to help you upskill in data.

With AWS, there are a series of 4 x 1-day courses that will enable students to gain a comprehensive understanding of AWS data services and how to leverage them for effective data management and analytics:

If you are looking for a data certification with AWS, the one to aim for is the AWS Certified Data Engineer – Associate.

With Azure, the best option is jump right in to the data fundamentals course:

If you are seeking a data certification with Azure, there is the Azure Data Engineer Associate for data engineers who manage and secure data using a range of Azure data services, or if you manage data ingestion, preparation, model training, deployment, and machine learning solution monitoring, then you would be looking for the Azure Data Scientist Associate certification.

Ready to accelerate your data-driven innovation journey? If you would like to talk to Bespoke about creating a learning plan to achieve your data certification just reach out to us.

Mastering Machine Learning: The Path to Certification Success

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Machine learning (ML) has emerged as a transformative technology driving innovation across industries.

From personalised recommendations on streaming platforms to predictive maintenance in manufacturing, ML applications are limitless —and its popularity has skyrocketed over the past few years.

Businesses are increasingly leveraging ML to gain actionable insights from data, automate processes, and enhance decision-making capabilities. As the demand for ML expertise grows, earning certifications like AWS Machine Learning Specialty becomes pivotal for professionals aiming to demonstrate proficiency and advance their careers in a rapidly evolving field.

What is the AWS ML Certification?

The AWS Certified Machine Learning – Specialty certification is designed to validate an individuals’ ability to design, implement, deploy, and maintain machine learning solutions on the AWS platform. Recognised globally, this certification signifies mastery in leveraging AWS services for ML.

It helps make candidates stand out in a competitive job market, and gives businesses provable in-house skills in an area of technology that is growing in demand. It not only aims to validate technical skills, but also enhances credibility by demonstrating practical experience and proficiency in AWS ML technologies.

Why Get Certified?

Getting certified in AWS Machine Learning offers several benefits for both employees and companies alike:

  • Global recognition: Widely recognised in the industry, the certification enhances career prospects globally
  • Provable expertise: Companies can feel confident in their team’s capabilities in designing and implementing ML solutions using AWS services
  • Credibility: Adds credibility to your team’s experience and expertise, making you a trusted professional in ML technologies.

Before you get started

It’s important to think about the fundamentals —and have a baseline knowledge of AWS before you start looking at ML certification. This could be AWS developer skill sets, an understanding of statistics and probability.

When first starting out, your best bet is to kick off with our AWS Technical Essentials training. The more you know about the AWS environment, the better to set you up for success in the ML speciality.

From here, you can build on your background knowledge with courses like Practical Data Science with Amazon SageMaker, to continue your learning in the AWS landscape and set you on your way to being a capable ML Engineer.

To learn more about pathways designed to boost your ML knowledge check out this blog.

So, what’s the exam like?

The exam runs for about 3 hours and assesses students on both practical and theoretical applications of ML in an AWS context. It will cover a range of topics, from engineering to security, using a range of question types.

Our top tips to prepare for your exam

1. Know what you need to study

Preparing for the AWS Machine Learning Specialty exam requires a thorough understanding of the exam guide and focus areas outlined by AWS. The AWS Machine Learning certification is largely broken down into a few key domains:

  • Data Engineering: designing and implementing data storage solutions to help with efficient data processing
  • Exploratory Data Analysis: Analysing and visualising data to output actionable insights to inform decision-making
  • Modelling: Building, optimising, and deploying machine learning models using AWS services
  • Machine Learning Implementation and Operations: Implementing and managing ML solutions on AWS, and best practices to ensure performance and operational efficiency

AWS has a detailed exam guide that outlines the topics covered in more depth. By knowing what you need to learn, you’ll be able to head straight into step number two.

2. Make a study plan and put together a learning pathway

A structured study plan will help you cover every topic required with enough depth to really understand the concepts. Allocate sufficient time for each area in the lead up to your exam —avoid cramming, and try to really understand the topics. Breaking down your study sessions into manageable chunks allows you to delve deep into each topic, reinforcing your understanding and proficiency in AWS ML services.

