Spot instances - available as Spot Instances on AWS, Spot VMs on Azure, and Spot VMs (formerly Preemptible VMs) on GCP - offer up to 90% cost savings compared to regular cloud pricing. These discounted compute resources help businesses reduce expenses by using unused cloud capacity. However, interruptions can occur with little or no warning, making them best suited for workloads like batch processing, CI/CD pipelines, data analytics, or machine learning training.
Key Takeaways:
- AWS: Offers the deepest discounts but has high price volatility (197 price changes/month) and a 2-minute interruption warning. Best for advanced automation setups.
- Azure: Provides stable pricing (less than one price change/month) and flexible interruption options. Ideal for predictable budgeting.
- GCP: Features consistent pricing (1 change every 3 months) but no interruption warning and a 24-hour runtime limit. Great for batch jobs and predictable costs.
Quick Comparison
| Provider | Discount Range | Price Volatility | Interruption Notice | London Pricing (4 vCPU, 16 GB RAM) | Max Runtime | ARM Savings |
|---|---|---|---|---|---|---|
| AWS | Up to 90% | Very high (197 changes/month) | 2-minute warning | £69.50/month | No limit | Up to 40% |
| Azure | Up to 90% | Low (0.76 changes/month) | At any time | £75.60/month | No limit | Up to 69% |
| GCP | 60–91% | Very low (0.35 changes/month) | No warning | £71.10/month | 24 hours | N/A |
For UK businesses, AWS offers the lowest prices but requires robust automation. Azure is best for stable costs, while GCP provides predictable pricing with fewer interruptions. Choose based on workload needs, automation readiness, and cost predictability.
AWS Spot Instances
How AWS Spot Instances Work
AWS Spot Instances allow users to tap into unused EC2 capacity at prices up to 90% lower than standard on-demand rates. For example, a general-purpose instance with 4 vCPUs and 16 GB of RAM, which typically costs around £88.33 per month, could be available for just 10% of that cost with spot pricing [5][3]. However, there’s a catch: these instances can be reclaimed with only a two-minute warning. This unique behaviour makes them best suited for specific use cases.
Best Use Cases for AWS Spot Instances
Spot Instances shine in scenarios where fault tolerance and cost savings are key priorities. Stateless applications, which can easily restart on new instances without losing critical data, are perfect candidates for spot pricing.
CI/CD pipelines are another excellent fit. Tasks like building and testing code can resume seamlessly if interrupted, allowing development teams to run extensive test suites and compile large projects at a fraction of the usual cost.
Machine learning (ML) training jobs also pair well with spot instances. For instance, a fintech company in the UK managed to cut ML training costs by over 80% by using spot instances alongside automated checkpointing and AWS Auto Scaling Groups [2][3]. This approach enabled them to handle interruptions without losing progress, making it a cost-effective way to scale experimental workloads.
Big data analytics and batch processing tasks, such as log analysis, data transformations, and report generation, also benefit greatly. By incorporating checkpointing, these workloads can resume efficiently after interruptions, with the savings far outweighing the occasional delays.
While the cost benefits are clear, using Spot Instances comes with its own set of challenges.
AWS Spot Instance Challenges
Despite the substantial savings, Spot Instances require careful planning to account for their inherent volatility. One of the major hurdles is pricing unpredictability. AWS Spot pricing can fluctuate frequently, with an average of 197 price changes per month, making it harder to forecast expenses compared to the steadier costs of on-demand instances [3].
This level of volatility is much higher than other cloud providers. For instance, Azure Spot VMs typically see fewer than one price change per month, and Google Cloud Platform (GCP) averages just one adjustment every three months [3]. Businesses using AWS Spot Instances need robust automation tools to monitor these price changes and optimise their instance choices in real-time.
Another challenge is the two-minute interruption notice, which demands that applications be designed to handle rapid shutdowns and restarts. Achieving this often involves significant setup, including implementing checkpointing systems, state management, and automated recovery processes. Tools like Kubernetes can help orchestrate such operations, ensuring service reliability despite interruptions. While this might feel overwhelming for smaller organisations, the long-term cost savings can make the effort worthwhile.
For companies without the necessary in-house expertise, working with cloud cost engineering specialists can be a smart move. These experts can guide organisations through the complexities of Spot Instances, helping them maximise savings while maintaining stable and efficient operations.
