How do you ensure scalability for your product launch?

I am in the voice telephony domain, which means dealing with real-time data all the time. If the system is slow, the calls become gibberish. So, we have to plan for scalability from day one. The usual expectation is that the telephony software must scale almost infinitely. Same performance is expected from 10, 100, 1000 or 10,000 concurrent calls. Even if a single call is gibberish, it is experienced by a real person (s), who can raise a complaint. Therefore, one has to be able to scale 1000 times while tracking the performance of every call, at every second of the call. That’s the scalability goal in voice telephony.

1. Use PM execution framework to define success metrics based on company goals, product stage, users, and user actions (identifying NSM and CMs) 2. Estimate the amount of usage and success then communicate with XFNs to design a robust system that can be both modular and flexible design 3. Especially for startups, be ready that things are going to break and you will be constantly juggling between stability vs. cost-saving

Based on my experience in Product Management, it is a multi-level approach. 1) Establish an exhaustive scalability plan, expecting strategic growth scenarios based on variables such as data traffic, data size, and data feed. 2) Continuous performance testing in different platforms and real-time tracking to find the bottlenecks, ensuring the system could handle increased traffic effectively. 3) Manage to get user response during beta release and co-ordinate with key customers to test with real-time data even before release, enabling to refine the product iteratively. 4) Prepare a checklist on scalability protocols and after going live, monitoring and facilitating continuous improvement will enhance scalability over time.

Consider the following early enough to plan for rapid growth. 1/ First cohort or set and profile of customers matter. (Think Virality, bandwagon effect) 2/ Channel/ partner ecosystem for distribution and marketing. 3/ potential strategic acquirer with mutual interests These can help you cross the chasm to mass late adopters, drive scale exponentially and efficiently.

Scalability is a critical aspect of product launches, encompassing technical, operational, business, and organizational dimensions. A scalable product launch strategy requires careful planning, investment in infrastructure and technology, and ongoing optimization to support growth and meet evolving customer needs effectively. By prioritizing scalability from the outset, companies can position themselves for long-term success and competitive advantage in the marketplace.

1. Architecture has to be scalable from the beginning. 2. Conduct thorough performance testing 3. Implement horizontal scaling by adding more servers 4. Implement caching mechanisms 5. Use monitoring tools to track key performance indicators , such as server CPU usage, memory consumption, network traffic, & response times. 6. Optimize your database queries, indexes, & caching strategies to improve database performance. 7. Implement a CI/CD (continuous integration & deployment) pipeline to automate the process of building, testing, and deploying your application. 8. If your product relies on external services, make sure they are scalable as well. 9. Continuously monitor & load test your application to identify its capacity limits.

For real-time applications like voice telephony, there are no readily available technology stack that will deliver scalability. However, such a stack can be put together by picking a few best of breed technologies. 1) Best way to grow is by horizontal scaling. That signals the need for an orchestration service like Kubernetes. 2) Voice telephony is a stateful application, this calls for state synchronization across the system. The need is for a push datastore. 3) Stateful applications require extremely fast interprocess messaging between the components, with and without queuing. 4) Use languages that support true concurrency using multithreading and asynchronous processing. (sorry Python) Bring them all together, make your magic. ;-)

Cuando se construye un producto hay que hacerlo pensando siempre en el mantenimiento y buscando el equilibrio entre frameworks de alto nivel, que con poco esfuerzo de desarrollo se consigue mucha productividad y frameworks de más bajo nivel que son más flexibles a la hora de aceptar cambios y mejoras en el producto. Los estándares nunca fallan.

In order to easily handle future expansion, choose a stable and adaptable technology stack that supports your scalability objectives. Take into account elements like cloud services, modular architecture, and horizontal scalability.

Vet your supply chain. Input technologies in your architecture should be sourced from companies with a credible path to scaling to meet the future needs of the product. Ensure your architecture has limited to no sole source dependencies which could constrain growth.

That’s all fine, but the emphasis on scalability can lead to overcomplexity, higher costs, and distraction from more immediate product goals like market fit and user satisfaction. It’s because, while scalability is important, it should be balanced with other factors and tailored to the specific needs and context of the product. In other words, while the product is capable of growing, it remains focused on meeting the current needs and expectations of its users.

Start with a few rules, eventually those will become life long habits. 1) Inject instrumentation to track performance in all the critical parts of the code. If you can’t measure it, you can’t make it fast. If it is not fast, it won’t scale. Also, ensure it can be turned off in production. 2) Any function that gets called a lot, make sure it is really fast. All the IO within it should be asynchronous. 3) Pick the third party libraries and cloud APIs with extreme care. Same rules, ensure they are fast, and preferably asynchronous. 4) Treat each module to be a member of a collective. Each module should be designed to join and leave the collective smoothly to enable growing and shrinking of the autoscaling cluster.

As referenced in question 1, the context may vary according to the characteristics of the company and the strategy adopted. If these questions are agreed, then some observations I can bring are to ensure your product is scalable, design it with modularity, reusability and extensibility in mind. - Leverage microservices, APIs, and serverless architectures to decouple components and reduce dependencies (use cloud computing, containers, and orchestration tools to automate and scale your product infrastructure). - Additionally, adopt user feedback and data-driven decisions to iterate and improve features and functionality.

Scalability is achieved by simplifying the design, designing for manufacturability, choosing as much off the shelf components as possible. Most of all: stopping feature creep.

