Why use the scaling service when Kubernetes can autoscale? Kubernetes autoscaling is based solely on generic metrics like CPU and memory usage. It doesn’t account for the nuances of your user traffic patterns, regional demands, and revenue impacts.
Our Kubernetes efficient scaling service provides far more customization. No under-scaling issues with too little capacity. But also no wasteful over-scaling and overspending on resources you don’t need.
We’ve helped multiple organizations scale their Kubernetes setups.
As more customers start using your services, the demands on your systems increase rapidly. The Kubernetes scaling service helps you dynamically provision resources without manual intervention. New customers get a fast, smooth experience from the start. And you avoid negative revenue impacts from performance issues or downtime during that crucial customer acquisition period.
When launching in new regions or countries, user traffic patterns and peak usage times can vary significantly. Kubernetes custom scaling allows you to adjust capacity based on the specific demand patterns in each new market you enter.
As your business scales, infrastructure costs can quickly get out of hand if not managed properly. With our cost optimization strategies, you avoid over-provisioning, which drives up costs.
While Kubernetes scaling automation is helpful, custom scaling delivers the most value. We’ll give you complete control and visibility over scaling operations. IT Outposts will partner with you to understand your business needs and existing infrastructure. Together, we can design the ideal scaling solution that gives you the flexibility you need.
Capacity planning and forecasting
Scaling with Kubernetes is a matter of control and cost management. Our goal is to align your infrastructure capacity with real business demand, increasing the efficiency of Kubernetes scaling.
We’ll collaborate with you to understand your app’s resource requirements and expected traffic patterns. This includes metrics from developers on typical service consumption as well as insights from marketing on upcoming campaigns that could drive demand spikes. With these forecasts, we configure smart scaling policies matched to the anticipated loads.
If detailed forecasts aren’t available upfront, we take an empirical approach. Our DevOps specialists will provide a reasonable starting capacity. Then we'll monitor actual live usage metrics and iteratively optimize resource allocation.
Cluster scaling optimization
Scaling with Kubernetes isn't just about provisioning more total resources. It's also about understanding how different services depend on each other and isolating their resource usage when needed. For example, some services have dynamic resource needs that can spike at certain times, pulling resources away from others in the shared cluster. We apply intelligent scaling policies to ensure each service gets the proper resources despite these fluctuations.
In addition, dynamic scaling with Kubernetes from 10,000 to 100,000 customers can't happen abruptly without over-provisioning. We initially size for a smaller capacity, like 12,000-15,000 customers. As the customer base grows, your cluster can automatically scale its resources according to the parameters we’ve configured.
Monitoring, logging, and observability
Monitoring, logging, and observability are key to understanding how our applications and infrastructure truly perform. We analyze system metrics but also conduct an audit of custom application metrics if available — user activity, conversions, revenue, and more.
By correlating technical and business data, we gain a complete view of performance aligned with actual user demands. This holistic visibility guides our scaling decisions.
For many apps, we go beyond default metrics and collaborate with developers to implement custom monitoring tailored to their specific behaviors and resource consumption patterns under varied loads.
Load balancing
Load balancing distributes traffic across your infrastructure for optimal performance. We set up custom routing rules to tailor infrastructure for local needs, ensuring a seamless user experience everywhere.
Load balancers themselves have throughput limits, so we continuously monitor and scale them up or down to match increasing or decreasing traffic in each region.
Cost optimization
At our company, we place a strong emphasis on cost efficiency across all our operations. Cloud computing can be expensive, which is why we diligently monitor and take advantage of any available cloud discounts or pricing strategies that can help reduce your expenses.
However, we also recognize that blindly pursuing cost-cutting measures can lead to performance degradation — that’s a total non-starter for us.
Multi-region scaling
Providing a good experience to users across different regions requires minimizing latency. Businesses can't afford long delays, as this could cause them to fall behind competitors.
We start by analyzing your app's latency needs and where your users are located. For latency-sensitive apps like e-commerce platforms, our DevOps engineers deploy separate Kubernetes clusters in key regions so users connect to the nearest service.