Azure Spot VMs
How Azure Spot VMs Differ from AWS
Azure Spot VMs offer discounts of up to 90% and stand out for their predictable pricing. Unlike AWS, where prices can fluctuate nearly 200 times a month, Azure's pricing adjusts on average only 0.76 times per month[3]. This pricing stability makes it easier for finance teams to plan quarterly cloud budgets with confidence.
For workloads that can run on ARM-based processors, Azure Spot VMs provide even greater savings. These workloads can be up to 69% cheaper compared to their x86 counterparts – a cost difference unmatched by other major cloud providers[2][3]. This makes Azure a compelling option for businesses looking to optimise their cloud spend.
Best Use Cases for Azure Spot VMs
Azure Spot VMs are ideal for scenarios where predictable costs matter more than chasing the absolute lowest price. Development and testing environments benefit greatly from the stable pricing, as do CI/CD pipelines and batch processing tasks, which can run without the need for constant cost monitoring.
Large-scale data analytics workloads also shine with Azure Spot VMs. Whether it's exploratory data projects or routine analytical processes, the combination of significant cost savings and pricing predictability makes such workloads more manageable and financially sensible.
Azure Interruption Behaviour and Pricing
Azure's approach to interruptions is straightforward, offering two options: 'Deallocate' or 'Delete'. This flexibility, combined with stable pricing, simplifies automation and budgeting for businesses in the UK[3]. It allows organisations to align interruption handling with their specific workload needs.
The predictable pricing not only reduces the frequency of price changes but also ensures more consistent eviction patterns. This reliability makes financial planning easier and allows IT teams to automate processes without the hassle of tracking price fluctuations. Smaller organisations, in particular, can integrate spot instances without the need for dedicated cloud cost management teams. For those seeking to maximise savings and streamline implementation, consulting firms like Hokstad Consulting can provide valuable insights.
Azure also offers a maximum price threshold feature, enabling businesses to cap their spending. This added control ensures cost certainty while still delivering the savings that UK organisations require.
GCP Spot VMs (Preemptible VMs)
How GCP Spot VMs Work
GCP Spot VMs are designed for cost-conscious computing, offering fixed 24-hour runtimes with discounts ranging from 60% to 91% compared to standard pricing. These savings come with a trade-off: Google Cloud can reclaim Spot VMs at any time without prior warning. This differs from AWS, which provides a 2-minute interruption notice[2][3].
Because of this, applications running on GCP Spot VMs need to be prepared for sudden interruptions. Features like robust checkpointing and automated restarts are essential. On the upside, the pricing is highly consistent, making it easier for finance teams to plan budgets with confidence.
Use Cases for GCP Spot VMs
Spot VMs shine in scenarios where cost savings and fault tolerance are priorities. Here are some common use cases:
Batch processing workloads: Tasks like data transformations, ETL jobs, and large-scale analytics are ideal. These workloads can pause and resume seamlessly after interruptions, and the 24-hour runtime limit is usually sufficient for most batch jobs. The cost savings make them a financially smart choice.
Machine learning training: Spot VMs are a great fit for model training and experimentation. By periodically saving model states, training jobs can pick up where they left off if interrupted. The stable pricing also helps ML teams plan for extensive training runs without unexpected costs.
CI/CD pipelines: Continuous integration and delivery workflows benefit from the predictable pricing and cost efficiency of Spot VMs. With per-second billing, short-lived build and test tasks can be completed at a fraction of the cost, keeping operational expenses in check.
For UK businesses, regional pricing advantages make these use cases even more appealing.
GCP Spot VM Benefits for UK Businesses
GCP Spot VMs offer specific cost advantages for UK organisations. For example, in the London region, C2 and N2 instance families are 5–8% cheaper per hour compared to AWS[4].
The sustained use discounts provide an additional layer of savings. Workloads running for a significant portion of the month automatically receive discounts of up to 30%, all without requiring upfront commitments[4]. Combined with spot pricing, this creates substantial savings for businesses with steady workload patterns.
GCP also stands out for its transparent billing and per-second pricing, which allow businesses to better predict and manage their cloud expenses. With fewer pricing surprises and competitive network egress costs, UK companies handling global data distribution can benefit significantly from GCP's pricing structure[4].
For even greater savings, UK businesses can integrate Spot VMs with committed use contracts. These contracts can reduce costs by up to 57% for one-year commitments and as much as 70% for three-year agreements[4]. This layered cost optimisation approach makes GCP an attractive option for organisations with predictable, long-term compute needs.