Consider using a training partner like Bespoke Training to help you create a structured learning path. From AWS basics through to ML specialities, Bespoke offers training programs designed specifically to prepare candidates for AWS certifications. Access expert-led courses, hands-on practice, and supplementary materials that enhance your understanding of AWS and ML services as a whole.

3. Take a Practice Exam

Another great tool in preparation for the certification exam is the practice exam. For an additional fee you’re able to sit a test prior to the real exam and get feedback on your result and performance. These simulated tests mimic the actual exam environment and help you assess your knowledge and readiness.

By identifying areas that require further study and practice, practice exams enable you to focus your efforts effectively and optimise your preparation time —and show you where you might need to bolster your efforts.

An extra tip? Get a little help from Bespoke Training

While there are free resources available to help you prepare for the exam, the proven best way to study for a certification exam is through instructor led training. Get access to experts in the field, practice resources and extra support through tricky concepts —so you’ll feel confident and fully prepared for whatever the exam throws at you.

Take the first step toward advancing your career in machine learning—start preparing for the AWS Machine Learning Specialty certification today.

For further insights and personalised training options, explore Bespoke’s AWS courses to find those that fit your learning path or get in touch with our team today to find the right learning path for you!

Why Cloud Training is Essential for Non-Technical Teams

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Cloud technology is no longer just the domain of IT departments.

As cloud solutions become integral to day-to-day business operations, it’s increasingly crucial for non-technical roles to understand and feel confident in leveraging these technologies. Whether it’s driving business transformations, addressing security concerns, or fostering personal and professional growth, there’s no doubt about it: cloud training for non-technical staff is a strategic investment.

Why Is It Important?

The cloud is at the heart of many business transformations. Understanding cloud technologies allows non-technical teams to support these changes effectively.

From streamlining marketing operations to enhancing customer experiences, cloud literacy can empower every department to contribute more meaningfully to the organisation’s goals: it’s a big booster to productivity. What’s more, a foundational knowledge of cloud computing helps bridge gaps between departments, leading to more cohesive and effective teams.

Investing in cloud training for your staff can also help to reduce security risks. In an era where data breaches and cyber threats are prevalent (and ever growing), having a basic understanding of cloud security is essential for all employees. Non-technical staff who are knowledgeable about cloud security can better adhere to best practices, identify potential risks, and contribute to the overall security posture of the organisation.

From the employee perspective, cloud training offers personal and professional development opportunities. For non-technical staff, acquiring cloud skills can open doors to new roles, career progression, and even complete career changes. Cross-functional skill development ensures that employees have versatility, stay engaged and are prepared for future challenges.

What roles need to know about cloud?

At the end of the day, knowing about cloud computing and having a good foundational knowledge is useful for anyone, in any role. But, if we’re going to pinpoint a few non-technical roles that can really benefit from technical training, let’s take a look at the top roles that can use cloud training to enhance their performance:

Analysts and Consultants

Analysts and consultants benefit from understanding cloud technology to enhance data analysis capabilities, improve collaboration, and optimise cost management. When these roles also have formal knowledge of cloud security and compliance, this will obviously help mitigate risks and ensure data protection.

Additionally, cloud literacy enables these professionals to drive innovation, make informed decisions, and provide strategic business recommendations.

Sales and Marketing

Sales and marketing teams need to understand cloud technologies to effectively communicate their benefits. Whether it’s discussing how cloud solutions impact business operations, timelines, or customer experiences, having a grasp of cloud concepts can enhance their ability to sell and market these solutions —or use them in their operations more effectively.

Procurement

When it comes to cloud in your organisation, who’s doing the purchasing? Procurement teams are so much more effective at their roles when they have a solid understanding of cloud technologies —to help make informed purchasing decisions. That way, when technical team leaders are asking for specific features or capabilities, the procurement team can go to market with confidence in their understanding.

Knowing what to procure and how it fits into the organisation’s cloud strategy is critical for optimising resources and ensuring that the right tools are acquired.

Executives

For executives and upper management, cloud literacy is vital to keeping a finger on the pulse of technological advancements. Understanding what’s necessary, what’s changing, and what’s next in the cloud helps them stay ahead of the competition and make strategic decisions that drive the organisation forward.