Staff training
If you have in-house DevOps engineers, we provide knowledge transfer on the infrastructure setup, enabling them to fully own and manage future scaling operations. If we're the sole DevOps team, we offer training sessions so your developers can understand scaling operations from the infrastructure side and bake scalability into code from the start. Shared knowledge also helps prevent potential bottlenecks before they occur. Developers can pinpoint whether issues originate from their code or infrastructure, allowing precise support requests.
Adapting to your needs
Our scaling solutions are flexible so you can adapt as your business requirements change. Need to scale up quickly when demand surges? Or scale down during quieter times? We’ve got you covered.
Rapid market expansion
Looking to expand into new markets? Kubernetes custom scaling allows for fast deployments, helping you take advantage of new opportunities swiftly. We can quickly set up and scale the necessary infrastructure, ensuring your applications are ready to serve your new customers without delays.
Predictable budgeting
Through advanced capacity planning and forecasting, we help you accurately predict and plan your infrastructure budget. Our cost optimization strategies ensure you only pay for the resources you actually require.
Uninterrupted operations
Scaling with Kubernetes doesn’t have to mean disrupting your services. Our scaling processes are designed to occur seamlessly, without any downtime or impact on your ongoing operations. Your customers and users won’t even notice the transition, ensuring a consistently smooth experience.
Staying ahead of the curve
With proactive monitoring, you can anticipate and address potential bottlenecks. This means you’ll always stay one step ahead of changing demands, ensuring your applications remain responsive, even during unexpected traffic spikes.
Discovery phase
During this phase, we meet with stakeholders across teams to learn about your business goals and applications. Usage metrics, traffic trends, and performance data are collected to analyze patterns. Current scaling configurations, automation policies, and any pain points are documented. This way, you get a comprehensive picture of your scaling needs and areas for optimization
Analysis phase
In the analysis phase, we assess all the collected data to find the best opportunities to optimize scaling applications with Kubernetes. This helps identify waste from having too many unused resources, delays in scaling, and risks of unstable performance. We suggest a scaling approach tailored to your needs. Next, we get feedback from your teams to refine the plan and ensure it fits your priorities.
Implementation phase
During this stage, we add instrumentation for custom metrics and data pipelines. Components are integrated for horizontal and vertical scaling for high availability. Extensive testing with simulated traffic ensures smooth performance before the full launch. This validation ensures that scaling with Kubernetes works seamlessly in production.
Optimization phase
After launching, we keep optimizing business-driven scaling, continuously monitoring metrics. As patterns change, scaling policies are tuned to fit emerging traffic patterns and app changes. Regular reviews help find new efficiency opportunities.
Wrap-up phase
Finally, thanks to the knowledge transfer, your team can manage scaling for high availability on their own. As a result, your transfer is smooth, with your staff enabled to sustain and optimize Kubernetes resource scaling independently.
Contact us today to discuss your current Kubernetes scaling challenges and goals.
With years of experience, we’ve successfully designed and implemented scaling solutions for organizations large and small across various industries.
Our track record demonstrates we can tailor Kubernetes resources scaling to match diverse needs. Our engineers are certified professionals with hands-on expertise in Kubernetes autoscaling concepts and tools who stay current with the latest developments.
Yes, Kubernetes is excellent for scaling applications and infrastructure. Its architecture and tools allow easy scaling up or down of resources to match changes in usage load.
Kubernetes can scale pods extremely quickly, often adding or removing instances within seconds of metrics reaching defined thresholds. Speed depends on factors like cluster size and resource availability.
For scaling applications with Kubernetes, we take a comprehensive approach. Our team right-sizes capacity based on expected traffic. For global apps, we use multi-region deployments, minimizing latency. Cost is prioritized, too. Our monitoring approach at UT Outposts combines system metrics and custom app data to guide scale decisions. In addition, our DevOps engineers provide scalability training to your teams. Overall, it’s a data-driven strategy that balances performance and cost-efficiency per your unique needs.
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