To help UK businesses fully leverage these advantages, Hokstad Consulting offers expertise in cloud cost engineering. They assist in designing and implementing solutions that maximise savings with GCP Spot VMs, ensuring reliability and compliance with UK-specific requirements.
Need help optimizing your cloud costs?
Get expert advice on how to reduce your cloud expenses without sacrificing performance.
AWS vs Azure vs GCP Comparison
Pricing and Features Comparison Table
As covered earlier, pricing and interruption policies differ significantly across providers. Here's a quick comparison to help UK businesses make informed decisions.
When evaluating spot instance providers, it's crucial to consider pricing, reliability, and operational factors. Here's how AWS, Azure, and GCP compare:
| Provider | Discount Range | Price Volatility | Interruption Notice | London Pricing (4 vCPU, 16 GB RAM) | Maximum Runtime | ARM Cost Reduction |
|---|---|---|---|---|---|---|
| AWS | Up to 90% | Very high (197 changes/month) | 2-minute warning | £69.50/month | No limit | Up to 40% vs x86 |
| Azure | Up to 90% | Low (0.76 changes/month) | At any time | £75.60/month | No limit | Up to 69% vs x86 |
| GCP | 60-91% | Very low (0.35 changes/month) | At any time | £71.10/month | 24 hours | - |
The data shows that AWS offers the lowest base pricing in the London region, while GCP delivers better value for C2 and N2 instance families, often costing 5-8% less than AWS equivalents [4]. Azure, though typically the most expensive, compensates with impressive price stability.
For businesses in the UK looking for predictable costs, Azure's minimal price changes - less than once per month - simplify financial planning. On the other hand, AWS's frequent price changes require advanced automation to manage effectively [3]. These distinctions highlight the unique strengths and challenges of each provider.
Main Differences Between Providers
Expanding on the table, here’s a closer look at the key differences in how these providers operate and price their services.
AWS Spot Instances are unmatched for cost savings but require high operational expertise. Their 2-minute interruption notice means workloads must be able to checkpoint quickly. While this suits dynamic environments, the extreme price volatility can create budgeting challenges unless automation handles bid management [3].
Azure Spot VMs combine up to 90% discounts with low price volatility, making them an excellent choice for predictable cost management. Features like maximum price thresholds offer additional control, which is particularly useful for industries with tight budget restrictions [3].
GCP Spot VMs bring the most stable pricing, with changes occurring only about once every three months. However, this comes with limitations: no interruption warnings and a fixed 24-hour runtime. These constraints are ideal for workloads like batch processing or data analytics that can complete within a day [3].
When it comes to ARM-based instances, all providers offer substantial savings, but Azure leads with up to 69% cost reductions compared to x86 instances. For UK businesses running compatible workloads, these savings are worth exploring [3].
Regional factors also play a role, with GCP standing out in the London region due to its competitive pricing and lower network egress costs. This is particularly advantageous for businesses managing global data distribution [4].
To help UK businesses make the most of these options and maintain operational resilience, Hokstad Consulting offers tailored cloud cost engineering services. Their expertise in designing fault-tolerant systems and implementing automated cost optimisation ensures businesses can navigate the complexities of spot instance pricing across AWS, Azure, and GCP.
Choosing the Right Spot Solution for UK Businesses
Factors to Consider in Your Decision
When selecting a spot solution, it's essential to weigh your workload needs, budget flexibility, integration capabilities, and automation readiness. Certain workloads, like stateless applications, batch processing jobs, and CI/CD pipelines, thrive on spot instances. On the other hand, stateful databases and latency-sensitive services may struggle due to the risk of sudden interruptions [2][3].
Price stability is another key factor. If your finance team prioritises predictable monthly costs, Azure's stable pricing might be a better fit compared to AWS's more variable pricing model. However, if your organisation has strong automation systems in place to handle frequent price changes, AWS could offer greater savings through its deeper discounts.
Integration with DevOps workflows is critical as well. For UK businesses, regional pricing differences can make a big impact. For example, Google Cloud Platform (GCP) offers pricing in its London region that's approximately 5–8% lower than comparable AWS options for certain instance types. GCP also provides lower network egress costs, which is particularly beneficial for businesses managing global data distribution [4].