Legal and Compliance

Legal and compliance teams need to understand cloud technologies to assess risks and ensure regulatory compliance. Knowledge of cloud security, data governance, and compliance standards helps these teams safeguard the organisation against legal pitfalls and security breaches —and give the teams the skills needed to ensure the solutions chosen are fit for purpose from a compliance perspective.

Finance

Finance teams must understand cloud costs and investment opportunities. Knowing where to find extra value, identify potential savings, and prioritise higher investment areas ensures that the organisation’s cloud spending is strategic and efficient.

Where to Get Started

The best place for non-technical people to start is with the basics. Fundamentals courses like our AWS and Azure fundamentals provide a solid foundation in cloud concepts, and a great foundation to build upon.

These courses cover essential topics such as cloud infrastructure, security, compliance, and cost management, offering a comprehensive overview that is accessible to all staff members.

Start your cloud journey with Bespoke

At Bespoke, we specialise in helping organisations integrate cloud training across their teams —technical or not! Our training programs ensure that every team member, regardless of their technical background, is equipped with the knowledge they need to excel in a cloud-driven world.

Ready to start your cloud training journey? Get in touch with us today or browse our training directory to find the perfect courses to launch your team on their cloud journey.

Harnessing the Power of a Multi-Cloud Strategy

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With growing demands and increasingly complex cloud environments, more and more businesses are turning to multi-cloud strategies —to enhance the agility of their infrastructure, and mitigate risks. Savvy organisations engage with multiple cloud providers to better meet their diverse and evolving needs. Let’s take a look at the rising trend of multi-cloud adoption: its benefits, its challenges, and best practices for flawless implementation and ongoing optimisation.

Understanding multi-cloud strategy

Multi-cloud strategy involves the use of multiple cloud computing services from different providers, in order to build a custom solution tailored to the unique requirements of your business. Rather than relying on a single cloud provider, organisations can leverage a combination of public, private, or hybrid clouds to optimise performance, resilience, and cost-effectiveness. By distributing workloads across multiple environments and technology types, businesses gain greater flexibility, scalability —and better in-built redundancy.

The key benefits of a multi-cloud approach

Flexibility is a core pillar of multi-cloud strategy. With the ability to blend services from various providers, organisations can build their cloud infrastructure to suit specific workloads and applications. This malleability also extends to geographic diversity — for example businesses are able to use multi-cloud to deploy resources closer to end-users for improved performance and compliance.

Many organisations today are also seeking the resilience of a multi-cloud approach. By distributing workloads across multiple cloud environments, companies can mitigate the risk of downtime and data loss. In the event of a service outage or disruption, redundancy across multiple clouds ensures business continuity and minimises the impact on operations.

Finally, vendor diversification is another key driver behind multi-cloud adoption. By avoiding vendor lock-in, organisations maintain leverage over pricing negotiations —and service quality. Additionally, spreading workloads across multiple providers reduces dependency on any single vendor, mitigating the risk of service disruptions or counterproductive contractual disputes.

What are the challenges in multi-cloud adoption?

While the benefits of multi-cloud strategy are undeniable, actually making the shift is a challenge in itself. Navigating the complexities of a multi-cloud environment means overcoming hurdles like: cross-compatibility issues, complex data integration and operational management of multiple vendors and technologies.

Cross-compatibility (or interoperability) challenges arise from differences in cloud platforms, APIs, and management tools. Achieving seamless integration and interoperability between disparate cloud environments requires careful planning and the right expertise. Data integration complexities can emerge when dealing with distributed data across multiple clouds. Businesses need to ensure data consistency, security, and compliance across disparate cloud environments —which necessitates robust data management practices and governance frameworks.

What’s more, with each cloud provider offering its own set of management tools and interfaces, organisations must know how to best manage resources, monitor performance, and enforce their security policies across multiple platforms.

