Horizontal Scaling vs Vertical Scaling - Which is Right for You?

Imagine a world where your favorite apps and websites crumble under the weight of their own popularity, leaving you frustrated and disconnected.

Scalability is the superhero that ensures your digital experiences remain seamless, even as the user base skyrockets and data flows like a never-ending river.

Scalability, the subject of our exploration today, is the hidden force behind the curtain, ensuring that your favorite tech services can handle the ever-increasing demands of a bustling online world.

At its core, scalability is the capacity of a system or application to gracefully handle increasing workloads, data volumes, and surges in traffic without breaking a sweat.

It's the unsung hero that keeps your apps responsive, your websites accessible, and your digital life smooth sailing.

Now, as we embark on this journey into the realm of scalability, we'll delve deep into horizontal scaling vs. vertical scaling.

These two pillars of scalability come with their own strengths and weaknesses in real-world applications. But before we dive into the nitty-gritty of these scaling strategies, let's establish why scalability is such a crucial factor in today's tech-driven world.

Stay tuned as we uncover the intricacies of scalability, learn how it impacts system performance and reliability, and unveil the secrets of choosing the right scaling strategy for your specific needs.

Whether you're a developer, a tech enthusiast, or simply someone curious about the inner workings of the digital world, this journey promises to be enlightening and empowering.

Understanding Scalability

In the digital realm, where competition is fierce and user expectations are constantly on the rise, the term "scalability" isn't just a buzzword—it's a mission-critical concept.

But what exactly is scalability, and why does it hold such paramount importance in the world of software and hardware systems?

Defining Scalability

At its core, scalability is the dynamic ability of a system or application to gracefully handle increasing workloads, data volumes, and surges in traffic without experiencing a significant drop in performance or efficiency.

It's the ability to adapt and expand, ensuring that as the user base grows, your digital platform remains responsive, reliable, and readily available.

Significance of Scalability

Imagine a scenario where your favorite online service couldn't scale. As more users joined the platform and data poured in, it would slow to a crawl, crash, or even become entirely inaccessible.

In a world where every millisecond counts, such a scenario is simply unacceptable.

Scalability isn't just a luxury; it's a necessity.

It's the backbone of digital growth, ensuring that whether you're a tech giant managing billions of users or a startup on the cusp of discovery, your digital offerings can expand and evolve without disruption.

Now that we've grasped the essence of scalability, let's introduce the dynamic duo of scaling strategies that organizations employ to achieve this essential goal: Horizontal Scaling vs. Vertical Scaling.

Horizontal Scaling - Buying More Machines

What is Horizontal scaling?

It is often referred to as scale-out scaling, which is the art of adding more machines or nodes to distribute the workload across multiple instances.

This strategy excels in handling the ever-increasing demand for digital services.

Imagine it as a well-choreographed dance where new machines gracefully step onto the stage to keep the performance running smoothly.

Stay with us as we delve deeper into the world of Horizontal Scaling.

We'll explore the intricacies of load balancing, fault tolerance, network considerations, and the challenges of maintaining data consistency in a distributed environment.

But that's not all; we'll also investigate how Horizontal Scaling shines in scenarios of rapid user growth, making it the go-to strategy for applications that need to accommodate hordes of concurrent users and a deluge of requests.

Intrigued?

You should be.

The world of Horizontal Scaling is dynamic, fascinating, and essential to understanding how modern systems can stay agile and responsive.

Imagine a popular eCommerce website during a flash sale. Without horizontal scaling, the server might buckle under the sudden influx of shoppers.

But with this strategy in place, new servers are seamlessly added to handle the surge in traffic. It's like opening new checkout lanes at a busy supermarket.

Key Concepts

To truly understand horizontal scaling, let's break down some key concepts that make it tick:

Load Balancing - Orchestrating Traffic

Imagine you're hosting a popular online shopping website during the holiday season. The traffic on your website suddenly surges as people rush to buy gifts. Without load balancing, your server might struggle to handle the influx of shoppers, leading to slow page loads or even crashes. It's like having a single cashier overwhelmed with a long line of customers.

Now, introduce load balancing into the picture. It acts as the traffic cop, directing customers to available cashiers (servers) efficiently. If one cashier is busy, the load balancer sends customers to the next available one. This ensures that no single server is overwhelmed, and everyone gets speedy service, even during the holiday rush.

