Pro Tier Benefits
• Save up to an extra 3% on Think everyday pricingPlus Tier Benefits
• Save up to an extra 5% on Think everyday pricingElite Tier Benefits
• Save up to an extra 8% on Think everyday pricingLenovo Pro Business Store
Lenovo Education Store
Lenovo Pro Business Store
Lenovo Education Store
Lenovo Pro Business Store
Lenovo Education Store
Lenovo Pro Business Store
Lenovo Education Store
Lenovo Pro Business Store
Lenovo Education Store
Sign in / Create Account
Keep track of your wishlist, orders, and My Lenovo rewards, all in one place
Access your orders, subscriptions, saved carts, rewards balance, and profile
Create a wishlist of your favorite products
View & track your orders
Register your product and/or update your warranty dates
Sign out
Sign in / Create Account
Keep track of your wishlist, orders, and My Lenovo rewards, all in one place
Access your orders, subscriptions, saved carts, rewards balance, and profile
Create a wishlist of your favorite products
View & track your orders
Register your product and/or update your warranty dates
Sign out
Sign in / Create Account
Keep track of your wishlist, orders, and My Lenovo rewards, all in one place
Access your orders, subscriptions, saved carts, rewards balance, and profile
Create a wishlist of your favorite products
View & track your orders
Register your product and/or update your warranty dates
Sign out
Sign in / Create Account
Keep track of your wishlist, orders, and My Lenovo rewards, all in one place
Access your orders, subscriptions, saved carts, rewards balance, and profile
Create a wishlist of your favorite products
View & track your orders
Register your product and/or update your warranty dates
Sign out
Sign in / Create Account
Keep track of your wishlist, orders, and My Lenovo rewards, all in one place
Access your orders, subscriptions, saved carts, rewards balance, and profile
Create a wishlist of your favorite products
View & track your orders
Register your product and/or update your warranty dates
Sign out
Laptops
Desktops
Workstations
Gaming
Tablets
Monitors
Accessories and Software
Support & Solutions
Warranty Lookup
PC Services
Data Center Services
Solutions
Support
Lenovo Pro Business Offer 20% OFF | Join us to get up to $6,000 Welcome Discount + Free Gift!
Back to School | Join Lenovo Education to enjoy up to 40% Discount for students & teachers. SheerID is applicable.
PC Up to 30% off | Selected models are on sale in stock, and the fastest delivery is 3 days! Free shipping site-wide, no minimum spend.
Need Help? Call 2593 0388 or Chat with us now! Contact Us
11.11 Crazy Deals | Laptop Starting at $1798! Get $400 supermarket vouchers! 11.11 Deals
In technology, scale refers to the ability of a system, application, or infrastructure to handle an increasing amount of data, users, or load without compromising performance or stability. Essentially, it's about accommodating growth without breaking.
Scaling is crucial because as your application or user base grows, it must handle the increasing demands. Without scaling, your system could become sluggish, leading to downtime, user frustration, and potential business losses.
Horizontal scaling involves adding more machines or nodes to distribute the load across multiple servers. Vertical scaling, on the other hand, means upgrading the existing server's resources like random-access memory (RAM) or control processing unit (CPU) to handle more load.
Vertical scaling is suitable when your application's performance bottlenecks are related to individual server limitations, such as running out of memory or processing power. By upgrading the server's resources, you can handle more load.
Horizontal scaling offers several benefits, such as improved fault tolerance since one server failure doesn't take down the entire application. It's also cost-effective as you can use commodity hardware and scale as needed.
You can implement automatic horizontal scaling by using cloud-based services like Auto Scaling or Kubernetes with Horizontal Pod Autoscalers. These tools monitor your application's performance and automatically adjust the number of instances based on predefined rules.
Scaling up is another term for vertical scaling, where you increase the capacity of a single server. Scaling out is synonymous with horizontal scaling, where you add more servers to handle the load.
Yes, this is known as diagonal scaling. You can upgrade the resources of each server (vertical scaling) and add more servers (horizontal scaling) to create a robust and scalable infrastructure.