Best Practices for Implementing Multi-Cloud Strategy

Successful implementation of a multi-cloud approach hinges on proper planning, and the right know-how. Here are a few top tips to get you started:

  1. Start with comprehensive planning: Start by conducting a thorough assessment of your organisation’s business and technical requirements. Define clear objectives, evaluate the strengths and weaknesses of different cloud providers to develop an actionable roadmap for multi-cloud adoption.
  2. Build robust governance frameworks: Establish robust governance frameworks to ensure consistency, compliance, and security across multiple cloud environments. Define policies, procedures, and controls for resource provisioning, access management, and data protection.
  3. Use automation: Leverage automation tools and DevOps practices to streamline provisioning, configuration management, and deployment across heterogeneous cloud environments. Automation reduces manual overhead, improves efficiency, and ensures consistency in operations.
  4. Deploy continuous monitoring and optimisation: Implement comprehensive monitoring and analytics solutions to gain visibility into cloud performance, security, and costs.
  5. Prioritise skills development: Perhaps most importantly, companies need to invest in employee training and skills development to build expertise in managing multi-cloud environments. Equip your team with the knowledge and tools needed to effectively navigate the complexities of multi-cloud architecture.

Make multi-cloud manageable: train your team with Bespoke

Multi-cloud adoption offers businesses a compelling path towards agility, resilience, and innovation. But, the successful implementation of a multi-cloud strategy hinges not only on robust planning and governance but also on equipping your team with the necessary skills and knowledge.

Investing in comprehensive training ensures that your team can effectively manage and optimise multi-cloud environments, turning potential challenges into opportunities for growth.

At Bespoke, we specialise in cloud training programs designed to empower your workforce with the expertise required to navigate complex cloud landscapes. Are you ready to empower your team with the skills they need to thrive? Get in touch with us today to start your team’s cloud learning journey!

Navigating AWS AI and ML Learning Paths

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Updated 25 September 2024

The rise of Generative AI is set to transform industries and reshape the way modern businesses operate. From chatbots revolutionising customer service, to AI-powered analytics enhancing decision-making processes, the potential applications of AI and Machine Learning (ML) in business are far-reaching.

With 93% of organisations planning to integrate generative AI into their operations within the next five years, the demand for skilled professionals in this field has never been higher. However, despite this growing demand, a staggering 75% of organisations struggle to find the talent they need to harness the power of AI effectively.

Generative AI and ML represent more than just technological advancements— they require team members to be empowered to work alongside rapidly emerging technologies. To bridge the talent gap and prepare for the AI-driven future, organisations need to take proactive steps to upskill their existing talent in preparation for this future world of work.

How? Let’s explore the critical steps businesses can take to upskill their existing talent and navigate the path to success in the AI-driven future.

Upskill Existing Talent

The first step in preparing for the AI revolution is to upskill your existing talent. AI developers, ML engineers, data scientists, ML ops engineers and statistical analysts can each play pivotal roles in harnessing the power of AI and ML technologies within organisations. But, what this application would look like to each role is very different —specialised application of this technology required a specialised learning pathway.

At Bespoke, we offer a range of learning pathways designed to equip professionals with the skills they need to harness the power of these emerging technologies. Whether you’re a developer looking to incorporate AI into your applications or a data scientist seeking to streamline your analysis, our comprehensive training programs provide the perfect blend of instructor-led sessions and self-paced learning modules.

Let’s take a look at some of these pathways in more detail:

AI Developer Learning Pathway

AI developers are instrumental in integrating AI solutions into various applications and systems to address increasingly complex challenges. Our learning pathway for AI developers is designed to equip you with a solid understanding of AI algorithms, frameworks, and tools.

With this foundation, you’ll be empowered to create intelligent applications that leverage AI to its fullest potential, collaborating seamlessly with data scientists and machine learning engineers along the way.

 

Data Scientist Learning Pathway

Data scientists are indispensable in today’s data-driven world. They employ advanced statistical and computational techniques to unlock valuable insights from vast datasets.

Our learning pathways for data scientists delve deep into tools like SageMaker and advanced data engineering techniques, equipping professionals with the skills they need to harness the full potential of data for informed decision-making and predictive modelling.

Role Data Scientist 2024ML Engineer Learning Pathway

ML Engineers are the architects behind the implementation and maintenance of ML systems, driving predictive analytics and data-driven decision-making. Collaborating closely with data scientists and software engineers, ML Engineers integrate models into production, optimising performance and scalability.

Our pathways for ML engineers help to develop your expertise in evaluating and selecting ML algorithms and frameworks, paving the way for impactful solutions.

