You're faced with client demands for unlimited scalability. How do you balance performance considerations?
When clients demand unlimited scalability, ensuring your systems maintain performance can be a tightrope walk. Here are some strategies to balance these demands:
What strategies have worked for you in balancing scalability with performance?
You're faced with client demands for unlimited scalability. How do you balance performance considerations?
When clients demand unlimited scalability, ensuring your systems maintain performance can be a tightrope walk. Here are some strategies to balance these demands:
What strategies have worked for you in balancing scalability with performance?
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1. Embrace microservices architecture to isolate components and scale independently based on specific workload needs. 2. Implement intelligent caching at multiple levels (CDN, application, database) to reduce redundant processing and database load. 3. Adopt asynchronous processing for non-critical operations to maintain responsiveness during traffic spikes. 4. Utilize vertical scaling strategically for database systems where horizontal scaling introduces complexity. 5. Establish clear performance SLAs and proactively communicate trade-offs to stakeholders, managing expectations through data-driven discussions.
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Most clients do NOT know for sure what they mean by unlimited scalability. It's a big, loose, fat, and sometimes exciting requirement. As a matter of fact, many big-data frameworks can do unlimited scalability, such as the stone-age-old Hadoop, however, when talking about performance (which is another big ask and most clients or even vendors don't know for sure), Hadoop, and even Spark, are very backwardish -- meaning: SLOW! The 3 things mentioned, IMO, are too general, too simplified, too ideal, to take care of scalability (& performance) -- techniques like auto-scaling and even cloud-native services do offer some flexibility in terms of on-demand elasticity, but it shouldn't be seen as equivalent to scalability. TBC
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To balance unlimited scalability with performance, use cloud infrastructure for dynamic resource allocation, implement load balancing to distribute traffic, and continuously monitor and optimize your system. This ensures that your application can handle increasing demand without sacrificing speed.
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Scalabiliy is based on the assumption that all the parameters vary linearly. This is an approximation that only works over a limited range so eventually something becomes non-linear and the scaling doesnt work.
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I think performance should not be considered once it is demanded, it should be served with every deliverable. Things to be balanced during performance considerations: - Cache the frequent query results using redis. - Add slow log query in the database or use any APM tool to identify the costly queries. - Add appropriate indexes on the columns with higer cardinality and frequent where clause conditions. - Order of conditions in the where clause should be closely evaluated. - Add required timeouts during interservice communication or third party api call. Consider using circuit breaker to avoid bottlenecks. Hope it helps.
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Tell the client, “We’ll scale as far as you grow, but let’s keep it fast and affordable.” It’s a balancing act—flexible capacity without choking on complexity.
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I presuppose unlimited scalability is for the software that the client wants to now scale up to the factory level. The problem starts at the design and conceptualization stage. Most developers make erroneous assumptions about "scale", for example a country's population will be in thousands, 25 characters are enough to store a person's name. Nothing can be done later. A software written with false assumptions can never be scaled up. The best solution is to select a designer who thinks realistically.
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design a system where the scale is just a variable and the system works regardless. use necessary items and trim the fat, like a brisket, doesnt matter the size, you have to get the bark right, the texture and the flavor. Miss one and it wont matter what size it is.
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Scaling for Success: How to Balance Performance and Demand Ensuring seamless performance while scaling to meet growing demands can be a delicate balancing act. Here are some proven strategies to help you achieve this balance: 1. Auto-scaling: Leverage cloud-based services that automatically adjust resources to match demand. 2. Optimize code and queries: Fine-tune your codebase and database queries for maximum speed and efficiency. 3. Monitor and adjust: Continuously track performance metrics and make timely adjustments to prevent bottlenecks. What strategies have worked for you in balancing scalability with performance? Share your insights and experiences in the comments below!
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