Scaling databases is essential as they are often a critical part of applications. You can horizontally scale databases by using techniques like sharding, where data is distributed across multiple database instances.
When scaling databases, you may encounter issues like data consistency, where different nodes might have different versions of the same data. Additionally, managing data distribution and ensuring efficient queries can be challenging.
It's best to optimize code first. Efficient code reduces resource consumption and can delay the need for scaling. Scaling should come after you've maximized the performance of your application.
Scaling might mask software design issues temporarily, but it won't fix them. In fact, scaling poorly designed software can lead to more complex problems in the long run. It's essential to address the design issues before scaling.
You can simulate high user loads using tools like Apache JMeter or Siege. By stress-testing your application, you can identify bottlenecks and weaknesses that need to be addressed before scaling.
CDNs can significantly help with scaling. They distribute content geographically across multiple servers, reducing the load on the main server and providing faster access to users by serving content from the nearest edge server.
Cloud computing allows you to easily scale your infrastructure up or down based on demand. Cloud providers offer auto-scaling services that automatically adjust resources to match load, making scaling more flexible and cost-efficient.
Scaling monolithic applications can be more challenging than scaling microservices due to their tightly coupled nature. However, you can still scale them vertically by upgrading the server or by using caching and load balancing techniques.
DevOps plays a crucial role in scaling applications by automating deployment, monitoring, and managing infrastructure. It enables smooth collaboration between development and operations teams, making scaling more efficient.
Load balancing evenly distributes incoming network traffic across multiple servers or resources. This ensures that no single server gets overwhelmed, enhancing performance, availability, and scalability of the overall system.
Load balancing algorithms include Round Robin, Least Connections, IP Hash, and Weighted Round Robin. These algorithms determine how incoming requests are distributed among the available servers.
Yes, you can create a basic load balancer using open-source tools or programming languages like Python. However, for production environments, it's often better to use dedicated load balancers provided by cloud services or hardware appliances.
Yes, scaling can impact costs. While horizontal scaling with cloud services can be cost-effective, adding more servers or upgrading resources for vertical scaling may lead to increased operational expenses.
Yes, there are design patterns like the Microservices architecture, the Database Sharding pattern, and the pattern of command query responsibility segregation (CQRS), which can help build scalable systems.
Auto-scaling policies are rules defined by you to instruct the system on when and how to scale resources automatically. They use metrics like control processing unit (CPU) utilization, network traffic, or custom application metrics to trigger scaling actions.
Bursting is the ability to temporarily exceed the allocated resources to handle sudden spikes in traffic. Cloud providers often allow limited bursting before additional charges or resource upgrades are required.
Scaling can help maintain optimal response times during periods of high traffic. By distributing the load, each server can handle a smaller number of requests, leading to faster response times.
Caching stores frequently accessed data in a faster and easily retrievable location, reducing the need to fetch data from the original source. This helps reduce database load and speeds up application response times, aiding in scaling.
Achieving data consistency in a horizontally scaled system can be challenging. Using distributed databases with support for multi-master replication or employing a consensus algorithm can help maintain data consistency.
Yes, machine learning models can be scaled to handle larger datasets and higher prediction loads. You can use distributed computing frameworks like Apache Spark or cloud-based machine learning services to achieve scalability.
While every effort has been made to ensure accuracy, this glossary is provided for reference purposes only and may contain errors or inaccuracies. It serves as a general resource for understanding commonly used terms and concepts. For precise information or assistance regarding our products, we recommend visiting our dedicated support site, where our team is readily available to address any questions or concerns you may have.
Save big with our top doorbuster deals. Our selections offer the best combination of value and discounts on popular products.
Shop now >Free-to-join for businesses of any size or maturity. Get free welcome gift and exclusive business pricing on Lenovo's entire catalog, get 1-on-1 help from tech advisors, and access to multiple member perks!
Learn more >Signup for Lenovo email notifications to receive valuable updates on products, sales, events, and more...
Sign up >