 

Statistical Analyst Learning Pathway

Statistical analysts are the masters of advanced statistical techniques, leveraging their expertise to extract actionable insights and drive business value from data, including those derived from AI and ML models.

Collaborating closely with data scientists, they validate and refine solutions through rigorous statistical analysis, ensuring accuracy and efficacy in model performance while contributing to the broader AI and ML ecosystem.

MLOps Engineer Learning Pathway

ML Ops engineers are the architects of seamless machine learning operations, equipped with the skills to build robust pipelines, automate deployments, and optimise performance.

This pathway will give you the skills needed to bridge the gap between data science and production environments and ensure efficient and scalable operations. Learn how to use ML to maximise performance and reliability throughout the organisation’s operational infrastructure.

 

ML/AI Certification

Once you’ve got the foundations down, the next step is to pursue your AWS ML/AI certification.

Current ML certifications include the AWS Certified Machine Learning – Specialty, and the AWS Certified Machine Learning Engineer – Associate, which was launched in August 2024.

The current AI certification on offer, is the AWS Certified AI Practitioner – Foundational, which was also launched in August 2024.

As an individual contributor, certification validates your ability to build, train, tune, and deploy ML models using AWS solutions —and makes you more employable. For organisations, having certified staff ensures you’ve got team members with highly specialised knowledge, leading to better project delivery.

Bespoke training programs are comprehensive —designed to help you prepare for certification exams, with a focus on hands-on experience and practical skills development. Our expert instructors can guide you through the exam preparation process, ensuring you’re well-equipped to achieve success and advance your career in the rapidly evolving fields of AI and ML.

Get Future-Ready with Bespoke

Don’t let the talent gap hold your organisation back from embracing the transformative power of AI and ML. At Bespoke, we’re committed to helping you upskill your existing talent and thrive in the AI-driven future. With some of the best instructors in the industry and learning pathways that take a blended approach, we’ll set you up for success and empower you to achieve optimal outcomes in the dynamic world of AI and ML. Explore our training programs today and take the first step towards a future-ready workforce.

Ready to take your first step towards a future-proofed workforce? Get in touch today or explore our learning pathways to learn more.

Adopt and scale AI and ML using AWS instructor-led training

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As organisations continue to face skills shortages and resource restraints, the race to harness the power of artificial intelligence (AI) is heating up. With leaders focused on innovating to outpace their competition, new technologies are emerging to accelerate this process — and generative AI is a prime example.

Throughout APAC, the pace of AI transformation is nothing short of remarkable. Research research from AWS revealed that 92% of employers anticipate their organisations will be AI-enabled by 2028. What’s more, within the next five years, over 90% of employers and workers are poised to integrate generative AI tools into their workflows. From chatbots and learning models to content generators, the use of generative AI is on the rise, as teams search for ways to increase their productivity dividends.

But, investing in these cutting-edge tools is only part of the equation —your team also needs to know how to use them effectively. When it comes to harnessing AI, equally crucial is the development of skilled teams capable of navigating the ethical, logistical and security concerns that this tech brings with it. To truly build a future-ready team, you need to invest not just in tools, but in training.

Let’s dive into the transformative potential of upskilling your team. Whether you’re a team member looking to hone your skills, or a leader aiming to steer your employees towards an AI-filled future, we’ve got some practical strategies to help organisations embrace this evolving technology.

The importance of AWS Workforce Training for AI

AI expertise is in high demand. This means that investing in the upskilling of employees is no longer optional—it’s a strategic imperative. Empowering teams with AI proficiency not only drives efficiency, but also fosters a culture of innovation, paving the way for substantial long-term improvements in productivity.

By integrating AI into their operations, APAC employers anticipate a remarkable 51% boost in organisational productivity, while workers themselves expect their individual productivity to soar by as much as 50%.

While the potential benefits of AI are vast, its successful integration into existing processes requires careful navigation. Firstly, learning new skills takes time —and with a complex technology like AI, workforce adoption poses a significant challenge. What’s more, it’s a relatively new technology — an unknown quantity — so organisations need to tread carefully to navigate security concerns and ensure ethical usage.

In this landscape, comprehensive training becomes not just a means of acquiring new skills but a crucial strategy for minimising risks and finding synergies —to enhance, and safely and effectively reshape processes using generative AI.