Ensuring Fair Workload Distribution - No Server Left Behind

Imagine a cloud-based gaming platform where players from around the world connect to the same game server. Without fair workload distribution, some players might experience lag and frustration, while others enjoy a seamless gaming experience.

With horizontal scaling, the game server spreads the player load across multiple machines. Think of it like a multiplayer video game where everyone has an equal chance to participate and contribute to the game's success. No player (machine) is left idle, and the game runs smoothly for everyone involved.

Fault Tolerance - The Show Must Go On

Consider a popular streaming platform hosting a live concert. If one of the servers handling the stream suddenly crashes, the concert must go on without interruption for the viewers.

Without fault tolerance, the stream would be disrupted, and viewers would miss out on the performance.

Horizontal scaling's fault tolerance comes to the rescue in such situations. When one server encounters an issue, the load balancer seamlessly redirects viewers to other healthy servers. It's like having backup performers ready to step in if the lead singer needs a break. The show continues without missing a beat.

Data Inconsistency and Synchronization Challenges - Keeping Everyone in Sync

Imagine a global e-commerce platform with multiple servers that need to keep track of inventory levels. If two servers simultaneously receive requests to update the inventory for a product, there's a risk of data inconsistency.

For instance, one server might update the inventory to 10 items, while the other updates it to 8 items.

Synchronizing data across different servers in a horizontally scaled environment can be challenging. It's like maintaining a shared document with colleagues in different time zones.

To avoid conflicts and inconsistencies, sophisticated synchronization mechanisms are put in place to ensure that all servers have access to the latest and most accurate data.

Advantages of Horizontal Scaling

Now, let's explore the advantages of horizontal scaling:

1. Improved Scalability and Flexibility

Horizontal scaling, also known as scaling out, offers superior scalability and flexibility. It allows you to expand your computing resources by adding more machines or nodes to your system as needed. This flexibility means you can accommodate increased workloads or user demand without relying on expensive, high-end hardware upgrades.

2. Cost-Effective Resource Expansion

Horizontal scaling is a cost-effective approach to handle growth. Instead of investing in a single, powerful server, you can start with more modest hardware and add additional servers as your application's demands grow. This incremental approach to resource expansion aligns with your budget and helps you allocate resources efficiently.

3. High Availability and Fault Tolerance

Horizontal scaling enhances high availability and fault tolerance. By distributing workloads across multiple servers or nodes, the system can continue to operate even if one server fails. This redundancy ensures minimal downtime and improves the overall reliability of your application or service.

4. Load Balancing for Even Work Distribution

Load balancing is a key feature of horizontal scaling. Load balancers distribute incoming requests or tasks evenly among available servers, preventing any single server from becoming overwhelmed. This ensures consistent performance and responsiveness, even during peak usage periods.

5. Easier Maintenance and Upgrades

Managing and maintaining a horizontally scaled system is generally easier compared to vertical scaling. When you need to perform maintenance or upgrades, you can take individual servers offline without disrupting the entire system. This minimizes downtime and reduces the impact on end-users.

6. Elasticity for Dynamic Workloads

Horizontal scaling offers elasticity, making it well-suited for applications with dynamic workloads. You can automatically add or remove servers based on real-time demand, ensuring that your resources match the current requirements. This ability to auto-scale is particularly advantageous for cloud-based applications.

7. Scalability Across Geographical Locations

For applications that need to serve users across different geographic regions, horizontal scaling allows you to deploy servers in multiple locations. This reduces latency and provides a better user experience by serving content from servers that are geographically closer to the users.

8. Future-Proofing Your Infrastructure

Horizontal scaling future-proofs your infrastructure by providing a clear path for growth. As your application continues to expand, you can seamlessly add more servers, keeping your system responsive and accommodating new users or features.

These advantages make it a popular choice for modern applications and services that need to adapt to changing demands and ensure a reliable user experience.

Challenges of Horizontal Scaling:

1. Scaling Out vs. Scaling Up

Imagine an e-commerce platform experiencing a surge in traffic during the holiday season. Horizontal scaling allows you to add more servers to handle the increased load, ensuring your website remains responsive.

Limitation: Complexity in Distributed Systems

As you add more servers, the complexity of managing a distributed system increases. Ensuring that each server works seamlessly together can be challenging. Issues like load balancing, data synchronization, and fault tolerance become more intricate to handle, which can lead to increased operational overhead.