Es muy relevante para las organizaciones identificar desde un inicio los esquemas para escalar un producto o servicio, desde luego a pesar de que estamos en un mundo altamente globalizado y tecnificado, las etapas de la escalabilidad son las que marcan los recursos, es decir si tenemos que ir por regiones o sectores, es algo que se presentaría de una manera o si tiene un impacto global, sería de otra. Los recursos se convierten en el medio, no en el fin para lograr una escalabilidad y en este punto debemos tener cuidado, no es que debamos tener por ejemplo una campa?a, sino que requerimos una campa?a.

Something that needs to be called out: scalability isn't just a technical challenge; it involves business planning, customer service, and marketing strategies as well. It's about building a product that handles growth and maintains or improves quality and user experience as it grows. Scalability is an ongoing process!

This is the most important stage of product engineering. A good test engineering setup should be able to simulate the exact field conditions, while tracking every step of every transaction. What works well at 10 concurrent transactions, should work well at 1000 or 10000 concurrent transactions. The test plan should be able collect all the measurements for later analysis. Live monitoring is also useful in case of real-time applications, where transient data can show anomalies not apparent in historical data.

Na minha opini?o, para testar e garantir a escalabilidade, basicamente existem 3 pilares que precisamos observar: 1- testes de carga, para garantir que seu produto aguenta volumes razoavelmente maiores do que o dia-a-dia; 2 - Monitoria para garantir que o aumento de volume no produto n?o bata em algum limite e comece a ter problemas; 3 - Melhoria contínua no produto garantindo que ecolu??es continuem a manter o produto estável a pesar do crescimento.

As an example, in financial analytics domain, it is possible that a large traditional bank may like your product with simple analytics but another large digital bank may not have the demand for it and their in house team may already have such capabilities. On the other hand, a small digital bank may have the need where they want to outsource such solutions and focus in house team on their core projects. Hence, this consultation and closed group feedback from diverse groups of market players is an important step to test the scalability. On the other hand, interoperability and adaptability to multiple technology platforms is a key consideration to test scalability.

you need to know when the system, organization and technology will start to degrade in performance and then at what level it will fail entirely. Test to ensure you can predict this. And have a response plan ready.

Monitoring and optimizing the product's scalability is so important to evaluate right the cost of the product that you are selling to be competitive but also to have correct COGs in order to stay on business and able to grab market shares.

In addition to the points raised in item 1, monitoring and optimizing the scalability of a product is an ongoing process involving continuously monitoring key metrics, identifying areas for improvement, and implementing optimizations. Some of the actions to be taken may be: - Establish KPIs and use monitoring tools to track them: this way you can take real-time actions to reach them - Monitor User Feedback: Gather feedback from users about the product and use this feedback to prioritize optimizations and improvements. Based on the two items above, it is possible to minimally establish a roadmap to fix the most critical bugs and implement the most desired features to maintain an on-time marketing positioning.

Failure to establish clear goals, closely monitor progress, and iterate accordingly can prove to be a critical misstep for many product teams, leading them to initiate launches without much consideration. Striking a balance between swift adaptation and adherence to a well-defined product strategy is essential. For me, regularly monitoring Key Performance Indicators (KPIs) becomes paramount in ensuring scalability. It serves as a guiding mechanism, helping teams pivot and adapt strategically while also guaranteeing that the chosen path has been tested and validated for sustained success.

Metrics are key to understanding how the product scales over time. This includes the velocity of launching new features and assessing whether the necessary support infrastructure (customer service, bug reporting, platform systems) scale accordingly. It is also important to track release cadences and to keep a pulse on health indicators such as the number of new features per release, growth in adoption and engagement, and incremental cost of acquiring new users. Similarly, an organization should track the technical overhead and maintenance required to support the product's growth as it scales - headcount and time devoted to existing features, resources and time spent triaging issues, and inbound bug reports normalized per user/account.

Utilizing tools for performance monitoring and error tracking, you should continuously monitor the scalability of your product in real time through continuous monitoring. Your infrastructure should be optimized on a regular basis based on the insights gathered from doing monitoring.

Com minha experiência na área de desenvolvimento de produtos, identificar o cerne do problema é o catalisador para inova??es eficazes. Tenho pensado que o primeiro passo para algo escalar, é resolver de fato, um problema que gere valor ao usuário. N?o estou descartando os próximos passar do modelo de negócio, mas acredito que o primeiro ponto é compreens?o profunda do problema. Ao nos depararmos com um desafio, é comum come?armos a pensar em diversas maneiras de resolvê-lo, buscando a solu??o perfeita. No entanto, a verdadeira base para uma inova??o eficaz reside na compreens?o profunda do problema. é imperativo imergir na base do desafio antes de apresentar solu??es, permitindo assim o direcionamento de estratégias mais impactantes.

I would want to emphasise the role of people in this process. It is people that will determine whether something can be scaled, or has been scaled successfully. It is critical to get engagement from day 1 and continue to reinforce that as the main barrier will never be tech driven (there is always a solution) but always people and their willingness to change and adopt new ways of working and new tools.

Always be engaged in technical forums to understand the latest and if new practices emerge. It is essential to connect and always validate if technology, practices and processes are the best for your case

Many companies think Minimum Viable Product (MVP) in terms of product launch. At BorderlessHR, we think Minimum Marketable Product (MMP). Experience has taught us that the scaling of the product is directly correlated to the product's market performance. Thinking distribution and feedback loop from the get go is the bedrock of any future scale, technical or otherwise.

Scaling is first and foremost an issue of Product Supply (for physical goods / CPG) Most new brands spend way too much time on sales and marketing before they answer the question of “how will I ensure I hit 99% OTIF (On Time In Full) orders to Walmart on truckload quantities?”