Automation capabilities within your organisation also play a vital role. AWS provides a 2-minute interruption warning, which requires robust checkpoint and recovery systems. GCP, while offering no warning, has a predictable 24-hour maximum runtime, making it ideal for batch jobs that can complete within that window. Azure, on the other hand, pairs immediate interruptions with more stable pricing, making it suitable for businesses with moderate automation capabilities.
Another consideration is ARM-based instance compatibility. If your workloads can run on ARM architecture, Azure's spot instances can deliver up to a 69% cost reduction compared to x86 instances. This represents the largest savings potential among the major providers [3].
By carefully evaluating these factors, you can ensure your chosen solution aligns with both your operational needs and budgetary goals.
Getting Expert Help for Cost Reduction
Navigating the complexities of spot instance adoption can be challenging, but expert guidance can make the process smoother and more cost-effective. With proper optimisation strategies, businesses can achieve savings of 30–50% on infrastructure costs [1].
Managing price fluctuations and interruptions requires specialised expertise. This is where Hokstad Consulting comes in. They specialise in helping UK businesses optimise cloud costs through tailored solutions. Their approach combines technical expertise in DevOps with a deep understanding of spot instance management across AWS, Azure, and GCP. Instead of generic advice, they focus on creating automated systems that handle interruptions effectively while maximising savings.
Their services address common challenges such as designing failover mechanisms, implementing intelligent scheduling systems, and developing effective checkpoint strategies to minimise disruptions during interruptions [2][3]. The result? Reduced operational overhead and significant cost savings.
For UK businesses, working with specialists like Hokstad Consulting offers a structured and results-driven approach to spot instance adoption. Their no savings, no fee
model ensures that their success is directly tied to delivering measurable cost reductions for their clients [1].
EC2 Spot Instances Explained: Save Up to 90% on AWS Compute Costs
FAQs
How do AWS, Azure, and GCP handle interruptions for spot instances, and how can I choose the best option for my workload?
Spot instances can be a great way to cut costs, but they come with a catch: the cloud provider can reclaim them at any time, which means your workloads might face interruptions. Here's how the major providers handle this:
- AWS Spot Instances give you a two-minute warning before termination. This brief notice can help you wrap things up or save data before the instance shuts down.
- Azure Spot Virtual Machines work similarly but don’t offer any guarantee of advance notice. This means your applications need to be designed to handle interruptions without warning.
- GCP Preemptible VMs have a maximum lifespan of 24 hours and terminate automatically after that. Like Azure, they don’t provide any warning before shutting down.
Choosing the right spot instance depends on your workload and its ability to handle interruptions. For instance, AWS might be ideal if you need a short heads-up to preserve data. GCP's 24-hour limit could work well for predictable batch jobs, while Azure might be the better option if you're already deeply integrated with Microsoft services. By weighing these factors, you can strike a balance between cost savings and application reliability.
How can UK businesses save money with spot instances while managing price fluctuations and potential disruptions?
UK businesses looking to cut costs with spot instances should focus on strategies that tackle price changes and reduce the risk of disruptions. For example, automating workloads allows companies to capitalise on cheaper periods, while right-sizing resources helps avoid unnecessary spending on over-provisioned systems. Additionally, having backups or fallback systems in place ensures operations continue smoothly, even during interruptions.
By fine-tuning cloud infrastructure and adopting smart cost-saving methods, businesses can trim their cloud bills significantly. Seeking expert advice can help tailor these approaches to specific requirements, balancing performance and cost management effectively.
How can businesses effectively use spot instances in DevOps workflows, particularly for CI/CD pipelines and batch processing tasks?
To make the most of spot instances in DevOps workflows, businesses can use them for tasks that typically consume a lot of resources, such as continuous integration/continuous delivery (CI/CD) pipelines and batch processing. These instances are a great fit for jobs that are flexible and can handle interruptions, offering a much lower cost compared to on-demand instances.
For CI/CD pipelines, spot instances work well in build and test environments. Since these tasks are usually short-lived and can be restarted if interrupted, they align perfectly with the nature of spot instances. Adding a solid retry mechanism to your setup can minimise any disruption. When it comes to batch processing, you can configure workloads to save their progress at checkpoints. This way, even if an instance is reclaimed, the job can pick up right where it left off.
To manage interruptions and optimise resources, tools like auto-scaling groups and workload schedulers can be incredibly helpful. By designing workflows to account for the nature of spot instances, businesses can enjoy significant cost savings while maintaining efficiency.