2. Balancing Workloads Efficiently

Consider a popular social media platform where user activity varies throughout the day. Horizontal scaling can distribute user requests across multiple servers for smoother performance.

Limitation: Uneven Workload Distribution

In a horizontally scaled system, achieving an even distribution of workloads can be a tricky task. Some servers may be underutilized, while others are pushed to their limits. This imbalance can lead to inefficient resource utilization and may require complex load-balancing algorithms to address.

3. Data Consistency Across Distributed Nodes

Imagine a global banking network that uses horizontal scaling to process transactions. This approach can handle high transaction volumes, but it introduces data consistency challenges.

Limitation: Data Consistency and Latency

Maintaining data consistency across distributed nodes is a significant challenge in horizontal scaling. As data is distributed across servers, ensuring that all nodes have access to the most up-to-date information can lead to latency issues. Implementing mechanisms like distributed databases or caching layers becomes necessary but adds complexity to the system.

Scalability with User Growth

The true beauty of horizontal scaling emerges as your user base grows. It efficiently accommodates the expanding crowd and prevents performance bottlenecks.

Think of it as having a team of dedicated workers who effortlessly adapt to meet increasing demands, ensuring that your digital service remains a top performer.

As we wrap up this section on horizontal scaling vs. vertical scaling, you've uncovered the magic of adding more machines to the mix. But our journey is far from over. In the next section, we'll explore the equally fascinating world of Vertical Scaling, where the focus shifts to buying bigger, more powerful machines.

Vertical Scaling: Buying Bigger Machines

In the world of scalability, another approach stands in stark contrast to horizontal scaling. It's called vertical scaling, often referred to as scale-up scaling. Instead of adding more machines to your digital orchestra, vertical scaling focuses on making your existing machine the star of the show.

Definition and Mechanism

Vertical scaling is all about supercharging your existing machine. When you're faced with an increasing workload, rather than expanding your army of servers, you invest in upgrading your existing machine's resources.

It's like transforming a compact car into a high-performance sports car by upgrading the engine, suspension, and other components.

Think of it as having a single powerhouse at your disposal, capable of handling more tasks and processing data at lightning speed.

Key Concepts

To grasp vertical scaling fully, let's explore some key concepts:

No Need for Load Balancing - All Eyes on One

Imagine you're the captain of a ship, navigating through treacherous waters. With horizontal scaling, you'd have multiple ships sailing together, each with its crew. You'd need a skilled navigator to coordinate their movements, and if one ship encounters a storm, it could disrupt the entire fleet.

Now, picture vertical scaling as upgrading your flagship vessel. You invest in making it larger, faster, and more robust. With this single powerful ship, there's no need for coordinating multiple ships or worrying about load balancing. Your flagship easily handles the journey, ensuring a smoother and more predictable voyage.

Faster Interprocess Communication and Reduced Latency

Consider a virtual reality (VR) gaming experience where players interact in a shared virtual world. In a horizontally scaled environment, where game servers are distributed across multiple machines, players' actions might experience delays due to network communication. This can lead to a less immersive and responsive experience.

Now, shift to a vertically scaled VR setup. All players are on the same machine, eliminating the need for network communication between servers. It's like everyone is in the same room, where their interactions are immediate and seamless. This results in a highly immersive and low-latency VR experience that keeps players engaged and thrilled.

Advantages of Vertical Scaling

1. Increased Processing Power

Vertical scaling, also known as scaling up, involves upgrading the existing hardware of a single server or machine. One of the primary benefits is the immediate boost in processing power and capacity. This allows the server to handle more significant workloads and complex computations without the need for a distributed system.

2. Simplified Resource Management

Vertical scaling simplifies resource management because you're dealing with a single server. This can be advantageous for applications that have a consistent and predictable workload, as there's no need to manage the complexities of load balancing and data synchronization across multiple machines.

3. Improved Single-Thread Performance

Vertical scaling often leads to improved single-thread performance, which can be crucial for applications that rely heavily on single-threaded operations. Certain tasks, such as database transactions or legacy software, may benefit significantly from increased processing speed.

4. Reduced Software Licensing Costs

In some cases, vertical scaling can lead to reduced software licensing costs. Instead of licensing multiple instances of software to run on distributed servers, you can run a single instance on a more powerful machine, potentially saving on licensing fees.