How to upskill your team

Like many complex topics, AI requires a more ‘hands-on’ approach when it comes to learning. Whether that’s instructor-led or blended learning, it’s important to find ways to give your employees access to experts in the field to learn from.

At Bespoke, we offer AWS-certified instructor-led training across AI and ML. With in-depth theory content, practical exercises and real-world examples, our learning paths empower teams to master generative AI.

Empower Your Team for Future Success

As businesses navigate the AI-driven future, investing in generative AI training is essential for staying competitive. By upskilling your team on how to adopt these cutting-edge tools, organisations can build a future-ready workforce.

With Bespoke Training’s learning paths for AI and ML, organisations can unlock the full potential of generative AI and drive success in the future world of work.

Ready to revolutionise your team’s AI capabilities?

Download our latest eBook now to explore our AI and ML learning pathways. Whether you’re looking to upskill yourself or your entire team, this guide is your roadmap to success.

Get your copy today and unlock the full potential of generative AI in your organisation!

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6 pitfalls leading to breaches in the cloud

Over the past year we’ve seen a big uptick in organisational security breaches. From data leaks to cyber attacks —these breaches have the potential to impact not only business operations, but also reputation, consumer trust, and long-term sustainability. The good news? Many cloud breaches are preventable.

With a proactive approach and a highly skilled team, organisations can greatly reduce risk and build ‘bullet-proof’ online environments. Let’s dive into six common cloud security pitfalls, and how you can avoid them.

1. Misconfigurations

Misconfigurations are one of the leading causes of cloud security breaches —and one of the most avoidable! Simple errors in configuring cloud services can inadvertently expose sensitive data or resources to unauthorised access. The solution? Implement robust cloud security policies and procedures. Regular audits and automated tools can also help to identify and rectify misconfigurations —before they cause trouble.

Want to learn how to safeguard your security position with AWS cloud? Take a look at our on-demand webinar here to get started!

2. Lack of data governance

Overlooking data governance can result in data leakage, unauthorised logins or compliance violations. It’s vital to establish clear data governance policies: encryption, access controls, and data classification frameworks can all be used to ensure data integrity and confidentiality.

3. Insufficient User Access Management (UAM)

Weak user access management practices, such as lax password policies or improper user permissions, can leave organisations vulnerable to insider threats or issues with unauthorised access. Implementing robust identity and access management (IAM) controls, including multi-factor authentication (MFA) and least privilege access principles, can help mitigate the risks associated with inadequate UAM.

4. Cyber Attacks

Cloud environments are prime targets for cyber attacks —including malware, ransomware, and phishing scams. To defend against cyber threats, organisations should implement comprehensive security measures, including endpoint protection, network segmentation, and threat intelligence monitoring. Regular security assessments and penetration testing can help identify and address vulnerabilities before they are exploited by malicious actors.

5. Insecure APIs

APIs play a crucial role in enabling communication and integration between cloud services. But, insecure APIs can introduce vulnerabilities that attackers can exploit to gain access or manipulate data. Address API security by implementing robust authentication mechanisms, encryption, and access controls. Regular API security assessments and code reviews can also help to identify and resolve any API vulnerabilities before they become a problem.

6. Outdated security architecture

Cloud architecture is different from traditional architecture. Trying to use traditional security architecture in a cloud environment is like fitting a square peg into a round hole. This mismatched approach risks gaps in security coverage or ineffective threat detection and response capabilities. Adopting a cloud-native security approach involves leveraging cloud-native security tools and services tailored to the dynamic nature of cloud infrastructure.

How can organisations avoid these pitfalls?

While we’ve mentioned a few ways to mitigate these risks at a tactical level, strategically the best place to start is to ensure your IT team is well trained in security best practices. Comprehensive cloud security training programs can empower IT professionals with the knowledge and skills needed to identify security risks and stop them before they become a problem. In emergency scenarios, it also equips them to respond quickly and effectively to minimise the impact of security incidents.

Through a solid investment in continuous education and training, organisations can create a security-aware culture and strengthen their defenses against evolving cyber threats in the cloud.

Are you ready for your team to learn best-practice cloud security? Explore our security courses or get in touch today for a learning plan tailored to your goals.

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