5. Lower Operational Overhead

Managing a single server is generally less complex and requires fewer resources than managing a distributed system. This can result in lower operational overhead, reduced staffing needs, and decreased maintenance costs.

6. Enhanced Data Consistency

Vertical scaling can simplify data consistency because all data resides on one machine. In situations where maintaining data integrity and consistency is critical, vertical scaling can help ensure that updates and transactions happen on a single, authoritative source.

7. Ease of Hardware Upgrades

Upgrading hardware in a vertical scaling environment typically involves replacing components within the existing server. This process can be more straightforward and cost-effective compared to acquiring entirely new servers for horizontal scaling.

8. Predictable Performance

Vertical scaling can offer predictable performance improvements. When you upgrade the CPU, RAM, or storage of a server, you can anticipate the extent of the performance gain, making capacity planning more predictable.

9. Energy Efficiency

In certain scenarios, vertical scaling can be more energy-efficient. Consolidating workloads onto a single, powerful server can result in better energy utilization compared to maintaining multiple lower-powered servers.

10. Compatibility with Legacy Systems

For organizations with legacy software or systems that cannot easily be distributed across multiple servers, vertical scaling can be a practical solution. It allows you to extend the life of older systems by enhancing their performance.

In summary, vertical scaling provides increased processing power, simplified resource management, improved single-thread performance, potential cost savings on software licensing, reduced operational overhead, enhanced data consistency, ease of hardware upgrades, predictable performance, energy efficiency, and compatibility with legacy systems. These advantages make vertical scaling a valuable choice for applications and environments where a single, robust server can meet the requirements effectively.

Challenges of Vertical Scaling

1. Powerful Hardware Costs

Vertical scaling, or scaling up, involves increasing the capabilities of an individual machine to handle more tasks. This approach offers advantages but also has its limitations.

Think of a legacy database system that relies on vertical scaling to handle increased transactional demands.

Limitation: Cost and Hardware Limitations

Vertical scaling often requires investing in high-end, expensive hardware components. As your system's demands grow, the cost of acquiring and maintaining such hardware can become prohibitive. Furthermore, there's a physical limit to how much you can vertically scale a machine, eventually reaching a point where further upgrades are no longer feasible.

2. Single Point of Failure

Consider a critical government database that uses vertical scaling. While this approach provides robust performance, it introduces a single point of failure.

Limitation: Reliability and Fault Tolerance

In vertical scaling, if the primary machine encounters hardware issues or experiences downtime, the entire system can become unavailable. Implementing redundancy and fault-tolerant mechanisms can be challenging, especially when dealing with costly, high-end hardware.

3. Scalability Bottlenecks

Imagine an online gaming platform that vertically scales its game servers to handle increased player traffic.

Limitation: Scalability Bottlenecks

Vertical scaling can hit scalability bottlenecks. While it can handle increased loads to a certain extent, there's a limit to how much a single machine can scale. Beyond that point, the only solution is to transition to a more distributed, horizontally scaled architecture.

Difference Between Horizontal and Vertical Scaling

To make an informed choice between horizontal vs. vertical scaling, it's crucial to understand the nuances of each approach, their differences, and the factors that guide your decision.

Let's delve into this comparison and address some common questions along the way.

Horizontal vs. Vertical Scaling

The eternal question: Is horizontal scaling superior to vertical scaling, or vice versa? The answer lies in the specifics of your project's requirements.

Let's break down the strengths of each approach to help you decide.

Scaling Type	Strengths	Example
Horizontal Scaling	- Ideal for handling a large number of concurrent users or requests. - Scales easily to accommodate rapid user growth. - Offers improved fault tolerance through redundancy.	A popular social media platform that experiences unpredictable spikes in user activity benefits from horizontal scaling to maintain responsiveness.
Vertical Scaling	- Efficiently handles complex computations and data processing tasks. - Reduces latency with faster interprocess communication. - Simplifies data consistency in a single-machine environment.	A financial institution processing extensive data calculations relies on vertical scaling for rapid, accurate results.

What is the Difference Between Vertical and Horizontal Scaling Up?

The difference between these two strategies lies in how they address increased demands.

Scaling Type	Description	Use Cases
Horizontal Scaling Up (Scale-Out)	Involves adding more machines or nodes to distribute the workload.	- Increases capacity by expanding the number of servers. - Ensures fault tolerance through redundancy. - Ideal for applications with unpredictable traffic spikes.
Vertical Scaling Up (Scale-Up)	Focuses on upgrading the existing machine's resources.	- Enhances capacity by improving the capabilities of a single machine. - Reduces latency and network communication bottlenecks. - Suited for tasks demanding substantial computational power.

What is the Difference Between Horizontal and Vertical Scaling Medium?

The choice between horizontal vs. vertical scaling can also depend on the scale you're operating at,

Horizontal Scaling	Vertical Scaling
Works well when you need to distribute the load across multiple machines	Effective for tasks requiring increasing processing power or memory
Scalable for applications with moderate to high user activity	Ideal for applications with data-intensive computations.
Offers redundancy for fault tolerance	Reduced latency and simplified data consistency
Commonly used in mid-sized companies or projects	Suitable for mid-sized enterprises with specific performance needs.

Is Horizontal Scaling Cheaper than Vertical?

The cost factor often plays a significant role in the decision-making process:

Horizontal Scaling	Vertical Scaling
Typically involves adding more, potentially lower cost-machines	Requires investment in high-end hardware upgrades
The initial setup can be budget-friendly	Initial costs can be higher due to hardware expenses
Costs can increase as you add more machines, especially for redundancy	Offers potential cost savings by maximizing existing infrastructure

Factors Influencing the Decision Between Horizontal & Vertical Scaling

The choice between horizontal vs. vertical scaling hinges on several critical factors:

1. Workload Characteristics

• The nature of the workloads your application handles.
• Examples include concurrent users, computational intensity, and data processing demands.

2. Cost Considerations

• Your budget and cost-effectiveness concerns.
• Weigh the initial costs, long-term expenses, and potential cost savings.

3. Performance Needs

• The importance of low-latency communication and network overhead.
• Evaluate the impact on user experience and application responsiveness.

4. Future Growth Expectations

• Anticipate how your application's user base and workload will evolve.
• Consider whether growth will be gradual and predictable or sporadic.

Hybrid Scaling: Combining the Best of Both Worlds

In a rapidly evolving digital landscape, sometimes the best approach is a balanced one. Enter hybrid scaling, a strategy that combines horizontal and vertical scaling for optimal results.

Why Choose Hybrid Scaling?

Hybrid scaling offers the flexibility to adapt to changing demands. By strategically combining horizontal and vertical scaling, you can achieve the best of both worlds.

Example: Picture an e-commerce platform that utilizes horizontal scaling for the high-traffic "Search Product Functionality," ensuring seamless user experiences during peak hours by distributing the load across multiple servers. For the "Contact Us Page," which encounters lower and intermittent traffic, they opt for vertical scaling, efficiently boosting the resources of a single server to handle occasional user requests. This hybrid approach provides scalability and performance precisely when needed.

In the ongoing quest for scalability, your choice between scaling horizontally vs vertically or a hybrid approach should align with your project's unique requirements, budget, and future aspirations.

As we move forward in our exploration of scalability, remember that the best strategy is the one that empowers your digital endeavors.

Overcoming Scalability Challenges

Scaling your applications to meet increasing demands is a rewarding endeavor, but it comes with its fair share of challenges.

To navigate these complexities successfully, it's essential to recognize the obstacles that scalability efforts can encounter and develop effective strategies to overcome them.

Common Challenges Faced During Scalability Efforts

Scaling a system isn't just about adding more hardware or servers; it involves intricacies that demand attention. Here are some of the most prevalent challenges you might encounter:

Database Management Challenges

Scaling often goes hand-in-hand with increased data volumes and user activity. As your application grows, database management becomes more intricate. Issues can manifest as:

• Slow Queries: Larger datasets can lead to sluggish database queries, impacting application performance.
• Data Fragmentation: Data can become fragmented across multiple database servers, making efficient retrieval a challenge.
• Data Availability: Ensuring data availability during database maintenance or failures becomes critical as uptime expectations rise.

Data Consistency and Synchronization Challenges

Maintaining data consistency across distributed systems is a complex task. Challenges in this domain can include:

• Synchronization Issues: Coordinating data updates across multiple servers while avoiding conflicts and race conditions can be daunting.
• Concurrency Control: Ensuring that multiple users or processes can access and modify data concurrently without conflicts is a significant challenge.
• Distributed Transactions: Implementing distributed transactions without compromising data integrity is a complex problem.

Handling High Traffic Loads

Scalability efforts are often driven by the need to accommodate traffic surges, such as during product launches or major events. Challenges in this area involve:

• Traffic Surges: Sudden spikes in user traffic can overwhelm your system, leading to performance degradation or downtime.
• Load Balancing: Ensuring that incoming traffic is distributed evenly among multiple servers to prevent overload on any single instance.
• Resource Management: Effectively managing resources, such as server capacity and network bandwidth, is essential for handling high traffic loads.

Performance Maintenance

As your application scales, maintaining performance is an ongoing concern. Challenges include:

• Identifying Bottlenecks: Pinpointing performance bottlenecks, whether in code, database queries, or network communication, is crucial.
• Resource Limitations: Dealing with resource limitations, such as memory constraints or CPU usage, can be challenging.
• Latency Optimization: Reducing latency in communication between different components of a distributed system is essential for responsiveness.

Strategies for Addressing Scalability Challenges

Overcoming these challenges requires a combination of effective strategies and continuous improvement efforts. Here are strategies to tackle each of these challenges:

Effective Database Management

To address database challenges, consider the following strategies:

• Database Sharding: Distribute data across multiple servers using sharding techniques to improve query performance and manage data effectively.
• Caching Mechanisms: Implement caching mechanisms to reduce the load on your database, especially for read-heavy operations.
• Query Optimization: Regularly optimize database queries and indexes to ensure efficient data retrieval and processing.

Data Consistency & Synchronization Strategies

For data consistency and synchronization challenges, these strategies can prove invaluable:

• Distributed Database Systems: Utilize distributed databases that offer built-in mechanisms for maintaining data consistency across multiple nodes.
• Distributed Locking: Implement distributed locking mechanisms to prevent data conflicts and race conditions in a multi-user environment.
• Event Sourcing and Eventual Consistency: Employ event sourcing and eventual consistency patterns to handle real-time data synchronization in distributed systems.

Handling High Traffic Loads

When dealing with high-traffic loads, these strategies can help your system stay responsive:

• Load Balancing: Implement load balancing mechanisms to evenly distribute incoming traffic among multiple servers, ensuring optimal resource utilization.
• Content Delivery Networks (CDNs): Use CDNs to cache and serve static assets, reducing the load on your application servers and enhancing user experience.
• Auto-Scaling: Deploy auto-scaling solutions that can automatically adjust server resources based on traffic levels, ensuring your system can handle sudden traffic surges.

Performance Maintenance & Optimization

To maintain and optimize performance, follow these guidelines:

• Performance Monitoring: Continuously monitor your system's performance using tools and analytics to identify and address bottlenecks promptly.
• Code Profiling and Optimization: Implement code profiling techniques to identify areas of code that require optimization, enhancing overall system efficiency.
• Microservices Architecture: Consider adopting a microservices architecture, which allows you to isolate and scale individual components independently, improving performance and scalability.

Scaling is an ongoing journey, and addressing these scalability challenges is essential to ensure a smooth and reliable user experience.

By implementing the right strategies and staying vigilant in your performance optimization efforts, you'll be well-equipped to handle the demands of a growing user base and evolving workloads.

Conclusion: The Scaling Odyssey

We've journeyed through the intricacies of horizontal vs. vertical scaling, explored the art of hybrid scaling, and deciphered the challenges and strategies that accompany scaling efforts. But as we conclude this expedition, we leave you with a thought-provoking question:

"How far can your dreams and ambitions take you in the digital realm?"

Scalability isn't merely about accommodating growth; it's about empowering your digital aspirations. Whether you're a tech trailblazer steering a startup toward success, a developer seeking the next big breakthrough, or a business striving for digital excellence, scalability is your compass.

At F22 Labs, we understand the significance of this journey. That's why we're offering you a chance to explore the possibilities further. Claim your 1-hour free consultation with our experts, and together, we can map out a scalable future for your digital endeavors.

From code optimization to infrastructure assessment, we're here to propel you toward your goals.

The path to scalability is an adventure, and your adventure begins now.

Are you ready to take the next step?